NC State

BioResources

  • About the Journal
  • Authors & Reviewers
  • How to Self-Register
  • Full Site Navigation
  • Editorial Board
  • Meet the Staff
  • Editorial Policies
  • General Instructions
  • Ethics & Responsibilities
  • Article Preparation
  • Submission Instructions
  • Acknowledgment of your Peer-Reviewing
  • Writing Style Suggestions
  • Reviewer Guidelines
  • Back and Current Issues
  • Scholarly Reviews
  • Special Conference Collection Issues
  • Competition Print Edition
  • FRC: Pulp and Paper Fundamental Research Symposia Proceedings
  • Paper Manufacturing Chemistry
  • BioResources Early Career Investigator Award
  • Distance Education: Online Masters Degree & Individual Courses
  • Upcoming Conferences
  • Hands-On Courses
  • Affiliate Journal

The use of social media and its impact for research

Social media is an omnipresent part of everyday life. It provides users with an easy way to engage and connect with others without meeting face-to-face. This form of communication provides a lot of opportunity for companies and individuals to reach a massive audience. What is the purpose of social media, and how does it tie into science? Well, you see, it all depends on who you know and how active your social media presence is. Is there a benefit for sharing research across social media? The benefits of social media stem from active participation and the generation of new attractive content from an individual. Research is about producing new information, and social media offers unique opportunities to present new content.

Full Article

The Use of Social Media and its Impact for Research

Jessica Rogers

Keywords: Social media; Research; Engagement

Contact information: BioResources Process Editor, Department of Forest Biomaterials, North Carolina State University, Campus Box 8005, Raleigh, NC 27606, USA; e-mail: [email protected]

What is Social Media?

In today’s world social media is an ever-present facet of life that surrounds us. Almost every advertisement, whether television, radio, magazine, movie preview, podcast, newspaper, or elsewhere, will mention its social media presence in some way. ‘You can like us on Facebook, Check us out on Instagram,’ or perhaps ‘Watch our channel on YouTube’, are just some of the hooks that companies will provide to further build their brand and increase their visibility. As of January 2019, there were around 7.7 billion people in the world, of which 3.397 billion were active social media users (Smith 2019). Moreover, there are almost one million new users to some form of social media each day, or a new user every 10 seconds; 300 hours of video are uploaded to YouTube alone every minute (Smith 2019). To summarize, if you have found yourself boycotting the idea of social media, I hate to break it to you but it is here to stay.

The Underlying Purpose of Social Media

For those who do not know, a key theme of social media is ‘engagement’. Have you ever reached out to a company on their social media for any reason? The different social media outlets are simply interactive pathways on the internet that companies and businesses use to form relationships and network with others without leaving one’s desk. As a scientist, it is essential to attend conferences, give lectures, and lead panel discussions to network with others about common science interests. Today, there are an endless amount of resources accessible on the internet at your fingertips that allow you to do the same thing. Twitter first surfaced as a news and social networking site in which users post content and interact with each other through messages called ‘tweets’. The use of hashtags (a type of metadata tag) across all social media platforms allows people to search for certain interests and see all content related to that particular hashtag. This is a quick way to find and engage with people through common interests. Of course, you should still actively participate in your community by attending conventions and conferences, but if you truly seek to engage with more people, then you should not simply ignore the outlet of social media until you try it, as it can connect you with an even larger audience. Think of it this way, your lecture or discussion is most likely already being recorded, so what will you do with that recording?

Social media has a clear and direct purpose for businesses that sell a product or service and are searching for ways to advertise their brand. Of course, there other ways to use social media. Most people use social media to be, well, social, and communicate with family, former colleagues, or keep in touch with old classmates. The idea of a technological way of staying in touch with people is how Facebook was created. Facebook adds 500,000 new accounts each day, which equates to 6 new profiles every second (Smith 2019). So who exactly is in your friends list on Facebook? Who is subscribing to your channel on YouTube? Who is retweeting your tweets? If you want to broaden your impact beyond your discipline, you need to have a strong base of connections in your network.

The average person has 5.54 social media accounts (Smith 2019). Of those accounts, whatever one’s goal is, is it being projected across multiple platforms? Exactly who is engaged? These are all important questions that deal with your potential reach as an individual. The bottom line is if you seek community engagement in what you are doing, you must first be active in that particular community.

Social Media and Research

Now let us change course and focus on a different path of social media, that is where scientists use it to promote their research. The same rule applies. While all social media outlets have the potential for massive reach, it all comes back to a matter of whom you connect with or engage. However, the fast-paced and live aspect of social media can drive skeptical researchers not to publish, but successful reactions and quick responses can increase a researcher’s credibility. Research is about producing new information, and social media offers unique opportunities to present new content.

As a scientist, once you publish your research, you want to share it with as many colleagues and people so that they may read your novel findings. You want to share your hard work with many individuals. Almost all researchers send an email to their colleagues and individuals within their institution, which essentially is the first step in promoting their work. What if you took that one-step further and reached out to the scientific community on social media? You probably already have some form of a social media account and possibly one that relates to the scientific community; ResearchGate is a popular academic social media outlet. ResearchGate is a website that provides scientists with a forum to share and discuss their research as well as find collaborators. If you share your research on your personal account, then the only people that will see it are those whom you connect with. However, if you were active on different community or special interest pages that relate to your area of study and participate in regular discussions with other researchers on these sites, then you may find yourself having a much wider reach. Again, it all stems back to what you wish to accomplish with your research.

What Does that Mean for you?

Before getting started, you must ask yourself what exactly you want to gain from social media. If an increased reach is primarily what you seek, then you must be active in multiple communities related to your specialty. You already stay current on industry news and new research on your own, which is what others may be doing when they discover your research. However, if engagement and stimulated discussions are what you seek, then your active presence is required. Participating and driving discussions and posting content is what ultimately increases your visibility. Sharing and reposting others’ work, and being an active member on social media brings more attention to your profile and can enhance your reputation. A good place to start is with the professional social networking site LinkedIn that allows you to make connections with people based on job interests.

You can always go the old fashioned, tried and true route and send an email about your research, but how many new people reach out to you regarding your work? Maybe next time, try posting your research on a couple of industry pages, tag a few people in the community, and see if you make any new connections or spark any intriguing conversations. Because social media allows you to interact instantly with people across the globe, you may be surprised at who or how many people engage with you.

References Cited

Jaring, P., and Bäck, A. (2017). “How researchers use social media to promote their research and network with industry,”  Technology Information Management Review  7(8), 32-39. DOI: 10.22215/timreview/1098

Smith, K. (2019). “123 Amazing social media statistics and facts,”  brandwatch , (https://www.brandwatch.com/blog/amazing-social-media-statistics-and-facts/), Accessed 26 March 2019.

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

  • We're Hiring!
  • Help Center

paper cover thumbnail

The Advantages and Disadvantages of Social Media to the Selected Students of MMMHS

Profile image of Angela Dela Cruz

Related Papers

Teachers College Record

Emilia Askari

Background/Context: Educators are increasingly using social media in different ways, but they often do so without considering the ways in which social media corporations profit from their uses or the hidden mechanisms social media platforms use to steer connectivity among users. Moreover, very few studies have hitherto addressed critical challenges that social media services pose to users in general and to teachers/learners specifically. Purpose/Objective: In this exploratory paper, we seek to identify a number of key issues concerning corporate social media design and implementation, and the technoethical concerns to which educators should attend. Research setting: This project emerged from collaborations at the 2018 #Cloud2Class conference at Michigan State University. Our team of researchers agreed to examine scholarly and popular literature to better understand the ways in which social media corporations influence online experiences and how educators might address such issues in...

advantages and disadvantages of social media for students research paper

Tayo Olaleye

Mia Joy Manalastas

Martin A M Gansinger

This volume compiles international contributions that explore the potential risks and chances coming along with the wide-scale migration of society into digital space. Suggesting a shift of paradigm from Spiral of Silence to Nexus of Noise, the opening chapter provides an overview on systematic approaches and mechanisms of manipulation – ranging from populist political players to Cambridge Analytica. After a discussion of the the juxtaposition effects of social media use on social environments, the efficient instrumentalization of Twitter by Turkish politicans in the course of the US-decision to recognize Jerusalem as Israel’s capital is being analyzed. Following a case study of Instagram, Black Lives Matter and racism is a research about the impact of online pornography on the academic performance of university students. Another chapter is pointing out the potential of online tools for the successful relaunch of shadow brands. The closing section of the book deals with the role of social media on the opinion formation about the Euromaidan movement during the Ukrainian revolution and offers a comparative study touching on Russian and Western depictions of political documentaries in the 2000s.

C21: Communicating in the 21st Century 4/e

Baden Eunson

Mandavi Singh

This research-cum-presentation paper evaluated the history, phenomenal growth and socio-legal benefits of social media, juxtaposed with the costs of not regulating or censoring it, and the possible means and models for harnessing and streamlining social media. Prepared in conjunction with the work of the Centre for Global Internet Governance & Advocacy (GIGA).

Vortex of the Web. Potentials of the online environment

Gender equality and political democracy are important factors that concern almost every area of note in our modern era. Therefore, the notion that social media is to be considered as the mouthpiece of freedom of speech has achieved a status of powerful magnitude. It has also come to acceptance that the social media platforms have assumed the role of expressing opinions that could be barred from the established media arenas, thus making them ideal in terms of providing an outlet for the voice of the voiceless, so to speak. Yet, governments are able to block these platforms on a national scale. Key Words: Social Media, Gender, Political Opinion

International Journal of Scientific & Technology Research

Pronami Bora

Social media have found a remarkable jump in the number of users and their popularity in the last decade. The users of these social media platforms are found to express their opinion, views on different diverse topics. The discussion may be on a simple opinion regarding a particular product or opinion for a social issue. It might also be someone’s political view or view on some religious issue. At some point of time these discussions may enter into controversial topics and users may engage in some very provocative discussion in the social media platforms. For some considerable amount of time these issues have become common in social media. Users become aggressive at time in their opinion expressed in their posts. The aggressions in social media sometimes lead to disturbances in the social equilibrium. Many a time the situation goes so wrong that it disturbs the law and order situation may also lead to loss of life and public properties. Thus detection and control of these aggression...

RELATED PAPERS

International Research Journal of Modernization in Engineering Technology and Science

International Research Journal of Modernization in Engineering Technology and Science (IRJMETS)

Dominic Tufuor

Golden Meteorite Press

Austin A Mardon

Yousef T Alfarhoud

International Journal of Languages, Literature and Linguistics

Reena Mittal

Chakma Ratan

Peter Osharive

Franilyn A Sendiong-Dacono

Peter Osharive , Peter Osharive

Titilope Shukurah

Dr. Trisha Dowerah Baruah

jee-ar alamo

Chinmaya college of arts science and commerce

Aakanksha Agarwal

Contemporary Media Culture and Communication - 3

Thevanayagam Thevananth

LUIS DANIEL SALGADO ROMERO

maidul islam

Damian Maher

Ahmad Waheidi

Library Philosophy and Practice

Dr. Frankie Asare-Donkoh

Lawrence Villarin

pranshu sharma

Prattusha Chakraborty

… -Joint Research Centre- …

alexandra haché

Leslie Cole - Showers

International Journal of Electronics and Information Engineering

Sam Goundar

RITA NJOROGE

Louise Stoch , Sumarie Roodt

Faeizuan Zainal Abidin

Jayr Santiago

sireesh kondra

Grace Karanja

Joseph Osei Kuffour

Intersocial Workshop on Online Social Networks: Challenges and Perspectives (IWOSN)

Angeliki Antoniou

julius abiodun

  •   We're Hiring!
  •   Help Center
  • Find new research papers in:
  • Health Sciences
  • Earth Sciences
  • Cognitive Science
  • Mathematics
  • Computer Science
  • Academia ©2024

Advertisement

Advertisement

Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice

  • Published: 20 April 2020
  • Volume 5 , pages 245–257, ( 2020 )

Cite this article

advantages and disadvantages of social media for students research paper

  • John A. Naslund 1 ,
  • Ameya Bondre 2 ,
  • John Torous 3 &
  • Kelly A. Aschbrenner 4  

369k Accesses

183 Citations

146 Altmetric

12 Mentions

Explore all metrics

Avoid common mistakes on your manuscript.

Introduction

Social media has become a prominent fixture in the lives of many individuals facing the challenges of mental illness. Social media refers broadly to web and mobile platforms that allow individuals to connect with others within a virtual network (such as Facebook, Twitter, Instagram, Snapchat, or LinkedIn), where they can share, co-create, or exchange various forms of digital content, including information, messages, photos, or videos (Ahmed et al. 2019 ). Studies have reported that individuals living with a range of mental disorders, including depression, psychotic disorders, or other severe mental illnesses, use social media platforms at comparable rates as the general population, with use ranging from about 70% among middle-age and older individuals to upwards of 97% among younger individuals (Aschbrenner et al. 2018b ; Birnbaum et al. 2017b ; Brunette et al. 2019 ; Naslund et al. 2016 ). Other exploratory studies have found that many of these individuals with mental illness appear to turn to social media to share their personal experiences, seek information about their mental health and treatment options, and give and receive support from others facing similar mental health challenges (Bucci et al. 2019 ; Naslund et al. 2016b ).

Across the USA and globally, very few people living with mental illness have access to adequate mental health services (Patel et al. 2018 ). The wide reach and near ubiquitous use of social media platforms may afford novel opportunities to address these shortfalls in existing mental health care, by enhancing the quality, availability, and reach of services. Recent studies have explored patterns of social media use, impact of social media use on mental health and wellbeing, and the potential to leverage the popularity and interactive features of social media to enhance the delivery of interventions. However, there remains uncertainty regarding the risks and potential harms of social media for mental health (Orben and Przybylski 2019 ) and how best to weigh these concerns against potential benefits.

In this commentary, we summarized current research on the use of social media among individuals with mental illness, with consideration of the impact of social media on mental wellbeing, as well as early efforts using social media for delivery of evidence-based programs for addressing mental health problems. We searched for recent peer reviewed publications in Medline and Google Scholar using the search terms “mental health” or “mental illness” and “social media,” and searched the reference lists of recent reviews and other relevant studies. We reviewed the risks, potential harms, and necessary safety precautions with using social media for mental health. Overall, our goal was to consider the role of social media as a potentially viable intervention platform for offering support to persons with mental disorders, promoting engagement and retention in care, and enhancing existing mental health services, while balancing the need for safety. Given this broad objective, we did not perform a systematic search of the literature and we did not apply specific inclusion criteria based on study design or type of mental disorder.

Social Media Use and Mental Health

In 2020, there are an estimated 3.8 billion social media users worldwide, representing half the global population (We Are Social 2020 ). Recent studies have shown that individuals with mental disorders are increasingly gaining access to and using mobile devices, such as smartphones (Firth et al. 2015 ; Glick et al. 2016 ; Torous et al. 2014a , b ). Similarly, there is mounting evidence showing high rates of social media use among individuals with mental disorders, including studies looking at engagement with these popular platforms across diverse settings and disorder types. Initial studies from 2015 found that nearly half of a sample of psychiatric patients were social media users, with greater use among younger individuals (Trefflich et al. 2015 ), while 47% of inpatients and outpatients with schizophrenia reported using social media, of which 79% reported at least once-a-week usage of social media websites (Miller et al. 2015 ). Rates of social media use among psychiatric populations have increased in recent years, as reflected in a study with data from 2017 showing comparable rates of social media use (approximately 70%) among individuals with serious mental illness in treatment as compared with low-income groups from the general population (Brunette et al. 2019 ).

Similarly, among individuals with serious mental illness receiving community-based mental health services, a recent study found equivalent rates of social media use as the general population, even exceeding 70% of participants (Naslund et al. 2016 ). Comparable findings were demonstrated among middle-age and older individuals with mental illness accessing services at peer support agencies, where 72% of respondents reported using social media (Aschbrenner et al. 2018b ). Similar results, with 68% of those with first episode psychosis using social media daily were reported in another study (Abdel-Baki et al. 2017 ).

Individuals who self-identified as having a schizophrenia spectrum disorder responded to a survey shared through the National Alliance of Mental Illness (NAMI) and reported that visiting social media sites was one of their most common activities when using digital devices, taking up roughly 2 h each day (Gay et al. 2016 ). For adolescents and young adults ages 12 to 21 with psychotic disorders and mood disorders, over 97% reported using social media, with average use exceeding 2.5 h per day (Birnbaum et al. 2017b ). Similarly, in a sample of adolescents ages 13–18 recruited from community mental health centers, 98% reported using social media, with YouTube as the most popular platform, followed by Instagram and Snapchat (Aschbrenner et al. 2019 ).

Research has also explored the motivations for using social media as well as the perceived benefits of interacting on these platforms among individuals with mental illness. In the sections that follow (see Table 1 for a summary), we consider three potentially unique features of interacting and connecting with others on social media that may offer benefits for individuals living with mental illness. These include: (1) Facilitate social interaction; (2) Access to a peer support network; and (3) Promote engagement and retention in services.

Facilitate Social Interaction

Social media platforms offer near continuous opportunities to connect and interact with others, regardless of time of day or geographic location. This on demand ease of communication may be especially important for facilitating social interaction among individuals with mental disorders experiencing difficulties interacting in face-to-face settings. For example, impaired social functioning is a common deficit in schizophrenia spectrum disorders, and social media may facilitate communication and interacting with others for these individuals (Torous and Keshavan 2016 ). This was suggested in one study where participants with schizophrenia indicated that social media helped them to interact and socialize more easily (Miller et al. 2015 ). Like other online communication, the ability to connect with others anonymously may be an important feature of social media, especially for individuals living with highly stigmatizing health conditions (Berger et al. 2005 ), such as serious mental disorders (Highton-Williamson et al. 2015 ).

Studies have found that individuals with serious mental disorders (Spinzy et al. 2012 ) as well as young adults with mental illness (Gowen et al. 2012 ) appear to form online relationships and connect with others on social media as often as social media users from the general population. This is an important observation because individuals living with serious mental disorders typically have few social contacts in the offline world and also experience high rates of loneliness (Badcock et al. 2015 ; Giacco et al. 2016 ). Among individuals receiving publicly funded mental health services who use social media, nearly half (47%) reported using these platforms at least weekly to feel less alone (Brusilovskiy et al. 2016 ). In another study of young adults with serious mental illness, most indicated that they used social media to help feel less isolated (Gowen et al. 2012 ). Interestingly, more frequent use of social media among a sample of individuals with serious mental illness was associated with greater community participation, measured as participation in shopping, work, religious activities, or visiting friends and family, as well as greater civic engagement, reflected as voting in local elections (Brusilovskiy et al. 2016 ).

Emerging research also shows that young people with moderate to severe depressive symptoms appear to prefer communicating on social media rather than in-person (Rideout and Fox 2018 ), while other studies have found that some individuals may prefer to seek help for mental health concerns online rather than through in-person encounters (Batterham and Calear 2017 ). In a qualitative study, participants with schizophrenia described greater anonymity, the ability to discover that other people have experienced similar health challenges and reducing fears through greater access to information as important motivations for using the Internet to seek mental health information (Schrank et al. 2010 ). Because social media does not require the immediate responses necessary in face-to-face communication, it may overcome deficits with social interaction due to psychotic symptoms that typically adversely affect face-to-face conversations (Docherty et al. 1996 ). Online social interactions may not require the use of non-verbal cues, particularly in the initial stages of interaction (Kiesler et al. 1984 ), with interactions being more fluid and within the control of users, thereby overcoming possible social anxieties linked to in-person interaction (Indian and Grieve 2014 ). Furthermore, many individuals with serious mental disorders can experience symptoms including passive social withdrawal, blunted affect, and attentional impairment, as well as active social avoidance due to hallucinations or other concerns (Hansen et al. 2009 ), thus potentially reinforcing the relative advantage, as perceived by users, of using social media over in person conversations.

Access to a Peer Support Network

There is growing recognition about the role that social media channels could play in enabling peer support (Bucci et al. 2019 ; Naslund et al. 2016b ), referred to as a system of mutual giving and receiving where individuals who have endured the difficulties of mental illness can offer hope, friendship, and support to others facing similar challenges (Davidson et al. 2006 ; Mead et al. 2001 ). Initial studies exploring use of online self-help forums among individuals with serious mental illnesses have found that individuals with schizophrenia appeared to use these forums for self-disclosure and sharing personal experiences, in addition to providing or requesting information, describing symptoms, or discussing medication (Haker et al. 2005 ), while users with bipolar disorder reported using these forums to ask for help from others about their illness (Vayreda and Antaki 2009 ). More recently, in a review of online social networking in people with psychosis, Highton-Williamson et al. ( 2015 ) highlight that an important purpose of such online connections was to establish new friendships, pursue romantic relationships, maintain existing relationships or reconnect with people, and seek online peer support from others with lived experience (Highton-Williamson et al. 2015 ).

Online peer support among individuals with mental illness has been further elaborated in various studies. In a content analysis of comments posted to YouTube by individuals who self-identified as having a serious mental illness, there appeared to be opportunities to feel less alone, provide hope, find support and learn through mutual reciprocity, and share coping strategies for day-to-day challenges of living with a mental illness (Naslund et al. 2014 ). In another study, Chang ( 2009 ) delineated various communication patterns in an online psychosis peer-support group (Chang 2009 ). Specifically, different forms of support emerged, including “informational support” about medication use or contacting mental health providers, “esteem support” involving positive comments for encouragement, “network support” for sharing similar experiences, and “emotional support” to express understanding of a peer’s situation and offer hope or confidence (Chang 2009 ). Bauer et al. ( 2013 ) reported that the main interest in online self-help forums for patients with bipolar disorder was to share emotions with others, allow exchange of information, and benefit by being part of an online social group (Bauer et al. 2013 ).

For individuals who openly discuss mental health problems on Twitter, a study by Berry et al. ( 2017 ) found that this served as an important opportunity to seek support and to hear about the experiences of others (Berry et al. 2017 ). In a survey of social media users with mental illness, respondents reported that sharing personal experiences about living with mental illness and opportunities to learn about strategies for coping with mental illness from others were important reasons for using social media (Naslund et al. 2017 ). A computational study of mental health awareness campaigns on Twitter provides further support with inspirational posts and tips being the most shared (Saha et al. 2019 ). Taken together, these studies offer insights about the potential for social media to facilitate access to an informal peer support network, though more research is necessary to examine how these online interactions may impact intentions to seek care, illness self-management, and clinically meaningful outcomes in offline contexts.

Promote Engagement and Retention in Services

Many individuals living with mental disorders have expressed interest in using social media platforms for seeking mental health information (Lal et al. 2018 ), connecting with mental health providers (Birnbaum et al. 2017b ), and accessing evidence-based mental health services delivered over social media specifically for coping with mental health symptoms or for promoting overall health and wellbeing (Naslund et al. 2017 ). With the widespread use of social media among individuals living with mental illness combined with the potential to facilitate social interaction and connect with supportive peers, as summarized above, it may be possible to leverage the popular features of social media to enhance existing mental health programs and services. A recent review by Biagianti et al. ( 2018 ) found that peer-to-peer support appeared to offer feasible and acceptable ways to augment digital mental health interventions for individuals with psychotic disorders by specifically improving engagement, compliance, and adherence to the interventions and may also improve perceived social support (Biagianti et al. 2018 ).

Among digital programs that have incorporated peer-to-peer social networking consistent with popular features on social media platforms, a pilot study of the HORYZONS online psychosocial intervention demonstrated significant reductions in depression among patients with first episode psychosis (Alvarez-Jimenez et al. 2013 ). Importantly, the majority of participants (95%) in this study engaged with the peer-to-peer networking feature of the program, with many reporting increases in perceived social connectedness and empowerment in their recovery process (Alvarez-Jimenez et al. 2013 ). This moderated online social therapy program is now being evaluated as part of a large randomized controlled trial for maintaining treatment effects from first episode psychosis services (Alvarez-Jimenez et al. 2019 ).

Other early efforts have demonstrated that use of digital environments with the interactive peer-to-peer features of social media can enhance social functioning and wellbeing in young people at high risk of psychosis (Alvarez-Jimenez et al. 2018 ). There has also been a recent emergence of several mobile apps to support symptom monitoring and relapse prevention in psychotic disorders. Among these apps, the development of PRIME (Personalized Real-time Intervention for Motivational Enhancement) has involved working closely with young people with schizophrenia to ensure that the design of the app has the look and feel of mainstream social media platforms, as opposed to existing clinical tools (Schlosser et al. 2016 ). This unique approach to the design of the app is aimed at promoting engagement and ensuring that the app can effectively improve motivation and functioning through goal setting and promoting better quality of life of users with schizophrenia (Schlosser et al. 2018 ).

Social media platforms could also be used to promote engagement and participation in in-person services delivered through community mental health settings. For example, the peer-based lifestyle intervention called PeerFIT targets weight loss and improved fitness among individuals living with serious mental illness through a combination of in-person lifestyle classes, exercise groups, and use of digital technologies (Aschbrenner et al. 2016b , c ). The intervention holds tremendous promise as lack of support is one of the largest barriers towards exercise in patients with serious mental illness (Firth et al. 2016 ), and it is now possible to use social media to counter such. Specifically, in PeerFIT, a private Facebook group is closely integrated into the program to offer a closed platform where participants can connect with the lifestyle coaches, access intervention content, and support or encourage each other as they work towards their lifestyle goals (Aschbrenner et al. 2016a ; Naslund et al. 2016a ). To date, this program has demonstrated preliminary effectiveness for meaningfully reducing cardiovascular risk factors that contribute to early mortality in this patient group (Aschbrenner, Naslund, Shevenell, Kinney, et al., 2016), while the Facebook component appears to have increased engagement in the program, while allowing participants who were unable to attend in-person sessions due to other health concerns or competing demands to remain connected with the program (Naslund et al. 2018 ). This lifestyle intervention is currently being evaluated in a randomized controlled trial enrolling young adults with serious mental illness from real world community mental health services settings (Aschbrenner et al. 2018a ).

These examples highlight the promise of incorporating the features of popular social media into existing programs, which may offer opportunities to safely promote engagement and program retention, while achieving improved clinical outcomes. This is an emerging area of research, as evidenced by several important effectiveness trials underway (Alvarez-Jimenez et al. 2019 ; Aschbrenner et al. 2018a ), including efforts to leverage online social networking to support family caregivers of individuals receiving first episode psychosis services (Gleeson et al. 2017 ).

Challenges with Social Media for Mental Health

The science on the role of social media for engaging persons with mental disorders needs a cautionary note on the effects of social media usage on mental health and wellbeing, particularly in adolescents and young adults. While the risks and harms of social media are frequently covered in the popular press and mainstream news reports, careful consideration of the research in this area is necessary. In a review of 43 studies in young people, many benefits of social media were cited, including increased self-esteem and opportunities for self-disclosure (Best et al. 2014 ). Yet, reported negative effects were an increased exposure to harm, social isolation, depressive symptoms, and bullying (Best et al. 2014 ). In the sections that follow (see Table 1 for a summary), we consider three major categories of risk related to use of social media and mental health. These include: (1) Impact on symptoms; (2) Facing hostile interactions; and (3) Consequences for daily life.

Impact on Symptoms

Studies consistently highlight that use of social media, especially heavy use and prolonged time spent on social media platforms, appears to contribute to increased risk for a variety of mental health symptoms and poor wellbeing, especially among young people (Andreassen et al. 2016 ; Kross et al. 2013 ; Woods and Scott 2016 ). This may partly be driven by the detrimental effects of screen time on mental health, including increased severity of anxiety and depressive symptoms, which have been well documented (Stiglic and Viner 2019 ). Recent studies have reported negative effects of social media use on mental health of young people, including social comparison pressure with others and greater feeling of social isolation after being rejected by others on social media (Rideout and Fox 2018 ). In a study of young adults, it was found that negative comparisons with others on Facebook contributed to risk of rumination and subsequent increases in depression symptoms (Feinstein et al. 2013 ). Still, the cross-sectional nature of many screen time and mental health studies makes it challenging to reach causal inferences (Orben and Przybylski 2019 ).

Quantity of social media use is also an important factor, as highlighted in a survey of young adults ages 19 to 32, where more frequent visits to social media platforms each week were correlated with greater depressive symptoms (Lin et al. 2016 ). More time spent using social media is also associated with greater symptoms of anxiety (Vannucci et al. 2017 ). The actual number of platforms accessed also appears to contribute to risk as reflected in another national survey of young adults where use of a large number of social media platforms was associated with negative impact on mental health (Primack et al. 2017 ). Among survey respondents using between 7 and 11 different social media platforms compared with respondents using only 2 or fewer platforms, there were 3 times greater odds of having high levels of depressive symptoms and a 3.2 times greater odds of having high levels of anxiety symptoms (Primack et al. 2017 ).

Many researchers have postulated that worsening mental health attributed to social media use may be because social media replaces face-to-face interactions for young people (Twenge and Campbell 2018 ) and may contribute to greater loneliness (Bucci et al. 2019 ) and negative effects on other aspects of health and wellbeing (Woods and Scott 2016 ). One nationally representative survey of US adolescents found that among respondents who reported more time accessing media such as social media platforms or smartphone devices, there were significantly greater depressive symptoms and increased risk of suicide when compared with adolescents who reported spending more time on non-screen activities, such as in-person social interaction or sports and recreation activities (Twenge et al. 2018 ). For individuals living with more severe mental illnesses, the effects of social media on psychiatric symptoms have received less attention. One study found that participation in chat rooms may contribute to worsening symptoms in young people with psychotic disorders (Mittal et al. 2007 ), while another study of patients with psychosis found that social media use appeared to predict low mood (Berry et al. 2018 ). These studies highlight a clear relationship between social media use and mental health that may not be present in general population studies (Orben and Przybylski 2019 ) and emphasize the need to explore how social media may contribute to symptom severity and whether protective factors may be identified to mitigate these risks.

Facing Hostile Interactions

Popular social media platforms can create potential situations where individuals may be victimized by negative comments or posts. Cyberbullying represents a form of online aggression directed towards specific individuals, such as peers or acquaintances, which is perceived to be most harmful when compared with random hostile comments posted online (Hamm et al. 2015 ). Importantly, cyberbullying on social media consistently shows harmful impact on mental health in the form of increased depressive symptoms as well as worsening of anxiety symptoms, as evidenced in a review of 36 studies among children and young people (Hamm et al. 2015 ). Furthermore, cyberbullying disproportionately impacts females as reflected in a national survey of adolescents in the USA, where females were twice as likely to be victims of cyberbullying compared with males (Alhajji et al. 2019 ). Most studies report cross-sectional associations between cyberbullying and symptoms of depression or anxiety (Hamm et al. 2015 ), though one longitudinal study in Switzerland found that cyberbullying contributed to significantly greater depression over time (Machmutow et al. 2012 ).

For youth ages 10 to 17 who reported major depressive symptomatology, there were over 3 times greater odds of facing online harassment in the last year compared with youth who reported mild or no depressive symptoms (Ybarra 2004 ). Similarly, in a 2018 national survey of young people, respondents ages 14 to 22 with moderate to severe depressive symptoms were more likely to have had negative experiences when using social media and, in particular, were more likely to report having faced hostile comments or being “trolled” from others when compared with respondents without depressive symptoms (31% vs. 14%) (Rideout and Fox 2018 ). As these studies depict risks for victimization on social media and the correlation with poor mental health, it is possible that individuals living with mental illness may also experience greater hostility online compared to individuals without mental illness. This would be consistent with research showing greater risk of hostility, including increased violence and discrimination, directed towards individuals living with mental illness in in-person contexts, especially targeted at those with severe mental illnesses (Goodman et al. 1999 ).

A computational study of mental health awareness campaigns on Twitter reported that while stigmatizing content was rare, it was actually the most spread (re-tweeted) demonstrating that harmful content can travel quickly on social media (Saha et al. 2019 ). Another study was able to map the spread of social media posts about the Blue Whale Challenge, an alleged game promoting suicide, over Twitter, YouTube, Reddit, Tumblr, and other forums across 127 countries (Sumner et al. 2019 ). These findings show that it is critical to monitor the actual content of social media posts, such as determining whether content is hostile or promotes harm to self or others. This is pertinent because existing research looking at duration of exposure cannot account for the impact of specific types of content on mental health and is insufficient to fully understand the effects of using these platforms on mental health.

Consequences for Daily Life

The ways in which individuals use social media can also impact their offline relationships and everyday activities. To date, reports have described risks of social media use pertaining to privacy, confidentiality, and unintended consequences of disclosing personal health information online (Torous and Keshavan 2016 ). Additionally, concerns have been raised about poor quality or misleading health information shared on social media and that social media users may not be aware of misleading information or conflicts of interest especially when the platforms promote popular content regardless of whether it is from a trustworthy source (Moorhead et al. 2013 ; Ventola 2014 ). For persons living with mental illness, there may be additional risks from using social media. A recent study that specifically explored the perspectives of social media users with serious mental illnesses, including participants with schizophrenia spectrum disorders, bipolar disorder, or major depression, found that over one third of participants expressed concerns about privacy when using social media (Naslund and Aschbrenner 2019 ). The reported risks of social media use were directly related to many aspects of everyday life, including concerns about threats to employment, fear of stigma and being judged, impact on personal relationships, and facing hostility or being hurt (Naslund and Aschbrenner 2019 ). While few studies have specifically explored the dangers of social media use from the perspectives of individuals living with mental illness, it is important to recognize that use of these platforms may contribute to risks that extend beyond worsening symptoms and that can affect different aspects of daily life.

In this commentary, we considered ways in which social media may yield benefits for individuals living with mental illness, while contrasting these with the possible harms. Studies reporting on the threats of social media for individuals with mental illness are mostly cross-sectional, making it difficult to draw conclusions about direction of causation. However, the risks are potentially serious. These risks should be carefully considered in discussions pertaining to use of social media and the broader use of digital mental health technologies, as avenues for mental health promotion or for supporting access to evidence-based programs or mental health services. At this point, it would be premature to view the benefits of social media as outweighing the possible harms, when it is clear from the studies summarized here that social media use can have negative effects on mental health symptoms, can potentially expose individuals to hurtful content and hostile interactions, and can result in serious consequences for daily life, including threats to employment and personal relationships. Despite these risks, it is also necessary to recognize that individuals with mental illness will continue to use social media given the ease of accessing these platforms and the immense popularity of online social networking. With this in mind, it may be ideal to raise awareness about these possible risks so that individuals can implement necessary safeguards, while highlighting that there could also be benefits. Being aware of the risks is an essential first step, before then recognizing that use of these popular platforms could contribute to some benefits like finding meaningful interactions with others, engaging with peer support networks, and accessing information and services.

To capitalize on the widespread use of social media and to achieve the promise that these platforms may hold for supporting the delivery of targeted mental health interventions, there is need for continued research to better understand how individuals living with mental illness use social media. Such efforts could inform safety measures and also encourage use of social media in ways that maximize potential benefits while minimizing risk of harm. It will be important to recognize how gender and race contribute to differences in use of social media for seeking mental health information or accessing interventions, as well as differences in how social media might impact mental wellbeing. For example, a national survey of 14- to 22-year olds in the USA found that female respondents were more likely to search online for information about depression or anxiety and to try to connect with other people online who share similar mental health concerns when compared with male respondents (Rideout and Fox 2018 ). In the same survey, there did not appear to be any differences between racial or ethnic groups in social media use for seeking mental health information (Rideout and Fox 2018 ). Social media use also appears to have a differential impact on mental health and emotional wellbeing between females and males (Booker et al. 2018 ), highlighting the need to explore unique experiences between gender groups to inform tailored programs and services. Research shows that lesbian, gay, bisexual, or transgender individuals frequently use social media for searching for health information and may be more likely compared with heterosexual individuals to share their own personal health experiences with others online (Rideout and Fox 2018 ). Less is known about use of social media for seeking support for mental health concerns among gender minorities, though this is an important area for further investigation as these individuals are more likely to experience mental health problems and online victimization when compared with heterosexual individuals (Mereish et al. 2019 ).

Similarly, efforts are needed to explore the relationship between social media use and mental health among ethnic and racial minorities. A recent study found that exposure to traumatic online content on social media showing violence or hateful posts directed at racial minorities contributed to increases in psychological distress, PTSD symptoms, and depression among African American and Latinx adolescents in the USA (Tynes et al. 2019 ). These concerns are contrasted by growing interest in the potential for new technologies including social media to expand the reach of services to underrepresented minority groups (Schueller et al. 2019 ). Therefore, greater attention is needed to understanding the perspectives of ethnic and racial minorities to inform effective and safe use of social media for mental health promotion efforts.

Research has found that individuals living with mental illness have expressed interest in accessing mental health services through social media platforms. A survey of social media users with mental illness found that most respondents were interested in accessing programs for mental health on social media targeting symptom management, health promotion, and support for communicating with health care providers and interacting with the health system (Naslund et al. 2017 ). Importantly, individuals with serious mental illness have also emphasized that any mental health intervention on social media would need to be moderated by someone with adequate training and credentials, would need to have ground rules and ways to promote safety and minimize risks, and importantly, would need to be free and easy to access.

An important strength with this commentary is that it combines a range of studies broadly covering the topic of social media and mental health. We have provided a summary of recent evidence in a rapidly advancing field with the goal of presenting unique ways that social media could offer benefits for individuals with mental illness, while also acknowledging the potentially serious risks and the need for further investigation. There are also several limitations with this commentary that warrant consideration. Importantly, as we aimed to address this broad objective, we did not conduct a systematic review of the literature. Therefore, the studies reported here are not exhaustive, and there may be additional relevant studies that were not included. Additionally, we only summarized published studies, and as a result, any reports from the private sector or websites from different organizations using social media or other apps containing social media–like features would have been omitted. Although, it is difficult to rigorously summarize work from the private sector, sometimes referred to as “gray literature,” because many of these projects are unpublished and are likely selective in their reporting of findings given the target audience may be shareholders or consumers.

Another notable limitation is that we did not assess risk of bias in the studies summarized in this commentary. We found many studies that highlighted risks associated with social media use for individuals living with mental illness; however, few studies of programs or interventions reported negative findings, suggesting the possibility that negative findings may go unpublished. This concern highlights the need for a future more rigorous review of the literature with careful consideration of bias and an accompanying quality assessment. Most of the studies that we described were from the USA, as well as from other higher income settings such as Australia or the UK. Despite the global reach of social media platforms, there is a dearth of research on the impact of these platforms on the mental health of individuals in diverse settings, as well as the ways in which social media could support mental health services in lower income countries where there is virtually no access to mental health providers. Future research is necessary to explore the opportunities and risks for social media to support mental health promotion in low-income and middle-income countries, especially as these countries face a disproportionate share of the global burden of mental disorders, yet account for the majority of social media users worldwide (Naslund et al. 2019 ).

Future Directions for Social Media and Mental Health

As we consider future research directions, the near ubiquitous social media use also yields new opportunities to study the onset and manifestation of mental health symptoms and illness severity earlier than traditional clinical assessments. There is an emerging field of research referred to as “digital phenotyping” aimed at capturing how individuals interact with their digital devices, including social media platforms, in order to study patterns of illness and identify optimal time points for intervention (Jain et al. 2015 ; Onnela and Rauch 2016 ). Given that most people access social media via mobile devices, digital phenotyping and social media are closely related (Torous et al. 2019 ). To date, the emergence of machine learning, a powerful computational method involving statistical and mathematical algorithms (Shatte et al. 2019 ), has made it possible to study large quantities of data captured from popular social media platforms such as Twitter or Instagram to illuminate various features of mental health (Manikonda and De Choudhury 2017 ; Reece et al. 2017 ). Specifically, conversations on Twitter have been analyzed to characterize the onset of depression (De Choudhury et al. 2013 ) as well as detecting users’ mood and affective states (De Choudhury et al. 2012 ), while photos posted to Instagram can yield insights for predicting depression (Reece and Danforth 2017 ). The intersection of social media and digital phenotyping will likely add new levels of context to social media use in the near future.

Several studies have also demonstrated that when compared with a control group, Twitter users with a self-disclosed diagnosis of schizophrenia show unique online communication patterns (Birnbaum et al. 2017a ), including more frequent discussion of tobacco use (Hswen et al. 2017 ), symptoms of depression and anxiety (Hswen et al. 2018b ), and suicide (Hswen et al. 2018a ). Another study found that online disclosures about mental illness appeared beneficial as reflected by fewer posts about symptoms following self-disclosure (Ernala et al. 2017 ). Each of these examples offers early insights into the potential to leverage widely available online data for better understanding the onset and course of mental illness. It is possible that social media data could be used to supplement additional digital data, such as continuous monitoring using smartphone apps or smart watches, to generate a more comprehensive “digital phenotype” to predict relapse and identify high-risk health behaviors among individuals living with mental illness (Torous et al. 2019 ).

With research increasingly showing the valuable insights that social media data can yield about mental health states, greater attention to the ethical concerns with using individual data in this way is necessary (Chancellor et al. 2019 ). For instance, data is typically captured from social media platforms without the consent or awareness of users (Bidargaddi et al. 2017 ), which is especially crucial when the data relates to a socially stigmatizing health condition such as mental illness (Guntuku et al. 2017 ). Precautions are needed to ensure that data is not made identifiable in ways that were not originally intended by the user who posted the content as this could place an individual at risk of harm or divulge sensitive health information (Webb et al. 2017 ; Williams et al. 2017 ). Promising approaches for minimizing these risks include supporting the participation of individuals with expertise in privacy, clinicians, and the target individuals with mental illness throughout the collection of data, development of predictive algorithms, and interpretation of findings (Chancellor et al. 2019 ).

In recognizing that many individuals living with mental illness use social media to search for information about their mental health, it is possible that they may also want to ask their clinicians about what they find online to check if the information is reliable and trustworthy. Alternatively, many individuals may feel embarrassed or reluctant to talk to their clinicians about using social media to find mental health information out of concerns of being judged or dismissed. Therefore, mental health clinicians may be ideally positioned to talk with their patients about using social media and offer recommendations to promote safe use of these sites while also respecting their patients’ autonomy and personal motivations for using these popular platforms. Given the gap in clinical knowledge about the impact of social media on mental health, clinicians should be aware of the many potential risks so that they can inform their patients while remaining open to the possibility that their patients may also experience benefits through use of these platforms. As awareness of these risks grows, it may be possible that new protections will be put in place by industry or through new policies that will make the social media environment safer. It is hard to estimate a number needed to treat or harm today given the nascent state of research, which means the patient and clinician need to weigh the choice on a personal level. Thus, offering education and information is an important first step in that process. As patients increasingly show interest in accessing mental health information or services through social media, it will be necessary for health systems to recognize social media as a potential avenue for reaching or offering support to patients. This aligns with growing emphasis on the need for greater integration of digital psychiatry, including apps, smartphones, or wearable devices, into patient care and clinical services through institution-wide initiatives and training clinical providers (Hilty et al. 2019 ). Within a learning healthcare environment where research and care are tightly intertwined and feedback between both is rapid, the integration of digital technologies into services may create new opportunities for advancing use of social media for mental health.

As highlighted in this commentary, social media has become an important part of the lives of many individuals living with mental disorders. Many of these individuals use social media to share their lived experiences with mental illness, to seek support from others, and to search for information about treatment recommendations, accessing mental health services and coping with symptoms (Bucci et al. 2019 ; Highton-Williamson et al. 2015 ; Naslund et al. 2016b ). As the field of digital mental health advances, the wide reach, ease of access, and popularity of social media platforms could be used to allow individuals in need of mental health services or facing challenges of mental illness to access evidence-based treatment and support. To achieve this end and to explore whether social media platforms can advance efforts to close the gap in available mental health services in the USA and globally, it will be essential for researchers to work closely with clinicians and with those affected by mental illness to ensure that possible benefits of using social media are carefully weighed against anticipated risks.

Abdel-Baki, A., Lal, S., Charron, D.-C., Stip, E., & Kara, N. (2017). Understanding access and use of technology among youth with first-episode psychosis to inform the development of technology-enabled therapeutic interventions. Early Intervention in Psychiatry, 11 (1), 72–76.

PubMed   Google Scholar  

Ahmed, Y. A., Ahmad, M. N., Ahmad, N., & Zakaria, N. H. (2019). Social media for knowledge-sharing: a systematic literature review. Telematics and Informatics, 37 , 72–112.

Google Scholar  

Alhajji, M., Bass, S., & Dai, T. (2019). Cyberbullying, mental health, and violence in adolescents and associations with sex and race: data from the 2015 youth risk behavior survey. Global Pediatric Health, 6 , 2333794X19868887.

PubMed   PubMed Central   Google Scholar  

Alvarez-Jimenez, M., Bendall, S., Lederman, R., Wadley, G., Chinnery, G., Vargas, S., Larkin, M., Killackey, E., McGorry, P., & Gleeson, J. F. (2013). On the HORYZON: moderated online social therapy for long-term recovery in first episode psychosis. Schizophrenia Research, 143 (1), 143–149.

Alvarez-Jimenez, M., Gleeson, J., Bendall, S., Penn, D., Yung, A., Ryan, R., et al. (2018). Enhancing social functioning in young people at ultra high risk (UHR) for psychosis: a pilot study of a novel strengths and mindfulness-based online social therapy. Schizophrenia Research, 202 , 369–377.

Alvarez-Jimenez, M., Bendall, S., Koval, P., Rice, S., Cagliarini, D., Valentine, L., et al. (2019). HORYZONS trial: protocol for a randomised controlled trial of a moderated online social therapy to maintain treatment effects from first-episode psychosis services. BMJ Open, 9 (2), e024104.

Andreassen, C. S., Billieux, J., Griffiths, M. D., Kuss, D. J., Demetrovics, Z., Mazzoni, E., & Pallesen, S. (2016). The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: a large-scale cross-sectional study. Psychology of Addictive Behaviors, 30 (2), 252.

Aschbrenner, K. A., Naslund, J. A., & Bartels, S. J. (2016a). A mixed methods study of peer-to-peer support in a group-based lifestyle intervention for adults with serious mental illness. Psychiatric Rehabilitation Journal, 39 (4), 328–334.

Aschbrenner, K. A., Naslund, J. A., Shevenell, M., Kinney, E., & Bartels, S. J. (2016b). A pilot study of a peer-group lifestyle intervention enhanced with mHealth technology and social media for adults with serious mental illness. The Journal of Nervous and Mental Disease, 204 (6), 483–486.

Aschbrenner, K. A., Naslund, J. A., Shevenell, M., Mueser, K. T., & Bartels, S. J. (2016c). Feasibility of behavioral weight loss treatment enhanced with peer support and mobile health technology for individuals with serious mental illness. Psychiatric Quarterly, 87 (3), 401–415.

Aschbrenner, K. A., Naslund, J. A., Gorin, A. A., Mueser, K. T., Scherer, E. A., Viron, M., et al. (2018a). Peer support and mobile health technology targeting obesity-related cardiovascular risk in young adults with serious mental illness: protocol for a randomized controlled trial. Contemporary Clinical Trials, 74 , 97–106.

Aschbrenner, K. A., Naslund, J. A., Grinley, T., Bienvenida, J. C. M., Bartels, S. J., & Brunette, M. (2018b). A survey of online and mobile technology use at peer support agencies. Psychiatric Quarterly , 1–10.

Aschbrenner, K. A., Naslund, J. A., Tomlinson, E. F., Kinney, A., Pratt, S. I., & Brunette, M. F. (2019). Adolescents’ use of digital technologies and preferences for mobile health coaching in mental health settings. Frontiers in Public Health. 7 , 178.

Badcock, J. C., Shah, S., Mackinnon, A., Stain, H. J., Galletly, C., Jablensky, A., & Morgan, V. A. (2015). Loneliness in psychotic disorders and its association with cognitive function and symptom profile. Schizophrenia Research, 169 (1–3), 268–273.

Batterham, P. J., & Calear, A. J. (2017). Preferences for internet-based mental health interventions in an adult online sample: findings from ann online community survey. JMIR Mental Health, 4 (2), e26.

Bauer, R., Bauer, M., Spiessl, H., & Kagerbauer, T. (2013). Cyber-support: an analysis of online self-help forums (online self-help forums in bipolar disorder). Nordic Journal of Psychiatry, 67 (3), 185–190.

Berger, M., Wagner, T. H., & Baker, L. C. (2005). Internet use and stigmatized illness. Social Science & Medicine, 61 (8), 1821–1827.

Berry, N., Lobban, F., Belousov, M., Emsley, R., Nenadic, G., & Bucci, S. (2017). # WhyWeTweetMH: understanding why people use Twitter to discuss mental health problems. Journal of Medical Internet Research, 19 (4), e107.

Berry, N., Emsley, R., Lobban, F., & Bucci, S. (2018). Social media and its relationship with mood, self-esteem and paranoia in psychosis. Acta Psychiatrica Scandinavica, 138 , 558–570.

Best, P., Manktelow, R., & Taylor, B. (2014). Online communication, social media and adolescent wellbeing: a systematic narrative review. Children and Youth Services Review, 41 , 27–36.

Biagianti, B., Quraishi, S. H., & Schlosser, D. A. (2018). Potential benefits of incorporating peer-to-peer interactions into digital interventions for psychotic disorders: a systematic review. Psychiatric Services, 69 (4), 377–388.

Bidargaddi, N., Musiat, P., Makinen, V.-P., Ermes, M., Schrader, G., & Licinio, J. (2017). Digital footprints: facilitating large-scale environmental psychiatric research in naturalistic settings through data from everyday technologies. Molecular Psychiatry, 22 (2), 164.

Birnbaum, M. L., Ernala, S. K., Rizvi, A. F., De Choudhury, M., & Kane, J. M. (2017a). A collaborative approach to identifying social media markers of schizophrenia by employing machine learning and clinical appraisals. Journal of Medical Internet Research, 19 (8), e289.

Birnbaum, M. L., Rizvi, A. F., Correll, C. U., Kane, J. M., & Confino, J. (2017b). Role of social media and the Internet in pathways to care for adolescents and young adults with psychotic disorders and non-psychotic mood disorders. Early Intervention in Psychiatry, 11 (4), 290–295.

Booker, C. L., Kelly, Y. J., & Sacker, A. (2018). Gender differences in the associations between age trends of social media interaction and well-being among 10-15 year olds in the UK. BMC Public Health, 18 (1), 321.

Brunette, M., Achtyes, E., Pratt, S., Stilwell, K., Opperman, M., Guarino, S., & Kay-Lambkin, F. (2019). Use of smartphones, computers and social media among people with SMI: opportunity for intervention. Community Mental Health Journal , 1–6.

Brusilovskiy, E., Townley, G., Snethen, G., & Salzer, M. S. (2016). Social media use, community participation and psychological well-being among individuals with serious mental illnesses. Computers in Human Behavior, 65 , 232–240.

Bucci, S., Schwannauer, M., & Berry, N. (2019). The digital revolution and its impact on mental health care. Psychology and Psychotherapy: Theory, Research and Practice, 92 (2), 277–297.

Chancellor, S., Birnbaum, M. L., Caine, E. D., Silenzio, V. M., & De Choudhury, M. (2019). A taxonomy of ethical tensions in inferring mental health states from social media. In Proceedings of the Conference on Fairness, Accountability, and Transparency, 79–88.

Chang, H. J. (2009). Online supportive interactions: using a network approach to examine communication patterns within a psychosis social support group in Taiwan. Journal of the American Society for Information Science and Technology, 60 (7), 1504–1517.

Davidson, L., Chinman, M., Sells, D., & Rowe, M. (2006). Peer support among adults with serious mental illness: a report from the field. Schizophrenia Bulletin, 32 (3), 443–450.

De Choudhury, M., Gamon, M., & Counts, S. (2012). Happy, nervous or surprised? classification of human affective states in social media. Paper presented at the sixth international Association for Advancement of Artificial Intelligence (AAAI) Conference on Weblogs and Social Meedia, 435–438.

De Choudhury, M., Gamon, M., Counts, S., & Horvitz, E. (2013). Predicting depression via social media. Paper presented at the seventh international Association for Advancement of Artificial Intelligence (AAAI) Conference on Weblogs and Social Media, 128–137.

Docherty, N. M., Hawkins, K. A., Hoffman, R. E., Quinlan, D. M., Rakfeldt, J., & Sledge, W. H. (1996). Working memory, attention, and communication disturbances in schizophrenia. Journal of Abnormal Psychology, 105 (2), 212–219.

Ernala, S. K., Rizvi, A. F., Birnbaum, M. L., Kane, J. M., & De Choudhury, M. (2017). Linguistic markers indicating therapeutic outcomes of social media disclosures of schizophrenia. Proceedings of the ACM on Human-Computer Interaction, 1 (1), 43.

Feinstein, B. A., Hershenberg, R., Bhatia, V., Latack, J. A., Meuwly, N., & Davila, J. (2013). Negative social comparison on Facebook and depressive symptoms: rumination as a mechanism. Psychology of Popular Media Culture, 2 (3), 161.

Firth, J., Cotter, J., Torous, J., Bucci, S., Firth, J. A., & Yung, A. R. (2015). Mobile phone ownership and endorsement of “mHealth” among people with psychosis: a meta-analysis of cross-sectional studies. Schizophrenia Bulletin, 42 (2), 448–455.

Firth, J., Rosenbaum, S., Stubbs, B., Gorczynski, P., Yung, A. R., & Vancampfort, D. (2016). Motivating factors and barriers towards exercise in severe mental illness: a systematic review and meta-analysis. Psychological Medicine, 46 (14), 2869–2881.

Gay, K., Torous, J., Joseph, A., Pandya, A., & Duckworth, K. (2016). Digital technology use among individuals with schizophrenia: results of an online survey. JMIR Mental Health, 3 (2), e15.

Giacco, D., Palumbo, C., Strappelli, N., Catapano, F., & Priebe, S. (2016). Social contacts and loneliness in people with psychotic and mood disorders. Comprehensive Psychiatry, 66 , 59–66.

Gleeson, J., Lederman, R., Herrman, H., Koval, P., Eleftheriadis, D., Bendall, S., Cotton, S. M., & Alvarez-Jimenez, M. (2017). Moderated online social therapy for carers of young people recovering from first-episode psychosis: study protocol for a randomised controlled trial. Trials, 18 (1), 27.

Glick, G., Druss, B., Pina, J., Lally, C., & Conde, M. (2016). Use of mobile technology in a community mental health setting. Journal of Telemedicine and Telecare, 22 (7), 430–435.

Goodman, L. A., Thompson, K. M., Weinfurt, K., Corl, S., Acker, P., Mueser, K. T., & Rosenberg, S. D. (1999). Reliability of reports of violent victimization and posttraumatic stress disorder among men and women with serious mental illness. Journal of Traumatic Stress: Official Publication of the International Society for Traumatic Stress Studies, 12 (4), 587–599.

Gowen, K., Deschaine, M., Gruttadara, D., & Markey, D. (2012). Young adults with mental health conditions and social networking websites: seeking tools to build community. Psychiatric Rehabilitation Journal, 35 (3), 245–250.

Guntuku, S. C., Yaden, D. B., Kern, M. L., Ungar, L. H., & Eichstaedt, J. C. (2017). Detecting depression and mental illness on social media: an integrative review. Current Opinion in Behavioral Sciences, 18 , 43–49.

Haker, H., Lauber, C., & Rössler, W. (2005). Internet forums: a self-help approach for individuals with schizophrenia? Acta Psychiatrica Scandinavica, 112 (6), 474–477.

Hamm, M. P., Newton, A. S., Chisholm, A., Shulhan, J., Milne, A., Sundar, P., Ennis, H., Scott, S. D., & Hartling, L. (2015). Prevalence and effect of cyberbullying on children and young people: a scoping review of social media studies. JAMA Pediatrics, 169 (8), 770–777.

Hansen, C. F., Torgalsbøen, A.-K., Melle, I., & Bell, M. D. (2009). Passive/apathetic social withdrawal and active social avoidance in schizophrenia: difference in underlying psychological processes. The Journal of Nervous and Mental Disease, 197 (4), 274–277.

Highton-Williamson, E., Priebe, S., & Giacco, D. (2015). Online social networking in people with psychosis: a systematic review. International Journal of Social Psychiatry, 61 (1), 92–101.

Hilty, D. M., Chan, S., Torous, J., Luo, J., & Boland, R. J. (2019). Mobile health, smartphone/device, and apps for psychiatry and medicine: competencies, training, and faculty development issues. Psychiatric Clinics, 42 (3), 513–534.

Hswen, Y., Naslund, J. A., Chandrashekar, P., Siegel, R., Brownstein, J. S., & Hawkins, J. B. (2017). Exploring online communication about cigarette smoking among Twitter users who self-identify as having schizophrenia. Psychiatry Research, 257 , 479–484.

Hswen, Y., Naslund, J. A., Brownstein, J. S., & Hawkins, J. B. (2018a). Monitoring online discussions about suicide among Twitter users with schizophrenia: exploratory study. JMIR Mental Health, 5 (4), e11483.

Hswen, Y., Naslund, J. A., Brownstein, J. S., & Hawkins, J. B. (2018b). Online communication about depression and anxiety among twitter users with schizophrenia: preliminary findings to inform a digital phenotype using social media. Psychiatric Quarterly, 89 (3), 569–580.

Indian, M., & Grieve, R. (2014). When Facebook is easier than face-to-face: social support derived from Facebook in socially anxious individuals. Personality and Individual Differences, 59 , 102–106.

Jain, S. H., Powers, B. W., Hawkins, J. B., & Brownstein, J. S. (2015). The digital phenotype. Nature Biotechnology, 33 (5), 462–463.

Kiesler, S., Siegel, J., & McGuire, T. W. (1984). Social psychological aspects of computer-mediated communication. American Psychologist, 39 , 1123–1134.

Kross, E., Verduyn, P., Demiralp, E., Park, J., Lee, D. S., Lin, N., Shablack, H., Jonides, J., & Ybarra, O. (2013). Facebook use predicts declines in subjective well-being in young adults. PLoS One, 8 (8), e69841.

Lal, S., Nguyen, V., & Theriault, J. (2018). Seeking mental health information and support online: experiences and perspectives of young people receiving treatment for first-episode psychosis. Early Intervention in Psychiatry, 12 (3), 324–330.

Lin, L. Y., Sidani, J. E., Shensa, A., Radovic, A., Miller, E., Colditz, J. B., Hoffman, B. L., Giles, L. M., & Primack, B. A. (2016). Association between social media use and depression among US young adults. Depression and Anxiety, 33 (4), 323–331.

Machmutow, K., Perren, S., Sticca, F., & Alsaker, F. D. (2012). Peer victimisation and depressive symptoms: can specific coping strategies buffer the negative impact of cybervictimisation? Emotional and Behavioural Difficulties, 17 (3–4), 403–420.

Manikonda, L., & De Choudhury, M. (2017). Modeling and understanding visual attributes of mental health disclosures in social media. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 170–181.

Mead, S., Hilton, D., & Curtis, L. (2001). Peer support: a theoretical perspective. Psychiatric Rehabilitation Journal, 25 (2), 134–141.

Mereish, E. H., Sheskier, M., Hawthorne, D. J., & Goldbach, J. T. (2019). Sexual orientation disparities in mental health and substance use among Black American young people in the USA: effects of cyber and bias-based victimisation. Culture, Health & Sexuality, 21 (9), 985–998.

Miller, B. J., Stewart, A., Schrimsher, J., Peeples, D., & Buckley, P. F. (2015). How connected are people with schizophrenia? Cell phone, computer, email, and social media use. Psychiatry Research, 225 (3), 458–463.

Mittal, V. A., Tessner, K. D., & Walker, E. F. (2007). Elevated social Internet use and schizotypal personality disorder in adolescents. Schizophrenia Research, 94 (1–3), 50–57.

Moorhead, S. A., Hazlett, D. E., Harrison, L., Carroll, J. K., Irwin, A., & Hoving, C. (2013). A new dimension of health care: systematic review of the uses, benefits, and limitations of social media for health communication. Journal of Medical Internet Research, 15 (4), e85.

Naslund, J. A., & Aschbrenner, K. A. (2019). Risks to privacy with use of social media: understanding the views of social media users with serious mental illness. Psychiatric Services, 70 (7), 561–568.

Naslund, J. A., Grande, S. W., Aschbrenner, K. A., & Elwyn, G. (2014). Naturally occurring peer support through social media: the experiences of individuals with severe mental illness using YouTube. PLoS One, 9 (10), e110171.

Naslund, J. A., Aschbrenner, K. A., & Bartels, S. J. (2016). How people living with serious mental illness use smartphones, mobile apps, and social media. Psychiatric Rehabilitation Journal, 39 (4), 364–367.

Naslund, J. A., Aschbrenner, K. A., Marsch, L. A., & Bartels, S. J. (2016a). Feasibility and acceptability of Facebook for health promotion among people with serious mental illness. Digital Health, 2 , 2055207616654822.

PubMed Central   Google Scholar  

Naslund, J. A., Aschbrenner, K. A., Marsch, L. A., & Bartels, S. J. (2016b). The future of mental health care: peer-to-peer support and social media. Epidemiology and Psychiatric Sciences, 25 (2), 113–122.

Naslund, J. A., Aschbrenner, K. A., McHugo, G. J., Unützer, J., Marsch, L. A., & Bartels, S. J. (2019). Exploring opportunities to support mental health care using social media: A survey of social media users with mental illness. Early Intervention in Psychiatry, 13 (3), 405–413.

Naslund, J. A., Aschbrenner, K. A., Marsch, L. A., McHugo, G. J., & Bartels, S. J. (2018). Facebook for supporting a lifestyle intervention for people with major depressive disorder, bipolar disorder, and schizophrenia: an exploratory study. Psychiatric Quarterly, 89 (1), 81–94.

Naslund, J. A., Gonsalves, P. P., Gruebner, O., Pendse, S. R., Smith, S. L., Sharma, A., & Raviola, G. (2019). Digital innovations for global mental health: opportunities for data science, task sharing, and early intervention. Current Treatment Options in Psychiatry , 1–15.

Onnela, J.-P., & Rauch, S. L. (2016). Harnessing smartphone-based digital phenotyping to enhance behavioral and mental health. Neuropsychopharmacology, 41 (7), 1691–1696.

Orben, A., & Przybylski, A. K. (2019). The association between adolescent well-being and digital technology use. Nature Human Behaviour, 3 (2), 173–182.

Patel, V., Saxena, S., Lund, C., Thornicroft, G., Baingana, F., Bolton, P., et al. (2018). The Lancet Commission on global mental health and sustainable development. The Lancet, 392 (10157), 1553–1598.

Primack, B. A., Shensa, A., Escobar-Viera, C. G., Barrett, E. L., Sidani, J. E., Colditz, J. B., & James, A. E. (2017). Use of multiple social media platforms and symptoms of depression and anxiety: a nationally-representative study among US young adults. Computers in Human Behavior, 69 , 1–9.

Reece, A. G., & Danforth, C. M. (2017). Instagram photos reveal predictive markers of depression. EPJ Data Science, 6 (1), 15.

Reece, A. G., Reagan, A. J., Lix, K. L., Dodds, P. S., Danforth, C. M., & Langer, E. J. (2017). Forecasting the onset and course of mental illness with Twitter data. Scientific Reports, 7 (1), 13006.

Rideout, V., & Fox, S. (2018). Digital health practices, social media use, and mental well-being among teens and young adults in the U.S. Retrieved from San Francisco, CA: https://www.hopelab.org/reports/pdf/a-national-survey-by-hopelab-and-well-being-trust-2018.pdf . Accessed 10 Jan 2020.

Saha, K., Torous, J., Ernala, S. K., Rizuto, C., Stafford, A., & De Choudhury, M. (2019). A computational study of mental health awareness campaigns on social media. Translational behavioral medicine, 9 (6), 1197–1207.

Schlosser, D. A., Campellone, T., Kim, D., Truong, B., Vergani, S., Ward, C., & Vinogradov, S. (2016). Feasibility of PRIME: a cognitive neuroscience-informed mobile app intervention to enhance motivated behavior and improve quality of life in recent onset schizophrenia. JMIR Research Protocols, 5 (2).

Schlosser, D. A., Campellone, T. R., Truong, B., Etter, K., Vergani, S., Komaiko, K., & Vinogradov, S. (2018). Efficacy of PRIME, a mobile app intervention designed to improve motivation in young people with schizophrenia. Schizophrenia Bulletin, 44 (5), 1010–1020.

Schrank, B., Sibitz, I., Unger, A., & Amering, M. (2010). How patients with schizophrenia use the internet: qualitative study. Journal of Medical Internet Research, 12 (5), e70.

Schueller, S. M., Hunter, J. F., Figueroa, C., & Aguilera, A. (2019). Use of digital mental health for marginalized and underserved populations. Current Treatment Options in Psychiatry, 6 (3), 243–255.

Shatte, A. B., Hutchinson, D. M., & Teague, S. J. (2019). Machine learning in mental health: a scoping review of methods and applications. Psychological Medicine, 49 (9), 1426–1448.

Spinzy, Y., Nitzan, U., Becker, G., Bloch, Y., & Fennig, S. (2012). Does the Internet offer social opportunities for individuals with schizophrenia? A cross-sectional pilot study. Psychiatry Research, 198 (2), 319–320.

Stiglic, N., & Viner, R. M. (2019). Effects of screentime on the health and well-being of children and adolescents: a systematic review of reviews. BMJ Open, 9 (1), e023191.

Sumner, S. A., Galik, S., Mathieu, J., Ward, M., Kiley, T., Bartholow, B., et al. (2019). Temporal and geographic patterns of social media posts about an emerging suicide game. Journal of Adolescent Health, 65 (1), 94–100.

Torous, J., & Keshavan, M. (2016). The role of social media in schizophrenia: evaluating risks, benefits, and potential. Current Opinion in Psychiatry, 29 (3), 190–195.

Torous, J., Chan, S. R., Tan, S. Y.-M., Behrens, J., Mathew, I., Conrad, E. J., et al. (2014a). Patient smartphone ownership and interest in mobile apps to monitor symptoms of mental health conditions: a survey in four geographically distinct psychiatric clinics. JMIR Mental Health, 1 (1), e5.

Torous, J., Friedman, R., & Keshavan, M. (2014b). Smartphone ownership and interest in mobile applications to monitor symptoms of mental health conditions. JMIR mHealth and uHealth, 2 (1), e2.

Torous, J., Wisniewski, H., Bird, B., Carpenter, E., David, G., Elejalde, E., et al. (2019). Creating a digital health smartphone app and digital phenotyping platform for mental health and diverse healthcare needs: an interdisciplinary and collaborative approach. Journal of Technology in Behavioral Science, 4 (2), 73–85.

Trefflich, F., Kalckreuth, S., Mergl, R., & Rummel-Kluge, C. (2015). Psychiatric patients' internet use corresponds to the internet use of the general public. Psychiatry Research, 226 , 136–141.

Twenge, J. M., & Campbell, W. K. (2018). Associations between screen time and lower psychological well-being among children and adolescents: evidence from a population-based study. Preventive Medicine Reports, 12 , 271–283.

Twenge, J. M., Joiner, T. E., Rogers, M. L., & Martin, G. N. (2018). Increases in depressive symptoms, suicide-related outcomes, and suicide rates among US adolescents after 2010 and links to increased new media screen time. Clinical Psychological Science, 6 (1), 3–17.

Tynes, B. M., Willis, H. A., Stewart, A. M., & Hamilton, M. W. (2019). Race-related traumatic events online and mental health among adolescents of color. Journal of Adolescent Health, 65 (3), 371–377.

Vannucci, A., Flannery, K. M., & Ohannessian, C. M. (2017). Social media use and anxiety in emerging adults. Journal of Affective Disorders, 207 , 163–166.

Vayreda, A., & Antaki, C. (2009). Social support and unsolicited advice in a bipolar disorder online forum. Qualitative Health Research, 19 (7), 931–942.

Ventola, C. L. (2014). Social media and health care professionals: benefits, risks, and best practices. Pharmacy and Therapeutics, 39 (7), 491–520.

We Are Social. (2020). Digital in 2020. Retrieved from https://wearesocial.com/global-digital-report-2019 . Accessed 10 Jan 2020.

Webb, H., Jirotka, M., Stahl, B. C., Housley, W., Edwards, A., Williams, M., ... & Burnap, P. (2017). The ethical challenges of publishing Twitter data for research dissemination . Paper presented at the proceedings of the 2017 ACM on Web Science Conference, 339–348.

Williams, M. L., Burnap, P., & Sloan, L. (2017). Towards an ethical framework for publishing twitter data in social research: taking into account users’ views, online context and algorithmic estimation. Sociology, 51 (6), 1149–1168.

Woods, H. C., & Scott, H. (2016). # Sleepyteens: social media use in adolescence is associated with poor sleep quality, anxiety, depression and low self-esteem. Journal of Adolescence, 51 , 41–49.

Ybarra, M. L. (2004). Linkages between depressive symptomatology and internet harassment among young regular Internet users. Cyberpsychology & Behavior, 7 (2), 247–257.

Download references

Dr. Naslund is supported by a grant from the National Institute of Mental Health (U19MH113211). Dr. Aschbrenner is supported by a grant from the National Institute of Mental Health (1R01MH110965-01).

Author information

Authors and affiliations.

Department of Global Health and Social Medicine, Harvard Medical School, 641 Huntington Avenue, Boston, MA, 02115, USA

John A. Naslund

Digital Mental Health Research Consultant, Mumbai, India

Ameya Bondre

Division of Digital Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA

John Torous

Department of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA

Kelly A. Aschbrenner

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to John A. Naslund .

Ethics declarations

Conflict of interest.

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Naslund, J.A., Bondre, A., Torous, J. et al. Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice. J. technol. behav. sci. 5 , 245–257 (2020). https://doi.org/10.1007/s41347-020-00134-x

Download citation

Received : 19 October 2019

Revised : 24 February 2020

Accepted : 17 March 2020

Published : 20 April 2020

Issue Date : September 2020

DOI : https://doi.org/10.1007/s41347-020-00134-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Find a journal
  • Publish with us
  • Track your research

Ten (10) Advantages and Disadvantages of Social Media to Students

  • Post author: Edeh Samuel Chukwuemeka ACMC
  • Post published: March 3, 2024
  • Post category: Scholarly Articles

What are the impact, advantages and disadvantages of social media to students? Since the advent of Social media in late 20th century, humans who are Social animals have been inclined to make use of Social media to enjoy its numerous benefits which includes: Social networking and Communication with one another. The development of more sophisticated and enticing Social media however has made Social media become a habit amongst students. While there are numerous advantages of Social Media, its disadvantages flow in the same vein.

This article highlights these advantages and disadvantages of social media to students, and I trust that by the end of this article every reader will become acquainted with the meaning of Social media, its advantages, and disadvantages to a student.

Here are the advantages and disadvantages of social media to students

RECOMMENDED: How to become an intelligent student in school

Table of Contents

What Is Social Media?

According to Wikipedia, Social Media are interactive digitally mediated technologies that facilitate the creation or exchange of information , ideas, career interests, and other forms of expression via virtual communities.

The Merriam Webster dictionary further defines Social Media as the forms of electronic communication (such as website for social networking and micro blogging) through which users create online communities to share information, ideas, personal messages, and other contents.

The above definition implies that Social Media was created for purposes of: Sharing information, exchanging personal messages, viewing videos and images, sharing ideas, and posting. Examples of Social media includes: Whatsapp, LinkedIn, Tik tok, Twitter, Tumblr, Facebook, Instagram, Snapchat, YouTube, Quora, Telegram, Wechat, Pinterest, amongst others.

Advantages and disadvantages of social media to students

Also see: How to prepare and pass law exams

Advantages (merits) of Social Media To Students

1. Social Media aids research: Social media is beneficial to students, especially students of the university or other tertiary institutions who are charged with term paper, project, and other forms of academic activities which require research, as it aids their research.

The social media aids research through vital information provided on various social media platforms, blogs, and websites. This enables students to make a search on a particular topic and instantly get results. Also through the Social Media, such student will be able to ask questions to friends and even strangers; as there are currently some social media platforms where question and genuine answers on any particular topic or question is entertained. This will help the student in acquiring the necessary materials and information for his or her research work.

MUST READ: Best time to read and understand effectively

2. Social Media is a tool of receiving information: Nowadays, a student can barely survive without Social media. Information even to the barest minimum are usually communicated to students of tertiary institutions and above via Social media. Hence, your unavailability on Social media will mean that you are bound to miss vital information’s. However, where you are available on Social media it will be a tool of receiving information.

effects of social media to students

3. Communication: Social Media is very important to students as it helps them communicate with one another without requiring physical contact or connection. Hence through the social media, students can make friends, develop relationship, and build connection with others. This is what we refer to as networking and it is essential because it often helps students to discover opportunities while in school, not to mention where such connection may lead the student outside school.

Also see: Exceptions to the rule in Adams v Lindsell

4. Improves Learning: Social media improves learning of students as individuals, and standard of learning of a school. As an individual, through the social media a student comes across materials, articles, stories, quotes, status update, documentaries, amongst others which will make such student learn one or two important things. I for example became grammatically eloquent through words I learnt from the social media.

Same is applicable to every student who must have learnt something vital via the social media, even something as basic as personal message on social media could ensure you learn a lot each day depending on the person you are chatting with.

As an educational institution, Social Media improves the standard of learning thanks to the advent of modernized and sophisticated social media platforms which has resulted in schools introducing online classes and programmes wherein students will learn from the comfort of their home.

Also see: Best science courses to study in the university

5. Brand Development: It is often said that School should pass through you as you pass through school. Sequel to this, students are usually encouraged to start up an initiative or build a brand while in school. Social Media which boasts of a very large audience is the potent tool for students who have a brand to develop and promote such brand even without spending money.

6. Social Media helps students to express themselves in ways such as posting pictures, posting videos, creating contents, writing articles, poems, short stories, posting on blogs, making podcasts, amongst others.

how social media aid students

RECOMMENDED: How to answer law problem questions using IRAC Method

7. Networking: As already mentioned above, social media is an effective communication medium that enables interconnectivity amongst individuals and groups. This is a major advantage because it promotes networking amongst students with like mindedness.

Advantages and disadvantages of social media in relationships

It creates an avenue for new friendship and allies to be formed which in turn brings about self-discovery, self-development and human capital development in general. In order to brushup on goals and objectives, networking is quite important and that is what social media provides for a student.

Also see: Best Smartphones For Students 2024

8. Creativity: Social media as we know it is a communication channel however, it can be used for several other purposes that could be more productive and rewarding to students.

What are the advantages of using social media?

The digitization of most aspects of human endeavors has created an opportunity for students to venture into different areas of life in form of diversification. It creates an avenue for creativity.

Recommended: How To Know If Your Laptop Is Refurbished

9. Confidence: Self security is one of the major challenge most people have. Some persons are introverts and find it very challenging to freely and boldly communicate with other people face-to-face. It is sometimes considered as inferiority complex and could spur intimidation in such people.

What is the main disadvantage of social media?

This is where social media comes in to breach the gap. Since social media is a virtual interactive platform, anyone could freely interact with who ever they want not minding the numbers. They are more confident it such situations and are able to effectively share their opinions on substantive matters.

10. Self Evaluation: Because no one lives and survives in isolation, the concept of the world being a global village is affirmed by social connectivity. As people interact on social media platforms and share valuable ideas, they get to do some self evaluation on themselves and know areas they need to improve on and how to effectively achieve such improvement.

This is one of the major advantages of social media because the absence of such platform might leave one in the dark as to the trending phenomenon.

Recommended: Countries With The Lowest Inflation In The World 2023: Top 10

Disadvantages (Demerits) of Social Media To Students

The following are the disadvantages of Social media to students:

1. Social Media is distractive: A wise man once said that “ Distraction leads to destruction.” Thus via the Social Media a whole lot of students become distracted, and this often leads to the destruction of their academic excellence; which is the major reason why they are in school.

2. Social Media is addictive: This flows from the fact that Social Media distracts students as a result of their overreliance on it. This overreliance makes students become addicted to social media, and this will have a negative effect on such student within and outside school. This is the reason why you may see a student pressing phone in a crucial meeting or chatting on Social Media while in Church.

Also see: How to become a successful lawyer in your area of Jurisdiction

3. Leads to poor time management: Time is of essence in school where there is always an academic calendar which must be adhered to. Failure to work alongside this calendar is detrimental to the student’s bid to move into the next class. This is why time management is very essential for students in school. However, Social Media impedes time Management as you could see a student spend hours on Social Media forgetting all other thing he or she was meant to do.

4. Cyber bullying: One devastating disadvantage of Social Media is Cyber bullying. Cyber bullying is the use of electronic communication to bully a person, typically by sending messages of intimidating or threatening nature. Cyber bullying is prevalent on Social Media, and has led to numerous cases of students taking their own lives.

5. Social Media makes students Lazy: Social Media makes students lazy as most students will rather stay at home and copy and paste the opinion of the author of an article rather than go to the library to make findings, enquires, and formulate an independent opinion on such topic or subject of discourse.

merits and demerits of social media to students

6. Social Media facilitates Criminal activities: Social Media induces students to be either victims or perpetrators of fraudulent activities. There have been numerous cases of students who have been duped online, resulting in them becoming stranded to cope with the financial demands of school.

On the other hand, Social Media has induced some students to become perpetrators of fraudulent activities of scamming fellow students, lecturers or citizens, and in no mean time leading to such student losing focus in school activities, and dropping out in the process.

Recommended: Which Country Is More Powerful/Stronger, Russia or USA? (Comparison)

7. Fake news: The possibilities and opportunities available on social media for students are quite enormous however, there are quite a level of exposure to spurious information out there for students consumption and it in turn disabuse their mind on the order of things while reshaping their mindset on a negative trend. It is quite a disadvantage because it seem to be very prevalent in recent time.

The rate at which such information spread even when it can’t be easily verified, students consume these information without even making reasonable effort to verify it’s authenticity.

Also see: Differences Between Bookkeeping and Accounting

8. Hacking: Cyber phishing and system interruptions is also another major disadvantage of social media used by students as it exposes the students to online hackers and fraudsters who are out there with malicious intent to take undue advantage of such student with vulnerable exposure on the cyber space.

It is quite regrettable as the level of security system on some of these social media sites are not strong enough to ensure privacy for students using the platforms.

Also see: Salary of lawyers in the United States of America

9. Fake News: The possibilities and opportunities available on social media for students are quite enormous however, there are quite a level of exposure to spurious information out there for students consumption and it in turn disabuse their mind on the order of things while reshaping their mindset on a negative trend. It is quite a disadvantage because it seem to be very prevalent in recent time.

What is the disadvantage of the impact of social media on the students?

The rate at which such information spread even when it can’t be easily verified,  students consume these information without even making reasonable effort to verify it’s authenticity.

10. Hacking: Cyber phishing and system interruptions is also another major disadvantage of social media used by students as it exposes the students to online hackers and fraudsters who are out there with malicious intent to take undue advantage of such student with vulnerable exposure on the cyber space.

What are five disadvantages of using social media 5 points?

Recommended: Best Ways To Make Money From An App

In conclusion, while there are numerous disadvantages of Social Media to students, its advantages seem to outweigh its disadvantages. I therefore submit and urge students to be disciplined and courteous in their use of Social Media. This way they will be able to maximize the benefits of social media rather than fall prey to its disadvantages.

advantages and disadvantages of social media for students research paper

Edeh Samuel Chukwuemeka, ACMC, is a lawyer and a certified mediator/conciliator in Nigeria. He is also a developer with knowledge in various programming languages. Samuel is determined to leverage his skills in technology, SEO, and legal practice to revolutionize the legal profession worldwide by creating web and mobile applications that simplify legal research. Sam is also passionate about educating and providing valuable information to people.

This Post Has 3 Comments

advantages and disadvantages of social media for students research paper

Thanks very much for answering my question

advantages and disadvantages of social media for students research paper

I think social media can be a great way for students to stay connected with their friends and family, but it can also be a distraction.

Comments are closed.

Vittana.org

23 Biggest Advantages and Disadvantages of Social Media

Social media has become an integral component of modern life. We use the various platforms in this industry to connect with friends, chat with family members, and catch up on the current events happening in our world. Over 70% of Americans have at least one profile, and over 3 billion people around the globe are counted as social media users.

The growth of social media over the past decade has been staggering. The participation rate for this industry in 2005 was only 5%. Most people didn’t even know what it was at the time, and for those who did, the option to create a MySpace page usually meant fancy backgrounds and personal playlists more than personal communication.

We can even go further back to the invention of blogging on the Internet for the first real taste of social media. The first accounts began appearing in the 1980s, and then free platforms like Blogger mixed with chat rooms from AOL and others to create new social opportunities. Now we have Facebook, Twitter, and many more.

The advantages and disadvantages of social media are many, so here are the critical points to review in each area.

List of the Advantages of Social Media

1. It is easier to carry out research work using social media. Today’s social media platforms are a fantastic study tool that students can use. These platforms make it possible to ask challenging questions that would be difficult to solve on one’s own. It is also an easier way to create group discussions or study opportunities when people are far away from one another. Students even have the option to post their research work online to help educate others on specific topics.

If you have a question that needs to get answered, a simple status update with your family and friends is usually enough to get what you need.

2. Social media can boost individual self-esteem levels. Modern social media might feel toxic to some individuals, but it can also be a place where everyone can express themselves freely. These platforms provide ways to join groups or fan pages where shared interests become a reflection of each person’s unique personality. It offers a way to embrace empowerment because it communicates that each opinion counts. This advantage can lead to a significant boost in personal self-esteem.

When someone feels confident because of the online interactions that happen on social media platforms, it is a character trait that transfers to physical life. Many people can pursue what they’re passionate about today because of the positive feedback they received with this tool.

3. It creates more equality in today’s world. When people have differing social, economic, or physical traits, then society naturally limits a person’s ability to interact at the same level as others when they have negative traits in those areas. Even if you are in a wheelchair, the presence of a curb to make you stand out in the general public. Social media can work to illuminate these stigmas.

Anyone with any disability can perform all of the activities that their peers can accomplish online because of social media. This advantage makes people feel like they belong to their communities instead of being separated from them.

4. Social media can help people to find meaningful employment opportunities. Social media has become a go-to resource for employers who need help. Each community has several jobs posted and applied for because of the tools that are available in this industry. These jobs can be full-time positions, part-time, volunteer, or internships. Contract jobs are available all of the time with this resource. That means each user has the option to create a unique profile that features their skills and interests.

You can find a job anywhere in the world if you’re willing to embrace self-employment because of the benefits that social media provides.

5. You can stay up-to-date on current trends and technology. We are living in an era where rapid technological advancements occur. The tools that we use today are items that were only a part of the imagination a mere 20 years ago. When we take the time to embrace the advantages of social media, then we get to use these widely available technologies that can benefit the world in numerous ways. Social media helps us to stay informed of the natural evolutionary processes of each industry.

This advantage also applies to current events. We can quickly find out what is happening in our communities, schools, workplaces, states, and countries. It is an essential way to equip ourselves with adequate knowledge of what is happening around us. This benefit helps us to make informed and empowered decisions.

6. Law enforcement can use social media to capture criminals. Law enforcement agencies in the United States say that social media is a tool that helps them to solve crimes faster. 85% of American police departments use this tool as a way to find suspects. These platforms are also instrumental in the prosecution and conviction of several criminals, including professional athletes charged with inappropriate activity with minors.

When we are willing to be truthful with one another, social media gives us a variety of ways to keep our neighborhoods and communities safer.

7. Social media gives us opportunities to start making new friends. According to research published by Pew Internet, 93% of adults say that they use Facebook to connect with family. 91% are using it to stay in touch with their current friends, while 87% say that the platform helps them catch up with the people they know from their past. Over half of the respondents to this project stated that they use the various social media outlets to make new friends, even if they know that they won’t be meeting those people in real life.

One of the reasons why we focus on these connections is because it allows us to feel like we are a part of each person’s life. 70% of teams that use social media say that it helps them to feel more connected to the emotions that we all experience every day.

8. Businesswomen receive empowerment because of social media. When we look at women CEOs in the Fortune 500, they are outnumbered by their male counterparts by a ratio of 10 to 1 in most years. Finding ways to network with each other and feel like an impossible task when it seems like the cards are stacked against you from the very start. Businesswomen have found that social media can empower them to make better decisions because they can stay connected with other entrepreneurs who are like them.

Women dominate the social media spectrum. They are 80% of Pinterest users, 70% of Snapchat users, and 68% of Instagram users. Men are also in the minority on Facebook and Twitter. Women use these tools to have business chats, create global connections, and receive peer-related knowledge.

9. Social media has the power to increase a person’s quality of life. The power of social media can be experienced on the individual level in a variety of ways. It can improve a person’s overall life satisfaction, help with stroke recovery, or create gains in memory retention. When someone has a large online social group, then there is typically a higher level of well-being experienced.

Friends on social media can also help people to stay accountable for their health and wellness goals. This benefit promotes more exercise, improved nutrition, weight loss, and other lifestyle habit changes that may be desirable.

10. Social media can facilitate face-to-face interactions. People often use social media as a way to network at face-to-face events. It’s a chance to get to know others before having personal or business meetings. Messaging opportunities that occur on these platforms can lead to real-life interactions because plans get made online, and then implemented off-line.

The average person will see their close friends in person over 200 days each year while messaging them an average of 39 days annually.

11. The use of social media can increase voter participation rates. Facebook reports that people are more likely to vote if they see others are doing the same thing. 35% of students said that the status updates from their family members and friends led them to vote in the 2016 presidential election in the United States. That means this influence is even higher than what television, radio, and direct mail provide.

12. Social media can help to remove social stigmas. Society contains several stigmas that the average person doesn’t think about until there are direct impacts on their life. Various campaigns are running right now to reduce the bias that exists surrounding learning disabilities, mental health concerns, and health issues that people face. These platforms have been useful in the reduction of homophobia, lowering HIV rates, and promoting educational opportunities.

We can use social media to tell our stories. The lessons that we’ve learned in life can provide mentorship opportunities for other people, even if we’ve never met them before. Although some people will always try to troll others, the benefits often far outweigh whatever disadvantages we might encounter.

List of the Disadvantages of Social Media

1. Social media enables the spreading of false information rapidly. Over 60% of Twitter users say that they have encountered news stories on that platform that eventually turned out to be false. About one in five people say that they had retweeted or posted something that they later discovered was false. Social media provides the advantage of giving information to all of us quickly, but the lies typically spread much faster than the truth. The reason why this happens is that we create echo chambers for ourselves with this tool.

When we surround ourselves with information that supports our personal opinions about the world, then the posts that we see on social media reinforce each bias that we have. Instead of seeking diversity, these platforms end up encouraging more segregation.

2. These platforms expose people to government intrusions. About half of the people that use social media right now say that they have problems trying to manage the privacy settings for the profile. Over 80% say that they don’t feel secure when using the sites to share private information. This disadvantage applies to corporate and government intrusions because of all of the data that we share on these platforms.

The U.S. government submitted over 43,000 requests for data from Facebook and Twitter in 2015. About four out of every five of them were honored by these organizations. The National Security Agency reportedly can monitor private social messages by entering a specific username into their system. That means what we share can go to everyone.

3. Social media causes student grades to drop. Students who use social media heavily tend to have lower grades at every level of education when compared to those who avoid these platforms. Over 30% of teens say that using social media during their homework reduces the quality of their studies, resulting in grades that were 20% lower. Students at the college or university level experience a 0.12 drop in GPA for every 93 minutes above the average amount of time spent on Facebook per day.

Students who identify as being heavy social media users have an average GPA of 3.06 across all grades. Those who don’t use these platforms regularly have an average GPA of 3.82.

4. These platforms can lead to offline relationship problems. About one in every three social media users reports that they have had an argument or fight with a friend or family member because of something that happened online. Over-using social media can potentially decrease a person’s success in real-life relationships as they get older because of how it can hinder communication development. People are less likely to pick up on nonverbal communication signals when messaging has been their primary form of talking to other people.

Active social media use can lead to higher levels of platform-related conflict between friends and romantic partners. Higher risks of conflict, infidelity, and divorce are all associated with above-average active users.

5. Social media can encourage people to waste a lot of time. The average person spends almost two hours every day browsing through their social media feeds. This figure represents over one-quarter of the total time that people spend online every day. When asked about what their biggest waste of time was every day, almost 40% of respondents referred to social media. That placed it above watching TV at 23% or playing fantasy sports at 25%.

When the average person received a notification about a new social media activity, then it takes up to 25 minutes for them to return to their original tasks. And 30% of these instances, it can take up to two hours to fully return their attention to what they were doing.

6. It can harm an individual’s employment prospects or job stability. Social media gives all of us an opportunity to express ourselves freely. That benefit doesn’t always translate into life stability. Job recruiters and hiring managers report feeling negative reactions to profanity, poor spelling and grammar, references to illegal drugs, and sexualized content when reviewing the profiles of their applicants. 55% say that they reconsidered someone based on what they saw of a person’s online activities.

This disadvantage applies to people from all walks of life. Former MLB pitcher Curt Schilling was terminated from ESPN because of comments he left on Facebook about transgender individuals. This action followed a suspension he’d received earlier for comparing radical Muslims to the Nazis.

7. Social media can be used to commit or promote criminal activity. Gangs are known to use social media as a way to recruit younger members. Terrorist organizations create propaganda to accomplish the same goal. These platforms are useful in the coordination of violent crimes or to threaten other people. Sex offenders use websites like this to find victims to exploit.

Almost 80% of burglars admit that they use several different social media platforms to select the properties of their victims. Over half of them say that they track that person’s posting status or current whereabouts to know when they can enter a home or business safely. Some criminals have even started live streaming their activities.

8. It places the lives of activists, journalists, and military personnel in danger. When military personnel use social media as a way to check in with location-based services, the activity can expose their current position. This data can then endanger certain operations. ISIS used these platforms to locate a freelance journalist who reported what life was like under their regime. Several bloggers in Bangladesh posted their thoughts about atheism online only to be killed by zealots who opposed their opinion.

This disadvantage happens all over the world. A blogger in Mexico was found murdered by a cartel with a note stating that the individual was reporting things on social networks.

9. Social media can encourage cyberbullying activities. Over half of students today say that they have encountered cyberbullying online directed at them at least once in the past year. 84% of the incidents occurred on Facebook. What makes this disadvantage such a devastating experience is the fact that the information is available all day, every day on a public forum. There is no way to take a break from it, and you don’t even need to be present for people to start this behavior.

Middle school students who are victims of cyberbullying are almost twice as likely to attempt suicide when compared to those who are not. Adults who experience this disadvantage can experience higher levels of depression, anxiety, and suicidal ideation.

10. The people who use social media are prone to isolation. Social media might provide opportunities for personal connections when used correctly, but it can also increase feelings of disconnect. This disadvantage is especially powerful for young people with disabilities. It places them in a higher risk category for eating disorders, low self-esteem, and clinical depression. Passively consuming social media content, including the scanning of posts without leaving a comment, is directly related to personal feelings of loneliness.

11. Children can endanger themselves on social media without realizing it. Kids don’t always understand the viral nature of social media posts. Even though young people traditionally are more tech-savvy than their parents and previous generations, social media is a different beast. Children and teens see activities that happen online that seem fun, and so they attempt to duplicate them in real life. Some of these incidents even happen accidentally.

Over 600 police officers once had to disperse a teen’s birthday party in the Netherlands because a private invitation ended up being public and going viral. Over 30,000 people showed up for the event. A similar issue happened in Los Angeles that resulted in the host of the party being hospitalized after an attack.

Social media gives us the opportunity to create an online extension of our physical lives. It creates more connections while facilitating communication. That’s why the use of Facebook, Twitter, Pinterest, LinkedIn, and Instagram have risen from about 26% in 2008 on all platforms to over 80% today.

There are always benefits of social networking to find if we’re willing to look for them. These online communities promote increased interaction with our family and friends, educational support from teachers, information about current events, and opportunities to create political or social change. It disseminates useful information to us all quickly.

The advantages and disadvantages of social media can also swing in the other direction. It can prevent face-to-face communication for some people, alter behavioral patterns, and expose our youth to potential predators. Even when individuals use it to spread false information, we still decide what we want to focus on with this platform. If we can stay disciplined in its use, then social media is a tremendous asset to the world.

REVIEW article

On the advantages and disadvantages of choice: future research directions in choice overload and its moderators.

Raffaella Misuraca

  • 1 Department of Political Science and International Relations (DEMS), University of Palermo, Palermo, Italy
  • 2 Atkinson Graduate School of Management, Willamette University, Salem, OR, United States
  • 3 Department of Psychology, Educational Science and Human Movement, University of Palermo, Palermo, Italy

Researchers investigating the psychological effects of choice have provided extensive empirical evidence that having choice comes with many advantages, including better performance, more motivation, and greater life satisfaction and disadvantages, such as avoidance of decisions and regret. When the decision task difficulty exceeds the natural cognitive resources of human mind, the possibility to choose becomes more a source of unhappiness and dissatisfaction than an opportunity for a greater well-being, a phenomenon referred to as choice overload. More recently, internal and external moderators that impact when choice overload occurs have been identified. This paper reviews seminal research on the advantages and disadvantages of choice and provides a systematic qualitative review of the research examining moderators of choice overload, laying out multiple critical paths forward for needed research in this area. We organize this literature review using two categories of moderators: the choice environment or context of the decision as well as the decision-maker characteristics.

Introduction

The current marketing orientation adopted by many organizations is to offer a wide range of options that differ in only minor ways. For example, in a common western grocery store contains 285 types of cookies, 120 different pasta sauces, 175 salad-dressing, and 275 types of cereal ( Botti and Iyengar, 2006 ). However, research in psychology and consumer behavior has demonstrated that when the number of alternatives to choose from becomes excessive (or superior to the decision-makers’ cognitive resources), choice is mostly a disadvantage to both the seller and the buyer. This phenomenon has been called choice overload and it refers to a variety of negative consequences stemming from having too many choices, including increased choice deferral, switching likelihood, or decision regret, as well as decreased choice satisfaction and confidence (e.g., Chernev et al., 2015 ). Choice overload has been replicated in numerous fields and laboratory settings, with different items (e.g., jellybeans, pens, coffee, chocolates, etc.), actions (reading, completing projects, and writing essays), and populations (e.g., Chernev, 2003 ; Iyengar et al., 2004 ; Schwartz, 2004 ; Shah and Wolford, 2007 ; Mogilner et al., 2008 ; Fasolo et al., 2009 ; Misuraca and Teuscher, 2013 ; Misuraca and Faraci, 2021 ; Misuraca et al., 2022 ; see also Misuraca, 2013 ). Over time, we have gained insight into numerous moderators of the choice overload phenomena, including aspects of the context or choice environment as well as the individual characteristics of the decision-maker (for a detailed review see Misuraca et al., 2020 ).

The goal of this review is to summarize important research findings that drive our current understanding of the advantages and disadvantages of choice, focusing on the growing body of research investigating moderators of choice overload. Following a discussion of the advantages and disadvantages of choice, we review the existing empirical literature examining moderators of choice overload. We organize this literature review using two categories of moderators: the choice environment or context of the decision as well as the decision-maker characteristics. Finally, based on this systematic review of research, we propose a variety of future research directions for choice overload investigators, ranging from exploring underlying mechanisms of choice overload moderators to broadening the area of investigation to include a robust variety of decision-making scenarios.

Theoretical background

The advantages of choice.

Decades of research in psychology have demonstrated the many advantages of choice. Indeed, increased choice options are associated with increase intrinsic motivation ( Deci, 1975 ; Deci et al., 1981 ; Deci and Ryan, 1985 ), improved task performance ( Rotter, 1966 ), enhanced life satisfaction ( Langer and Rodin, 1976 ), and improved well-being ( Taylor and Brown, 1988 ). Increased choice options also have the potential to satisfy heterogeneous preferences and produce greater utility ( Lancaster, 1990 ). Likewise, economic research has demonstrated that larger assortments provide a higher chance to find an option that perfectly matches the individual preferences ( Baumol and Ide, 1956 ). In other words, with larger assortments it is easier to find what a decision-maker wants.

The impact of increased choice options extends into learning, internal motivation, and performance. Zuckerman et al. (1978) asked college students to solve puzzles. Half of the participants could choose the puzzle they would solve from six options. For the other half of participants, instead, the puzzle was imposed by the researchers. It was found that the group free to choose the puzzle was more motivated, more engaged and exhibited better performance than the group that could not choose the puzzle to solve. In similar research, Schraw et al. (1998) asked college students to read a book. Participants were assigned to either a choice condition or a non-choice condition. In the first one, they were free to choose the book to read, whereas in the second condition the books to read were externally imposed, according to a yoked procedure. Results demonstrated the group that was free to make decisions was more motivated to read, more engaged, and more satisfied compared to the group that was not allowed to choose the book to read ( Schraw et al., 1998 ).

These effects remain consistent with children and when choice options are constrained to incidental aspects of the learning context. In the study by Cordova and Lepper (1996) , elementary school children played a computer game designed to teach arithmetic and problem-solving skills. One group could make decisions about incidental aspects of the learning context, including which spaceship was used and its name, whereas another group could not make any choice (all the choices about the game’s features were externally imposed by the experimenters). The results demonstrated that the first group was more motivated to play the game, more engaged in the task, learned more of the arithmetical concepts involved in the game, and preferred to solve more difficult tasks compared to the second group.

Extending benefits of choice into health consequences, Langer and Rodin (1976) examined the impact that choice made in nursing home patients. In this context, it was observed that giving patients the possibility to make decisions about apparently irrelevant aspects of their life (e.g., at what time to watch a movie; how to dispose the furniture in their bedrooms, etc.), increased psychological and physiological well-being. The lack of choice resulted, instead, in a state of learned helplessness, as well as deterioration of physiological and psychological functions.

The above studies lead to the conclusion that choice has important advantages over no choice and, to some extent, limited choice options. It seems that providing more choice options is an improvement – it will be more motivating, more satisfying, and yield greater well-being. In line with this conclusion, the current orientation in marketing is to offer a huge variety of products that differ only in small details (e.g., Botti and Iyengar, 2006 ). However, research in psychology and consumer behavior demonstrated that when the number of alternatives to choose from exceeds the decision-makers’ cognitive resources, choice can become a disadvantage.

The disadvantages of choice

A famous field study conducted by Iyengar and Lepper (2000) in a Californian supermarket demonstrated that too much choice decreases customers’ motivation to buy as well as their post-choice satisfaction. Tasting booths were set up in two different areas of the supermarket, one of which displayed 6 different jars of jam while the other displayed 24 options, with customers free to taste any of the different flavors of jam. As expected, the larger assortment attracted more passers-by compared to the smaller assortment; Indeed, 60% of passers-by stopped at the table displaying 24 different options, whereas only 40% of the passers-by stopped at the table displaying the small variety of 6 jams. This finding was expected given that more choice options are appealing. However, out of the 60% of passers-by who stopped at the table with more choices, only 3% of them decided to buy jam. Conversely, 30% of the consumers who stopped at the table with only 6 jars of jam decided to purchase at least one jar. Additionally, these customers expressed a higher level of satisfaction with their choices, compared to those who purchased a jar of jam from the larger assortment. In other words, it seems that too much choice is at the beginning more appealing (attracts more customers), but it decreases the motivation to choose and the post-choice satisfaction.

This classic and seminal example of choice overload was quickly followed by many replications that expanded the findings from simple purchasing decisions into other realms of life. For example, Iyengar and Lepper (2000) , asked college students to write an essay. Participants were randomly assigned to one of the following two experimental conditions: limited-choice condition, in which they could choose from a list of six topics for the essay, and extensive-choice condition, in which they could choose from a list of 30 different topics for the essay. Results showed that a higher percentage of college students (74%) turned in the essay in the first condition compared to the second condition (60%). Moreover, the essays written by the students in the limited-choice conditions were evaluated as being higher quality compared to the essays written by the students in the extensive choice condition. In a separate study, college students were asked to choose one chocolate from two randomly assigned choice conditions with either 6 or 30 different chocolates. Those participants in the limited choice condition reporting being more satisfied with their choice and more willing to purchase chocolates at the end of the experiment, compared to participants who chose from the larger assortment ( Iyengar and Lepper, 2000 ).

In the field of financial decision-making, Iyengar et al. (2004) analyzed 800,000 employees’ decisions about their participation in 401(k) plans that offered from a minimum of 2 to a maximum of 59 different fund options. The researchers observed that as the fund options increased, the participation rate decreased. Specifically, plans offering less than 10 options had the highest participation rate, whereas plans offering 59 options had the lowest participation rate.

The negative consequences of having too much choice driven by cognitive limitations. Simon (1957) noted that decision-makers have a bounded rationality. In other words, the human mind cannot process an unlimited amount of information. Individuals’ working memory has a span of about 7 (plus or minus two) items ( Miller, 1956 ), which means that of all the options to choose from, individuals can mentally process only about 7 alternatives at a time. Because of these cognitive limitations, when the number of choices becomes too high, the comparison of all the available items becomes cognitively unmanageable and, consequently, decision-makers feel overwhelmed, confused, less motivated to choose and less satisfied (e.g., Iyengar and Lepper, 2000 ). However, a more recent meta-analytic work [ Chernev et al., 2015 : see also Misuraca et al. (2020) ] has shown that choice overload occurs only under certain conditions. Many moderators that mitigate the phenomenon have been identified by researchers in psychology and consumer behavior (e.g., Mogilner et al., 2008 ; Misuraca et al., 2016a ). In the next sections, we describe our review methodology and provide a detailed discussion of the main external and internal moderators of choice overload.

Literature search and inclusion criteria

Our investigation consisted of a literature review of peer-reviewed empirical research examining moderators of choice overload. We took several steps to locate and identify eligible studies. First, we sought to establish a list of moderators examined in the choice overload literature. For this, we referenced reviews conducted by Chernev et al. (2015) , McShane and Böckenholt (2017) , as well as Misuraca et al. (2020) and reviewed the references sections of the identified articles to locate additional studies. Using the list of moderators generated from this examination, we conducted a literature search using PsycInfo (Psychological Abstracts), EBSCO and Google Scholar. This search included such specific terms such as choice set complexity, visual preference heuristic, and choice preference uncertainty, as well as broad searches for ‘choice overload’ and ‘moderator’.

We used several inclusion criteria to select relevant articles. First, the article had to note that it was examining the choice overload phenomena. Studies examining other theories and/or related variables were excluded. Second, to ensure that we were including high-quality research methods that have been evaluated by scholars, only peer-reviewed journal articles were included. Third, the article had to include primary empirical data (qualitative or quantitative). Thus, studies that were conceptual in nature were excluded. This process yielded 49 articles for the subsequent review.

Moderators of choice overload

Choice environment and context.

Regarding external moderators of choice overload, several aspects about the choice environment become increasingly relevant. Specifically, these include the perceptual attributes of the information, complexity of the set of options, decision task difficulty, as well as the presence of brand names.

Perceptual characteristics

As Miller (1956) noted, humans have “channel capacity” for information processing and these differ for divergent stimuli: for taste, we have a capacity to accommodate four; for tones, the capacity increased to six; and for visual stimuli, we have the capacity for 10–15 items. Accordingly, perceptual attributes of choice options are an important moderator of choice overload, with visual presentation being one of the most important perceptual attributes ( Townsend and Kahn, 2014 ). The visual preference heuristic refers to the tendency to prefer a visual rather than verbal representation of choice options, regardless of assortment size ( Townsend and Kahn, 2014 ). However, despite this preference, visual presentations of large assortments lead to suboptimal decisions compared to verbal presentations, as visual presentations activate a less systematic decision-making approach ( Townsend and Kahn, 2014 ). Visual presentation of large choice sets is also associated with increased perceptions of complexity and likelihood of decisions deferral. Visual representations are particularly effective with small assortments, as they increase consumers’ perception of variety, improve the likelihood of making a choice, and reduce the time spent examining options ( Townsend and Kahn, 2014 ).

Choice set complexity

Choice set complexity refers to a wide range of aspects of a decision task that affect the value of the available choice options without influencing the structural characteristics of the decision problem ( Payne et al., 1993 ). Thus, choice set complexity does not influence aspects such as the number of options, number of attributes of each option, or format in which the information is presented. Rather, choice set complexity concerns factors such as the attractiveness of options, the presence of a dominant option, and the complementarity or alignability of the options.

Choice set complexity increases when the options include higher-quality, more attractive options ( Chernev and Hamilton, 2009 ). Indeed, when the variability in the relative attractiveness of the choice alternatives increases, the certainty about the choice and the satisfaction with the task increase ( Malhotra, 1982 ). Accordingly, when the number of attractive options increases, more choice options led to a decline in consumer satisfaction and likelihood of a decision being made, but satisfaction increases and decision deferral decreased when the number of unattractive options increases ( Dhar, 1997 ). This occurs when increased choice options make the weakness and strengths of attractive and unattractive options more salient ( Chan, 2015 ).

Similarly, the presence of a dominant option simplifies large choice sets and increased the preference for the chosen option; however, the opposite effect happens in small choice sets ( Chernev, 2003 ). Choice sets containing an ideal option have been associated with increased brain activity in the areas involved in reward and value processing as well as in the integration of costs and benefits (striatum and the anterior cingulate cortex; Reutskaja et al., 2018 ) which could explain why larger choice sets are not always associated with choice overload. As Misuraca et al. (2020 , p. 639) noted, “ the benefits of having an ideal item in the set might compensate for the costs of overwhelming set size in the bounded rational mind of humans . ”

Finally, choice set complexity is impacted by the alignability and complementarity of the attributes that differentiate the options ( Chernev et al., 2015 ). When unique attributes of options exist within a choice set, complexity and choice overload increase as the unique attributes make comparison more difficult and trade-offs more salient. Indeed, feature alignability and complementarity (meaning that the options have additive utility and need to be co-present to fully satisfy the decision-maker’s need) 1 have been associated with decision deferral ( Chernev, 2005 ; Gourville and Soman, 2005 ) and changes in satisfaction ( Griffin and Broniarczyk, 2010 ).

Decision task difficulty

Decision task difficulty refers to the structural characteristics of a decision problem; unlike choice set complexity, decision task difficulty does not influence the value of the choice options ( Payne et al., 1993 ). Decision task difficulty is influenced by the number of attributes used to describe available options, decision accountability, time constraints, and presentation format.

The number of attributes used to describe the available options within an assortment influences decision task difficulty and choice overload ( Hoch et al., 1999 ; Chernev, 2003 ; Greifeneder et al., 2010 ), such that choice overload increases with the number of dimensions upon which the options differ. With each additional dimension, decision-makers have another piece of information that must be attended to and evaluated. Along with increasing the cognitive complexity of the choice, additional dimensions likely increase the odds that each option is inferior to other options on one dimension or another (e.g., Chernev et al., 2015 ).

When individuals have decision accountability or are required to justify their choice of an assortment to others, they tend to prefer larger assortments; However, when individuals must justify their particular choice from an assortment to others, they tend to prefer smaller choice sets ( Ratner and Kahn, 2002 ; Chernev, 2006 ; Scheibehenne et al., 2009 ). Indeed, decision accountability is associated with decision deferral when choice sets are larger compared to smaller ( Gourville and Soman, 2005 ). Thus, decision accountability influences decision task difficulty differently depending on whether an individual is selecting an assortment or choosing an option from an assortment.

Time pressure or constraint is an important contextual factor for decision task difficulty, choice overload, and decision regret ( Payne et al., 1993 ). Time pressure affects the strategies that are used to make decisions as well as the quality of the decisions made. When confronted with time pressure, decision-makers tend to speed up information processing, which could be accomplished by limiting the amount of information that they process and use ( Payne et al., 1993 ; Pieters and Warlop, 1999 ; Reutskaja et al., 2011 ). Decision deferral becomes a more likely outcome, as is choosing at random and regretting the decision later ( Inbar et al., 2011 ).

The physical arrangement and presentation of options and information affect information perception, processing, and decision-making. This moderates the effect of choice overload because these aspects facilitate or inhibit decision-makers’ ability to process a greater information load (e.g., Chernev et al., 2015 ; Anderson and Misuraca, 2017 ). The location of options and structure of presented information allow the retrieval of information about the options, thus allowing choosers to distinguish and evaluate various options (e.g., Chandon et al., 2009 ). Specifically, organizing information into “chunks” facilitates information processing ( Miller, 1956 ) as well as the perception of greater variety in large choice sets ( Kahn and Wansink, 2004 ). Interestingly, these “chunks” do not have to be informative; Mogilner et al. (2008) found that choice overload was mitigated to the same extent when large choice sets were grouped into generic categories (i.e., A, B, etc.) as when the categories were meaningful descriptions of characteristics.

Beyond organization, the presentation order can facilitate or inhibit decision-makers cognitive processing ability. Levav et al. (2010) found that choice overload decreased and choice satisfaction increased when smaller choice sets were followed by larger choice sets, compared to the opposite order of presentation. When sets are highly varied, Huffman and Kahn (1998) found that decision-makers were more satisfied and willing to make a choice when information was presented about attributes (i.e., price and characteristics) rather than available alternatives (i.e., images of options). Finally, presenting information simultaneously, rather than sequentially, increases decision satisfaction ( Mogilner et al., 2013 ), likely due to decision-makers choosing among an available set rather than comparing each option to an imaged ideal option.

Brand names

The presence of brand names is an important moderator of choice overload. As recently demonstrated by researchers in psychology and consumer behavior, choice overload occurs only when options are not associated with brands, choice overload occurs when the same choice options are presented without any brand names ( Misuraca et al., 2019 , 2021a ). When choosing between 6 or 24 different mobile phones, choice overload did not occur in the condition in which phones were associated with a well-known brand (i.e., Apple, Samsung, Nokia, etc.), although it did occur when the same cell phones were displayed without information about their brand. These findings have been replicated with a population of adolescents ( Misuraca et al., 2021a ).

Decision-maker characteristics

Beyond the choice environment and context, individual differences in decision-maker characteristics are significant moderators of choice overload. Several critical characteristics include the decision goal as well as an individual’s preference uncertainty, affective state, decision style, and demographic variables such as age, gender, and cultural background (e.g., Misuraca et al., 2021a ).

Decision goal

A decision goal refers to the extent to which a decision-maker aims to minimize the cognitive resources spent making a decision ( Chernev, 2003 ). Decision goals have been associated with choice overload, with choice overload increasing along with choice set options, likely due to decision-makers unwillingness to make tradeoffs between various options. As a moderator of choice overload, there are several factors which impact the effect of decision goals, including decision intent (choosing or browsing) and decision focus (choosing an assortment or an option) ( Misuraca et al., 2020 ).

Decision intent varies between choosing, with the goal of making a decision among the available options, and browsing, with the goal of learning more about the options. Cognitive overload is more likely to occur than when decision makers’ goal is choosing compared to browsing. For choosing goals, decision-makers need to make trade-offs among the pros and cons of the options, something that demands more cognitive resources. Accordingly, decision-makers whose goal is browsing, rather than choosing, are less likely to experience cognitive overload when facing large assortments ( Chernev and Hamilton, 2009 ). Furthermore, when decision-makers have a goal of choosing, brain research reveals inverted-U-shaped function, with neither too much nor too little choice providing optimal cognitive net benefits ( Reutskaja et al., 2018 ).

Decision focus can target selecting an assortment or selecting an option from an assortment. When selecting an assortment, cognitive overload is less likely to occur, likely due to the lack of individual option evaluation and trade-offs ( Chernev et al., 2015 ). Thus, when choosing an assortment, decision-makers tend to prefer larger assortments that provide more variety. Conversely, decision-makers focused on choosing an option from an assortment report increased decision difficulty and tend to prefer smaller assortments ( Chernev, 2006 ). Decision overload is further moderated by the order of decision focus. Scheibehenne et al. (2010) found that when decision-makers first decide on an assortment, they are more likely to choose an option from that assortment, rather than an option from an assortment they did not first select.

Preference uncertainty

The degree to which decision-makers have preferences varies regarding comprehension and prioritization of the costs and benefits of the choice options. This is referred to as preference uncertainty ( Chernev, 2003 ). Preference uncertainty is influenced by decision-maker expertise and an articulated ideal option, which indicates well-defined preferences. When decision-makers have limited expertise, larger choice sets are associated with weaker preferences as well as increased choice deferral and choice overload compared to smaller choice sets. Conversely, high expertise decision-makers experience weaker preferences and increased choice deferral in the context of smaller choice sets compared to larger ( Mogilner et al., 2008 ; Morrin et al., 2012 ). Likewise, an articulated ideal option, which implies that the decision-maker has already engaged in trade-offs, is associated with reduced decision complexity. The effect is more pronounced in larger choice sets compared to smaller choice sets ( Chernev, 2003 ).

Positive affect

Positive affect tends to moderate the impact of choice overload on decision satisfaction. Indeed, Spassova and Isen (2013) found that decision-makers reporting positive affect did not report experiencing dissatisfaction when choosing from larger choice sets while those with neutral affect reported being more satisfied when choosing from smaller choice sets. This affect may be associated with the affect heuristic, or a cognitive shortcut that enables efficient decisions based on the immediate emotional response to a stimulus ( Slovic et al., 2007 ).

Decision-making tendencies

Satisfaction with extensive choice options may depend on whether one is a maximizer or a satisficer. Maximizing refers to the tendency to search for the best option. Maximizers approach decision tasks with the goal to find the absolute best ( Carmeci et al., 2009 ; Misuraca et al., 2015 , 2016b , 2021b ; Misuraca and Fasolo, 2018 ). To do that, they tend to process all the information available and try to compare all the possible options. Conversely, satisficers are decision-makers whose goal is to select an option that is good enough, rather than the best choice. To find such an option, satisficers evaluate a smaller range of options, and choose as soon as they find one alternative that surpasses their threshold of acceptability ( Schwartz, 2004 ). Given the different approach of maximizers and satisficers when choosing, it is easy to see why choice overload represents more of a problem for maximizers than for satisficers. If the number of choices exceeds the individuals’ cognitive resources, maximizers more than satisficers would feel overwhelmed, frustrated, and dissatisfied, because an evaluation of all the available options to select the best one is cognitively impossible.

Maximizers attracted considerable attention from researchers because of the paradoxical finding that even though they make objectively better decisions than satisficers, they report greater regret and dissatisfaction. Specifically, Iyengar et al. (2006) , analyzed the job search outcomes of college students during their final college year and found that maximizer students selected jobs with 20% higher salaries compared to satisficers, but they felt less satisfied and happy, as well as more stressed, frustrated, anxious, and regretful than students who were satisficers. The reasons for these negative feelings of maximizers lies in their tendency to believe that a better option is among those that they could not evaluate, given their time and cognitive limitations.

Choosing for others versus oneself

When decision-makers must make a choice for someone else, choice overload does not occur ( Polman, 2012 ). When making choices for others (about wines, ice-cream flavors, school courses, etc.), decision makers reported greater satisfaction when choosing from larger assortments rather than smaller assortments. However, when choosing for themselves, they reported higher satisfaction after choosing from smaller rather than larger assortments.

Demographics

Demographic variables such as gender, age, and cultural background moderate reactions concerning choice overload. Regarding gender, men and women may often employ different information-processing strategies, with women being more likely to attend to and use details than men (e.g., Meyers-Levy and Maheswaran, 1991 ). Gender differences also arise in desire for variety and satisfaction depending on choice type. While women were more satisfied with their choice of gift boxes regardless of assortment size, women become more selective than men when speed-dating with larger groups of speed daters compared to smaller groups ( Fisman et al., 2006 ).

Age moderates the choice overload experience such that, when choosing from an extensive array of options, adolescents and adults suffer similar negative consequences (i.e., greater difficulty and dissatisfaction), while children and seniors suffer fewer negative consequences (i.e., less difficulty and dissatisfaction than adolescents and adults) ( Misuraca et al., 2016a ). This could be associated with decision-making tendencies. Indeed, adults and adolescents tend to adopt maximizing approaches ( Furby and Beyth-Marom, 1992 ). This maximizing tendency aligns with their greater perceived difficulty and post-choice dissatisfaction when facing a high number of options ( Iyengar et al., 2006 ). Seniors tend to adopt a satisficing approach when making decisions ( Tanius et al., 2009 ), as well as become overconfident in their judgments ( Stankov and Crawford, 1996 ) and focused on positive information ( Mather and Carstensen, 2005 ). Taken together, these could explain why the negative consequences of too many choice options were milder among seniors. Finally, children tend to approach decisions in an intuitive manner and quickly develop strong preferences ( Schlottmann and Wilkening, 2011 ). This mitigates the negative consequences of choice overload for this age group.

Finally, decision-makers from different cultures have different preferences for variety (e.g., Iyengar, 2010 ). Eastern Europeans report greater satisfaction with larger choice sets than Western Europeans ( Reutskaja et al., 2022 ). Likewise, cultural differences in perception may impact how choice options affect decision-makers from Western and non-Western cultures (e.g., Miyamoto et al., 2006 ).

Future research directions

As researchers continue to investigate the choice overload phenomenon, future investigations can provide a deeper understanding of the underlying mechanisms that influence when and how individuals experience the negative impacts of choice overload as well as illuminate how this phenomenon can affect people in diverse contexts (such as hiring decisions, sports, social media platforms, streaming services, etc.).

For instance, the visual preference heuristic indicates, and subsequent research supports, the human tendency to prefer visual rather than verbal representations of choice options ( Townsend and Kahn, 2014 ). However, in Huffman and Kahn’s (1998) research, decision-makers preferred written information, such as characteristics of the sofa, rather than visual representations of alternatives. Future researchers can investigate the circumstances that underlie when individuals prefer detailed written or verbal information as opposed to visual images.

Furthermore, future researchers can examine the extent to which the mechanisms underlying the impact of chunking align with those underlying the effect of brand names. Research has supported that chunking information reduces choice overload, regardless of the sophistication of the categories ( Kahn and Wansink, 2004 ; Mogilner et al., 2008 ). The presence of a brand name has a seemingly similar effect ( Misuraca et al., 2019 , 2021a ). The extent to which the cognitive processes underlying these two areas of research the similar, as well as the ways in which they might differ, can provide valuable insights for researchers and practitioners.

More research is needed that considers the role of the specific culture and cultural values of the decision-maker on choice overload. Indeed, the traditional studies on the choice overload phenomenon mentioned above predominantly focused on western cultures, which are known for being individualistic cultures. Future research should explore whether choice overload replicates in collectivistic cultures, which value the importance of making personal decisions differently than individualist cultures. Additional cultural values, such as long-term or short-term time orientation, may also impact decision-makers and the extent to which they experience choice overload ( Hofstede and Minkov, 2010 ).

While future research that expands our understanding of the currently known and identified moderators of choice overload can critically inform our understanding of when and how this phenomenon occurs, there are many new and exciting directions into which researchers can expand.

For example, traditional research on choice overload focused on choice scenarios where decision-makers had to choose only one option out of either a small or a large assortment of options. This is clearly an important scenario, yet it represents only one of many scenarios that choice overload may impact. Future research could investigate when and how this phenomenon occurs in a wide variety of scenarios that are common in the real-world but currently neglected in classical studies on choice overload. These could include situations in which the individual can choose more than one option (e.g., more than one type of ice cream or cereal) (see Fasolo et al., 2024 ).

Historically, a significant amount of research on choice overload has focused on purchasing decisions. Some evidence also indicates that the phenomenon occurs in a variety of situations (e.g., online dating, career choices, retirement planning, travel and tourism, and education), potentially hindering decision-making processes and outcomes. Future research should further investigate how choice overload impacts individuals in a variety of untested situations. For instance, how might choice overload impact the hiring manager with a robust pool of qualified applicants? How would the occurrence of choice overload in a hiring situation impact the quality of the decision, making an optimal hire? Likewise, does choice overload play a role in procrastination? When confronted with an overwhelming number of task options, does choice overload play a role in decision deferral? It could be that similar cognitive processes underlie deferring a choice on a purchase and deferring a choice on a to-do list. Research is needed to understand how choice overload (and its moderators) may differ across these scenarios.

Finally, as society continues to adapt and develop, future research will be needed to evaluate the impact these technological and sociological changes have on individual decision-makers. The technology that we interact with has become substantially more sophisticated and omnipresent, particularly in the form of artificial intelligence (AI). As AI is adopted into our work, shopping, and online experiences, future researchers should investigate if AI and interactive decision-aids (e.g., Anderson and Misuraca, 2017 ) can be effectively leveraged to reduce the negative consequences of having too many alternatives without impairing the sense of freedom of decision-makers.

As with technological advancements, future research could examine how new sociological roles contribute to or minimize choice overload. For example, a social media influencer could reduce the complexity of the decision when there is a large number of choice options. If social media influencers have an impact, is that impact consistent across age groups and culturally diverse individuals? Deepening our understanding of how historical and sociological events have impacted decision-makers, along with how cultural differences in our perceptions of the world as noted above, could provide a rich and needed area of future research.

Discussion and conclusion

Research in psychology demonstrated the advantages of being able to make choices from a variety of alternatives, particularly when compared to no choice at all. Having the possibility to choose, indeed, enhances individuals’ feeling of self-determination, motivation, performance, well-being, and satisfaction with life (e.g., Zuckerman et al., 1978 ; Cordova and Lepper, 1996 ). As the world continues to globalize through sophisticated supply chains and seemingly infinite online shopping options, our societies have become characterized by a proliferation of choice options. Today, not only stores, but universities, hospitals, financial advisors, sport centers, and many other businesses offer a huge number of options from which to choose. The variety offered is often so large that decision-makers can become overwhelmed when trying to compare and evaluate all the potential options and experience choice overload ( Iyengar and Lepper, 2000 ). Rather than lose the benefits associated with choice options, researchers and practitioners should understand and leverage the existence of the many moderators that affect the occurrence of choice overload. The findings presented in this review indicate that choice overload is influenced by several factors, including perceptual attributes, choice set complexity, decision task difficulty, and brand association. Understanding these moderators can aid in designing choice environments that optimize decision-making processes and alleviate choice overload. For instance, organizing options effectively and leveraging brand association can enhance decision satisfaction and reduce choice overload. Additionally, considering individual differences such as decision goals, preference uncertainty, affective state, decision-making tendencies, and demographics can tailor decision-making environments to better suit the needs and preferences of individuals, ultimately improving decision outcomes. Future research is needed to fully understand the role of many variables that might be responsible for the negative consequences of choice overload and to better understand under which conditions the phenomenon occurs.

Author contributions

RM: Writing – review & editing, Conceptualization, Data curation, Investigation, Methodology, Writing – original draft. AN: Writing – review & editing. SM: Writing – review & editing. GD: Methodology, Writing – review & editing. CS: Writing – review & editing, Supervision.

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

1. ^ For example, gloves and socks have complementary features, in that they provide warmth to different parts of the body.

Anderson, B. F., and Misuraca, R. (2017). Perceptual commensuration in decision tables. Q. J. Exp. Psychol. 70, 544–553. doi: 10.1080/17470218.2016.1139603

Crossref Full Text | Google Scholar

Baumol, W., and Ide, E. A. (1956). Variety in retailing. Manag. Sci. 3, 93–101. doi: 10.1287/mnsc.3.1.93

Botti, S., and Iyengar, S. S. (2006). The dark side of choice: when choice impairs social welfare. J. Public Policy Mark. 25, 24–38. doi: 10.1509/jppm.25.1.24

Carmeci, F., Misuraca, R., and Cardaci, M. (2009). A study of temporal estimation from the perspective of the mental clock model. J. Gen. Psychol. 136, 117–128. doi: 10.3200/GENP.136.2.117-128

PubMed Abstract | Crossref Full Text | Google Scholar

Chan, E. Y. (2015). Attractiveness of options moderates the effect of choice overload. Int. J. Res. Mark. 32, 425–427. doi: 10.1016/j.ijresmar.2015.04.001

Chandon, P., Hutchinson, J. W., Bradlow, E. T., and Young, S. H. (2009). Does in-store marketing work? Effects of the number and position of shelf facings on brand attention and evaluation at the point of purchase. J. Mark. 73, 1–17. doi: 10.1509/jmkg.73.6.1

Chernev, A. (2003). When more is less and less is more: the role of ideal point availability and assortment in consumer choice. J. Consum. Res. 30, 170–183. doi: 10.1086/376808

Chernev, A. (2005). Feature complementarity and assortment in choice. J. Consum. Res. 31, 748–759. doi: 10.1086/426608

Chernev, A. (2006). Decision focus and consumer choice among assortments. J. Consum. Res. 33, 50–59. doi: 10.1086/504135

Chernev, A., Böckenholt, U., and Goodman, J. (2015). Choice overload: a conceptual review and meta-analysis. J. Consum. Psychol. 25, 333–358. doi: 10.1016/j.jcps.2014.08.002

Chernev, A., and Hamilton, R. (2009). Assortment size and option attractiveness in consumer choice among retailers. J. Mark. Res. 46, 410–420. doi: 10.1509/jmkr.46.3.410

Cordova, D. I., and Lepper, M. R. (1996). Intrinsic motivation and the process of learning: beneficial effects of contextualization, personalization, and choice. J. Educ. Psychol. 88, 715–730. doi: 10.1037/0022-0663.88.4.715

Deci, E. (1975). Intrinsic motivation . New York, NY, London: Plenum Press.

Google Scholar

Deci, E. L., Nezlek, J., and Sheinman, L. (1981). Characteristics of the rewarder and intrinsic motivation of the rewardee. J. Pers. Soc. Psychol. 40, 1–10. doi: 10.1037/0022-3514.40.1.1

Deci, E. L., and Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior . Berlin: Springer Science & Business Media.

Dhar, R. (1997). Context and task effects on choice deferral. Mark. Lett. 8, 119–130. doi: 10.1023/A:1007997613607

Fasolo, B., Carmeci, F. A., and Misuraca, R. (2009). The effect of choice complexity on perception of time spent choosing: when choice takes longer but feels shorter. Psychol. Mark. 26, 213–228. doi: 10.1002/mar.20270

Fasolo, B., Misuraca, R., and Reutskaja, E. (2024). Choose as much as you wish: freedom cues in the marketplace help consumers feel more satisfied with what they choose and improve customer experience. J. Exp. Psychol. Appl. 30, 156–168. doi: 10.1037/xap0000481

Fisman, R., Iyengar, S. S., Kamenica, E., and Simonson, I. (2006). Gender differences in mate selection: evidence from a speed dating experiment. Q. J. Econ. 121, 673–697. doi: 10.1162/qjec.2006.121.2.673

Furby, L., and Beyth-Marom, R. (1992). Risk taking in adolescence: a decision-making perspective. Dev. Rev. 12, 1–44. doi: 10.1016/0273-2297(92)90002-J

Gourville, J. T., and Soman, D. (2005). Overchoice and assortment type: when and why variety backfires. Mark. Sci. 24, 382–395. doi: 10.1287/mksc.1040.0109

Greifeneder, R., Scheibehenne, B., and Kleber, N. (2010). Less may be more when choosing is difficult: choice complexity and too much choice. Acta Psychol. 133, 45–50. doi: 10.1016/j.actpsy.2009.08.005

Griffin, J. G., and Broniarczyk, S. M. (2010). The slippery slope: the impact of feature alignability on search and satisfaction. J. Mark. Res. 47, 323–334. doi: 10.1509/jmkr.47.2.323

Hoch, S. J., Bradlow, E. T., and Wansink, B. (1999). The variety of an assortment. Mark. Sci. 18, 527–546. doi: 10.1287/mksc.18.4.527

Hofstede, G., and Minkov, M. (2010). Long-versus short-term orientation: new perspectives. Asia Pac. Bus. Rev. 16, 493–504. doi: 10.1080/13602381003637609

Huffman, C., and Kahn, B. E. (1998). Variety for sale: mass customization or mass confusion? J. Retail. 74, 491–513. doi: 10.1016/S0022-4359(99)80105-5

Inbar, Y., Botti, S., and Hanko, K. (2011). Decision speed and choice regret: when haste feels like waste. J. Exp. Soc. Psychol. 47, 533–540. doi: 10.1016/j.jesp.2011.01.011

Iyengar, S. S. (2010). The art of choosing . London: Little Brown.

Iyengar, S. S., Huberman, G., and Jiang, W. (2004). “How much choice is too much? Contributions to 401 (k) retirement plans” in Pension design and structure New Lessons from Behavioral Finance . Oxford University Press, 83–95.

Iyengar, S. S., and Lepper, M. R. (2000). When choice is demotivating: can one desire too much of a good thing? J. Pers. Soc. Psychol. 79, 995–1006. doi: 10.1037/0022-3514.79.6.995

Iyengar, S. S., Wells, R. E., and Schwartz, B. (2006). Doing better but feeling worse looking for the ‘best’ job undermines satisfaction. Psychol. Sci. 17, 143–150. doi: 10.1111/j.1467-9280.2006.01677.x

Kahn, B. E., and Wansink, B. (2004). The influence of assortment structure on perceived variety and consumption quantities. J. Consum. Res. 30, 519–533. doi: 10.1086/380286

Lancaster, K. (1990). The economics of product variety: a survey. Mark. Sci. 9, 189–206. doi: 10.1287/mksc.9.3.189

Langer, E. J., and Rodin, J. (1976). The effects of choice and enhanced personal responsibility for aged: a field experiment in an institutional setting. J. Pers. Soc. Psychol. 34, 191–198. doi: 10.1037/0022-3514.34.2.191

Levav, J., Heitmann, M., Herrmann, A., and Iyengar, S. S. (2010). Order in product customization decisions: evidence from field experiments. J. Polit. Econ. 118, 274–299. doi: 10.1086/652463

Malhotra, N. K. (1982). Information load and consumer decision making. J. Consum. Res. 8, 419–430. doi: 10.1086/208882

Mather, M., and Carstensen, L. L. (2005). Aging and motivated cognition: the positivity effect in attention and memory. Trends Cogn. Sci. 9, 496–502. doi: 10.1016/j.tics.2005.08.005

McShane, B. B., and Böckenholt, U. (2017). Multilevel multivariate Meta-analysis with application to choice overload. Psychometrika 83, 255–271. doi: 10.1007/s11336-017-9571-z

Meyers-Levy, J., and Maheswaran, D. (1991). Exploring differences in males' and females' processing strategies. J. Consum. Res. 18, 63–70. doi: 10.1086/209241

Miller, G. A. (1956). The magic number seven plus or minus two: some limits on our capacity for processing information. Psychol. Rev. 63, 81–97. doi: 10.1037/h0043158

Misuraca, R. (2013). Do too many choices have negative consequences? An empirical review. Troppa scelta ha veramente conseguenze negative? Una rassegna di studi empirici. G. Ital. Psicol. 35, 129–154,

Misuraca, R., Ceresia, F., Nixon, A. E., and Scaffidi Abbate, C. (2021a). When is more really more? The effect of brands on choice overload in adolescents. J. Consum. Mark. 38, 168–177. doi: 10.1108/JCM-08-2020-4021

Misuraca, R., Ceresia, F., Teuscher, U., and Faraci, P. (2019). The role of the brand on choice overload. Mind Soc. 18, 57–76. doi: 10.1007/s11299-019-00210-7

Misuraca, R., and Faraci, P. (2021). Choice overload: A study on children, adolescents, adults and seniors/L’effetto del sovraccarico di scelta: un’indagine su bambini, adolescent, adulti e anziani. Ricerche Psicol. 43, 835–847,

Misuraca, R., Faraci, P., Gangemi, A., Carmeci, F. A., and Miceli, S. (2015). The decision-making tendency inventory: a new measure to assess maximizing, satisficing, and minimizing. Personal. Individ. Differ. 85, 111–116. doi: 10.1016/j.paid.2015.04.043

Misuraca, R., Faraci, P., Ruthruff, E., and Ceresia, F. (2021b). Are maximizers more normative decision-makers? An experimental investigation of maximizers' susceptibility to cognitive biases. Personal. Individ. Differ. 183:111123. doi: 10.1016/j.paid.2021.111123

Misuraca, R., Faraci, P., and Scaffidi-Abbate, C. (2022). Maximizers’ susceptibility to the effect of frequency vs. percentage format in risk representation. Behav. Sci. 12:496. doi: 10.3390/bs12120496

Misuraca, R., and Fasolo, B. (2018). Maximizing versus satisficing in the digital age: disjoint scales and the case for “construct consensus”. Personal. Individ. Differ. 121, 152–160. doi: 10.1016/j.paid.2017.09.031

Misuraca, R., Reutskaja, E., Fasolo, B., and Iyengar, S. S. (2020). “How much choice is ‘good enough’? Moderators of information and choice overload” in Routledge handbook of bounded rationality . ed. R. Viale (Abingdon, UK: Routledge).

Misuraca, R., and Teuscher, U. (2013). Time flies when you maximize – maximizers and satisficers perceive time differently when making decisions. Acta Psychol. 143, 176–180. doi: 10.1016/j.actpsy.2013.03.004

Misuraca, R., Teuscher, U., and Carmeci, F. A. (2016b). Who are maximizers? Future oriented and highly numerate individuals. Int. J. Psychol. 51, 307–311. doi: 10.1002/ijop.12169

Misuraca, R., Teuscher, U., and Faraci, P. (2016a). Is more choice always worse? Age differences in the overchoice effect. J. Cogn. Psychol. 28, 242–255. doi: 10.1080/20445911.2015.1118107

Miyamoto, Y., Nisbett, R. E., and Masuda, T. (2006). Culture and the physical environment: holistic versus analytic perceptual affordances. Psychol. Sci. 17, 113–119. doi: 10.1111/j.1467-9280.2006.01673.x

Mogilner, C., Rudnick, T., and Iyengar, S. S. (2008). The mere categorization effect: how the presence of categories increases choosers’ perceptions of assortment variety and outcome satisfaction. J. Consum. Res. 35, 202–215. doi: 10.1086/588698

Mogilner, C., Shiv, B., and Iyengar, S. S. (2013). Eternal quest for the best: sequential (vs. simultaneous) option presentation undermines choice commitment. J. Consum. Res. 39, 1300–1312. doi: 10.1086/668534

Morrin, M., Broniarczyk, S. M., and Inman, J. J. (2012). Plan format and participation in 401 (k) plans: the moderating role of investor knowledge. J. Public Policy Mark. 31, 254–268. doi: 10.1509/jppm.10.122

Payne, J. W., Bettman, J. R., and Johnson, E. J. (1993). The adaptive decision maker . Cambridge: Cambridge University Press.

Pieters, R., and Warlop, L. (1999). Visual attention during brand choice: the impact of time pressure and task motivation. Int. J. Res. Mark. 16, 1–16. doi: 10.1016/S0167-8116(98)00022-6

Polman, E. (2012). Effects of self-other decision making on regulatory focus and choice overload. J. Pers. Soc. Psychol. 102, 980–993. doi: 10.1037/a0026966

Ratner, R. K., and Kahn, B. E. (2002). The impact of private versus public consumption on variety-seeking behavior. J. Consum. Res. 29, 246–257. doi: 10.1086/341574

Reutskaja, E., Cheek, N. N., Iyengar, S., and Schwartz, B. (2022). Choice deprivation, choice overload, and satisfaction with choices across six nations. J. Int. Mark. 30, 18–34. doi: 10.1177/1069031X211073821

Reutskaja, E., Lindner, A., Nagel, R., Andersen, R. A., and Camerer, C. F. (2018). Choice overload reduces neural signatures of choice set value in dorsal striatum and anterior cingulate cortex. Nat. Hum. Behav. 2, 925–935. doi: 10.1038/s41562-018-0440-2

Reutskaja, E., Nagel, R., Camerer, C. F., and Rangel, A. (2011). Search dynamics in consumer choice under time pressure: an eye-tracking study. Am. Econ. Rev. 101, 900–926. doi: 10.1257/aer.101.2.900

Rotter, J. B. (1966). Generalized expectancies for internal versus external control of reinforcement. Psychol. Monogr. Gen. Appl. 80, 1–28. doi: 10.1037/h0092976

Scheibehenne, B., Greifeneder, R., and Todd, P. M. (2009). What moderates the too-much-choice effect? Psychol. Mark. 26, 229–253. doi: 10.1002/mar.20271

Scheibehenne, B., Greifeneder, R., and Todd, P. M. (2010). Can there ever be too many options? A meta-analytic review of choice overload. J. Consum. Res. 37, 409–425.

Schlottmann, A., and Wilkening, F. (2011). Judgment and decision making in young children . Cambridge: Cambridge University Press.

Schraw, G., Flowerday, T., and Reisetter, M. F. (1998). The role of choice in reader engagement. J. Educ. Psychol. 90, 705–714. doi: 10.1037/0022-0663.90.4.705

Schwartz, B. (2004). The paradox of choice: why more is less . New York, NY: Ecco.

Shah, A. M., and Wolford, G. (2007). Buying behavior as a function of parametric variation of number of choices. Psychol. Sci. 18, 369–370. doi: 10.1111/j.1467-9280.2007.01906.x

Simon, H. A. (1957). Models of man: social and rational . Oxford: John Wiley & Sons.

Slovic, P., Finucane, M. L., Peters, E., and MacGregor, D. G. (2007). The affect heuristic. Eur. J. Oper. Res. 177, 1333–1352. doi: 10.1016/j.ejor.2005.04.006

Spassova, G., and Isen, A. M. (2013). Positive affect moderates the impact of assortment size on choice satisfaction. J. Retail. 89, 397–408. doi: 10.1016/j.jretai.2013.05.003

Stankov, L., and Crawford, J. D. (1996). Confidence judgments in studies of individual differences. Personal. Individ. Differ. 21, 971–986. doi: 10.1016/S0191-8869(96)00130-4

Tanius, B. E., Wood, S., Hanoch, Y., and Rice, T. (2009). Aging and choice: applications to Medicare part D. Judgm. Decis. Mak. 4, 92–101. doi: 10.1017/S1930297500000735

Taylor, S. E., and Brown, J. D. (1988). Illusion and well-being: a social psychological perspective on mental health. Psychol. Bull. 103, 193–210. doi: 10.1037/0033-2909.103.2.193

Townsend, C., and Kahn, B. E. (2014). The “visual preference heuristic”: the influence of visual versus verbal depiction on assortment processing, perceived variety, and choice overload. J. Consum. Res. 40, 993–1015. doi: 10.1086/673521

Zuckerman, M., Porac, J., Latin, D., Smith, R., and Deci, E. L. (1978). On the importance of self-determination for intrinsically motivated behavior. Personal. Soc. Psychol. Bull. 4, 443–446. doi: 10.1177/014616727800400317

Keywords: choice-overload, decision-making, choice set complexity, decision task difficulty, decision goal, decision-making tendency

Citation: Misuraca R, Nixon AE, Miceli S, Di Stefano G and Scaffidi Abbate C (2024) On the advantages and disadvantages of choice: future research directions in choice overload and its moderators. Front. Psychol . 15:1290359. doi: 10.3389/fpsyg.2024.1290359

Received: 07 September 2023; Accepted: 24 April 2024; Published: 09 May 2024.

Reviewed by:

Copyright © 2024 Misuraca, Nixon, Miceli, Di Stefano and Scaffidi Abbate. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Raffaella Misuraca, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

IMAGES

  1. (DOC) Advantages and Disadvantages of Social Media to Students

    advantages and disadvantages of social media for students research paper

  2. Advantages and Disadvantages of Social Media for Students

    advantages and disadvantages of social media for students research paper

  3. 12 Advantages and Disadvantages of using Social media

    advantages and disadvantages of social media for students research paper

  4. Pros and Cons of Social Media Inforgraphic

    advantages and disadvantages of social media for students research paper

  5. Advantages and Disadvantages of Social Media

    advantages and disadvantages of social media for students research paper

  6. Top 10 most common advantages and disadvantages of social media

    advantages and disadvantages of social media for students research paper

VIDEO

  1. 10 disadvantages of Social media//Social media//Beautiful Handwriting 🖊️

  2. Advantages and Disadvantages of Social Media

  3. SOCIAL MEDIA EFFECT ON YOUTH

  4. Social Media ka use. advantages and disadvantages. Enjoy fun and musty

  5. The Impact of social media on the academic performance of social science students at UWI T&T

  6. Social media study by Rice University finds high levels of distraction among younger users

COMMENTS

  1. Advantages and Disadvantages of Social Media and Its Effects on Young Learners

    Social media is something. students use at home, on the go, and sometimes in school, but usually not in the classroom. This. generation of students has grown up with the internet and expects to ...

  2. The effect of social media on the development of students' affective

    In recent years, several studies have been conducted to explore the potential effects of social media on students' affective traits, such as stress, anxiety, depression, and so on. The present paper reviews the findings of the exemplary published works of research to shed light on the positive and negative potential effects of the massive use ...

  3. Advantages and Disadvantages of Social Media and Its Effects on ...

    Kemp reported that social media users increased over the past year to reach 4.55 billion in October 2021. Furthermore, the number of new social media users increases by more than 1 million every day. Many people nowadays, including students, prefer to communicate with each other through social networking rather than interacting face-to-face.

  4. PDF Considering the Advantages and Disadvantages of Utilizing Social Media

    Research in Social Sciences and Technology https://ressat.org E-ISSN: 2468-6891 Volume: 8 Issue: 2 2023 pp. 83-100 Considering the Advantages and Disadvantages of Utilizing Social Media to Enhance Learning and Engagement in K-12 Education Kaan Güney* * Sivas Cumhuriyet University, Sivas, Türkiye. Email: [email protected] Article Info

  5. PDF Understanding the impacts of social media platforms on students

    The impacts of social media on students' academic learning progress According to Gudelliwar et al. (2019), social media platforms enable teachers and students to ... Problem statement and research motivation Social media usage is increasing among students and youths, especially during and after crises, such as the COVID-19 pandemic outbreak. At ...

  6. Analysing the Impact of Social Media on Students' Academic Performance

    Past research by Choney , Karpinski and Duberstein , Khan and Kubey et al. was done mostly in developed countries to analyse the impact of social media on the students' academic performance, effect of social media on adolescence, and addictiveness of social media in students. There are no published research studies where the impact of social ...

  7. Social media brings benefits and risks to teens. Psychology can help

    Social media brings benefits and risks to teens. Psychology can help identify a path forward. New psychological research exposes the harms and positive outcomes of social media. APA's recommendations aim to add science-backed balance to the discussion. By Kirsten Weir Date created: September 1, 2023 15 min read.

  8. How social media use is related to student engagement and creativity

    Recent research reveals that the social media usage has been rapidly increased in higher education. Yet we know a little about the consequences of social media use among students. The current study is an attempt to understand how and when the use of social media by the students is related to their academic engagement and creativity.

  9. The Opportunities and Challenges of Social Media in Higher ...

    This paper presents a review of the use of social media for learning and teaching in higher education, as well as the opportunities and challenges revealed from its use. A total of 77 related case studies published from 2010 to 2019 were collected from Scopus and Google Scholar for analysis. The results showed that social media was usually used as a learning management system and for enhancing ...

  10. PDF Analysing the Impact of Social Media on Students' Academic ...

    has more disadvantages than advantages. Social media severely impacts the academic performance of a student. The addiction to social media is found more among the students of higher studies which ruins the academic excel-lence of an individual (Nalwa & Anand, 2003). Among the social media users, Facebook users' academic perfor-

  11. Social media usage: Analyzing its effect on academic performance and

    The rest of this research paper is ordered into 5 sections: ... The study's conclusions show that when students use social media websites for academic reasons, the learning outcomes of those students improve, and their academic performance is impacted by social media's knowledge-sharing function. Overall, the study presents in-depth data ...

  12. The use of social media and its impact for research

    Research is about producing new information, and social media offers unique opportunities to present new content. As a scientist, once you publish your research, you want to share it with as many colleagues and people so that they may read your novel findings. You want to share your hard work with many individuals.

  13. Advantages and Disadvantages of Social Media to Students

    Social media could improve students' academic levels, but it may lead to adverse outcomes if it is misused. This article aims to discuss some advantages and disadvantages of the use of social media and its impacts on students. In this article, alternative activities will be shared to motivate students engage in their life experiences frequently.

  14. The analysis of advantages and disadvantages of use of social media in

    3. Conclusion Following research in in the literature, we have identified several advantages of social media. These include information exchange and communication, teamwork and work from home, data sharing, sharing hardware and peripherals, services and education. Advantages of social media, we offered respondents a choice perceived as follows.

  15. Perceived Benefits and Risks of Social Media: Ethiopian Secondary

    This study investigated the perceived benefits and risks associated with using social media among teenager students in Ethiopia. Based on the findings, teenager students used social media primarily for recreational and social networking purposes. The academic value of social media, which is basically vital for students, was likely less considered.

  16. The Advantages and Disadvantages of Social Media to the Selected

    The research is conducted wherein students with different status in life are asked to answer certain questions with regards to the advantages and disadvantages of Social Media. In particular as the main issue of influence. The study aims to establish whether using Social Media can make student a better leader or a troublemaker.

  17. Social Media and Mental Health: Benefits, Risks, and ...

    Social media has become a prominent fixture in the lives of many individuals facing the challenges of mental illness. Social media refers broadly to web and mobile platforms that allow individuals to connect with others within a virtual network (such as Facebook, Twitter, Instagram, Snapchat, or LinkedIn), where they can share, co-create, or exchange various forms of digital content, including ...

  18. Ten (10) Advantages and Disadvantages of Social Media to Students

    Advantages (merits) of Social Media To Students. 1. Social Media aids research: Social media is beneficial to students, especially students of the university or other tertiary institutions who are charged with term paper, project, and other forms of academic activities which require research, as it aids their research.

  19. Benefits and harms of social media use: A latent profile analysis of

    We identified "profiles" of social media use among young adults based on the frequency and purposes of use, and examined their associations with benefits and harms to psychosocial well-being, using data from 2828 incoming undergraduate students ( Mage = 18.29 years; age range: 17 to 25 years). Using Latent Profile Analysis, we identified ...

  20. 23 Biggest Advantages and Disadvantages of Social Media

    The advantages and disadvantages of social media are many, so here are the critical points to review in each area. List of the Advantages of Social Media. 1. It is easier to carry out research work using social media. Today's social media platforms are a fantastic study tool that students can use.

  21. On the advantages and disadvantages of choice: future research

    This paper reviews seminal research on the advantages and disadvantages of choice and provides a systematic qualitative review of the research examining moderators of choice overload, laying out multiple critical paths forward for needed research in this area. ... Moreover, the essays written by the students in the limited-choice conditions ...