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

Fitzsimmons‐Craft, Ellen E.; Taylor, C. Barr; Newman, Michelle G.; Zainal, Nur Hani; Rojas-Ashe, Elsa E.; Lipson, Sarah Ketchen; Firebaugh, Marie Laure; Ceglarek, Peter; Topooco, Naira; Jacobson, Nicholas C.; Graham, Andrea K.; Kim, Hyungjin Myra; Eisenberg, Daniel; Wilfley, Denise E.

doi:10.1016/j.cct.2021.106320

Cited by 27 publications

(13 citation statements)

References 72 publications

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“…In recent years, a growing number of online technologies have been applied to the treatment of depression among college students thanks to the rapid development of internet technology and mobile terminal devices[ 116 - 120 ], and some of the technologies were even skillfully combined with cognitive behavioral therapy[ 121 , 122 ]. For example, there are many apps that incorporate elements of cognitive behavioral therapy and mindfulness.…”

Section: Nonpharmaceutical Prevention Of Depressionmentioning

confidence: 99%

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

Liu¹,

Guo²,

Zhang³

et al. 2022

WJP

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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.

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Section: Nonpharmaceutical Prevention Of Depressionmentioning

confidence: 99%

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

Liu¹,

Guo²,

Zhang³

et al. 2022

WJP

View full text Add to dashboard Cite

show abstract

“…If eligible, teens were asked to provide contact information and continued to the baseline survey. After completing the baseline survey, teens were sent an email invite to access the standard app (with content for body image and EDs previously developed and tested with adults) [19,49] and PDF copies of app content tailored for teens. Teens were asked to review app features and content in the standard app and to compare these with the proposed content changes for teens in the PDFs for up to one week.…”

Section: Discovery Group Methodsmentioning

confidence: 99%

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

Kasson

Vázquez

Doroshenko

et al. 2021

IJERPH

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(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.

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“…Participants were selected to ensure a diverse sample based on gender identity, race, ethnicity, and undergraduate institution, so as to maximize generalizability. However, one of the 13 participants was excluded from data analysis because the primary mental health condition they disclosed experiencing, autism, was not a focus of the mobile mental health platform under study in the parent project (Fitzsimmons-Craft et al 2021) and is a less common concern addressed by college student mental health centers (Center for Collegiate Mental Health 2021). The characteristics (gender, race and ethnicity, age, type of university, and year in school) of the 12 participants whose data was analyzed, along with their corresponding ID numbers, are presented in Table 1 below.…”

Section: Participantsmentioning

confidence: 99%

“…Therefore, the aim of this study was to explore how digital overload and other phone use factors might relate to the use of mental health apps among college students. We focused on college students, given our team's ongoing research studying the effectiveness of a mobile platform for college students with or at high risk of depression, anxiety, and/or eating disorders (Fitzsimmons-Craft et al 2021). Semi-structured interviews were conducted to collect quantitative data on phone use and notifications as well as qualitative data on (1) the digital overload phenomenon, (2) notification preferences and other phone use preferences that may generalize to mental health apps, and (3) recommendations on how mental health app use can be improved.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

Self Cite

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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.

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

Cited by 27 publications

References 72 publications

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

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

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

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

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