Harnessing mobile technology to reduce mental health disorders in college populations: A randomized controlled trial study protocol

The relationship of race, ethnicity, gender identity, sex assigned at birth, sexual orientation, parental education, financial hardship and comorbid mental disorders with quality of life in college students with anxiety, depression or eating disorders

BACKGROUND

Previous studies showed that comorbidity and demographic factors added to burden on health-related quality of life (HRQoL). Only one study explored the relationship between HRQoL and comorbidity in college students with mental disorders, leaving generalizability of findings uncertain. Less is known about the association of demographics on HRQoL. This study investigated HRQoL based on demographics and comorbidity among college students with mental disorders.

METHODS

Participants were students (N = 5535) across 26 U.S. colleges and universities who met criteria for depression, generalized anxiety, panic, social anxiety, post-traumatic stress, or eating disorders based on self-report measures. ANOVA and linear regressions were conducted.

RESULTS

Overall, female, minoritized (gender, sexual orientation, race, or ethnicity), and lower socioeconomic status students reported lower HRQoL than male, heterosexual, White, non-Hispanic, and higher socioeconomic status peers. After accounting for comorbidity, differences in physical HRQoL based on sex assigned at birth and gender were no longer significant. For mental HRQoL, only gender and sexual orientation remained significant. A greater number of comorbidities was associated with lower HRQoL regardless of demographic group.

LIMITATIONS

The non-experimental design limits causal inference. The study focused on univariable associations without examining potential interactions between demographic factors. Future research should explore structural factors like discrimination.

CONCLUSION

Results suggested that increased comorbidities placed an additional burden on HRQoL and that certain demographic groups were more vulnerable to HRQoL impairment among students with mental disorders. Findings suggest the need for prevention of disorders and their comorbidity and implementing tailored interventions for specific student subgroups with increased vulnerability.

Racial and Ethnic Disparities in Barriers to Mental Health Treatment Among U.S. College Students

OBJECTIVE

Using a sample of U.S. college students, the authors evaluated whether barriers to mental health treatment varied by race and ethnicity.

METHODS

Data were drawn from a large multicampus study conducted across 26 U.S. colleges and universities. The sample (N=5,841) included students who screened positive for at least one mental disorder and who were not currently receiving psychotherapy.

RESULTS

The most prevalent barriers to treatment across the sample were a preference to deal with issues on one's own, lack of time, and financial difficulties. Black and Hispanic/Latine students reported a greater willingness to seek treatment than did White students. However, Black and Hispanic/Latine students faced more financial barriers to treatment, and Hispanic/Latine students also reported lower perceived importance of mental health. Asian American students also reported financial barriers and preferred to handle their issues on their own or with support from family or friends and had lower readiness, willingness, and intentionality to seek help than did White students.

CONCLUSIONS

Disparities in unmet treatment needs may arise from both distinct and common barriers and point to the potential benefits of tailored interventions to address the specific needs of students of color from various racial and ethnic backgrounds. The findings further underscore the pressing need for low-cost and brief treatment models that can be used or accessed independently to address the most prevalent barriers for students.

Evaluating the Efficacy of a Digital Therapeutic (CT-152) as an Adjunct to Antidepressant Treatment in Adults With Major Depressive Disorder: Protocol for the MIRAI Remote Study

BACKGROUND

Major depressive disorder (MDD) is common worldwide and can be highly disabling. People with MDD face many barriers to treatment and may not experience full symptom relief even when treated. Therefore, new treatment modalities are needed for MDD. Digital therapeutics (DTx) may provide people with MDD an additional treatment option.

OBJECTIVE

This study aimed to describe a phase 3 remote, multicenter, randomized, masked, sham-controlled trial evaluating the efficacy of a smartphone app-based DTx (CT-152) in adult participants diagnosed with MDD, used as an adjunct to antidepressant therapy (ADT).

METHODS

Participants aged 22-64 years with a current primary diagnosis of MDD and an inadequate response to ADT were included. Participants were randomized 1:1 to CT-152 or a sham DTx. CT-152 is a smartphone app-based DTx that delivers a cognitive-emotional and behavioral therapeutic intervention. The core components of CT-152 are the Emotional Faces Memory Task exercises, brief lessons to learn and apply key therapeutic skills, and SMS text messaging to reinforce lessons and encourage engagement with the app. The sham DTx is a digital working memory exercise with emotionally neutral stimuli designed to match CT-152 for time and attention. Participants took part in the trial for up to 13 weeks. The trial included a screening period of up to 3 weeks, a treatment period of 6 weeks, and an extension period of 4 weeks to assess the durability of the effect. Sites and participants had the option of an in-person or remote screening visit; the remaining trial visits were remote. Efficacy was evaluated using the Montgomery-Åsberg Depression Rating Scale, the Generalized Anxiety Disorder-7, Clinical Global Impression-Severity scale, the Patient Health Questionnaire-9, and the World Health Organization Disability Assessment Schedule 2.0. The durability of the effect was evaluated with the Montgomery-Åsberg Depression Rating Scale and Generalized Anxiety Disorder-7 scale. Adverse events were also assessed. Satisfaction, measured by the Participant and Healthcare Professional Satisfaction Scales, and health status, measured by the EQ-5D-5L, were summarized using descriptive statistics.

RESULTS

This study was initiated in February 2021 and had a primary completion date in October 2022.

CONCLUSIONS

This represents the methodological design for the first evaluation of CT-152 as an adjunct to ADT. This study protocol is methodologically robust and incorporates many aspects of conventional pivotal pharmaceutical phase 3 trial design, such as randomization and safety end points. Novel considerations included the use of a sham comparator, masking considerations for visible app content, and outcome measures relevant to DTx. The rigor of this methodology will provide a more comprehensive understanding of the effectiveness of CT-152.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04770285; https://clinicaltrials.gov/study/NCT04770285.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR1-10.2196/56960.

Machine Learning and Bayesian Network Analyses Identifies Psychiatric Disorders and Symptom Associations with Insomnia in a national sample of 31,285 Treatment-Seeking College Students

Background

A better understanding of the structure of relations among insomnia and anxiety, mood, eating, and alcohol-use disorders is needed, given its prevalence among young adults. Supervised machine learning provides the ability to evaluate the discriminative accuracy of psychiatric disorders associated with insomnia. Combined with Bayesian network analysis, the directionality between symptoms and their associations may be illuminated.

Methods

The current exploratory analyses utilized a national sample of college students across 26 U.S. colleges and universities collected during population-level screening before entering a randomized controlled trial. Firstly, an elastic net regularization model was trained to predict, via repeated 10-fold cross-validation, which psychiatric disorders were associated with insomnia severity. Seven disorders were included: major depressive disorder, generalized anxiety disorder, social anxiety disorder, panic disorder, post-traumatic stress disorder, anorexia nervosa, and alcohol use disorder. Secondly, using a Bayesian network approach, completed partially directed acyclic graphs (CPDAG) built on training and holdout samples were computed via a Bayesian hill-climbing algorithm to determine symptom-level interactions of disorders most associated with insomnia [based on SHAP (SHapley Additive exPlanations) values)] and were evaluated for stability across networks.

Results

Of 31,285 participants, 20,597 were women (65.8%); mean (standard deviation) age was 22.96 (4.52) years. The elastic net model demonstrated clinical significance in predicting insomnia severity in the training sample [R2 = .449 (.016); RMSE = 5.00 [.081]), with comparable performance in accounting for variance explained in the holdout sample [R2 = .33; RMSE = 5.47). SHAP indicated the presence of any psychiatric disorder was associated with higher insomnia severity, with major depressive disorder demonstrated to be the most associated disorder. CPDAGs showed excellent fit in the holdout sample and suggested that depressed mood, fatigue, and self-esteem were the most important depression symptoms that presupposed insomnia.

Conclusion

These findings offer insights into associations between psychiatric disorders and insomnia among college students and encourage future investigation into the potential direction of causality between insomnia and major depressive disorder.

Trial registration

Trial may be found on the National Institute of Health RePORTER website: Project Number: R01MH115128-05.

Preferred treatment focus among college students with eating disorders and comorbid mental health problems in a digital cognitive-behavioral guided self-help program

OBJECTIVE

To examine the mental health problems that college students with eating disorders (EDs) and comorbid depression and/or anxiety disorders preferred to target first in a digital treatment program and explore correlates of preferred treatment focus.

METHODS

Four hundred and eighty nine college student users of a digital cognitive-behavioral guided self-help program targeting common mental health problems (76.7% female, Mage  = 20.4 ± 4.4, 64.8% White) screened positive for an ED and ≥one other clinical mental health problem (i.e., depression, generalized anxiety disorder, social phobia, and/or panic disorder). Students also reported on insomnia, post-traumatic stress, alcohol use, and suicide risk. Before treatment, they indicated the mental health problem that they preferred to target first in treatment. Preferred treatment focus was characterized by diagnostic profile (i.e., ED + Depression, ED + Anxiety, ED + Depression + Anxiety), symptom severity, and demographics.

RESULTS

58% of students with ED + Anxiety, 47% of those with ED + Depression, and 27% of those with ED + Depression + Anxiety chose to target EDs first. Across diagnostic profiles, those who chose to target EDs first had more severe ED symptoms than those who chose to target anxiety or depression (ps < .05). Among students with ED + Depression + Anxiety, those who chose to target EDs first had lower depression symptoms than those who chose to target depression, lower generalized anxiety than those who chose to target anxiety, and lower suicidality than those who chose to target anxiety or depression (ps < .01).

CONCLUSIONS

Students with EDs and comorbid depression and/or anxiety disorders showed variable preferred treatment focus across diagnostic profiles. Research should explore specific symptom presentations associated with preferred treatment focus.

PUBLIC SIGNIFICANCE

Findings indicate that a sizable percentage of college students with depression/anxiety who also have EDs prefer to target EDs first in treatment, highlighting the importance of increasing availability of ED interventions to college students. Students with EDs and comorbid depression and/or anxiety disorders showed variable preferred treatment focus across diagnostic profiles, and preference to target EDs was associated with greater ED psychopathology across diagnostic profiles.

Training, supervision, and experience of coaches offering digital guided self-help for mental health concerns

Accessible, low-cost intervention options are necessary to address the rise in mental health problems among college students. Digital guided self-help, or coached, programs have been developed to provide such services, with many commercially available. As such, there are a large and growing number of individuals coaching these programs. However, an unmet need is to evaluate and assess best practices for training and supervising individuals in these positions. To this end, we describe how we recruited, trained, and supervised coaches as part of a large randomized controlled trial using a widely available digital commercial platform. Coaches were trained to provide digital guided self-help for depression, anxiety, and/or eating disorders for college students. Coaches initially attended three live training sessions over 2-3 weeks, viewed multiple training videos, and read a detailed coaching manual developed by our team. Thereafter, they attended weekly supervision. Following their term, coaches completed an exit survey to assess their supervision and training experiences. A total of 37 of 70 (53%) graduate-level student coaches completed the survey. The experience was reported as very positive (95%). In particular, the majority reported feeling well prepared, more confident, and felt they had developed useful skills for their own practice.

Assessing Patient Adherence to and Engagement With Digital Interventions for Depression in Clinical Trials: Systematic Literature Review

BACKGROUND

New approaches to the treatment of depression are necessary for patients who do not respond to current treatments or lack access to them because of barriers such as cost, stigma, and provider shortage. Digital interventions for depression are promising; however, low patient engagement could limit their effectiveness.

OBJECTIVE

This systematic literature review (SLR) assessed how participant adherence to and engagement with digital interventions for depression have been measured in the published literature, what levels of adherence and engagement have been reported, and whether higher adherence and increased engagement are linked to increased efficacy.

METHODS

We focused on a participant population of adults (aged ≥18 years) with depression or major depressive disorder as the primary diagnosis and included clinical trials, feasibility studies, and pilot studies of digital interventions for treating depression, such as digital therapeutics. We screened 756 unique records from Ovid MEDLINE, Embase, and Cochrane published between January 1, 2000, and April 15, 2022; extracted data from and appraised the 94 studies meeting the inclusion criteria; and performed a primarily descriptive analysis. Otsuka Pharmaceutical Development & Commercialization, Inc (Princeton, New Jersey, United States) funded this study.

RESULTS

This SLR encompassed results from 20,111 participants in studies using 47 unique web-based interventions (an additional 10 web-based interventions were not described by name), 15 mobile app interventions, 5 app-based interventions that are also accessible via the web, and 1 CD-ROM. Adherence was most often measured as the percentage of participants who completed all available modules. Less than half (44.2%) of the participants completed all the modules; however, the average dose received was 60.7% of the available modules. Although engagement with digital interventions was measured differently in different studies, it was most commonly measured as the number of modules completed, the mean of which was 6.4 (means ranged from 1.0 to 19.7) modules. The mean amount of time participants engaged with the interventions was 3.9 (means ranged from 0.7 to 8.4) hours. Most studies of web-based (34/45, 76%) and app-based (8/9, 89%) interventions found that the intervention group had substantially greater improvement for at least 1 outcome than the control group (eg, care as usual, waitlist, or active control). Of the 14 studies that investigated the relationship between engagement and efficacy, 9 (64%) found that increased engagement with digital interventions was significantly associated with improved participant outcomes. The limitations of this SLR include publication bias, which may overstate engagement and efficacy, and low participant diversity, which reduces the generalizability.

CONCLUSIONS

Patient adherence to and engagement with digital interventions for depression have been reported in the literature using various metrics. Arriving at more standardized ways of reporting adherence and engagement would enable more effective comparisons across different digital interventions, studies, and populations.

Brief imaginal exposure exercises for social anxiety disorder: A randomized controlled trial of a self-help momentary intervention app

INTRODUCTION

Emerging technological interventions for psychological disorders are being developed continually. Offering imaginal exposure exercises as a self-help intervention presents the opportunity to acquire foundational skills to address social anxiety. The current study evaluates the feasibility and effectiveness of a novel smartphone application for social interaction anxiety.

METHODS

Participants (n = 82) were adults meeting criteria for social anxiety disorder. They were randomly assigned to imaginal exposure (IE; n = 39) or self-monitoring (n = 43) delivered multiple times daily via a smartphone application for a one-week trial. It was expected that participants using the IE exercises would demonstrate significantly greater declines in social anxiety in addition to increases in self-efficacy and that compliance would serve as a predictor of outcome. Mixed-effects models were utilized.

RESULTS

Participants using IE (vs. self-monitoring) evidenced significantly greater reductions in social anxiety from pre- to post-treatment and at 1-month follow-up. Similarly, IE (vs. self-monitoring) led to significantly greater increases in self-efficacy from pre- to post-treatment and 1-month follow-up. Further, more completed IE exercises predicted significantly greater changes in social anxiety and self-efficacy at subsequent timepoints compared with self-monitoring.

CONCLUSIONS

Findings suggest that a brief IE self-help intervention was effective in targeting social interaction anxiety.

Using Social Influence Strategies to Improve Rates of Online Mental Health Survey Participation: Results from Two Experiments

Online surveys are routinely used in mental health screening and treatment follow-up assessment, though they can yield low response rates. We tested the effects of social psychology-informed influence strategies for increasing rates of participation in an online mental health screening survey (Experiment 1) and a treatment follow-up survey (Experiment 2). In Experiment 1 (N = 45,569), embedding one or any combination of three motivational appeals (personal gain, community gain, and inclusivity) in screening survey invitation and reminder emails unexpectedly led to lower rates of survey participation compared to when the appeals were not included (overall participation rate = 12.02%, ORs = 0.75 to 0.97, ps < .001). In Experiment 2 (N = 873), a video of a TikTok influencer encouraging survey participation embedded in treatment follow-up survey invitation and reminder emails did not significantly affect survey completion compared to a humorous gif unrelated to survey participation (overall participation rate = 47.88%, OR = 1.18, p = .200). Moderator analyses revealed that the video led to higher rates of participation than the gif among White participants (OR = 1.39, p = .031) and non-Hispanic participants (OR = 1.35, p = .029) only, whereas the video led to lower rates of participation than the gif among students who did not disclose their race (OR = 0.31, p = .010). Results suggested that efforts to improve online survey participation should be balanced with possible downsides (e.g., added email length) and should be evaluated for differential performance among population subgroups prior to widespread implementation.

Adapting a mobile app to support patients with anorexia nervosa following post-acute care: perspectives from eating disorder treatment center stakeholders

Introduction

Anorexia nervosa (AN) is a harmful, life-threatening illness. Patients with severe AN often receive acute treatment but, upon discharge, experience high relapse rates. Evidence-based, outpatient treatment following acute care is critical to preventing relapse; however, numerous barriers (e.g., location, financial limitations, low availability of providers) preclude individuals from accessing treatment. mHealth technologies may help to address these barriers, but research on such digital approaches for those with AN is limited. Further, such technologies should be developed with all relevant stakeholder input considered from the outset. As such, the present study aimed to garner feedback from eating disorder (ED) treatment center providers on (1) the process of discharging patients to outpatient services, (2) their experiences with technology as a treatment tool, and (3) how future mHealth technologies may be harnessed to offer the most benefit to patients in the post-acute period.

Methods

Participants (N = 11, from 7 ED treatment centers across the United States) were interviewed. To analyze the data for this study, each interview was manually transcribed and analyzed using components of Braun and Clarke's six-phase thematic analysis framework (Braun & Clarke, 2006).

Results

Participants indicated proactively securing outpatient care for their patients, but mentioned several barriers their patients face in accessing evidence-based ED treatment. All participants had some experience using various technologies for treatment (e.g., teletherapy, self-monitoring apps), and mentioned a high level of interest in the development of a new app to be used by patients recently discharged from acute treatment for AN. Participants also offered suggestions of effective and relevant content for a potential app and adjunctive social networking component for post-acute care of AN.

Discussion

Overall, participants expressed positive attitudes toward the integration of an app into the care flow, suggesting the high potential benefit of harnessing technology to support individuals recovering from AN.

Risk factors and digital interventions for anxiety disorders in college students: Stakeholder perspectives

The worldwide prevalence of anxiety disorders among college students is high, which negatively affects countries, schools, families, and individual students to varying degrees. This paper reviews the relevant literature regarding risk factors and digital interventions for anxiety disorders among college students from the perspectives of different stakeholders. Risk factors at the national and societal levels include class differences and the coronavirus disease 2019 pandemic. College-level risk factors include the indoor environment design of the college environment, peer relationships, student satisfaction with college culture, and school functional levels. Family-level risk factors include parenting style, family relationship, and parental level of education. Individual-level risk factors include biological factors, lifestyle, and personality. Among the intervention options for college students' anxiety disorders, in addition to traditional cognitive behavioral therapy, mindfulness-based interventions, psychological counseling, and group counseling, digital mental health interventions are increasingly popular due to their low cost, positive effect, and convenient diagnostics and treatment. To better apply digital intervention to the prevention and treatment of college students' anxiety, this paper suggests that the different stakeholders form a synergy among themselves. The nation and society should provide necessary policy guarantees, financial support, and moral and ethical supervision for the prevention and treatment of college students' anxiety disorders. Colleges should actively participate in the screening and intervention of college students' anxiety disorders. Families should increase their awareness of college students' anxiety disorders and take the initiative to study and understand various digital intervention methods. College students with anxiety disorders should actively seek psychological assistance and actively accept and participate in digital intervention projects and services. We believe that in the future, the application of methods such as big data and artificial intelligence to improve digital interventions and provide individualized treatment plans will become the primary means of preventing and treating anxiety disorders among college students.

Enhancing Resilience in Family Caregivers Using an mHealth App

BACKGROUND

We previously developed a mobile health (mHealth) app (Roadmap) to promote the resilience of family caregivers during the acute phases of care in patients undergoing hematopoietic cell transplantation (HCT).

OBJECTIVE

This study explored users' perspectives on the uptake of Roadmap's multicomponent features and the app's utility in promoting resilience.

METHODS

Fifteen participants were randomized to the full version of the app that included resilience-building activities and the other 15 were randomized to the control version that included a limited view of the app (i.e., without any resilience-building activities). They were instructed to use the app for 120 days. Semistructured qualitative interviews were then conducted with users as part of an ongoing, larger Roadmap study (NCT04094844). During the interview, caregiver participants were asked about their overall experiences with the app, frequency of use, features used, facilitators of and barriers to use, and their perspectives on its utility in promoting resilience. Data were professionally transcribed, coded, and categorized through content analysis.

RESULTS

Interviews were conducted with 30 participants, which included 23 females and 7 males. The median age of the population was 58 years (range, 23-82). The four main themes that emerged included app use, ease of use, user experiences, and ability to foster resilience. The subthemes identified related to facilitators (convenience and not harmful), barriers (caregiver burden and being too overwhelmed during the acute phases of HCT care), resilience (optimism/positivity and self-care), and app design improvements (personalization and notifications/reminders).

CONCLUSION

The qualitative evaluation provided insights into which components were utilized and how one, or a combination of the multicomponent features, may be enhancing users' experiences. Lessons learned suggest that the Roadmap app contributed to promoting resilience during the acute phases of HCT care. Nonetheless, features that provided enhanced personalization may further improve longer-term engagement.

Influencing factors, prediction and prevention of depression in college students: A literature review

The high prevalence of depression among college students has a strong negative impact on individual physical and mental health, academic development, and interpersonal communication. This paper reviewed the extant literature by identifying nonpathological factors related to college students' depression, investigating the methods of predicting depression, and exploring nonpharmaceutical interventions for college students' depression. The influencing factors of college students' depression mainly fell into four categories: biological factors, personality and psychological state, college experience, and lifestyle. The outbreak of coronavirus disease 2019 has exacerbated the severity of depression among college students worldwide and poses grave challenges to the prevention and treatment of depression, given that the coronavirus has spread quickly with high infection rates, and the pandemic has changed the daily routines of college life. To predict and measure mental health, more advanced methods, such as machine algorithms and artificial intelligence, have emerged in recent years apart from the traditional commonly used psychological scales. Regarding nonpharmaceutical prevention measures, both general measures and professional measures for the prevention and treatment of college students' depression were examined in this study. Students who experience depressive disorders need family support and personalized interventions at college, which should also be supplemented by professional interventions such as cognitive behavioral therapy and online therapy. Through this literature review, we insist that the technology of identification, prediction, and prevention of depression among college students based on big data platforms will be extensively used in the future. Higher education institutions should understand the potential risk factors related to college students' depression and make more accurate screening and prevention available with the help of advanced technologies.

Digital interventions to address mental health needs in colleges: Perspectives of student stakeholders

Objective

The need for clinical services in U.S. colleges exceeds the supply. Digital Mental health Interventions (DMHIs) are a potential solution, but successful implementation depends on stakeholder acceptance. This study investigated the relevance of DMHIs from students' perspectives.

Methods

In 2020-2021, an online cross-sectional survey using mixed methods was conducted with 479 students at 23 colleges and universities. Respondents reported views and use of standard mental health services and DMHIs and rated the priority of various DMHIs to be offered through campus services. Qualitative data included open-ended responses.

Findings

Among respondents, 91% reported having experienced mental health problems, of which 91% reported barriers to receiving mental health services. Students highlighted therapy and counseling as desired and saw flexible access to services as important. With respect to DMHIs, respondents had the most experience with physical health apps (46%), mental health questionnaires (41%), and mental well-being apps (39%). Most were unaware of or had not used apps or self-help programs for mental health problems. Students were most likely to report the following DMHIs as high priorities: a crisis text line (76%), telehealth (66%), websites for connecting to services (62%), and text/messaging with counselors (62%). They considered a self-help program with coach support to be convenient but some also perceived such services to be possibly less effective than in-person therapy.

Conclusions

Students welcome DMHIs on campus and indicate preference for mental health services that include human support. The findings, with particular focus on characteristics of the DMHIs prioritized, and students' awareness and perceptions of scalable DMHIs emphasized by policymakers, should inform schools looking to implement DMHIs.

Exploring Social Media Recruitment Strategies and Preliminary Acceptability of an mHealth Tool for Teens with Eating Disorders

(1) Background: The current study leveraged social media to connect with teens with EDs to identify population specific characteristics and to gather feedback on an mHealth intervention. (2) Methods: We recruited teens with EDs from social media in two phases: (1) Discovery Group, (2) Testing Group. The Discovery Group (n = 14) participants were recruited from Facebook/Instagram and were asked to review the app for up to one week and provide qualitative feedback. After incorporating feedback from the Discovery Group, we refined our social media outreach methods to connect with 30 teens with EDs to pilot this mobile app. Recruitment from a variety of platforms on social media was successful, with the majority of enrolled participants in the Testing Group coming from Snapchat (60%) and a large percentage of participants belonging to gender and sexual minority groups (63%). (3) Results: Participants from both groups experienced extremely high rates of depression (100% Discovery, 90% Testing) and/or anxiety symptoms (100% Discovery, 93% Testing) in addition to ED symptoms, and noted this as a possible barrier to app engagement. (4) Conclusion: Use of social media for recruitment of teens with EDs is feasible and may connect with groups who may be more difficult to reach using traditional recruitment methods. Among the Discovery Group there was high acceptability of and interest in an app to support ED recovery, and characteristics of both groups demonstrated need for support in other mental health domains. Future studies should evaluate the preliminary efficacy of such tools among teens to determine the effects of such interventions on ED symptoms and other mental health outcomes.

Digital Overload among College Students: Implications for Mental Health App Use

Mental health phone applications (apps) provide cost-effective, easily accessible support for college students, yet long-term engagement is often low. Digital overload, defined as information burden from technological devices, may contribute to disengagement from mental health apps. This study aimed to explore the influence of digital overload and phone use preferences on mental health app use among college students, with the goal of informing how notifications could be designed to improve engagement in mental health apps for this population. A semi-structured interview guide was developed to collect quantitative data on phone use and notifications as well as qualitative data on digital overload and preferences for notifications and phone use. Interview transcripts from 12 college students were analyzed using thematic analysis. Participants had high daily phone use and received large quantities of notifications. They employed organization and management strategies to filter information and mitigate the negative effects of digital overload. Digital overload was not cited as a primary barrier to mental health app engagement, but participants ignored notifications for other reasons. Findings suggest that adding notifications to mental health apps may not substantially improve engagement unless additional factors are considered, such as users’ motivation and preferences.