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Perspectives Daily

“What Changed” in Social Studies Education

A View from the Classroom

Samantha Stearns | Jul 30, 2019

Editor’s note: This is the first installment of a two-part column. The second installment can be found here .

“What changed?” asked one of my graduate school professors. She was talking informally with me and another student about how so many undergraduate students seem unprepared for the rigor of college-level history courses. She observed that she had to constantly revise her syllabi due to the decreasing skill level of the students she taught from year to year. It frustrated her that she kept having to reduce the number of monographs she assigned and the amount of academic writing she required. But the question of “what changed” isn’t mysterious to me: not only am I a graduate student, finishing my master’s degree in history, I’m also an eighth-grade social studies teacher with a decade of classroom experience. Being on the front lines of social studies education in this way, I have a unique perspective from which to answer her question, and some ideas about finding a solution.

Social studies teachers at all levels are often forced into the stereotype of being a jack of all trades and master of none. Luis Pérez via Flickr/CC BY 2.0.

From a teacher’s point of view, the answer to “What changed?” is rooted in the ambiguous definition of “social studies” itself. In most American classrooms, social studies is an amalgam of disciplines largely dominated by history, but depending on the curriculum adopted by a district or school, it also may incorporate geography, political science, economics, religious studies, psychology, sociology, and archaeology. This means that social studies teachers at all levels are often forced into the stereotype of being a jack of all trades and master of none. For that reason, many history professors will end up seeing students with limited historical content knowledge and critical-thinking skills. But what they might not understand is that social studies curriculum is heavily dependent on not just teacher preferences (or preparation) but also the priorities of the government. District and state standards matter, but the status of social studies education as a mix-match of disciplines reflects priorities that start at the federal level.

Social studies education, it seems to many educators, has never recovered from the blow dealt to it by the No Child Left Behind (NCLB) Act of 2001, with its high-stakes standardized testing in math and reading, to the detriment of other subjects. The effects of NCLB are evident when students in a 100-level history course do not understand the difference between primary and secondary sources, for example, or when students in upper-level courses have trouble identifying and evaluating a historian’s argument. These gaps in the skills necessary to succeed in history courses are formed at an early age for most American students because of the emphasis on math and reading education.

On the ground, this means that elementary and intermediate school teachers have a dual mission: teaching multiple content areas and increasing reading and math standardized test scores. If teachers feel underqualified or ill-equipped to teach social studies curriculum per se, they might integrate pieces of it into content areas that students will be assessed on. For example, teachers might use a short story with the American Revolution as a backdrop in a reading or language arts class. Or, students might learn about the state bird in a science class as part of a broader unit on varying species. On paper, the student has received social studies “minutes” as mandated by the state or district, but in reality, the student has learned about an event, a person, or a place without any historical context. The student therefore views the topic in isolation, never to be thought about again. Young learners’ inherent curiosity is stifled when they can’t move beyond the what to also explore the why and how : the very essence of what quality social studies education should encourage.

Unfortunately, the lack of quality social studies education does not improve much as a student progresses in grade level. According to the most recent Schools and Staffing Survey , conducted in 2011, third graders in American schools spent less than 10 percent of their academic week learning social studies. By the eighth grade, students spent only 4.2 hours per week in a history or social studies class—as compared to 6.5 hours in English or Language Arts, 5 hours in math, and 4.3 hours in science. [1] What changed, then? Social studies, and therefore history as a discipline, became the bottom rung of the educational ladder for many schools and therefore the first of the core academic subjects to be modified or reduced to increase minutes in other subject areas, or to be scrapped completely.

Prioritizing social studies education probably won’t come from state or federal mandates, nor should it. Its needs to come from the grassroots level, by encouraging professionalization among those who teach social studies. Professionalization would increase educators’ authority to emphasize content-relevant skills in their curriculum, and to incorporate opportunities for students to experience what it means to be a professional historian. This would result in clear skill development among students, which would transcend the problem of social studies’ content variability—a problem that has contributed to its decline. At a time when it seems the only path to a subject’s legitimization is whether it is tested, professionalization would help teachers gain recognition for their content mastery while also reinforcing their ability to develop students’ critical-thinking skills.

The means of professionalization for social studies teachers can and should vary by individual, but there are several readily accessible pathways, including content-driven professional development, advanced study, and networking with professional historians. Professionalization will allow the conversation to move from “What changed?” to what works.

[1] Dinah Sparks and Kathleen Mulvaney Hoyer, Instruction Time for Third- and Eighth-Graders in Public and Private Schools: School Year 2011–2012 (NCES 2017-076) (Washington, DC: National Center for Education Statistics, Institute of Education Sciences, US Department of Education, 2017), https://nces.ed.gov/pubs2017/2017076.pdf .

Samantha Stearns is an eighth-grade social studies teacher and chair of the social studies department at Roosevelt Middle School in River Forest, Illinois. 

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Social Media Use and Its Connection to Mental Health: A Systematic Review

Fazida karim.

1 Psychology, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

2 Business & Management, University Sultan Zainal Abidin, Terengganu, MYS

Azeezat A Oyewande

3 Family Medicine, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

4 Family Medicine, Lagos State Health Service Commission/Alimosho General Hospital, Lagos, NGA

Lamis F Abdalla

5 Internal Medicine, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

Reem Chaudhry Ehsanullah

Safeera khan.

Social media are responsible for aggravating mental health problems. This systematic study summarizes the effects of social network usage on mental health. Fifty papers were shortlisted from google scholar databases, and after the application of various inclusion and exclusion criteria, 16 papers were chosen and all papers were evaluated for quality. Eight papers were cross-sectional studies, three were longitudinal studies, two were qualitative studies, and others were systematic reviews. Findings were classified into two outcomes of mental health: anxiety and depression. Social media activity such as time spent to have a positive effect on the mental health domain. However, due to the cross-sectional design and methodological limitations of sampling, there are considerable differences. The structure of social media influences on mental health needs to be further analyzed through qualitative research and vertical cohort studies.

Introduction and background

Human beings are social creatures that require the companionship of others to make progress in life. Thus, being socially connected with other people can relieve stress, anxiety, and sadness, but lack of social connection can pose serious risks to mental health [ 1 ].

Social media

Social media has recently become part of people's daily activities; many of them spend hours each day on Messenger, Instagram, Facebook, and other popular social media. Thus, many researchers and scholars study the impact of social media and applications on various aspects of people’s lives [ 2 ]. Moreover, the number of social media users worldwide in 2019 is 3.484 billion, up 9% year-on-year [ 3 - 5 ]. A statistic in Figure  1  shows the gender distribution of social media audiences worldwide as of January 2020, sorted by platform. It was found that only 38% of Twitter users were male but 61% were using Snapchat. In contrast, females were more likely to use LinkedIn and Facebook. There is no denying that social media has now become an important part of many people's lives. Social media has many positive and enjoyable benefits, but it can also lead to mental health problems. Previous research found that age did not have an effect but gender did; females were much more likely to experience mental health than males [ 6 , 7 ].

Impact on mental health

Mental health is defined as a state of well-being in which people understand their abilities, solve everyday life problems, work well, and make a significant contribution to the lives of their communities [ 8 ]. There is debated presently going on regarding the benefits and negative impacts of social media on mental health [ 9 , 10 ]. Social networking is a crucial element in protecting our mental health. Both the quantity and quality of social relationships affect mental health, health behavior, physical health, and mortality risk [ 9 ]. The Displaced Behavior Theory may help explain why social media shows a connection with mental health. According to the theory, people who spend more time in sedentary behaviors such as social media use have less time for face-to-face social interaction, both of which have been proven to be protective against mental disorders [ 11 , 12 ]. On the other hand, social theories found how social media use affects mental health by influencing how people view, maintain, and interact with their social network [ 13 ]. A number of studies have been conducted on the impacts of social media, and it has been indicated that the prolonged use of social media platforms such as Facebook may be related to negative signs and symptoms of depression, anxiety, and stress [ 10 - 15 ]. Furthermore, social media can create a lot of pressure to create the stereotype that others want to see and also being as popular as others.

The need for a systematic review

Systematic studies can quantitatively and qualitatively identify, aggregate, and evaluate all accessible data to generate a warm and accurate response to the research questions involved [ 4 ]. In addition, many existing systematic studies related to mental health studies have been conducted worldwide. However, only a limited number of studies are integrated with social media and conducted in the context of social science because the available literature heavily focused on medical science [ 6 ]. Because social media is a relatively new phenomenon, the potential links between their use and mental health have not been widely investigated.

This paper attempt to systematically review all the relevant literature with the aim of filling the gap by examining social media impact on mental health, which is sedentary behavior, which, if in excess, raises the risk of health problems [ 7 , 9 , 12 ]. This study is important because it provides information on the extent of the focus of peer review literature, which can assist the researchers in delivering a prospect with the aim of understanding the future attention related to climate change strategies that require scholarly attention. This study is very useful because it provides information on the extent to which peer review literature can assist researchers in presenting prospects with a view to understanding future concerns related to mental health strategies that require scientific attention. The development of the current systematic review is based on the main research question: how does social media affect mental health?

Research strategy

The research was conducted to identify studies analyzing the role of social media on mental health. Google Scholar was used as our main database to find the relevant articles. Keywords that were used for the search were: (1) “social media”, (2) “mental health”, (3) “social media” AND “mental health”, (4) “social networking” AND “mental health”, and (5) “social networking” OR “social media” AND “mental health” (Table  1 ).

Out of the results in Table  1 , a total of 50 articles relevant to the research question were selected. After applying the inclusion and exclusion criteria, duplicate papers were removed, and, finally, a total of 28 articles were selected for review (Figure  2 ).

PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Inclusion and exclusion criteria

Peer-reviewed, full-text research papers from the past five years were included in the review. All selected articles were in English language and any non-peer-reviewed and duplicate papers were excluded from finally selected articles.

Of the 16 selected research papers, there were a research focus on adults, gender, and preadolescents [ 10 - 19 ]. In the design, there were qualitative and quantitative studies [ 15 , 16 ]. There were three systematic reviews and one thematic analysis that explored the better or worse of using social media among adolescents [ 20 - 23 ]. In addition, eight were cross-sectional studies and only three were longitudinal studies [ 24 - 29 ].The meta-analyses included studies published beyond the last five years in this population. Table  2  presents a selection of studies from the review.

IGU, internet gaming disorder; PSMU, problematic social media use

This study has attempted to systematically analyze the existing literature on the effect of social media use on mental health. Although the results of the study were not completely consistent, this review found a general association between social media use and mental health issues. Although there is positive evidence for a link between social media and mental health, the opposite has been reported.

For example, a previous study found no relationship between the amount of time spent on social media and depression or between social media-related activities, such as the number of online friends and the number of “selfies”, and depression [ 29 ]. Similarly, Neira and Barber found that while higher investment in social media (e.g. active social media use) predicted adolescents’ depressive symptoms, no relationship was found between the frequency of social media use and depressed mood [ 28 ].

In the 16 studies, anxiety and depression were the most commonly measured outcome. The prominent risk factors for anxiety and depression emerging from this study comprised time spent, activity, and addiction to social media. In today's world, anxiety is one of the basic mental health problems. People liked and commented on their uploaded photos and videos. In today's age, everyone is immune to the social media context. Some teens experience anxiety from social media related to fear of loss, which causes teens to try to respond and check all their friends' messages and messages on a regular basis.

On the contrary, depression is one of the unintended significances of unnecessary use of social media. In detail, depression is limited not only to Facebooks but also to other social networking sites, which causes psychological problems. A new study found that individuals who are involved in social media, games, texts, mobile phones, etc. are more likely to experience depression.

The previous study found a 70% increase in self-reported depressive symptoms among the group using social media. The other social media influence that causes depression is sexual fun [ 12 ]. The intimacy fun happens when social media promotes putting on a facade that highlights the fun and excitement but does not tell us much about where we are struggling in our daily lives at a deeper level [ 28 ]. Another study revealed that depression and time spent on Facebook by adolescents are positively correlated [ 22 ]. More importantly, symptoms of major depression have been found among the individuals who spent most of their time in online activities and performing image management on social networking sites [ 14 ].

Another study assessed gender differences in associations between social media use and mental health. Females were found to be more addicted to social media as compared with males [ 26 ]. Passive activity in social media use such as reading posts is more strongly associated with depression than doing active use like making posts [ 23 ]. Other important findings of this review suggest that other factors such as interpersonal trust and family functioning may have a greater influence on the symptoms of depression than the frequency of social media use [ 28 , 29 ].

Limitation and suggestion

The limitations and suggestions were identified by the evidence involved in the study and review process. Previously, 7 of the 16 studies were cross-sectional and slightly failed to determine the causal relationship between the variables of interest. Given the evidence from cross-sectional studies, it is not possible to conclude that the use of social networks causes mental health problems. Only three longitudinal studies examined the causal relationship between social media and mental health, which is hard to examine if the mental health problem appeared more pronounced in those who use social media more compared with those who use it less or do not use at all [ 19 , 20 , 24 ]. Next, despite the fact that the proposed relationship between social media and mental health is complex, a few studies investigated mediating factors that may contribute or exacerbate this relationship. Further investigations are required to clarify the underlying factors that help examine why social media has a negative impact on some peoples’ mental health, whereas it has no or positive effect on others’ mental health.

Conclusions

Social media is a new study that is rapidly growing and gaining popularity. Thus, there are many unexplored and unexpected constructive answers associated with it. Lately, studies have found that using social media platforms can have a detrimental effect on the psychological health of its users. However, the extent to which the use of social media impacts the public is yet to be determined. This systematic review has found that social media envy can affect the level of anxiety and depression in individuals. In addition, other potential causes of anxiety and depression have been identified, which require further exploration.

The importance of such findings is to facilitate further research on social media and mental health. In addition, the information obtained from this study can be helpful not only to medical professionals but also to social science research. The findings of this study suggest that potential causal factors from social media can be considered when cooperating with patients who have been diagnosed with anxiety or depression. Also, if the results from this study were used to explore more relationships with another construct, this could potentially enhance the findings to reduce anxiety and depression rates and prevent suicide rates from occurring.

The content published in Cureus is the result of clinical experience and/or research by independent individuals or organizations. Cureus is not responsible for the scientific accuracy or reliability of data or conclusions published herein. All content published within Cureus is intended only for educational, research and reference purposes. Additionally, articles published within Cureus should not be deemed a suitable substitute for the advice of a qualified health care professional. Do not disregard or avoid professional medical advice due to content published within Cureus.

The authors have declared that no competing interests exist.

Journal of Social Studies Education Research

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Published on 4.4.2024 in Vol 11 (2024)

Studies of Social Anxiety Using Ambulatory Assessment: Systematic Review

Authors of this article:

• Javier Fernández-Álvarez 1, 2 , PhD   ; 
• Desirée Colombo 1 , PhD   ; 
• Juan Martín Gómez Penedo 3 , PhD   ; 
• Maitena Pierantonelli 4 , MSc   ; 
• Rosa María Baños 4, 5, 6 , Prof Dr   ; 
• Cristina Botella 1, 6 , Prof Dr  

1 Department of Basic and Clinical Psychology and Psychobiology, Jaume I University, Castellon de la Plana, Spain

2 Fundación Aiglé, Buenos Aires, Argentina

3 Facultad de Psicología, Universidad de Buenos Aires (CONICET), Buenos Aires, Argentina

4 Polibienestar Research Institute, University of Valencia, Valencia, Spain

5 Department of Personality, Evaluation, and Psychological Treatments, University of Valencia, Valencia, Spain

6 Ciber Fisiopatologia Obesidad y Nutricion (CB06/03 Instituto Salud Carlos III), Madrid, Spain

Corresponding Author:

Javier Fernández-Álvarez, PhD

Department of Basic and Clinical Psychology and Psychobiology

Jaume I University

Avda. Vicent Sos Baynat s/n

Castellon de la Plana, 12071

Phone: 34 964 72 80 0

Email: [email protected]

Background: There has been an increased interest in understanding social anxiety (SA) and SA disorder (SAD) antecedents and consequences as they occur in real time, resulting in a proliferation of studies using ambulatory assessment (AA). Despite the exponential growth of research in this area, these studies have not been synthesized yet.

Objective: This review aimed to identify and describe the latest advances in the understanding of SA and SAD through the use of AA.

Methods: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a systematic literature search was conducted in Scopus, PubMed, and Web of Science.

Results: A total of 70 articles met the inclusion criteria. The qualitative synthesis of these studies showed that AA permitted the exploration of the emotional, cognitive, and behavioral dynamics associated with the experience of SA and SAD. In line with the available models of SA and SAD, emotion regulation, perseverative cognition, cognitive factors, substance use, and interactional patterns were the principal topics of the included studies. In addition, the incorporation of AA to study psychological interventions, multimodal assessment using sensors and biosensors, and transcultural differences were some of the identified emerging topics.

Conclusions: AA constitutes a very powerful methodology to grasp SA from a complementary perspective to laboratory experiments and usual self-report measures, shedding light on the cognitive, emotional, and behavioral antecedents and consequences of SA and the development and maintenance of SAD as a mental disorder.

Introduction

Social anxiety (SA) is a normal and adaptive manifestation that all human beings experience in anticipation of a potential interactional threat. Similar to any adaptive response, it is enormously beneficial, particularly in protecting people from potential dangers that may arise from social interactions [ 1 ]. However, this adaptive response is sometimes exacerbated, and instead of preparing the individual for optimal performance, it becomes paralyzing, triggering intense fear, catastrophic thoughts, and avoidance behaviors, among other characteristic manifestations. When this pathological response becomes habitual in anticipation and confrontation of social interactions, it is referred to as SA disorder (SAD).

Accordingly, SAD is understood as a prevalent clinical condition characterized by intense fear and avoidance of social situations. SAD is a heterogeneous clinical condition that usually entails high levels of dysfunction in the lives of people who experience it. This heterogeneous nature of SAD is marked by the dynamic deployment of cognitions, emotions, and behaviors in the interaction with others and in different contexts [ 2 ].

Ambulatory Assessment

Ambulatory assessment (AA) serves as an umbrella term that includes specific techniques such as experience sampling methods, ecological momentary assessment, or daily retrospective methods. These techniques constitute a research methodology of paramount significance in the field of clinical psychology and psychotherapy, enabling researchers and clinicians to gather in-depth, ecologically valid data from individuals. Unlike traditional assessment methods that rely on retrospective self-reporting, AA involves the repeated real-time measurement and gauging of various aspects of an individual’s experiences, behaviors, and physiological responses. The fact that it entails multiple assessments over a certain period makes AA an optimal tool to explore within-person fluctuations and trajectories of these experiences and behaviors.

Moreover, AA circumvents the biases that usual retrospective reports may have because it is usually implemented in momentary assessments or recent retrospective reports (eg, daily diaries [ 3 ]). Owing to the variability of psychological processes such as affective and emotional dynamics [ 4 ], AA can more precisely determine the fluctuation of symptoms. In addition, owing to the possibility of incorporating sensors and biosensors, AA can provide multimodal assessment, overcoming the biases of self-reports [ 5 ].

Over the last few years, there has been an increasing interest in exploring the use of AA in clinical psychology and psychotherapy. Owing to the incorporation of digital technologies, namely, mobile phones, AA has become a very powerful add-on for clinical researchers [ 6 ], first and foremost due to the possibility that AA provides of capturing data in real time, thus grasping contextual aspects from naturalistic settings that laboratory-based assessment does not allow for [ 7 , 8 ]. SA symptoms are particularly contextually bound, and thus, it is of utmost relevance to consider the sensitivity of the context [ 2 ].

All these characteristics have a central and common pursuit to personalize models of psychopathology [ 9 ]. There is no doubt that every person has a certain and unique composition of traits that may lead to functional and dysfunctional states in continuous interaction with the context. Therefore, the revolution of AA is helping foster the creation of tailored models with intensive longitudinal data, which can shed light on the factors that may lead people to experience and behave in adaptive or maladaptive ways.

In this sense, AA proves to be a suitable tool for capturing the co-occurrence of symptoms and psychological processes, offering crucial insights into the antecedents and consequences of SA with enhanced accuracy. This, in turn, facilitates a comprehensive understanding of the factors contributing to the appearance and maintenance of SA and SAD. Given the dimensional nature of SA, AA can shed light on the differences among clinical, subclinical, and healthy participants.

The understanding of SAD in ecological settings may also lead to improving psychological treatments. The insights gained through AA can contribute to refining therapeutic approaches by investigating mechanisms of change [ 10 ]. However, to the best of our knowledge, no systematic review has synthesized the available evidence analyzing the strengths and limitations of the current state of the art.

For all the aforementioned reasons, AA provides a range of advantages that justify its exponential growth as a research methodology in clinical psychology. Although a plethora of research has implemented AA in individuals with SA, these data have not been synthesized yet. Hence, the main aim of this review was to identify studies that used AA to explore SA.

This review followed the recommendations of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement [ 11 ]. The full protocol was registered before the data analysis [ 12 ].

Literature Search

Scopus, PubMed, and Web of Science literature searches were conducted. The search strategy for PubMed is available in Multimedia Appendix 1 and was adapted to the syntax requirements of each database. No filters were included in the searches. The reference lists of eligible articles were manually reviewed to identify additional relevant publications.

Inclusion Criteria

To be included, the studies had to fulfill the following criteria: (1) studies that focused on participants with SAD or SA symptoms; (2) studies that used AA to explore the dynamics of SA, correlates of SA, or the feasibility of AA for SA assessment; (3) articles that included any sort of discussion regarding SA in AA (this criterion was included given that some articles fulfilled all the previous criteria but featured no specific discussion on SA); (4) articles published in peer-reviewed journals in English; and (5) studies that presented at least one active AA or passive data collected via sensor signals (eg, geo-mapping, accelerometer, or GPS) from a phone or smartwatch multiple times per day. Articles were excluded if they (1) were not empirical studies; (2) used a child or adolescent sample; and (3) did not use a daily diary, experience sampling, or AA approach that included assessment and discussion of SA.

Study Selection and Data Extraction

A database search was conducted until August 31, 2023. The literature search produced a total of 14,504 articles, 8926 (61.54%) of which were retained after removing duplicates. A total of 1.23% (110/8926) of these articles were retrieved after title and abstract screening. The subsequent application of the selection criteria resulted in the inclusion of 50% (55/110) of the articles, adding another 15 studies that were identified through citation searching. In total, we included 70 studies ( Figure 1 ). Studies were independently selected by 2 researchers, and disagreements were resolved through consensus.

Using premade tables, the following information was extracted: author and year of publication, study design, follow-up period and sample size and characteristics, aims of the study, measures collected through AA, app name in the case of smartphone-based AA, participation rate (ie, response to recruitment), attrition rate, compliance with AA questions, incentives, outcomes explored, AA measures, frequency of AA, and main findings.

Finally, to summarize the main information, 2 of the authors proposed categories. To form a category, it was required that at least 2 of the included studies addressed the same or a similar topic. To reach an agreement, the resulting categories underwent thorough discussion between the first and fourth authors. This criterion was applied to the “Principal themes explored” section. For the “Emerging topics” section, the criterion for category inclusion was based on relevance regarding addressing a key aspect of the literature that had not been explored before.

Sample Characteristics

Of the 70 studies selected for this systematic review, 29 (41%) used the same sample ( Textbox 1 ). Given that a large proportion of the studies were conducted in university settings, most of the included participants were undergraduate students and, therefore, young adults. Moreover, all the studies (70/70, 100%) were conducted in high-income countries, principally in the United States. A total of 43% (30/70) of the studies included both healthy and clinical populations. In total, 21% (15/70) of the studies were conducted only with clinical participants, whereas 36% (25/70) were conducted with healthy individuals exploring the dynamics of SA. In addition, 33% (23/70) of the studies included comorbid samples, mainly those with other anxiety or depressive disorders. Regarding gender, most studies (57/70, 81%) included more women than men. This reflects the prevalence rates of SAD, which have been shown to be higher in women than in men [ 13 ]. Table S1 in Multimedia Appendix 2 [ 14 - 81 ] and Table S2 in Multimedia Appendix 3 [ 14 - 81 ] summarize the characteristics and main findings of the included studies.

Studies with the same samples

• Blalock et al [ 14 , 15 ], Farmer and Kashdan [ 16 ], Goodman et al [ 17 , 18 ], Kashdan and Farmer [ 19 ], and Kashdan et al [ 20 , 21 ]
• Daniel et al [ 22 , 82 , 83 ] and Beltzer et al [ 23 ]
• Daniel et al [ 24 ], Daros et al [ 25 ], and Ladis et al [ 26 ]
• Doorley et al [ 27 , 28 ]
• Goodman et al [ 29 - 32 ]
• Oren-Yagoda et al [ 33 - 36 ]
• O’Toole et al [ 37 , 38 ]
• Villanueva et al [ 39 ] and Rinner et al [ 40 ]

Methodological Characteristics of the Studies

Sampling frequency.

There were 2 types of sampling identified among the included studies. On the one hand, there were some studies that implemented a daily diary, which typically entails an end-of-day report. On the other hand, other AA studies comprised different numbers of daily assessments and diverse types of prompt contingencies. The duration of the AA ranged from 4 to 35 days. The most commonly implemented study duration was 14 days.

Although a large proportion of the studies (63/70, 90%) used a fixed or random scheduled prompt structure, a range of studies incorporated an event-contingent design [ 40 - 45 ]. Indeed, SA determinants, correlates, and consequences are particularly triggered in interpersonal situations, and event-contingent designs may be suitable for detecting relevant moments. Finally, studies such as those by Daniel et al [ 24 ], Helbig-Lang et [ 46 ], and Kashdan et al [ 20 ] included a mix of different types of data collection, combining random prompt, event-contingent, and end-of-day records.

Compliance rates typically indicate the percentage of prompts or days that the participants completed on average. Compliance rates ranged from 40% to 95%, with average compliance across studies of 73.72% of prompts (SD 15.93%; median 80%).

Statistical Analysis

The vast majority of the studies (61/70, 87%) used hierarchical linear models to account for the nested nature of the collected data. A total of 4% (3/70) of the studies used a combination of hierarchical linear models and structural equation modeling [ 43 , 45 , 79 ], 1% (1/70) of the studies used machine learning techniques [ 47 ], 3% (2/70) of the studies calculated ANOVA models [ 23 , 42 ], and 1% (1/70) of the studies ran ordinary least squares regression [ 48 ].

Methodological Design Characteristics

Table 1 summarizes the principal methodological characteristics of each study. Power analysis to calculate the needed sample size (which was rarely conducted; 15/70, 21% of the studies) and the psychometric properties of the AA questions (37/70, 53% of the studies) were the 2 criteria that were reported the least, whereas the percentage of AA compliance (56/70, 80% of the studies) and attrition rates of AA (46/70, 66% of the studies) were the criteria that were reported the most among the studies in this review.

a AA: ambulatory assessment.

b Presence.

d N/A: not applicable.

Principal Themes Explored

Affective and emotional dynamics.

Naragon-Gainey [ 43 ] explored structural models of affect and internalizing symptoms. While the between-person variance in negative affect (NA) and concurrent levels of NA predicted SA, positive affect (PA) did not. This lack of significance contradicted many other AA studies that yielded significant between-person associations between lower levels of PA and higher levels of NA with SA [ 16 , 20 , 30 , 54 , 57 , 58 , 61 , 69 , 70 ].

Individuals with SAD showed not only higher overall levels of NA but also more emotional instability, which was not the case for PA [ 16 ]. These authors even suggested that the interaction between NA and instability could explain the appearance of SAD.

Discrete Emotions

As suggested by Rozen and Aderka [ 84 ], there is a wide range of discrete emotions that have not been integrated into classic models of SAD. In that sense, AA allows for a nuanced study of single emotions and how they are interconnected not only with each other but also with other cognitive-affective processes and behaviors.

First, Kashdan and Collins [ 70 ] revealed that SA was related to less time spent feeling happy and relaxed and more time spent feeling angry. The results also showed that happy moments were aroused in companion to others. The fact that SA was associated with fewer and less intense positive emotions and more anger episodes was independent of being with others or alone.

Oren-Yagoda et al [ 35 ] investigated the role of envy, showing that visual modes of communication are related to elevated envy compared to voice or text communication. In addition, envy predicted subsequent anxiety above and beyond previous anxiety as well as other negative emotions.

Loneliness is a defining emotion of people with SAD, and Oren-Yagoda et al [ 36 ] found that this relationship was also confirmed in an ecological setting using AA. A significant association was predicted in certain social situations (ie, negativity, positivity, and meaningfulness). Moreover, the relationship between loneliness and anxiety was shown to be reciprocal in individuals with SAD (loneliness predicted anxiety and anxiety predicted loneliness). This deleterious reciprocity was not found in healthy controls.

Finally, Oren-Yagoda et al [ 34 ] investigated the fluctuations of pride in individuals diagnosed with SAD. The results indicated that levels of pride were lower in patients with SAD than in nondiagnosed controls, although when pride was experienced, it predicted a reduction in anxiety levels.

Emotion Regulation

Emotion regulation (ER) was by far the most explored construct among the studies that implemented AA in individuals with SA. This may be explained by the fact that ER is a dynamic process, and AA is very suitable for detecting affect changes and fluctuations in daily life. In addition, not only are ER and SA symptoms highly context sensitive, but mounting research has also shown their interdependence [ 85 ], which justifies the importance of exploring how individuals with SAD use ER in daily life.

Discrete Strategies

Several studies explored only 1 strategy. For example, Kashdan et al [ 20 ] found that individuals with SAD experienced greater experiential avoidance than healthy individuals. Using the same sample, Kashdan et al [ 21 ] found that momentary experiential avoidance presented a stronger association with anxiety during social interactions for individuals with SAD than for individuals without SAD.

Similarly, another study explored the role of emotional suppression, demonstrating that, on days in which SA symptoms increased, the use of suppression tended also to increase [ 61 , 69 ]. The same was found by Beltzer et al [ 23 ], who identified that days with high levels of SA and expressive suppression led to fewer positive emotions.

Farmer and Kashdan [ 61 ] implemented a 2-week diary, showing that high SA was related to positive emotion suppression, fewer positive social events, and fewer positive emotions on subsequent days. In contrast, low SA was associated with fewer negative social events on the days after cognitive reappraisal was used to reduce distress. However, the use of cognitive reappraisal did not lead to any changes in people with high SA.

Meanwhile, Farmer and Kashdan [ 16 ] found that individuals with SAD were 3 times more likely to present acute shifts in NA, which may be a particular experience of this anxiety disorder and not others. This acute shift in NA may lead to experiencing emotions as uncontrollable and threatening, which in turn could explain the higher use of suppression.

Goodman et al [ 63 ] showed that alcohol consumption moderated the negative association between SA and a range of healthy social interactions such as laughter or feelings of acceptance; that is, SA was not related to the perceived quality of interpersonal interactions when participants consumed alcohol, suggesting that alcohol consumption may be a reinforcer of SA. These findings suggest that ER plays a central role in the experience of individuals with SAD who try to explicitly control their emotions and are aware of the effort they make to do so. In a different but related study, Goodman and Kashdan [ 29 ] found that both anxiety and pain were interfering factors in goal attainment, as well as finding an inverse association between daily meaning in life and perceived emotion-related goal interference.

Substance Use

Alcohol consumption and SAD are highly comorbid given that, among individuals with SAD, it is frequent to resort to alcohol as a coping strategy or, in other words, as an ER strategy. By means of AA, it is possible to detect how these 2 phenomena are interrelated. Therefore, several studies explored this topic. Battista et al [ 52 ] examined the relationship between alcohol consumption and SA, revealing that, after each alcoholic drink consumed, SA tended to decrease 2 hours later. Contrary to what the authors expected, this association was not explained by the level of trait SA.

Goodman et al [ 63 ] showed that alcohol consumption moderated the negative association between SA and a range of healthy social interactions such as laughter or feelings of acceptance; that is, alcohol consumption SA was no longer related to the perceived quality of interpersonal interactions, suggesting that SA may be a reinforcer of SA. This reinforcement could be either negative (attenuation of anxiety) or positive (better perception of social situations), which was the main finding of Goodman et al [ 64 ]. The results of this study yielded evidence supporting the negative reinforcement hypothesis such that people with SAD presented higher coping motives (negative reinforcers) but equal levels of affiliation motives (positive reinforcers).

Walukevich-Dienst et al [ 80 ] revealed that consuming substances as a coping strategy in SA is related to heavier consumption, especially on drinking days, which may be a risk factor for the development of an alcohol use disorder. Moreover, when there were SA coping motives, the consequences were more negative compared to days without SA coping motives. Interestingly, levels of SA at baseline were not moderators of these associations, indicating that the coping motive is more important than the antecedent levels of SA.

Kim and Kwon [ 73 ] showed that individuals with SAD had a higher increase rate of alcohol craving when they were tense and lonely and experiencing SA in comparison to individuals without a diagnosis of SAD. These results were moderated by the rate of rumination in the SAD group and avoidance in the non-SAD group. O’Grady et al [ 75 ] explored the role of social-contextual events in the relationship between trait SA and drinking. The results revealed a positive association between trait SA and drinking on the evenings of days in which the individuals experienced an embarrassing situation. This was significantly higher than in healthy participants, suggesting a behavioral maladaptive ER strategy to cope with the intensified levels of SA.

In addition, Buckner et al [ 56 ] studied the association between SA, cannabis use, cannabis craving, and situational variables. This study showed that SA interacted with cannabis craving predicting cannabis use, which sets out a complex relationship between SA and cannabis use and not a simple association (ie, cannabis use as a response to increased state SA).

In the study by Buckner et al [ 57 ], they showed that baseline SA was associated with increases in NA throughout the days in which the participants were monitored but was also significantly associated with postquit withdrawal. Participants with higher levels of SA presented more severe postquit withdrawal symptoms as well as an increase in NA during a cessation attempt. For this reason, the authors suggested that those participants may particularly benefit from intervention and treatment strategies.

Finally, Papp et al [ 76 ] found that students with higher levels of SA presented a stronger association between NA and prescription misuse. This study included externalizing and internalizing symptoms (depression and SA symptoms), and moderation was shown to be significant only for internalizing symptoms. This may indicate differential patterns of substance use as an ER strategy according to different personality traits.

The Complexity of ER: Polyregulation and Flexibility

Some studies incorporated a range of ER strategies in the AA process, which is in line with the current idea of polyregulation , that is, that individuals usually implement a range of strategies simultaneously [ 86 ]. For example, Daros et al [ 25 ] measured various strategies, and after clustering through a factorial analysis, 2 categories of ER strategies were considered for the analyses: avoidant and engagement strategies. However, the authors did not find any significant results for these 2 macrocategories.

On the basis of the model by Gross, Blalock et al [ 14 ] examined both suppression and cognitive reappraisal in SA in comparison to healthy individuals. Both groups presented worse emotional experiences when they suppressed positive versus negative emotions as well as when reappraising negative versus positive emotions. This suggests that suppression may be an adaptive strategy not to feel negative emotions, whereas reappraisal may be effective in increasing positive states. Interestingly, individuals with SAD showed more positive emotions after reappraising negative emotional states to feel fewer negative emotions than the healthy controls.

However, none of these previous examples explicitly framed their studies under the concept of emotion polyregulation, as did Ladis et al [ 26 ]. By including 8 strategies (problem-solving, introspection, distraction, acceptance, thought suppression, seeking advice, cognitive reappraisal, and expressive suppression), the authors systematically explored how often polyregulation occurs in daily life. Overall, the results yielded nonsignificant SA correlates of polyregulation, suggesting that it may be more dependent on within-person differences.

In addition to polyregulation, flexibility has been shown to be central in ER literature to distinguish adaptive from maladaptive regulatory processes [ 87 ]. Given that flexibility is mostly dependent on context, AA emerges as a very useful tool. O’Toole et al [ 38 ] investigated this specific topic in individuals with high and low SA and considered type and intensity as 2 contextual factors. This study revealed that SA moderated the relationship between emotion intensity and experiential avoidance. In individuals with high SA, there was a stronger association between experiential avoidance and specific emotions, such as guilt, nervousness, and sadness.

The study conducted by Beltzer et al [ 23 ] presents an illustrative example of how ER can be better explained by contextual triggers than by the adaptative or maladaptive continuum. The authors created an algorithm based on the 10 most used strategies to generate an ecological momentary intervention (EMI) based on contextual triggers. This algorithm was tested with a group of strategies (disengagement, engagement, and aversive cognitive perseveration) and with 10 individual single strategies compared with a random policy and a behavior policy, with ER effectiveness being the observed outcome. The contextual algorithm improved other policies in cases in which the top 10 strategies were considered separately. However, when the strategies were grouped into categories, the algorithm did not outperform the random recommender or the observed ER strategies.

Goodman et al [ 32 ] also explored ER flexibility considering 2 components of flexibility: the evaluation of contextual demands and matching regulatory strategies to contextual demands. The results indicated that people with SAD considered momentary assessments to be more anxiety provoking while presenting similar patterns to those of control participants when gauging contextual demands, particularly those related to perceived controllability. That is, some disengagement strategies (rumination, thought suppression, and expressive suppression) were found to be unrelated to perceived controllability. This means that these strategies were used independently of perceived controllability in a certain context. However, contrary to previous results, participants with SAD yielded similar patterns to those of control participants in response to anxiety intensity.

Higher anxiety ratings predicted greater use of all strategies regardless of the type of strategy used. In addition, this study showed that people with SAD may be more prone to use thought suppression but not engagement strategies, which is inconsistent with previous studies.

In other studies, a specific component of the heterogeneous and complex process of ER was explored. Although most clinical research on ER tends to simplify the discussion on putatively maladaptive (eg, expressive suppression) or adaptive (eg, cognitive reappraisal) strategies, there is a range of potential explanatory variables that set a more complex scenario than implementing certain strategies or not. For example, one study [ 24 ] investigated the perception of ER effectiveness, which is based on a robust research line that revolves around how goals shape and determine ER deployment and outcomes [ 88 ]. Daniel et al [ 24 ] found that, depending on the way in which effectiveness is measured (either judgment of effectiveness or change in affect), the results differ. While the judgment of effectiveness indicates that avoidance‐oriented ER attempts are less effective than engagement‐oriented ER attempts, changes in self-reported effects following ER attempts present the opposite results.

Similarly, Goodman et al [ 18 ] explored the extent to which beliefs of ER determine the use of specific patterns. In laboratory settings, De Castella et al [ 89 ] demonstrated that individuals with SAD presented low emotional self-efficacy, or the belief that emotions cannot be changed, but the results obtained by Goodman et al [ 18 ] provide ecological validity to a result that confirms the interdependency between cognitions and emotions [ 90 ].

Another approach is to calculate ER diversity, defined as the variety, frequency, and evenness of the implemented ER. Finally, Daniel et al [ 22 ] studied whether ER diversity predicted SA severity. The results showed that diversity within avoidance-oriented strategies was associated with both trait and state SA levels. At a more specific level of analysis, participants who responded more evenly and deployed a vast array of avoidance-oriented strategies more frequently were more prone to belonging to the high-SA group.

Emotion Clarity and Differentiation

Another important aspect that has been of increasing interest in the ER literature is linked to convergent processes such as emotion clarity and differentiation. Emotion clarity is defined as the ability to identify, distinguish, and describe specific emotions [ 91 ]. Park and Naragon-Gainey [ 45 ] found that lower momentary clarity was related to increases in subsequent momentary internalizing symptoms (ie, anxiety and depressive symptoms). This association was explained by an unsuccessful use of ER.

A total of 4% (3/70) of the studies examined emotion differentiation in individuals with SAD [ 19 , 37 , 48 ]. Emotion differentiation is conceptualized as the ability to recognize, identify, and label broad emotional experiences into discrete emotion categories [ 92 ]. Kashdan and Farmer [ 19 ] demonstrated that an increase in SA symptoms is linked to an impairment in negative emotion differentiation (ie, the ability to label and describe differences among negative emotions). In particular, it was found that negative emotion differentiation plays a relevant role in implementing more effective ER strategies. For example, Seah et al [ 48 ] conducted 2 studies that showed that negative emotion differentiation moderated the positive relationship between rumination and social avoidance. Similarly, O’Toole et al [ 37 ] showed that individuals with both high SA and poor negative emotion differentiation presented the least use of cognitive reappraisal. In addition, individuals with high SA used more suppression strategies despite the ability to differentiate positive emotions.

Perseverative Cognition and Mind Wandering

Although the most common variable that has been studied in individuals with SAD is postevent processing (PEP), there is a great overlap between PEP and rumination. In essence, both revolve around the perseverative thinking of past events, but PEP is strictly related to social interactions, including an important component of the actual interventions that both the individual and the others may have done or said. In total, 6% (4/70) of the studies used AA to examine processes related to PEP and rumination.

Helbig-Lang et al [ 46 ] studied individuals diagnosed with SAD to explore predictors of higher PEP levels. The results showed that higher PEP was predicted by self-attention, NA, social performance situations, and the use of safety behaviors. In addition, Badra et al [ 50 ] investigated PEP in a nonclinical sample of undergraduate students with high and low SA scores. Although no differences were detected between the groups, PEP was reduced to a single item, and no additional information on the social context was collected, which could have affected the results.

Another study that explored PEP showed that it decreased after a speech task [ 68 ]. The between-level average differed from the person-specific trajectories. This was the case not only for the decrease in PEP after the speech task but also in the temporal cascading relationship between PEP and the next measurement of PEP. The level of anxiety in the speech task predicted engagement in PEP, and this activated a more intense experience of the negative balanced memory, indicating the interconnectedness of cognitive-affective processes.

Bailey et al [ 51 ] studied perseverative cognition (worry and rumination) using physiological measures and found that there was a higher use of this type of repetitive thinking related to lower heart rate variability after negative social interactions. Finally, potential changes in momentary PEP throughout treatment were explored by Katz et al [ 41 ] showing that cognitive behavioral group therapy reduced levels of PEP.

In total, 3% (2/70) of the studies explored mind wandering, which is both an interesting and controversial topic. Traditionally, it was considered that mind wandering was just a negative process given that it was linked to the opposite of having a mindful disposition. However, the latest research has shown that it could be related to less boredom, more creativity, and a better mental health state [ 93 ].

In the study by Arch et al [ 49 ], the authors investigated differences in the frequency, range of content, and correlates of internal off-task thinking (ie, mind wandering). Relative to on-task thinking, internal off-task thinking was associated with worse mood, more self-focus, and less thought controllability for those with SAD compared to healthy controls. In addition, participants with SAD engaged in internal unrelated task thinking more frequently than those in the control group and presented more unintentional mind wandering on a trait questionnaire.

Specific Interactional Triggers, Patterns, and Activities

Geyer et al [ 62 ] investigated the association between NA in social interactions and perceived enjoyment of those interactions to explore specific real-time contributors to negative perceptions often experienced by individuals with SA. The results revealed that this association was more negative when SA was more severe, although the sample consisted of undiagnosed individuals.

Meanwhile, Blalock et al [ 15 ] studied the experience of flow in social and nonsocial situations in individuals with SAD and healthy participants. The results were contrary to the hypotheses, revealing that individuals with SAD presented flow more frequently in social situations than healthy participants. The authors explained this unexpected result using the concept of flow, which includes the component of experiencing a challenging situation as a defining feature. It is reasonable to think that people with SAD experience normal social interactions as more challenging than healthy participants.

In one study, the association between sexual activity and SA was explored in nonclinical individuals [ 71 ]. As could be expected, sexual activity was influenced by SA such that individuals with SA reported their sexual episodes as less pleasurable and reported being less connected with their partners as well as presenting a lower frequency of sexual activity. Overall, these results suggest that sexual activity is not fulfilling when experiencing SA.

Goodman et al [ 30 ] conducted 2 AA studies in which they concluded that, although individuals with SAD present fewer and less satisfying social relationships, they enjoy social interactions when they occur, which might indicate that they are happier with others than alone. In other words, experiencing SA and the relative concern about socializing does not hinder the pleasure of socializing.

These results are aligned with those of other 2 studies conducted on undergraduate students [ 54 , 83 ], which showed that SA was not related to a lower desire to be with others. However, in the study by Brown et al [ 54 ], a preference for solitude was found in interactions with unfamiliar people.

Villanueva et al [ 39 ] revealed that individuals with SAD presented a higher number of social interactions through their mobile phones than the control group. They were also the group with the least number of social interactions (vs the control group and individuals with depression). In-person interactions (ie, face-to-face) were revealed to be less related to increases in NA and decreases in PA.

In the study by Doorley et al [ 27 ], no significant association was found between the medium of communication (ie, digital vs face-to-face communication) and SA. That is, in both media, there was an association between SA and less positive and more negative emotions. Oren-Yagoda and Aderka [ 33 ] also explored media of communication in individuals diagnosed with SAD. In this case, the focus was on the media of communication and the associated perceptions and emotions. Individuals with SAD usually preferred to use voice and text media to a greater extent than visual media. However, the authors found that, despite this preference, when visual media were implemented, immediate increases in positive perceptions and emotions were experienced by people with SAD. These results support the idea that the selected medium functions as a safety behavior.

Meanwhile, Russell et al [ 44 ] revealed that individuals with SAD presented higher levels of submissive behavior and lower levels of dominant behavior compared to control participants. However, this was true in the presence of anxiety-eliciting cues, which means that there are certain situations that can be perceived as safe environments. In contexts of emotional security, all individuals with SAD presented an enhanced agreeable and deceased quarrelsome behavior, also meaning that there might be situations of security in which individuals with SAD can respond to positive appraisals with enhanced affiliative behavior.

Hur et al [ 66 ] found that individuals with SAD benefit more from having close friends, family members, and romantic partners in terms of resulting in lower levels of NA, anxiety, and depression compared to control participants. However, they tend to spend less time with those companions. These results emphasize the intact capacity of individuals with SAD to enhance their mood through social interactions.

In this line, Hannah Lee [ 65 ] obtained consistent results, suggesting a tight connection between the levels of SA and the degree of unfamiliarity and judgmentalness in the interactions. Namely, individuals with higher levels of SA presented a stronger association with the 2 processes as a consequence of being more sensitive to experiencing anxiety when facing interactions of the same level of unfamiliarity and judgmentalness compared to people with lower levels of trait SA.

Čolić et al [ 59 ] were the first to explore depersonalization and derealization in embarrassing situations. They showed that people with SAD presented more embarrassing social interactions than control participants, and as a result, they also presented more depersonalization and derealization, which can be seen as responses to strong emotions (including embarrassment) as well as attempts to cope with situational challenges.

Cognitive Factors

Social comparison is another important aspect to explore in individuals with SAD given that they usually tend to see themselves with a negative self-image [ 94 , 95 ]. In another study, Brown et al [ 54 ] showed that SA was associated with greater self-consciousness, which can also be aligned with the negative self-view that characterizes SAD.

Goodman et al [ 31 ] found that SA is related to less favorable and more unstable social comparisons, which can be explained by a negative self-image. Moreover, they demonstrated that, when people with SAD make less favorable social comparisons, they are especially fearful of others’ evaluations.

In a recent study, Brown et al [ 55 ] investigated interpersonal distress in heightened SA symptoms as predictors of suicidal ideation. Specifically, this study showed that hurdles to seeking social support and social comparisons mediated suicidal ideation.

Models of SAD have emphasized the central role of fear of evaluation in the appearance and maintenance of this clinical condition. This construct has been included in cognitive models related to attentional biases and negative interpretations of the self [ 96 - 98 ]. Although negative evaluation was considered a core dimension in early models of SAD, fear of positive evaluation has emerged as an important topic in recent years [ 78 , 99 ].

Another study explored anxiety sensitivity cognitive concerns and fear of negative evaluation as 2 potential predictors of SA amplification. Anxiety sensitivity cognitive concerns were shown to uniquely amplify arousal as a consequence of social stress, whereas fear of negative evaluation predicted anxiety fluctuations, indicating that these 2 cognitive constructs may be associated with SA in different ways [ 79 ].

By implementing 2 AA studies, Reichenberger et al [ 78 ] explored the interaction of both positive and negative evaluation, affect, and stress reactivity. Although the results were not fully in line with the hypotheses, fear of negative evaluation was negatively associated with PA. In addition, the results revealed that the closeness of the relationships was paramount to determine when the interaction was significant, with closer relationships being less anxiety provoking. Consistent with these results, positive and negative feedback seeking has been shown to be higher in individuals with SAD than in healthy participants [ 81 ], all of which is aligned with the mounting evidence developed in cross-sectional or laboratory settings. Similarly, Doorley et al [ 28 ] demonstrated that self-perceived intense positive events, which are normally reduced in SA, paradoxically provided more psychological benefits (reduced anxiety and motivation toward social situations as well as an increased sense of belonging).

Moreover, Nanamori et al [ 74 ] studied triggers of self-focused attention, which is another key component of classic cognitive models of SAD. The results showed that perception of gaze, evaluation, and authority predicted self-focused attention from the observer’s perspective, whereas perception of gaze also predicted self-focus on body sensation. Moreover, the perception of positive response and that of a stranger predicted self-focus on body sensation hinged on sex, suggesting that the positive response perception of female participants acted as a predictor of the self-focus on body sensation.

Emerging Topics

Use of aa to assess psychological interventions.

Daniel et al [ 83 ], Katz et al [ 41 ], and Kivity and Huppert [ 72 ] implemented AA to explore the course of treatment. In the case of Katz et al [ 41 ], PEP, a putative maintenance factor of SA symptoms, was assessed over the course of a cognitive behavioral therapy intervention with a subset of the 60 included participants answering an AA. The intervention yielded significant reductions in both general and momentary PEP, and both types of PEP were significant predictors of SA severity after treatment.

Another study was conducted by Kivity and Huppert [ 72 ]. It explored how ER in individuals with high and low SA responded to a practice of cognitive reappraisal using self-report, laboratory tasks, and daily diaries. Although the group with high SA presented lower symptom severity and greater self-efficacy of reappraisal, daily anxiety was not significantly different.

Daniel et al [ 83 ] conducted a randomized controlled trial testing whether cognitive bias modification for interpretation could decrease negative interpretation bias. Both the active and control conditions received an AA throughout the treatment period (5 weeks). While the active group also received cognitive bias modification training, the control group only answered the AA. A total of 2 publications were identified from this study, reporting self-report and passive sensing outcome measures. Despite the interesting approach of incorporating multimodal assessment, both analyses yielded nonsignificant results.

Use of Sensors and Biosensors in AA

Over the last few years, new advancements in wearable sensors and biosensors have enabled us to incorporate them into AA studies. In the case of SA, this has led to a considerable body of evidence. Specifically, Bailey et al [ 51 ], Boukhechba et al [ 53 ], Chow et al [ 58 ], Daniel et al [ 82 ], Di Matteo et al [ 60 ], and Jacobson et al [ 47 ] conducted studies using sensors (GPS location and accelerometers) and biosensors (heart rate and heart rate variability).

Bailey et al [ 51 ] investigated perseverative cognition in relation to the parasympathetic nervous system, which is considered of utmost relevance in the regulation of stress and emotions [ 100 ]. In this study, individuals with both depression and SAD were monitored, and individuals with SAD presented the highest frequency of daily perseverative cognition, which was statistically associated with lower heart rate variability, moderated by negative social interactions. Jacobson and Bhattacharya [ 67 ] showed that spending time indoors was associated with anxiety and avoidance symptoms, and this association was significantly higher in individuals with SAD than in those with generalized anxiety disorder.

Boukhechba et al [ 53 ] and Chow et al [ 58 ] used GPS and Jacobson et al [ 47 ] used an accelerometer to demonstrate the capability of passive sensing to predict the severity of SA symptomology according to the level of activity. Moreover, Di Matteo et al [ 60 ] designed an app to capture ambient audio, GPS location, screen state, and light sensor data, and this app was shown to be able to identify SAD patterns of behavior in a relatively accurate way.

Exploring Idiographic Comorbidity Patterns

Although a vast array of studies included heterogeneous samples in terms of their diagnosis, only Piccirillo and Rodebaugh [ 77 ] had the objective of exploring SAD and major depressive disorder comorbidity, aiming to model person-specific trajectories of cognitive-affective and behavioral dimensions related to these disorders. By including only cisgender women with comorbid SAD and major depressive disorder, this study showed the utmost relevance in disentangling between-person, within-person, and person-specific patterns. For example, loneliness was revealed to be a common predictor of depressive mood and social avoidance at the group level; however, this was not the case when examining the idiographic networks.

Transcultural Differences

Only 1% (1/70) of the studies examined potential variations between different cultural groups. Lee et al [ 42 ] explored differences between European Americans and Asian Americans, showing that both groups experienced the same number of anxious events during social situations but Asian Americans presented more negative emotions in those moments.

Principal Findings

Our review of 70 original studies using AA to explore SA showed that this methodology provides valuable real-time information on the momentary association of SA with several variables, such as context, affective dynamics, emotional states and regulation, social interactions, and other consequences and antecedents. This comprehensive understanding can contribute to better insights into the appearance and maintenance of symptoms and of this clinical disorder.

Aligned with the burgeoning literature on AA, affect and emotional dynamics emerged as the most studied topics. These investigations revealed a trend of an increase in NA levels leading to a heightened experience of SA, as well as a growing attention to positive emotions and PA deficits in individuals with SAD. This review also supports the notion that negative emotions and affect are not enough to distinguish normal from pathological SA. As demonstrated by Park and Naragon-Gainey [ 45 ], AA may help shed light on the structural models of affect both between and within individuals’ variances, evidence that traditional cross-sectional research or long-term longitudinal research may not capture.

Most interestingly, most of the studies exploring affect trends explored them coupled with ER strategies, consistently extending the vast literature in this regard. Exacerbated NA and PA and dysfunctional strategies to cope with them form a dysfunctional pattern that may be responsible for the appearance and maintenance of SA and SAD [ 85 ]. The studies revealed that the interpersonal encounters of individuals with SAD may differ from those of controls in terms of ER use and type of ER strategy. Specifically, both intra- and interpersonal regulatory mechanisms have been shown to be associated with increasing levels of SA. In clinical populations, what was shown to influence the levels of SA was not the use of certain strategies but rather the lack of effectiveness of their use. However, this was not the case in healthy populations. Accordingly, a potential difference between SA symptoms in healthy and clinical populations may lie on the effectiveness or underuse of ER strategies.

In line with the mounting evidence exploring suppression and both experiential and behavioral avoidance in individuals with SAD, this systematic review showed coherent and robust results across the included studies concerning the maladaptive use of these 2 strategies. People with SAD may present an overreliance on the use of suppression and avoidance [ 85 ], resulting in a range of negative outcomes such as an increase in NA and a decrease in PA.

In contrast, cognitive reappraisal, a putatively effective strategy, does not yield straightforward results. The problem with individuals with SAD is more the ineffective use of cognitive reappraisal rather than the scarce use of this strategy, although the studies did not seem to coherently yield conclusive results.

Taken together, the results on affective dynamics and ER indicate how appropriate AA can be to study these processes, especially in the case of SA and SAD. AA may be particularly helpful in disentangling between- and within-person effects, which the literature demonstrates can have different or even contrary results, especially in the context of psychological interventions [ 101 ].

As a key takeaway message, AA shows that individuals with high SA symptoms or a diagnosis of SAD may not use a narrower repertoire of ER strategies but rather implement that repertoire with less skillfulness or less ability to identify when it is appropriate to implement a certain strategy. In this sense, it is essential to continue exploring the role of polyregulation and flexibility to identify which specific facet of ER contributes as a mechanism of action of SAD.

In that vein, substance use can be seen as a maladaptive behavior that functions as a behavioral strategy to regulate emotions and cope with situations that elicit symptoms of SA. This is particularly recurrent in SA-provoking situations, constituting a reinforcement cycle that operates similarly to other safety behaviors. In particular, alcohol consumption may function as a negative reinforcer, attenuating the negative self-perceived quality of interpersonal encounters and anxiety levels. When this occurs, alcohol use becomes a rapidly established maladaptive behavior with negative consequences.

In addition, maladaptive cognitions, emotional mechanisms, and behaviors were found to be activated when levels of anxiety increased. More specifically, cognitive aspects such as beliefs in capacity, effectiveness in regulating emotions, and the ability to differentiate emotions appear to be relevant in explaining how SA is activated.

As a general takeaway message, there is ample evidence showing the mutual directionality between cognitive and affective or emotional facets and behaviors in the appearance and maintenance of SAD. The several sections in which the studies were categorized constitute just one way of organizing the information. However, many of these studies can be understood as forms of cognition or ER or specific interactional patterns. A clear example is alcohol consumption, which is a behavior that, in the context of SAD, can be understood as an ER strategy.

In that sense, ER is currently a trending topic in AA, but it is important to integrate this increasing amount of knowledge into classic cognitive models. This is pertinent for psychopathological developments in general, and SAD is not an exception. Over the years, the most influential developments in SAD have been cognitive and behavioral models [ 96 , 98 ]. Paradoxically, in this review, cognitive processes remained an underexplored area. An example of this is mental imagery, which has been shown to be a transdiagnostic process that explains the appearance and maintenance of a range of clinical conditions, including SAD [ 94 ]; however, there is a dearth of studies on this crucial construct.

An additional line of research that needs to be further explored is comorbidity to explore the mutual dependency of certain groups of signs and symptoms. However, given the lack of network analyses, this mutual dependency was not explored in depth. For example, there was only one study exploring suicidal ideation and attempts despite the ample existing literature on AA in suicide research [ 102 ] and the strong association between suicide and SA [ 103 ]. In the same vein, the relationship among personality, personality pathology, and SA is a relevant topic in contemporary psychopathology that could be further explored using AA strategies. Indeed, there is a growing body of evidence exploring personality and personality pathology dynamics and states, which should be considered in future studies of SA [ 9 ].

Another issue worth discussing revolves around the incorporation of AA into psychological interventions. This is an increasingly used practice and may be well integrated with routine outcome monitoring procedures that have been shown to yield significant effects when implemented in both controlled and naturalistic interventions [ 104 ]. Routine outcome monitoring is an increasingly implemented strategy that can connect research and practice in unprecedented ways. With that aim, it is necessary to create simple visualization interfaces to feed back the trajectories of certain patient variables. Some efforts have already been made in this direction [ 105 ]. If these endeavors are further developed, they can be used by clinicians as a clinical tool, and at the same time, researchers can collect naturalistic data.

Another topic with a lot of potential is the incorporation of behavioral and physiological processes by means of sensors and biosensors. Multimethod measurements that incorporate both passive and active assessments can be of tremendous relevance to harness the affordances of each approach. Together with the development of machine learning algorithms, the proliferation of EMIs is more plausible. This is very important to enhance the personalization of possible treatments.

Regarding data collection, there are now software solutions that are opening up unprecedented opportunities for future research. Older studies usually included PDAs or similar devices, which implies not only spending more resources to implement an AA study but also some degree of training in order for participants to be able to use these devices. Currently, there are studies that harness existing survey platforms such as Qualtrics to program either random or fixed prompts without the need for any specifically developed software.

Given that most of the studies were conducted in the United States and the rest were conducted in other Western high-income countries, the results should be generalized to other contexts. Cultural and contextual factors are determinant in all psychopathological conditions, and SAD is not an exception [ 106 ]. The proliferation of open-source platforms (eg, m-Path [ 107 ]) will permit the dissemination of this methodology to researchers without large budgets, such as researchers from low- and middle-income countries. This is crucial to guarantee that knowledge is not restricted to certain populations, fundamentally populations from Western, educated, industrialized, rich, and democratic countries. In addition, most of the studies (54/70, 77%) paid the participants to enhance the compliance rates, which turned out to be in line with the average compliance in AA literature (approximately 75% [ 108 ]). However, this should be considered in future research on AA that seeks to increase the external validity by means of ecological designs.

Methodological Design

Regarding the methodological design of the studies included in this systematic review, there are important aspects to discuss. Most of the studies were well designed; advanced statistical strategies were applied; and, accordingly, most of this research was published in journals with a high impact factor. However, there is a methodological pitfall in AA research that revolves around the lack of psychometrically sound instruments, usually because of trying to reduce participant burden as much as possible. According to Hopwood et al [ 109 ], four aspects are essential when discussing the theoretical and methodological implications for AA research: (1) How should time be scaled? (2) How many assessments are needed? (3) How frequently should assessments be conducted? and (4) When should the assessments occur? Researchers using AA methods to conduct research on SA and SAD should carefully consider these questions both theoretically and empirically. Moreover, there is a wider consensus on the need to conduct more theory-driven hypothesis testing [ 110 ]. All these methodological aspects should be considered with caution together with the importance of increasing the transparency of reporting the results of AA research [ 111 ].

Power analysis was revealed as a weak methodological aspect, with many of the studies not calculating the required sample sizes to anticipate the number of needed participants. Potential limitations concerning the quality of the studies seem to be related to the lack of clear guidelines and standards, which have only recently started to emerge [ 112 ].

Regarding the data analysis, most of the studies used multilevel or hierarchical linear models [ 113 ]. Indeed, in cases in which ANOVAs or ordinary least squares models were used instead of hierarchical models, the results should be interpreted with more caution. They do not account for the dependency of the data, and in longitudinal assessments such as AA in which data are essentially nested, using these strategies may yield inaccurate pictures of the data [ 114 ]. In addition, AAs generally entail mounting random missing data, and multilevel mixed models are appropriate to deal with that data structure.

Future studies need to incorporate new modalities of data analysis that might provide more complex information to understand the dynamics of SA. For example, multilevel network analyses [ 115 ] would allow for shedding light not only on the nested structure of the symptoms but also on the interconnectedness at every moment of the individuals’ experiences and behaviors. In addition, new-generation time-series analyses such as the time-varying change point autoregressive models would allow for the detection of gradual and abrupt changes in SA markers over the course of the AAs [ 116 ]. Furthermore, the recently developed dynamic structural equation modeling method [ 117 ] is particularly suitable for intensive longitudinal data from AA. This method allows for a more accurate estimation of individual differences in means and autoregressive effects from AA data. Finally, machine learning strategies will be paramount not only to build predictive models that can better explain SA but also to implement EMIs based on people’s needs [ 118 ]. In the field of SAD, there is a dearth of studies on EMIs, which is surprising given the ample evidence that has been found using AA.

Limitations

The results of this review should be considered in light of certain limitations. The first limitation concerns the inclusion criteria. Gray literature, including dissertations and preprint depositories, was not considered. Given the growing interest in this topic, we may have missed other relevant studies from these sources. However, this decision had the main aim of ensuring the rigor of including articles that had undergone a peer review process. In addition, we only included revised articles published in English, excluding articles published in different languages.

A second limitation is that this is the first synthesis that summarizes the literature on AA for SA, but further quantitative syntheses (ie, meta-analyses) should be conducted on the specific topics identified in this study. Thus, a qualitative review is a first step that contributes to taking stock of the principal topics studied in the field of SA and AA, but no conclusive statements should be drawn.

Conclusions

This systematic review shows that AA constitutes a very powerful modality to grasp SA from a complementary perspective to laboratory experiments and usual self-report measures. Over the last few years, mounting research has been conducted showing important trends that are shedding light on the understanding of SA and SAD using this ecological tool that is revolutionizing the field.

Acknowledgments

This work was supported by Margarita Salas postdoctoral contracts MGS/2021/37 (UP2021-021) and MGS/2022/18 (UP2022-024) financed by the European Union NextGenerationEU. This study was also funded by the Prometeo Programme grant for Research Groups of Excellence (CIPROM/2021/041—Project “IMPULSA”), Conselleria d’Innovació, Universitats, Ciència i Societat Digital, Generalitat Valenciana. Finally, this work was supported by the Generalitat Valenciana through the Santiago Grisolía predoctoral program (GRISOLIAP/2021/009).

Data Availability

All data generated or analyzed during this study are included in this published article and its supplementary information files.

Conflicts of Interest

None declared.

Syntax used in database searches.

Characteristics of the included studies.

Social anxiety disorder ambulatory assessment research design overview.

PRISMA Checklist.

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Abbreviations

Edited by J Torous; submitted 17.02.23; peer-reviewed by K Daniel, T Ranjan; comments to author 03.09.23; revised version received 28.01.24; accepted 07.02.24; published 04.04.24.

©Javier Fernández-Álvarez, Desirée Colombo, Juan Martín Gómez Penedo, Maitena Pierantonelli, Rosa María Baños, Cristina Botella. Originally published in JMIR Mental Health (https://mental.jmir.org), 04.04.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on https://mental.jmir.org/, as well as this copyright and license information must be included.

This paper is in the following e-collection/theme issue:

Published on 10.4.2024 in Vol 26 (2024)

Effectiveness of a Web-Based Individual Coping and Alcohol Intervention Program for Children of Parents With Alcohol Use Problems: Randomized Controlled Trial

Authors of this article:

Original Paper

• Håkan Wall 1 , PhD   ; 
• Helena Hansson 2 , PhD   ; 
• Ulla Zetterlind 3 , PhD   ; 
• Pia Kvillemo 1 , PhD   ; 
• Tobias H Elgán 1 , PhD  

1 Stockholm Prevents Alcohol and Drug Problems, Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Stockholm, Sweden

2 School of Social Work, Faculty of Social Sciences, Lund University, Lund, Sweden

3 Clinical Health Promotion Centre, Department of Health Sciences, Lund University, Lund, Sweden

Corresponding Author:

Tobias H Elgán, PhD

Stockholm Prevents Alcohol and Drug Problems, Centre for Psychiatry Research

Department of Clinical Neuroscience

Karolinska Institutet, & Stockholm Health Care Services

Norra Stationsgatan 69

Stockholm, 11364

Phone: 46 700011003

Email: [email protected]

Background: Children whose parents have alcohol use problems are at an increased risk of several negative consequences, such as poor school performance, an earlier onset of substance use, and poor mental health. Many would benefit from support programs, but the figures reveal that only a small proportion is reached by existing support. Digital interventions can provide readily accessible support and potentially reach a large number of children. Research on digital interventions aimed at this target group is scarce. We have developed a novel digital therapist-assisted self-management intervention targeting adolescents whose parents had alcohol use problems. This program aims to strengthen coping behaviors, improve mental health, and decrease alcohol consumption in adolescents.

Objective: This study aims to examine the effectiveness of a novel web-based therapist-assisted self-management intervention for adolescents whose parents have alcohol use problems.

Methods: Participants were recruited on the internet from social media and websites containing health-related information about adolescents. Possible participants were screened using the short version of the Children of Alcoholics Screening Test-6. Eligible participants were randomly allocated to either the intervention group (n=101) or the waitlist control group (n=103), and they were unblinded to the condition. The assessments, all self-assessed, consisted of a baseline and 2 follow-ups after 2 and 6 months. The primary outcome was the Coping With Parents Abuse Questionnaire (CPAQ), and secondary outcomes were the Center for Epidemiological Studies Depression Scale, Alcohol Use Disorders Identification Test (AUDIT-C), and Ladder of Life (LoL).

Results: For the primary outcome, CPAQ, a small but inconclusive treatment effect was observed (Cohen d =–0.05 at both follow-up time points). The intervention group scored 38% and 46% lower than the control group on the continuous part of the AUDIT-C at the 2- and 6-month follow-up, respectively. All other between-group comparisons were inconclusive at either follow-up time point. Adherence was low, as only 24% (24/101) of the participants in the intervention group completed the intervention.

Conclusions: The findings were inconclusive for the primary outcome but demonstrate that a digital therapist-assisted self-management intervention may contribute to a reduction in alcohol consumption. These results highlight the potential for digital interventions to reach a vulnerable, hard-to-reach group of adolescents but underscore the need to develop more engaging support interventions to increase adherence.

Trial Registration: ISRCTN Registry ISRCTN41545712; https://www.isrctn.com/ISRCTN41545712?q=ISRCTN41545712

International Registered Report Identifier (IRRID): RR2-10.1186/1471-2458-12-35

Introduction

Children who grow up with parents who have substance use problems or disorders face extraordinary challenges. Approximately 20% of all children have parents with alcohol problems [ 1 - 5 ], while approximately 5% have parents with alcohol use disorders [ 4 , 6 , 7 ]. Children growing up with parental substance abuse are at an increased risk of several negative outcomes, such as psychiatric morbidity [ 8 - 12 ]; poor intellectual, cognitive, and academic achievement [ 13 - 15 ]; domestic physical abuse [ 16 ]; and early drinking onset and the development of substance use problems [ 9 , 17 , 18 ]. Thus, children exposed to parental substance abuse comprise a target group for selective interventions and prevention strategies [ 19 - 22 ].

In Sweden, municipalities account for most of the support offered to these children. An annual survey by the junior association of the Swedish branch of Movendi International (ie, an international temperance movement) reported that 97% of all municipalities provided support resources [ 23 ]. However, estimates from the same survey showed that approximately 2% of the children in the target group received support. Hence, an overwhelming majority never receives support, mainly because of difficulties in identifying and attracting them to intervention programs [ 22 , 24 ].

The internet has become an appealing way to reach and support a large number of people [ 25 , 26 ]. Web-based interventions seem particularly attractive to adolescents, as they generally use digital technology and social media. Furthermore, research has shown that adolescents regard the internet as inviting because it is a readily accessible, anonymous way of seeking help [ 27 ]. Web-based interventions can reduce the stigma associated with face-to-face consultations in health care settings [ 28 ], and young people appreciate the flexibility of completing web-based sessions to fit their own schedules [ 29 ]. The positive effects of web-based interventions have been detected across a broad range of conditions. A recent review by Hedman-Lagerlöf et al [ 30 ] concluded that therapist-supported internet-based cognitive behavioral therapy for adults yielded similar effects as face-to-face therapy. To date, most web-based interventions have been designed for adults. Although the number of web-based interventions targeting children or adolescents is increasing [ 25 , 31 - 33 ], the number of digital interventions aimed at children of substance-abusing parents is still scarce [ 22 , 34 - 38 ]. Those described in the literature, however, all have in common that they are quite extensive, with a duration over several weeks, and a brief digital intervention could complement these more extended interventions. For instance, our research group initiated a study on a web-based group chat for 15- to 25-year-old individuals who have parents with mental illness or substance use problems [ 35 ]. The duration of the program is 8 weeks, and it is a translated version of a program from the Netherlands [ 34 ], which has been shown to have inconclusive treatment effects [ 39 ]. In Sweden, 2 other programs with inconclusive treatment effects have been tested that target significant others and their children [ 37 , 38 ]. Finally, a digital intervention developed in Australia for 18- to 25-year-old individuals with parents with mental illness or substance use disorder [ 36 ] was tested in a pilot study demonstrating positive findings [ 40 ].

To meet the need for a brief, web-based intervention that targets adolescents having parents with alcohol problems and build on the evidence base of digital interventions targeting this vulnerable group, we developed a novel internet-delivered therapist-assisted self-management intervention called “Alcohol and Coping.” Our program originated from a manual-based face-to-face intervention called the “Individual Coping and Alcohol Intervention Program” (ICAIP) [ 41 , 42 ]. Previous studies on both the ICAIP, which aimed at college students having parents with alcohol problems, and a coping skills intervention program, which aimed at spouses of partners with alcohol dependency [ 43 ], have demonstrated positive effects regarding decreased alcohol consumption and improved mental health and coping behaviors [ 41 - 44 ]. Furthermore, the results from these studies underscore the importance of improving coping skills [ 42 , 44 ]. Among college students, those who received a combination of coping skills and an alcohol intervention program had better long-term outcomes [ 42 ].

The aim of this study was to test the effectiveness of Alcohol and Coping among a sample of adolescents aged 15-19 years with at least 1 parent with alcohol use problems. We hypothesized that the intervention group would be superior to the control group in improving coping skills. Secondary research questions concerned the participants’ improvement in (1) depression, (2) alcohol consumption, and (3) quality of life.

This study was a parallel-group randomized controlled trial in which participants were randomized to either the intervention or waitlist control group in a 1:1 allocation ratio. The trial design is illustrated in Figure 1 .

Recruitment and Screening

The participants were recruited from August 2012 to December 2013 through advertisements on social media (Facebook). The advertisements targeted individuals aged 15-19 years with Facebook accounts. Participants were recruited on the internet through advertisements on websites containing health-related information about adolescents. The advertisements included the text, “Do your parents drink too much? Participate in a study.” The advertisement contained an invitation to perform a web-based, self-assessed screening procedure. In addition to questions about age and sex, participants were screened for having parents with alcohol problems using the short version of the Children of Alcoholics Screening Test-6 (CAST-6), developed from a 30-item original version [ 45 ]. The CAST-6 is a 6-item true-false measure designed to assess whether participants perceive their parents’ alcohol consumption to be problematic. The CAST-6 has demonstrated high internal consistency ( r =0.92-0.94), test-retest reliability ( r =0.94), and high validity as compared to the 30-item version ( r =0.93) using the recommended threshold score of 3 or higher [ 45 , 46 ]. We previously translated the CAST-6 into Swedish and validated the translated version among 1450 adolescents, showing good internal consistency (α=.88), excellent test-retest reliability (intraclass correlation coefficient=0.93), and loading into 1 latent factor [ 47 ]. Additional inclusion criteria included having access to a computer and the internet and being sufficiently fluent in Swedish. Participants were excluded from the study and were referred to appropriate care if there were indications of either suicidal or self-inflicted harmful behaviors. Individuals eligible for inclusion received further information about the study and were asked to provide consent to participate by providing an email address.

Data Collection and Measures

All assessments were administered through email invitations containing a hyperlink to the web-based self-reported assessments. Up to 3 reminders were sent through email at 5, 10, and 15 days after the first invitation. A baseline assessment (t 0 ) was collected before randomization, and follow-up assessments were conducted at 2 and 6 months (t 1 and t 2 , respectively) after the initial assessment.

Participants were asked for age, sex, whether they lived with a parent (mother and father, mother or father, mother or father and stepparent, or alternate between mother and father), where their parents were born (Sweden or a Nordic country excluding Sweden or outside of the Nordic countries), parental status (employed, student, on parental leave, or unemployed), and any previous or present participation in support activities for children having parents with alcohol use problems. The primary outcome was coping, measured using the Coping With Parents Abuse Questionnaire (CPAQ) based on the Coping Behavior Scale developed by Orford et al [ 48 ]. Secondary outcomes were the Center for Epidemiological Studies Depression Scale (CES-DC) [ 49 ], the 3-question Alcohol Use Disorders Identification Test (AUDIT-C) [ 50 ], and the Ladder of Life (LoL), which measures the overall quality of life by asking about the participants’ past, present, and future ratings of their overall life satisfaction [ 50 ]. CPAQ has been shown to be reliable [ 41 , 42 ]. For this study, this scale was factor-analyzed to reduce the number of questions from 37 to 20. The resulting scale measures 6 coping typologies (discord, emotion, control, relationship, avoidance, and taking specific action) using a 4-point Likert scale, with a threshold score above 50 points (out of 80) indicating dysfunctional coping behavior. The CES-DC measures depressive symptoms during the past week using a 4-point Likert scale, where a higher total score indicates more depressive symptoms [ 49 ]. A cutoff score of ≥16 indicates symptoms of moderate depression, while a score of ≥30 indicates symptoms of severe depression [ 51 , 52 ]. The scale measures 4 dimensions of depression: depressed mood, tiredness, inability to concentrate, and feelings of being outside and lonely, and has positively stated items [ 52 ]. Additionally, this scale is a general measure of childhood psychopathology [ 53 ] and has been demonstrated to be reliable and valid among Swedish adolescents [ 52 ]. Alcohol consumption was measured using a modified AUDIT-C, which assesses the frequency of drinking, quantity consumed on a typical occasion, and frequency of heavy episodic drinking (ie, binge drinking) [ 50 ] using a 30-day perspective (as opposed to the original 12-month perspective). These questions have previously been translated into Swedish [ 54 ], and a score of ≥4 and ≥5 points for women and men, respectively, was used as a cutoff for risky drinking. This scale has been demonstrated to be reliable and valid for Swedish adolescents [ 55 ]. Furthermore, 2 questions were added concerning whether the participants had ever consumed alcohol to the point of intoxication and their age at the onset of drinking and intoxication. The original version of the LoL was designed for adults and asked the respondents to reflect on their, present, and future life status from a 5-year perspective on a 10-point Visual Analogue Scale representing life status from “worst” to “best” possible life imaginable [ 56 ]. A modified version for children, using a time frame of 1 year, has been used previously in Sweden [ 57 ] and was used in this study.

Randomization

After completing the baseline assessment, each participant was allocated to either the intervention or the control group. An external researcher generated an unrestricted random allocation sequence using random allocation software [ 58 ]. Neither the participants nor the researchers involved in the study were blinded to group allocation.

Based on the order in which participants were included in the study, they were allocated to 1 of the 2 study groups and informed of their allocation by email. Additionally, those who were randomized to the intervention group received a hyperlink to the Alcohol and Coping program, whereas the control group participants received information that they would gain access to Alcohol and Coping after the last follow-up assessment (ie, the waitlist control group). All participants were informed about other information and support available through web pages, notably drugsmart [ 59 ], which contains general information and facts about alcohol and drugs, in addition to more specific information about having substance-abusing parents. Telephone numbers and contact information for other organizations and primary health care facilities were also provided.

The Intervention

As noted previously, Alcohol and Coping is derived from the aforementioned manual-based face-to-face ICAIP intervention program [ 41 , 42 ]. The ICAIP consists of a combination of an alcohol intervention program, which is based on the short version of the Brief Alcohol Screening and Intervention for College Students program [ 60 ], and a coping intervention program developed for the purpose of the ICAIP [ 41 , 42 ]. Like the original ICAIP intervention, Alcohol and Coping builds on psychoeducational principles and includes components such as film-based lectures, various exercises, and both automated and therapist-assisted feedback. Briefly, once the participants logged into the Alcohol and Coping platform, they were introduced to the program, which followed the pattern of a board game ( Figure 2 ). Following the introduction, participants took part in 3 film-based lectures (between 8 and 15 minutes each, Figure 3 ) concerning alcohol problems within the family. The respective lectures included information about (1) dependency in general as well as the genetic and environmental risks for developing dependency, (2) family patterns and how the family adapts to the one having alcohol problems, and (3) attitudes toward alcohol and how they influence drinking and the physiological effects of alcohol. After completing the lectures, the participants were asked to answer 2 questions about their own alcohol consumption (ie, how often they drink and how often they drink to intoxication), followed by an automatic feedback message that depended on their answers. It was then suggested that the participants log out of the intervention for a 1- to 2-day break. The reason for this break was to give the participants a chance to digest all information and impressions. When they logged back into the intervention, they were asked to answer 20 questions about their coping strategies, which were also followed by automatic feedback. This feedback comprised a library covering all the prewritten feedback messages, each of which was tailored to the participants’ specific answers. The participants then participated in a 5-minute–long film-based lecture on emotion and problem-focused coping in relation to family alcohol problems ( Figure 3 ). This was followed by 4 exercises where the participants read through vignette-like stories from 4 fictional persons describing their everyday lives related to coping and alcohol problems in the family. The stories are presented by film-based introductions that are each 1-2 minutes long. Participants were then requested to respond to each story by describing how the fictive person could have coped with their situation. As a final exercise, participants were asked to reflect on their own family situation and how they cope with situations. The participants then had to take a break for a few days.

During the break, a therapist composed individual feedback that covered reflections and confirmation of the participant’s exercises and answers to questions and included suggestions on well-suited coping strategies. Additionally, the therapist encouraged the participants to talk to others in their surroundings, such as friends, teachers, or coaches, and seek further support elsewhere, such as from municipal social services, youth health care centers, or other organizations. Finally, the therapist reflected on the participants’ alcohol consumption patterns and reminded them of increased genetic and environmental risks. Those who revealed patterns of risky alcohol use were encouraged to look at 2 additional film-based lectures with more information about alcohol and intoxication (4 minutes) and alcohol use and dependency (5 minutes). Participants received this feedback once they logged back into the program, but they also had the opportunity to receive feedback through email. The total estimated effective time for completing the program was about 1 hour, but as described above, there was 1 required break when the individualized feedback was written. To keep track of the dose each participant received, each of the 15 components in the program ( Figure 1 ) is equal to completing 6.7% (1/15) of the program in total.

Sample Size

The trial was designed to detect a medium or large effect size corresponding to a standardized mean difference (Cohen d >0.5) [ 61 ]. An a priori calculation of the estimated sample size, using the software G*Power (G*Power Team) [ 62 ], revealed that a total of 128 participants (64 in each group) were required to enroll in the trial (power=0.80; α=.05; 2-tailed). However, to account for an estimated attrition rate of approximately 30% [ 34 ], it was necessary to enroll a minimum of 128/(1 – 0.3) = 183 participants in the trial. After a total of 204 individuals had been recruited and randomized into 2 study arms, recruitment was ended.

Statistical Analysis

Data were analyzed according to the intention-to-treat (ITT) principle, and all randomized participants were included, irrespective of whether they participated in the trial. The 4 research variables were depression (CES-DC), coping (CPAQ), alcohol use (AUDIT-C), and life status (LoL).

Data analysis consisted of comparing outcome measurements at t 1 and t 2 . The baseline measurement t 0 value was added as an adjustment variable in all models. The resulting data from CPAQ, CES-DC, and LoL were normally distributed and analyzed using linear mixed models. The resulting AUDIT-C scores were nonnormally distributed, with an excess of 0 values, and were analyzed using a 2-part model for longitudinal data. This model is sufficiently flexible to account for numerous 0 reports. This was achieved by combining a logistic generalized linear mixed model (GLMM) for the 0 parts and a skewed continuous GLMM for the non-0 alcohol consumption parts. R-package brms (Bayesian regression models using Stan; R Foundation for Statistical Computing) [ 63 ], a higher-level interface for the probabilistic programming language Stan [ 64 ], and a custom brms family for a marginalized 2-part lognormal distribution were used to fit the model [ 65 ]. The logistic part of the model represents the subject-specific effects on the odds of reporting no drinking. The continuous part was modeled using a gamma GLMM with a log link. The exponentiated treatment effect represents the subject-specific ratio of the total AUDIT-C scores between the treatment and waitlist control groups for those who reported drinking during the specific follow-up period.

Handling of Missing Data

GLMMs include all available data and provide unbiased ITT estimates under the assumption that data are missing at random, meaning that the missing data can be explained by existing data. However, it is impossible to determine whether the data are missing at random or whether the missing data are due to unobserved factors [ 66 ]. Therefore, we also assumed that data were not missing at random, and subsequent sensitivity analyses were performed [ 66 ]. We used the pattern mixture method, which assumes not missing at random, to compare those who completed the follow-up at 6 months (t 2 ) with those who did not (but completed the 2-month follow-up). The overall effect of this model is a combination of the effects of each subgroup. We also tested the robustness of the results by performing ANCOVAs at the 2-month follow-up, both using complete cases and with missing values imputed using multilevel multiple imputation.

The effect of the program was estimated using Cohen d , where a value of approximately 0.2 indicates a small effect size and values of approximately 0.5 and 0.8 indicate medium and large effect sizes, respectively [ 61 ].

Ethical Considerations

All procedures were performed in accordance with the ethical standards of the institutional or national research committees, the 1964 Helsinki Declaration and its later amendments, and comparable ethical standards. Informed consent was obtained from all the participants included in the study. This study was approved by the Swedish Ethical Review Authority (formerly the Regional Ethical Review Board in Stockholm, No. 2011/1648-31/5).

To enhance the response rates, participants received a cinema gift certificate corresponding to approximately EUR 11 (US $12) as compensation for completing each assessment. If a participant completed all assessments, an additional gift certificate was provided. The participants could subsequently receive 4 cinema gift certificates totaling EUR 44 (US $48).

The trial profile is depicted in Figure 1 and reveals that 2722 individuals who were aged between 15 and 19 years performed the screening procedure. A total of 1448 individuals did not fulfill the inclusion criteria and were excluded, leaving 1274 eligible participants. Another 1070 individuals were excluded because they did not provide informed consent or complete the baseline assessment, leaving 204 participants who were allocated to 1 of the 2 study groups. A total of 140 (69%) and 131 (64%) participants completed t 1 and t 2 assessments, respectively. Of the participants in the intervention group (n=101), 63% (n=64) registered an account on the Alcohol and Coping website, 35% (n=35) completed the alcohol intervention section, and 24% (n=24) completed both the alcohol and coping intervention sections.

Sample Characteristics

The mean age of the sample was 17.0 (SD 1.23) years, and the vast majority were female, with both parents born in Sweden and currently working ( Table 1 ). Approximately one-third of the participants reported living with both parents. The mean score on the CAST-6 was 5.33 (SD 0.87) out of a total of 6, and the majority of the sample (147/204, 72.1%) perceived their father to have alcohol problems. Approximately 12% (25/204) had never consumed alcohol, whereas approximately 70% (144/204) had consumed alcohol at a level of intoxication. The mean age at onset was 13.7 (SD 2.07) years and the age at first intoxication was 14.8 (SD 1.56) years. The proportion of participants with symptoms of at least moderate depression was 77.5% (158/204), of whom 55.1% (87/158) had symptoms of severe depression and 42.6% (87/204) had symptoms of dysfunctional coping behaviors. The percentage of participants who consumed alcohol at a risky level was 39.7% (81/204). Table 1 provides complete information regarding the study sample.

a Significance levels calculated by Pearson chi-square statistics for categorical variables and 2-tailed t tests for continuous variables.

Treatment Effects

For the primary outcome, coping behavior (CPAQ), we found a small but inconclusive treatment effect in favor of treatment at both 2 (t 1 ) and 6 (t 2 ) months (Cohen d =–0.05 at both t 1 and t 2 ). For the secondary outcome, alcohol use (AUDIT-C), we found a treatment effect in that the intervention group scored 38% less than the control group on the continuous part (ie, drinking when it occurred) at t 1 and 46% less at t 2 . Regarding depression (CES-DC) and life status (LoL), all between-group comparisons of treatment effects were inconclusive at both follow-up time points ( Table 2 ).

a CPAQ: Coping With Parents Abuse Questionnaire.

b CES-DC: Center for Epidemiological Studies Depression Scale.

c LoL: Ladder of Life.

d AUDIT-C: Alcohol Use Disorders Identification Test.

e N/A: not applicable.

Missing Data

In contrast to the ITT analyses, the sensitivity analyses showed that the treatment group, averaged over the levels of dropout, scored higher (ie, a negative effect) on the main outcome, coping behavior (CPAQ), at t 1 (2.44; P =.20). However, the results remain inconclusive.

Dose-Response Effects

We did not find any evidence for greater involvement in the program being linked to improved outcomes with regard to coping behavior.

We did not find any support for the primary hypothesis: the intervention was not superior to the control condition with regard to coping behavior. Inconclusive results with small effect sizes were observed at both follow-up time points. However, for the secondary outcomes, we found that those in the intervention group who drank alcohol drank approximately 40%-50% less than those in the control group at both follow-ups. These results corroborate previous findings on the precursor face-to-face ICAIP intervention program, demonstrating that participants who received a combined alcohol and coping intervention reported superior outcomes with regard to alcohol-related outcomes compared to participants in the other 2 study arms, who received only a coping or alcohol intervention [ 41 , 42 ]. In contrast to this study, Hansson et al [ 42 ] found that all groups improved their coping skills, although the between-group comparisons were inconclusive and the improvements were maintained over time. These differences could be explained by the different settings in which the precursor program was provided (ie, face-to-face to young adults in a university setting), whereas this study targeted young people (15-19 years of age) through a web-based digital intervention. Additionally, the poor adherence in this study may explain the absence of primary results favoring the intervention group. In a recent study, parents without alcohol problems were recruited to participate in a randomized trial evaluating the web-based SPARE (Supportive Parenting and Reinforcement) program to improve children’s mental health and reduce coparents’ alcohol use. In line with our study, the authors did not find the primary outcome of the SPARE program to be superior to that of the active control group (which received written psychoeducation); however, both groups reported decreased coparental alcohol consumption [ 38 ].

Considering that approximately 3600 children in 2022 participated in various forms of support provided by Swedish municipalities [ 23 ], our recruitment activities reached a large number of eligible individuals, pointing to the potential of finding these children on these platforms. There were unexpectedly high levels of depression among the participants in this study. Although the intervention did not target depressive symptoms per se , there was a trend for the intervention group to have decreased depression levels compared to the control group. A large proportion of participants had symptoms of severe depression, which may have aggravated their capacity for improvement at follow-up [ 28 , 67 ]. Targeting dysfunctional coping patterns could affect an individual’s perceived mental health, and studies have shown that healthy coping strategies positively affect depression and anxiety in a positive way [ 68 ]. Using dysfunctional coping strategies, such as negative self-talk and alcohol consumption, can lead to depressive symptoms [ 69 ]. Targeting these symptoms in the context of healthy and unhealthy coping strategies may be a viable route to fostering appropriate coping strategies that work in the long run. Given that the young people who were reached by the intervention in this study displayed high levels of depression, future interventions for this group should include programs targeting depressive symptoms.

Almost 37% (37/101) of the intervention group did not log into the intervention at all, and only 24% (24/101) of the intervention group participants completed all parts of the program. The fact that a high proportion of the participants had symptoms of severe depression could explain the low adherence. Another reason could be that the initial film-based lectures were too long to maintain the participants’ attention, as the lectures ranged from 8-15 minutes. Yet a final reason could be that we had a 1- to 2-day break built into the intervention, and for unknown reasons, some participants did not log back into the intervention. However, we did not find a dose-response relationship indicating favorable outcomes for those who completed more of the program content. High levels of attrition are not uncommon in self-directed programs such as the one in this study; for example, in a study on a smoking cessation intervention, 37% of the participants never logged into the platform [ 70 ], and in a self-directed intervention for problem gamblers, a majority dropped out after 1 week and none completed the entire program [ 71 ]. Increased intervention adherence is a priority when developing new digital interventions, particularly for young people. One method is to use more persuasive technologies, such as primary tasks, dialogue, and social support [ 72 ]. Considering children whose parents have mental disorders, Grové and Reupert [ 73 ] suggested that digital interventions should include components such as providing information about parental mental illness, access to health care, genetic risk, and suggestions for how children might initiate conversations with parents who have the illness. These suggestions should be considered in future studies on interventions for youths whose parents have substance use problems. Representatives of the target group and other relevant stakeholders should also be involved in coproducing new interventions to increase the probability of developing more engaging programs [ 74 ]. Moreover, one cannot expect study participants to return to the program more than once, and for the sake of adherence, briefer interventions should not encourage participants to log-out for a break. To keep adherence at an acceptable level, similar future interventions for this target group should also consider having symptoms of severe depression as an exclusion criterion [ 28 , 67 ]. Further, to improve adherence, strategies of coproduction could be used where all stakeholders, including the target group, are involved in intervention development [ 75 ]. Other important factors identified to improve adherence to digital interventions are to make the content relatable, useful, and even more interactive [ 76 ]. Those participants who have symptoms of severe depression should be referred to other appropriate health care. Finally, it is probably beneficial to develop shorter psychoeducative film-based lectures than ours, lasting up to 15 minutes. Future self-directed digital interventions targeting this population should, therefore, focus on a very brief and focused intervention, which, based on theory, has the potential to foster healthy coping behaviors that can lead to an increased quality of life and improved mental health for this group of young people.

Another concern for future projects would be to use a data-driven approach during the program development phase, where A/B testing can be used to test different setups of the program to highlight which setup works best. Another aspect that must be considered is the fast-changing world of technology, where young people are exposed to an infinite number of different apps that grab their attention, which also calls for interventions to be short and to the point. Furthermore, if the program is to spread and become generally available, one must consider that keeping the program alive for a longer period will require funding and staffing for both product management and technical support.

Strengths and Limitations

This study had several strengths. First, Alcohol and Coping is a web-based intervention program, and it appears as if the internet is a particularly promising way to provide support to adolescents growing up with parents with alcohol problems because it offers an anonymous means of communicating and makes intervention programs readily accessible [ 25 ]. Our recruitment strategies reached a considerable number of interested and eligible individuals, demonstrating the potential for recruiting through social media and other web platforms. Additionally, this program is one of the first brief web-based interventions aimed at adolescents with parents with alcohol-related problems. We used the CAST-6, which has been validated among Swedish adolescents [ 47 ], to screen eligible participants. Another strength is that the intervention program involved personalized, tailored feedback in the form of prewritten automatic messages and therapist-written personalized feedback, both of which have proven to be important components of web-based interventions aimed at adolescents [ 77 , 78 ]. Finally, this study evaluated the effectiveness of the Alcohol and Coping program using a randomized controlled trial design, which is considered the strongest experimental design with regard to allocation bias.

This study had some limitations. First, the design with a passive waitlist control group and an active intervention group, both unblinded to study allocation, may have resulted in biased estimates of treatment effects. Intervention adherence was low, and most of the study participants had symptoms of depression, where 55% (87/158) had symptoms of severe depression. This may have contributed to the small and overall inconclusive effects on the primary outcomes of this study. Many digital interventions have problems with low adherence, and in a review by Välimäki et al [ 79 ], some studies reported adherence rates as low as 10%. A vast proportion of the study participants were women, making the findings difficult to generalize to men. However, another limitation concerns selection bias and external validity. We recruited study participants through social media and other relevant websites containing health-related information, including information about parents with alcohol-related problems. It is, therefore, possible that the study population can be classified as “information-seeking” adolescents, who may have different personality traits relative to other adolescents in the same home situation. Additionally, as an inclusion criterion was having ready access to computers and the internet, it is possible that participants belonging to a lower socioeconomic class were underrepresented in the study. It should also be noted that the data presented here were collected approximately 10 years ago. However, we believe our findings make an important contribution to the field since, like our intervention, many recent web-based interventions use strategies of psychoeducation, films, exercises, questions, and feedback. Further, the number of web-based interventions for this target group remains scarce in the literature, which underscores the need for future research. Finally, the study was powered to detect a medium effect size. However, given the small effect sizes detected in this study, it is plausible that too few participants were recruited to detect differences between the groups.

Implications for Practice

Although growing up with parents who have alcohol problems per se is not sufficient for developing psychosocial disorders, many children need support to manage their situation. Therefore, it is difficult to recruit children to support these groups. In Sweden, not even 2% of all children growing up with parental alcohol problems attend face-to-face support groups provided by municipalities.

Offering support through web-based intervention programs seems particularly attractive to adolescents whose parents have alcohol-related problems. To date, evidence for such programs is scarce, and there is an urgent need to develop and evaluate digital interventions targeting this group of adolescents. This study makes important contributions to this novel field of research. The results provide insight into effective strategies for delivering intervention programs to children of parents with substance abuse issues, highlighting the potential for digital interventions to reach a vulnerable, hard-to-reach group of adolescents. Our findings underscore the need to develop more engaging interventions in coproduction with the target group.

Conclusions

We found that a digital therapist-assisted self-management intervention for adolescents whose parents have alcohol use problems contributed to a reduction in the adolescents’ own alcohol consumption. This result highlights the potential for digital interventions to reach a large, vulnerable, and hard-to-reach group of adolescents with support efforts. Findings were inconclusive for all other outcomes, which may be attributable to low adherence. This points to the need for future research on developing more engaging digital interventions to increase adherence among adolescents.

Acknowledgments

This work was undertaken on behalf of the Swedish Council for Information on Alcohol and Other Drugs (CAN) and was supported by grants from the Swedish National Institute of Public Health and the Swedish Council for Working Life and Social Research.

Conflicts of Interest

HH and UZ developed the study interventions. However, the parties did not derive direct financial income from these interventions. HW, PK, and THE declare no conflicts of interest.

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Abbreviations

Edited by YH Lin; submitted 24.08.23; peer-reviewed by X Zhang, C Asuzu, D Liu; comments to author 28.01.24; revised version received 08.02.24; accepted 27.02.24; published 10.04.24.

©Håkan Wall, Helena Hansson, Ulla Zetterlind, Pia Kvillemo, Tobias H Elgán. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 10.04.2024.

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