Population-based RCT of a digital cognitive-behavioural guided self-help intervention for anxiety, depression and eating disorders in college students

Kessler, R. C. et al. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch. Gen. Psychiatry 62, 593–602 (2005).
Google Scholar
Auerbach, R. P. et al. WHO World Mental Health Surveys International College Student Project: prevalence and distribution of mental disorders. J. Abnorm. Psychol. 127, 623–638 (2018).
Google Scholar
Li, W., Zhao, Z., Chen, D., Peng, Y. & Lu, Z. Prevalence and associated factors of depression and anxiety symptoms among college students: a systematic review and meta-analysis. J. Child Psychol. Psychiatry 63, 1222–1230 (2022).
Google Scholar
Lipson, S. K. et al. Trends in college student mental health and help-seeking by race/ethnicity: findings from the national healthy minds study, 2013-2021. J. Affect. Disord. 306, 138–147 (2022).
Google Scholar
Blanco, C. et al. Mental health of college students and their non-college-attending peers: results from the National Epidemiologic Study on Alcohol and Related Conditions. Arch. Gen. Psychiatry 65, 1429–1437 (2008).
Google Scholar
Bruffaerts, R. et al. Mental health problems in college freshmen: prevalence and academic functioning. J. Affect. Disord. 225, 97–103 (2018).
Google Scholar
Gorman, K. S. et al. Association for University and College Counseling Center Directors: Annual Survey For Reporting Period July 1, 2021 Through June 30, 2022 (AUCCCD, 2022); https://www.aucccd.org/assets/documents/Survey/2021-22%20Annual%20Survey%20Report%20Public%20FINAL.pdf
Lipson, S. K., Lattie, E. G. & Eisenberg, D. Increased rates of mental health service utilization by U.S. College students: 10-year population-level trends (2007–2017). Psychiatr. Serv. 70, 60–63 (2019).
Google Scholar
Kim, H. et al. College mental health before and during the COVID-19 pandemic: Results from a nationwide survey. Cognit. Ther. Res. 46, 1–10 (2022).
Google Scholar
Rackoff, G. N. et al. Psychotherapy utilization by United States college students. J. Am. Coll. Health 73, 503–510 (2025).
Google Scholar
Eisenberg, D., Speer, N. & Hunt, J. B. Attitudes and beliefs about treatment among college students with untreated mental health problems. Psychiatr. Serv. 63, 711–713 (2012).
Google Scholar
Taylor, C. B., Graham, A. K., Flatt, R. E., Waldherr, K. & Fitzsimmons-Craft, E. E. Current state of scientific evidence on internet-based interventions for the treatment of depression, anxiety, eating disorders and substance abuse: an overview of systematic reviews and meta-analyses. Eur. J. Public Health 31, i3–i10 (2021).
Google Scholar
Mobile Fact Sheet https://www.pewresearch.org/internet/fact-sheet/mobile/ (Pew Research Center, 2024).
Wolitzky-Taylor, K., Wen, A., Freimer, N. & Craske, M. G. Anxiety and depression in emerging adults: the STAND program as a model of scalable screening and intervention. Neuropsychopharmacology 51, 244–258 (2026).
Google Scholar
NIH-Wide Strategic Plan, Fiscal Years 2022–2025 (NIH, 2021).
Dodge, K. A. et al. Population mental health science: guiding principles and initial agenda. Am. Psychol. 79, 805–823 (2024).
Google Scholar
Kumar, S. et al. Mobile health technology evaluation: the mHealth Evidence Workshop. Am. J. Prev. Med. 45, 228–236 (2013).
Google Scholar
US Preventive Services Task Force et al. Screening for depression and suicide risk in adults: U.S. preventive services task force recommendation statement. JAMA 329, 2057–2067 (2023).
US Preventive Services Task Force et al. Screening for anxiety disorders in adults: U.S. preventive services task force recommendation statement. JAMA 329, 2163–2170 (2023).
Grant, B. F. et al. Sociodemographic and psychopathologic predictors of first incidence of DSM-IV substance use, mood and anxiety disorders: results from the Wave 2 National Epidemiologic Survey on Alcohol and Related Conditions. Mol. Psychiatry 14, 1051–1066 (2009).
Google Scholar
Moffitt, T. E. et al. Depression and generalized anxiety disorder: Cumulative and sequential comorbidity in a birth cohort followed prospectively to age 32 years. Arch. Gen. Psychiatry 64, 651–660 (2007).
Google Scholar
Wittchen, H. U., Kessler, R. C., Pfister, H. & Lieb, M. Why do people with anxiety disorders become depressed? A prospective-longitudinal community study. Acta Psychiatr. Scand. 102, 14–23 (2000).
Pine, D. S., Cohen, P., Gurley, D., Brook, J. & Ma, Y. The risk for early-adulthood anxiety and depressive disorders in adolescents with anxiety and depressive disorders. Arch. Gen. Psychiatry 55, 56–64 (1998).
Google Scholar
Hettema, J. M., Prescott, C. A. & Kendler, K. S. The effects of anxiety, substance use and conduct disorders on risk of major depressive disorder. Psychol. Med. 33, 1423–1432 (2003).
Google Scholar
Ruscio, A. M. et al. Broadening the definition of generalized anxiety disorder: effects on prevalence and associations with other disorders in the National Comorbidity Survey Replication. J. Anxiety Disord. 21, 662–676 (2007).
Google Scholar
Jacobson, N. C. & Newman, M. G. Anxiety and depression as bidirectional risk factors for one another: a meta-analysis of longitudinal studies. Psychol. Bull. 143, 1155–1200 (2017).
Google Scholar
Zanella, E. & Lee, E. Integrative review on psychological and social risk and prevention factors of eating disorders including anorexia nervosa and bulimia nervosa: seven major theories. Heliyon 8, e11422 (2022).
Google Scholar
Swinbourne, J. et al. The comorbidity between eating disorders and anxiety disorders: prevalence in an eating disorder sample and anxiety disorder sample. Aust. N. Z. J. Psychiatry 46, 118–131 (2012).
Google Scholar
Godart, N. et al. Mood disorders in eating disorder patients: prevalence and chronology of ONSET. J. Affect. Disord. 185, 115–122 (2015).
Google Scholar
Presnell, K., Stice, E., Seidel, A. & Madeley, M. C. Depression and eating pathology: prospective reciprocal relations in adolescents. Clin. Psychol. Psychother. 16, 357–365 (2009).
Google Scholar
Skinner, H. H., Haines, J., Austin, S. B. & Field, A. E. A prospective study of overeating, binge eating, and depressive symptoms among adolescent and young adult women. J. Adolesc. Health 50, 478–483 (2012).
Google Scholar
Barakat, S. et al. Risk factors for eating disorders: findings from a rapid review. J. Eat. Disord. 11, 8 (2023).
Google Scholar
Schleider, J., Krause, E. & Gillham, J. Sequential comorbidity of anxiety and depression in youth: present knowledge and future directions. Curr. Psychiatry Rev. 10, 75–87 (2014).
Van Alsten, S. C. & Duncan, A. E. Lifetime patterns of comorbidity in eating disorders: an approach using sequence analysis. Eur. Eat. Disord. Rev. 28, 709–723 (2020).
Google Scholar
de Graaf, R., Bijl, R., Spijker, J., Beekman, A. & Vollebergh, W. Temporal sequencing of lifetime mood disorders in relation to comorbid anxiety and substance use disorders. Soc. Psychiatry Psychiatr. Epidemiol. 38, 1–11 (2003).
Google Scholar
Barkow, K. et al. Risk factors for new depressive episodes in primary health care: an international prospective 12-month follow-up study. Psychol. Med. 32, 595–607 (2002).
Google Scholar
D’Adamo, L. D. et al. Reach and uptake of digital mental health interventions based on cognitive-behavioral therapy for college students: a systematic review. J. Behav. Cognit. Ther. 33, 97–117 (2023).
Schueller, S. M., Hunter, J. F., Figueroa, C. & Aguilera, A. Use of digital mental health for marginalized and underserved populations. Curr. Treat. Options Psychiatry 6, 243–255 (2019).
Center for Collegiate Mental Health. Part 5 of 5: Counseling Center Experiences After the Onset of Covid-19 (PennState Student Affairs, 2022).
Fitzsimmons-Craft, E. E. et al. Effectiveness of a digital cognitive behavior therapy-guided self-help intervention for eating disorders in college women: a cluster randomized clinical trial. JAMA Netw. Open 3, e2015633 (2020).
Google Scholar
Feltner, C. et al. Screening for eating disorders in adolescents and adults: evidence report and systematic review for the US Preventive Services Task Force. JAMA 327, 1068–1082 (2022).
Google Scholar
Carey, E. G., Ridler, I., Ford, T. J. & Stringaris, A. Editorial perspective: when is a ‘small effect’ actually large and impactful? J. Child Psychol. Psychiatry 64, 1643–1647 (2023).
Google Scholar
Christensen, H., Griffiths, K. M. & Farrer, L. Adherence in internet interventions for anxiety and depression. J. Med. Internet Res. 11, e13 (2009).
Google Scholar
Bertuzzi, V. et al. Single-session therapy by appointment for the treatment of anxiety disorders in youth and adults: a systematic review of the literature. Front. Psychol. 12, 721382 (2021).
Google Scholar
Boucher, E. M. & Raiker, J. S. Engagement and retention in digital mental health interventions: a narrative review. BMC Digit. Health 2, 52 (2024).
Calderon, A. et al. Baseline prediction of two-year prevention and remission of anxiety, depression, and eating disorders in college students receiving a digital guided self-help intervention: derivation and external validation of a machine learning algorithm across 26 population-based cohorts. Preprint at OSF https://doi.org/10.31219/osf.io/63zqk (2024).
Fitzsimmons-Craft, E. E. et al. Harnessing mobile technology to reduce mental health disorders in college populations: a randomized controlled trial study protocol. Contemp. Clin. Trials 103, 106320 (2021).
Google Scholar
Kroenke, K. & Spitzer, R. L. The PHQ-9: a new depression diagnostic and severity measure. Psychiatr. Ann. 32, 509–515 (2002).
Richards, D. et al. A randomized controlled trial of an internet-delivered treatment: its potential as a low-intensity community intervention for adults with symptoms of depression. Behav. Res. Ther. 75, 20–31 (2015).
Google Scholar
Newman, M. G., Jacobson, N. C., Rackoff, G. N., Jones Bell, M. & Taylor, C. B. A randomized controlled trial of a smartphone-based application for the treatment of anxiety. Psychother. Res. 31, 443–454 (2021).
Google Scholar
Fitzsimmons-Craft, E. E. et al. Training, supervision, and experience of coaches offering digital guided self-help for mental health concerns. Front. Psychol. 14, 1217698 (2023).
Google Scholar
Newman, M. G. et al. Preliminary reliability and validity of the Generalized Anxiety Disorder Questionnaire-IV: a revised self-report diagnostic measure of generalized anxiety disorder. Behav. Ther. 33, 215–233 (2002).
Newman, M. G., Kachin, K. E., Zuellig, A. R., Constantino, M. J. & Cashman-McGrath, L. The Social Phobia Diagnostic Questionnaire: preliminary validation of a new self-report diagnostic measure of social phobia. Psychol. Med. 33, 623–635 (2003).
Google Scholar
Newman, M. G., Holmes, M., Zuellig, A. R., Kachin, K. E. & Behar, E. The reliability and validity of the Panic Disorder Self-Report: a new diagnostic screening measure of panic disorder. Psychol. Assess. 18, 49–61 (2006).
Google Scholar
Diagnostic and Statistical Manual of Mental Disorders 5th edn (American Psychiatric Association, 2022).
Graham, A. K. et al. A screening tool for detecting eating disorder risk and diagnostic symptoms among college-age women. J. Am. Coll. Health 67, 357–366 (2019).
Google Scholar
Fairburn, C. G. & Beglin, S. J. in Cognitive Behavior Therapy and Eating Disorders (ed. Fairburn, C. G.) 309–313 (Guilford Press, 2008).
Ware, J. Jr., Kosinski, M. & Keller, S. D. A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Med. Care 34, 220–233 (1996).
Google Scholar
Graham, J. W. Missing data analysis: making it work in the real world. Annu. Rev. Psychol. 60, 549–576 (2009).
Google Scholar
van Buuren, S. & Groothuis-Oudshoorn, K. mice: Multivariate Imputation by Chained Equations in R. J. Stat. Softw. https://doi.org/10.18637/jss.v045.i03 (2011).
Rubin, D. B. Multiple Imputation for Nonresponse in Surveys (Wiley, 1987).
Mustillo, S. & Kwon, S. Auxiliary variables in multiple imputation when data are missing not at random. J. Math. Sociol. 39, 73–91 (2015).
Feingold, A. Effect sizes for growth-modeling analysis for controlled clinical trials in the same metric as for classical analysis. Psychol. Methods 14, 43–53 (2009).
Google Scholar
Feingold, A. A regression framework for effect size assessments in longitudinal modeling of group differences. Rev. Gen. Psychol. 17, 111–121 (2013).
Google Scholar
Newman, M. G. et al. Data and statistical code from ‘Population-based RCT of a digital cognitive-behavioural guided self-help intervention for anxiety, depression, and eating disorders in college students. NDA database https://doi.org/10.15154/pz1r-0s31 (2026).



