The Appalachia Mind Health Initiative (AMHI): a pragmatic randomized clinical trial of adjunctive internet-based cognitive behavior therapy for treating major depressive disorder among primary care patients

Robert M Bossarte, Ronald C Kessler, Andrew A Nierenberg, Ambarish Chattopadhyay, Pim Cuijpers, Angel Enrique, Phyllis M Foxworth, Sarah M Gildea, Bea Herbeck Belnap, Marc W Haut, Kari B Law, William D Lewis, Howard Liu, Alexander R Luedtke, Wilfred R Pigeon, Larry A Rhodes, Derek Richards, Bruce L Rollman, Nancy A Sampson, Cara M Stokes, John Torous, Tyler D Webb, Jose R Zubizarreta, Robert M Bossarte, Ronald C Kessler, Andrew A Nierenberg, Ambarish Chattopadhyay, Pim Cuijpers, Angel Enrique, Phyllis M Foxworth, Sarah M Gildea, Bea Herbeck Belnap, Marc W Haut, Kari B Law, William D Lewis, Howard Liu, Alexander R Luedtke, Wilfred R Pigeon, Larry A Rhodes, Derek Richards, Bruce L Rollman, Nancy A Sampson, Cara M Stokes, John Torous, Tyler D Webb, Jose R Zubizarreta

Abstract

Background: Major depressive disorder (MDD) is a leading cause of disease morbidity. Combined treatment with antidepressant medication (ADM) plus psychotherapy yields a much higher MDD remission rate than ADM only. But 77% of US MDD patients are nonetheless treated with ADM only despite strong patient preferences for psychotherapy. This mismatch is due at least in part to a combination of cost considerations and limited availability of psychotherapists, although stigma and reluctance of PCPs to refer patients for psychotherapy are also involved. Internet-based cognitive behaviorial therapy (i-CBT) addresses all of these problems.

Methods: Enrolled patients (n = 3360) will be those who are beginning ADM-only treatment of MDD in primary care facilities throughout West Virginia, one of the poorest and most rural states in the country. Participating treatment providers and study staff at West Virginia University School of Medicine (WVU) will recruit patients and, after obtaining informed consent, administer a baseline self-report questionnaire (SRQ) and then randomize patients to 1 of 3 treatment arms with equal allocation: ADM only, ADM + self-guided i-CBT, and ADM + guided i-CBT. Follow-up SRQs will be administered 2, 4, 8, 13, 16, 26, 39, and 52 weeks after randomization. The trial has two primary objectives: to evaluate aggregate comparative treatment effects across the 3 arms and to estimate heterogeneity of treatment effects (HTE). The primary outcome will be episode remission based on a modified version of the patient-centered Remission from Depression Questionnaire (RDQ). The sample was powered to detect predictors of HTE that would increase the proportional remission rate by 20% by optimally assigning individuals as opposed to randomly assigning them into three treatment groups of equal size. Aggregate comparative treatment effects will be estimated using intent-to-treat analysis methods. Cumulative inverse probability weights will be used to deal with loss to follow-up. A wide range of self-report predictors of MDD heterogeneity of treatment effects based on previous studies will be included in the baseline SRQ. A state-of-the-art ensemble machine learning method will be used to estimate HTE.

Discussion: The study is innovative in using a rich baseline assessment and in having a sample large enough to carry out a well-powered analysis of heterogeneity of treatment effects. We anticipate finding that self-guided and guided i-CBT will both improve outcomes compared to ADM only. We also anticipate finding that the comparative advantages of adding i-CBT to ADM will vary significantly across patients. We hope to develop a stable individualized treatment rule that will allow patients and treatment providers to improve aggregate treatment outcomes by deciding collaboratively when ADM treatment should be augmented with i-CBT.

Trial registration: ClinicalTrials.gov NCT04120285 . Registered on October 19, 2019.

Keywords: Antidepressant medication; Appalachian Mind Health Initiative (AMHI); Heterogeneity of treatment effects; Major depressive disorder; Remission from depression; i-CBT.

Conflict of interest statement

In the past 3 years, RCK has been a consultant for Datastat, Inc, Sage Pharmaceuticals, and Takeda. WRP consulted for CurAegis Technologies and received clinical trial support from Pfizer, Inc and Abbvie, Inc. AE and DR are employees of SilverCloud Health, developers of computerized psychological interventions for depression, anxiety, stress, sleep, resilience, and comorbid long-term conditions. In the past 3 years, JT has received research support from Otsuka. MWH has received funding from Insightec and has been a paid grand rounds speaker for Medtronic and Atrium Health. AAN serves on scientific advisory boards for Alkermes, Jazz Pharmaceuticals, Sage Pharmaceuticals, Otsuka, and Neuronetics; was a consultant for Acadia Pharmaceuticals, Esai, Myriad, Merck, Ginger, Protogenics, Neurogenics and Clexio; and also reports receiving honoraria from Sunovion and Neurostar.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
Participant timeline

References

    1. Cuijpers P, Reynolds CF, 3rd, Donker T, Li J, Andersson G, Beekman A. Personalized treatment of adult depression: medication, psychotherapy, or both? A systematic review. Depress Anxiety. 2012;29(10):855–864. doi: 10.1002/da.21985.
    1. Kessler RC. The costs of depression. Psychiatr Clin North Am. 2012;35(1):1–14. doi: 10.1016/j.psc.2011.11.005.
    1. Ferrari AJ, Charlson FJ, Norman RE, Patten SB, Freedman G, Murray CJ, et al. Burden of depressive disorders by country, sex, age, and year: findings from the global burden of disease study 2010. PLoS Med. 2013;10(11):e1001547. doi: 10.1371/journal.pmed.1001547.
    1. Ferrari AJ, Norman RE, Freedman G, Baxter AJ, Pirkis JE, Harris MG, et al. The burden attributable to mental and substance use disorders as risk factors for suicide: findings from the Global Burden of Disease Study 2010. PLoS One. 2014;9(4):e91936. doi: 10.1371/journal.pone.0091936.
    1. Greenberg PE, Fournier AA, Sisitsky T, Pike CT, Kessler RC. The economic burden of adults with major depressive disorder in the United States (2005 and 2010) J Clin Psychiatry. 2015;76(2):155–162. doi: 10.4088/JCP.14m09298.
    1. Patten SB, Williams JV, Lavorato DH, Modgill G, Jetté N, Eliasziw M. Major depression as a risk factor for chronic disease incidence: longitudinal analyses in a general population cohort. Gen Hosp Psychiatry. 2008;30(5):407–413. doi: 10.1016/j.genhosppsych.2008.05.001.
    1. Deschênes SS, Burns RJ, Schmitz N. Associations between depression, chronic physical health conditions, and disability in a community sample: a focus on the persistence of depression. J Affect Disord. 2015;179:6–13. doi: 10.1016/j.jad.2015.03.020.
    1. Ishak WW, Balayan K, Bresee C, Greenberg JM, Fakhry H, Christensen S, et al. A descriptive analysis of quality of life using patient-reported measures in major depressive disorder in a naturalistic outpatient setting. Qual Life Res. 2013;22(3):585–596. doi: 10.1007/s11136-012-0187-6.
    1. Druss BG, Hwang I, Petukhova M, Sampson NA, Wang PS, Kessler RC. Impairment in role functioning in mental and chronic medical disorders in the United States: results from the National Comorbidity Survey Replication. Mol Psychiatry. 2009;14(7):728–737. doi: 10.1038/mp.2008.13.
    1. Viana MC, Gruber MJ, Shahly V, Alhamzawi A, Alonso J, Andrade LH, et al. Family burden related to mental and physical disorders in the world: results from the WHO World Mental Health (WMH) surveys. Braz J Psychiatry (Sao Paulo, Brazil: 1999) 2013;35(2):115–125. doi: 10.1590/1516-4446-2012-0919.
    1. Weissman MM, Wickramaratne P, Pilowsky DJ, Poh E, Hernandez M, Batten LA, et al. The effects on children of depressed mothers’ remission and relapse over 9 months. Psychol Med. 2014;44(13):2811–2824. doi: 10.1017/S003329171400021X.
    1. Olfson M, Blanco C, Marcus SC. Treatment of adult depression in the United States. JAMA Intern Med. 2016;176(10):1482–1491. doi: 10.1001/jamainternmed.2016.5057.
    1. American Psychiatric Association Practice guideline for the treatment of patients with major depressive disorder (revision) Am J Psychiatry. 2000;157(4 Suppl):1–45.
    1. Andersson G, Cuijpers P, Carlbring P, Riper H, Hedman E. Guided Internet-based vs. face-to-face cognitive behavior therapy for psychiatric and somatic disorders: a systematic review and meta-analysis. World Psychiatry. 2014;13(3):288–295. doi: 10.1002/wps.20151.
    1. Cuijpers P, Noma H, Karyotaki E, Vinkers CH, Cipriani A, Furukawa TA. A network meta-analysis of the effects of psychotherapies, pharmacotherapies and their combination in the treatment of adult depression. World Psychiatry. 2020;19(1):92–107. doi: 10.1002/wps.20701.
    1. Weitz ES, Hollon SD, Twisk J, van Straten A, Huibers MJ, David D, et al. Baseline depression severity as moderator of depression outcomes between cognitive behavioral therapy vs pharmacotherapy: an individual patient data meta-analysis. JAMA Psychiatry. 2015;72(11):1102–1109. doi: 10.1001/jamapsychiatry.2015.1516.
    1. Cohen ZD, DeRubeis RJ. Treatment selection in depression. Annu Rev Clin Psychol. 2018;14:209–236. doi: 10.1146/annurev-clinpsy-050817-084746.
    1. DeRubeis RJ, Cohen ZD, Forand NR, Fournier JC, Gelfand LA, Lorenzo-Luaces L. The Personalized Advantage Index: translating research on prediction into individualized treatment recommendations. A demonstration. PLoS One. 2014;9(1):e83875. doi: 10.1371/journal.pone.0083875.
    1. Karyotaki E, Smit Y, Holdt Henningsen K, Huibers MJ, Robays J, de Beurs D, et al. Combining pharmacotherapy and psychotherapy or monotherapy for major depression? A meta-analysis on the long-term effects. J Affect Disord. 2016;194:144–152. doi: 10.1016/j.jad.2016.01.036.
    1. Craighead WE, Dunlop BW. Combination psychotherapy and antidepressant medication treatment for depression: for whom, when, and how. Annu Rev Psychol. 2014;65:267–300. doi: 10.1146/annurev.psych.121208.131653.
    1. Carlbring P, Andersson G, Cuijpers P, Riper H, Hedman-Lagerlöf E. Internet-based vs. face-to-face cognitive behavior therapy for psychiatric and somatic disorders: an updated systematic review and meta-analysis. Cogn Behav Ther. 2018;47(1):1–18. doi: 10.1080/16506073.2017.1401115.
    1. Cuijpers P, Donker T, van Straten A, Li J, Andersson G. Is guided self-help as effective as face-to-face psychotherapy for depression and anxiety disorders? A systematic review and meta-analysis of comparative outcome studies. Psychol Med. 2010;40(12):1943–1957. doi: 10.1017/S0033291710000772.
    1. Van den Broeck K, Remmen R, Vanmeerbeek M, Destoop M, Dom G. Collaborative care regarding major depressed patients: a review of guidelines and current practices. J Affect Disord. 2016;200:189–203. doi: 10.1016/j.jad.2016.04.044.
    1. Rollman BL, Herbeck Belnap B, Abebe KZ, Spring MB, Rotondi AJ, Rothenberger SD, et al. Effectiveness of online collaborative care for treating mood and anxiety disorders in primary care: a randomized clinical trial. JAMA Psychiatry. 2018;75(1):56–64. doi: 10.1001/jamapsychiatry.2017.3379.
    1. Andersson G, Cuijpers P. Internet-based and other computerized psychological treatments for adult depression: a meta-analysis. Cogn Behav Ther. 2009;38(4):196–205. doi: 10.1080/16506070903318960.
    1. Richards D, Richardson T. Computer-based psychological treatments for depression: a systematic review and meta-analysis. Clin Psychol Rev. 2012;32(4):329–342. doi: 10.1016/j.cpr.2012.02.004.
    1. Wells MJ, Owen JJ, McCray LW, Bishop LB, Eells TD, Brown GK, et al. Computer-assisted cognitive-behavior therapy for depression in primary care: systematic review and meta-analysis. Prim Care Companion CNS Disord. 2018;20(2):24454. doi: 10.4088/PCC.17r02196.
    1. Wright JH, Owen JJ, Richards D, Eells TD, Richardson T, Brown GK, et al. Computer-assisted cognitive-behavior therapy for depression: a systematic review and meta-analysis. J Clin Psychiatry. 2019;80(2):3573. doi: 10.4088/JCP.18r12188.
    1. Cuijpers P, Noma H, Karyotaki E, Cipriani A, Furukawa T. Individual, group, telephone, self-help and internet-based cognitive behavior therapy for adult depression: a network meta-analysis of delivery methods. JAMA Psychiatry. 2019;76:700–707. doi: 10.1001/jamapsychiatry.2019.0268.
    1. Karyotaki E, Riper H, Twisk J, Hoogendoorn A, Kleiboer A, Mira A, et al. Efficacy of self-guided internet-based cognitive behavioral therapy in the treatment of depressive symptoms: a meta-analysis of individual participant data. JAMA Psychiatry. 2017;74(4):351–359. doi: 10.1001/jamapsychiatry.2017.0044.
    1. Cuijpers P, Sijbrandij M, Koole SL, Andersson G, Beekman AT, Reynolds CF., 3rd Adding psychotherapy to antidepressant medication in depression and anxiety disorders: a meta-analysis. World Psychiatry. 2014;13(1):56–67. doi: 10.1002/wps.20089.
    1. Grohol J. Mental health professionals: US statistics 2017. Psych Central; 2019.
    1. Kessler RC, van Loo HM, Wardenaar KJ, Bossarte RM, Brenner LA, Ebert DD, et al. Using patient self-reports to study heterogeneity of treatment effects in major depressive disorder. Epidemiol Psychiatr Sci. 2017;26(1):22–36. doi: 10.1017/S2045796016000020.
    1. Kraemer HC. Discovering, comparing, and combining moderators of treatment on outcome after randomized clinical trials: a parametric approach. Stat Med. 2013;32(11):1964–1973. doi: 10.1002/sim.5734.
    1. National Collaborating Centre for Mental Health . Depression: the treatment and management of depression in adults (updated edition) Leicester (UK): British Psychological Society; 2010.
    1. Gelenberg A, Freeman M, Markowitz J, Rosenbaum J, Thase M, Trivedi M, et al. American Psychiatric Association practice guideline for the treatment of patients with major depressive disorder. Am J Psychiatry. 2010;167(suppl 10):9–118.
    1. United States Census Bureau. American FactFinder 2015. . Accessed 15 Oct 2020.
    1. The Henry J. Kaiser Family Foundation. Medicaid fact sheets. In: Percent of people covered by Medicaid . Accessed 15 Oct 2020.
    1. National Institute on Drug Abuse. Opioid summaries by state 2020. . Accessed 15 Oct 2020.
    1. United States Census Bureau. 2010 census urban and rural classification and urban area criteria. . Accessed 15 Oct 2020.
    1. Mental Health America. The state of mental health in America 2017. . Accessed 15 Oct 2020.
    1. van Schaik DJ, Klijn AF, van Hout HP, van Marwijk HW, Beekman AT, de Haan M, et al. Patients’ preferences in the treatment of depressive disorder in primary care. Gen Hosp Psychiatry. 2004;26(3):184–189. doi: 10.1016/j.genhosppsych.2003.12.001.
    1. Lin P, Campbell DG, Chaney EF, Liu CF, Heagerty P, Felker BL, et al. The influence of patient preference on depression treatment in primary care. Ann Behav Med. 2005;30(2):164–173. doi: 10.1207/s15324796abm3002_9.
    1. Waltz TJ, Campbell DG, Kirchner JE, Lombardero A, Bolkan C, Zivin K, et al. Veterans with depression in primary care: provider preferences, matching, and care satisfaction. Fam Syst Health. 2014;32(4):367–377. doi: 10.1037/fsh0000071.
    1. Dunlop BW, Kelley ME, Aponte-Rivera V, Mletzko-Crowe T, Kinkead B, Ritchie JC, et al. Effects of patient preferences on outcomes in the Predictors of Remission in Depression to Individual and Combined Treatments (PReDICT) study. Am J Psychiatry. 2017;174(6):546–556. doi: 10.1176/appi.ajp.2016.16050517.
    1. Morris C. A finite selection model for experimental design of the health insurance study. J Econom. 1979;11(1):43–61. doi: 10.1016/0304-4076(79)90053-8.
    1. U.S. Department of Veterans Affairs. West Virginia 2018. . Accessed 1 Oct 2020.
    1. Harrington J. There are 18.2 million veterans in the US. Which state is home to the most of them? 2019.
    1. SilverCloud . SilverCloud digital mental health platform. 2019.
    1. Duffy D, Enrique A, Connell S, Connolly C, Richards D. Internet-delivered cognitive behaviour therapy as a prequel to face-to-face therapy for depression and anxiety: a naturalistic observation. Front Psychiatry. 2019;10:902. doi: 10.3389/fpsyt.2019.00902.
    1. Enrique A, Palacios JE, Ryan H, Richards D. Exploring the relationship between usage and outcomes of an internet-based intervention for individuals with depressive symptoms: secondary analysis of data from a randomized controlled trial. J Med Internet Res. 2019;21(8):e12775. doi: 10.2196/12775.
    1. Richards D, Enrique A, Eilert N, Franklin M, Palacios J, Duffy D, et al. A pragmatic randomized waitlist-controlled effectiveness and cost-effectiveness trial of digital interventions for depression and anxiety. NPJ Digit Med. 2020;3:85. doi: 10.1038/s41746-020-0293-8.
    1. Coyle D, Doherty G, Matthews M, Sharry J. Computers in talk-based mental health interventions. Interact Comput. 2007;19(4):545–562. doi: 10.1016/j.intcom.2007.02.001.
    1. Earley C, Joyce C, McElvaney J, Richards D, Timulak L. Preventing depression: qualitatively examining the benefits of depression-focused i-CBT for participants who do not meet clinical thresholds. Internet Interv. 2017;9:82. doi: 10.1016/j.invent.2017.07.003.
    1. Palacios JE, Richards D, Palmer R, Coudray C, Hofmann SG, Palmieri PA, et al. Supported internet-delivered cognitive behavioral therapy programs for depression, anxiety, and stress in university students: open, non-randomised trial of acceptability, effectiveness, and satisfaction. JMIR Ment Health. 2018;5(4):e11467. doi: 10.2196/11467.
    1. Doherty G, Coyle D, Sharry J. Proceedings of the SIGCHI conference on human factors in computing systems. 2012. Engagement with online mental health interventions: an exploratory clinical study of a treatment for depression.
    1. Richards D, Timulak L, O’Brien E, Hayes C, Vigano N, Sharry J, 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. 2015;75:20–31. doi: 10.1016/j.brat.2015.10.005.
    1. Enrique A, Duffy D, Lawler K, Richards D, Jones S. An internet-delivered self-management program for Bipolar Disorder in mental health services in Ireland. Results and learnings from a feasibility trial. Clin Psychol Psychother. 2020;27(6):925–939. doi: 10.1002/cpp.2480.
    1. Baumel A, Muench F, Edan S, Kane JM. Objective user engagement with mental health apps: systematic search and panel-based usage analysis. J Med Internet Res. 2019;21(9):e14567. doi: 10.2196/14567.
    1. Beck CD, Soucy JN, Hadjistavropoulos HD. Mixed-method evaluation of an online motivational intervention as a pre-treatment to internet-delivered cognitive behaviour therapy: immediate benefits and user feedback. Internet Interv. 2020;20:100311. doi: 10.1016/j.invent.2020.100311.
    1. Addington EL, Cheung EO, Bassett SM, Kwok I, Schuette SA, Shiu E, et al. The MARIGOLD study: feasibility and enhancement of an online intervention to improve emotion regulation in people with elevated depressive symptoms. J Affect Disord. 2019;257:352–364. doi: 10.1016/j.jad.2019.07.049.
    1. Cheung EO, Cohn MA, Dunn LB, Melisko ME, Morgan S, Penedo FJ, et al. A randomized pilot trial of a positive affect skill intervention (lessons in linking affect and coping) for women with metastatic breast cancer. Psychooncology. 2017;26(12):2101–2108. doi: 10.1002/pon.4312.
    1. Chien I, Enrique A, Palacios J, Regan T, Keegan D, Carter D, et al. A machine learning approach to understanding patterns of engagement with internet-delivered mental health interventions. JAMA Netw Open. 2020;3(7):e2010791. doi: 10.1001/jamanetworkopen.2020.10791.
    1. Zimmerman M, Martinez JH, Attiullah N, Friedman M, Toba C, Boerescu DA, et al. A new type of scale for determining remission from depression: the Remission from Depression Questionnaire. J Psychiatr Res. 2013;47(1):78–82. doi: 10.1016/j.jpsychires.2012.09.006.
    1. Montoya A, Lebrec J, Keane KM, Fregenal I, Ciudad A, Moríñigo Á, et al. Broader conceptualization of remission assessed by the remission from depression questionnaire and its association with symptomatic remission: a prospective, multicenter, observational study. BMC Psychiatry. 2016;16(1):352. doi: 10.1186/s12888-016-1067-3.
    1. DiBenedetti DB, Danchenko N, François C, Lewis S, Davis KH, Fehnel SE. Development of a family functioning scale for major depressive disorder. Curr Med Res Opin. 2012;28(3):303–313. doi: 10.1185/03007995.2012.658910.
    1. Lasch KE, Hassan M, Endicott J, Piault-Luis EC, Locklear J, Fitz-Randolph M, et al. Development and content validity of a patient reported outcomes measure to assess symptoms of major depressive disorder. BMC Psychiatry. 2012;12:34. doi: 10.1186/1471-244X-12-34.
    1. Vaccarino AL, Evans KR, Kalali AH, Kennedy SH, Engelhardt N, Frey BN, et al. The depression inventory development workgroup: a collaborative, empirically driven initiative to develop a new assessment tool for major depressive disorder. Innov Clin Neurosci. 2016;13(9-10):20–31.
    1. Zimmerman M, Martinez JH, Attiullah N, Friedman M, Toba C, Boerescu DA. The remission from depression questionnaire as an outcome measure in the treatment of depression. Depress Anxiety. 2014;31(6):533–538. doi: 10.1002/da.22178.
    1. Zimmerman M, Galione JN, Attiullah N, Friedman M, Toba C, Boerescu DA, et al. Depressed patients’ perspectives of 2 measures of outcome: the Quick Inventory of Depressive Symptomatology (QIDS) and the Remission from Depression Questionnaire (RDQ) Ann Clin Psychiatry. 2011;23(3):208–212.
    1. Trivedi MH, Rush AJ, Ibrahim HM, Carmody TJ, Biggs MM, Suppes T, et al. The Inventory of Depressive Symptomatology, Clinician Rating (IDS-C) and Self-Report (IDS-SR), and the Quick Inventory of Depressive Symptomatology, Clinician Rating (QIDS-C) and Self-Report (QIDS-SR) in public sector patients with mood disorders: a psychometric evaluation. Psychol Med. 2004;34(1):73–82. doi: 10.1017/S0033291703001107.
    1. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23(1):56–62. doi: 10.1136/jnnp.23.1.56.
    1. Inventory of Depressive Symptomatology (IDS) and Quick Inventory of Depressive Symptomatology (QIDS). . Accessed 1 Oct 2020.
    1. Jobst A, Brakemeier EL, Buchheim A, Caspar F, Cuijpers P, Ebmeier KP, et al. European Psychiatric Association Guidance on psychotherapy in chronic depression across Europe. Eur Psychiatry. 2016;33:18–36. doi: 10.1016/j.eurpsy.2015.12.003.
    1. Statista . Drug overdose death rate in the United States in 2015, by state (per 100,000 population) 2017.
    1. de Jonge P, Wardenaar KJ, Lim CCW, Aguilar-Gaxiola S, Alonso J, Andrade LH, et al. The cross-national structure of mental disorders: results from the World Mental Health Surveys. Psychol Med. 2018;48(12):2073–2084. doi: 10.1017/S0033291717003610.
    1. PROMIS . Short form v1.0 - severity of substance use (past 30 days) 7a. 2017.
    1. Castel AD, Tang W, Peterson J, Mikre M, Parenti D, Elion R, et al. Sorting through the lost and found: are patient perceptions of engagement in care consistent with standard continuum of care measures? J Acquir Immunue Defic Syndr. 2015;69 Suppl 1(0 1):S44–S55. doi: 10.1097/QAI.0000000000000575.
    1. Barr PJ, Thompson R, Walsh T, Grande SW, Ozanne EM, Elwyn G. The psychometric properties of CollaboRATE: a fast and frugal patient-reported measure of the shared decision-making process. J Med Internet Res. 2014;16(1):e2. doi: 10.2196/jmir.3085.
    1. Fava M, Rush AJ, Trivedi MH, Nierenberg AA, Thase ME, Sackeim HA, et al. Background and rationale for the sequenced treatment alternatives to relieve depression (STAR* D) study. Psychiatr Clin North Am. 2003;26(2):457–494. doi: 10.1016/S0193-953X(02)00107-7.
    1. Newman MG, Szkodny LE, Llera SJ, Przeworski A. A review of technology-assisted self-help and minimal contact therapies for anxiety and depression: is human contact necessary for therapeutic efficacy? Clin Psychol Rev. 2011;31(1):89–103. doi: 10.1016/j.cpr.2010.09.008.
    1. Vaidyam A, Halamka J, Torous J. Actionable digital phenotyping: a framework for the delivery of just-in-time and longitudinal interventions in clinical healthcare. mHealth. 2019;5:25. doi: 10.21037/mhealth.2019.07.04.
    1. Henson P, Torous J. Feasibility and correlations of smartphone meta-data toward dynamic understanding of depression and suicide risk in schizophrenia. Int J Methods Psychiatr Res. 2020;29(2):e1825. doi: 10.1002/mpr.1825.
    1. Yarkoni T. The abbreviation of personality, or how to measure 200 personality scales with 200 items. J Res Pers. 2010;44(2):180–198. doi: 10.1016/j.jrp.2010.01.002.
    1. Ustun B, Rudin C. Supersparse linear integer models for optimized medical scoring systems. Mach Learn. 2016;102(3):349–391. doi: 10.1007/s10994-015-5528-6.
    1. Germine L, Nakayama K, Duchaine BC, Chabris CF, Chatterjee G, Wilmer JB. Is the Web as good as the lab? Comparable performance from Web and lab in cognitive/perceptual experiments. Psychon Bull Rev. 2012;19(5):847–857. doi: 10.3758/s13423-012-0296-9.
    1. Hamilton CM, Strader LC, Pratt JG, Maiese D, Hendershot T, Kwok RK, et al. The PhenX Toolkit: get the most from your measures. Am J Epidemiol. 2011;174(3):253–260. doi: 10.1093/aje/kwr193.
    1. Department of Homeland Security. Cybersecurity and Infrastructure Security Agency. Identifying critical infrastructure during COVID-19. . Accessed 30 Oct 2020.
    1. Rush AJ, Trivedi MH, Ibrahim HM, Carmody TJ, Arnow B, Klein DN, et al. The 16-Item Quick Inventory of Depressive Symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression. Biol Psychiatry. 2003;54(5):573–583. doi: 10.1016/S0006-3223(02)01866-8.
    1. Rush AJ, Gullion CM, Basco MR, Jarrett RB, Trivedi MH. The inventory of depressive symptomatology (IDS): psychometric properties. Psychol Med. 1996;26(3):477–486. doi: 10.1017/S0033291700035558.
    1. American Psychiatric Association . Diagnostic and statistical manual of mental disorders (DSM-5®) Washington D.C.: American Psychiatric Pub; 2013.
    1. Day CV, John Rush A, Harris AW, Boyce PM, Rekshan W, Etkin A, et al. Impairment and distress patterns distinguishing the melancholic depression subtype: an iSPOT-D report. J Affect Disord. 2015;174:493–502. doi: 10.1016/j.jad.2014.10.046.
    1. Zimmerman M, Chelminski I, Young D, Dalrymple K, Martinez JH. A clinically useful self-report measure of the DSM-5 mixed features specifier of major depressive disorder. J Affect Disord. 2014;168:357–362. doi: 10.1016/j.jad.2014.07.021.
    1. Kessler RC, Ustün TB. The World Mental Health (WMH) Survey Initiative Version of the World Health Organization (WHO) Composite International Diagnostic Interview (CIDI) Int J Methods Psychiatr Res. 2004;13(2):93–121. doi: 10.1002/mpr.168.
    1. Rizvi SJ, Quilty LC, Sproule BA, Cyriac A, Michael Bagby R, Kennedy SH. Development and validation of the Dimensional Anhedonia Rating Scale (DARS) in a community sample and individuals with major depression. Psychiatry Res. 2015;229(1-2):109–119. doi: 10.1016/j.psychres.2015.07.062.
    1. Llerena K, Park SG, McCarthy JM, Couture SM, Bennett ME, Blanchard JJ. The Motivation and Pleasure Scale-Self-Report (MAP-SR): reliability and validity of a self-report measure of negative symptoms. Compr Psychiatry. 2013;54(5):568–574. doi: 10.1016/j.comppsych.2012.12.001.
    1. Stewart JW, McGrath PJ, Fava M, Wisniewski SR, Zisook S, Cook I, et al. Do atypical features affect outcome in depressed outpatients treated with citalopram? Int J Neuropsychopharmacol. 2010;13(1):15–30. doi: 10.1017/S1461145709000182.
    1. Ursano RJ, Colpe LJ, Heeringa SG, Kessler RC, Schoenbaum M, Stein MB, et al. The Army study to assess risk and resilience in servicemembers (Army STARRS) Psychiatry. 2014;77(2):107–119. doi: 10.1521/psyc.2014.77.2.107.
    1. Kessler RC, Üstün TB. The world mental health (WMH) survey initiative version of the world health organization (WHO) composite international diagnostic interview (CIDI) Int J Methods Psychaitr Res. 2004;13(2):93–121. doi: 10.1002/mpr.168.
    1. Sotsky SM, Glass DR, Shea MT, Pilkonis PA, Collins JF, Elkin I, et al. Patient predictors of response to psychotherapy and pharmacotherapy: findings in the NIMH Treatment of Depression Collaborative Research Program. Am J Psychiatry. 1991;148(8):997–1008. doi: 10.1176/ajp.148.8.997.
    1. Posner K, Brown GK, Stanley B, Brent DA, Yershova KV, Oquendo MA, et al. The Columbia–Suicide Severity Rating Scale: initial validity and internal consistency findings from three multisite studies with adolescents and adults. Am J Psychiatry. 2011;168(12):1266–1277. doi: 10.1176/appi.ajp.2011.10111704.
    1. Nock MK, Holmberg EB, Photos VI, Michel BD. Self-Injurious Thoughts and Behaviors Interview: development, reliability, and validity in an adolescent sample. Psychol Assess. 2007;19(3):309–317. doi: 10.1037/1040-3590.19.3.309.
    1. Dube P, Kurt K, Bair MJ, Theobald D, Williams LS. The p4 screener: evaluation of a brief measure for assessing potential suicide risk in 2 randomized effectiveness trials of primary care and oncology patients. Prim Care Companion J Clin Psychiatry. 2010;12(6).
    1. Blevins CA, Weathers FW, Davis MT, Witte TK, Domino JL. The posttraumatic stress disorder checklist for DSM-5 (PCL-5): development and initial psychometric evaluation. J Trauma Stress. 2015;28(6):489–498. doi: 10.1002/jts.22059.
    1. Zuromski KL, Ustun B, Hwang I, Keane TM, Marx BP, Stein MB, et al. Developing an optimal short-form of the PTSD Checklist for DSM-5 (PCL-5) Depress Anxiety. 2019;36(9):790–800. doi: 10.1002/da.22942.
    1. Gibbons LE, Fredericksen R, Merrill JO, McCaul ME, Chander G, Hutton H, et al. Suitability of the PROMIS alcohol use short form for screening in a HIV clinical care setting. Drug Alcohol Depend. 2016;164:113–119. doi: 10.1016/j.drugalcdep.2016.04.038.
    1. Spitzer RL, Williams JB, Gibbon M, First MB. User’s guide for the structured clinical interview for DSM-III-R: SCID. Washington D.C.: American Psychiatric Association; 1990.
    1. Joyce PR, McKenzie JM, Carter JD, Rae AM, Luty SE, Frampton CM, et al. Temperament, character and personality disorders as predictors of response to interpersonal psychotherapy and cognitive-behavioural therapy for depression. Br J Psychiatry. 2007;190(6):503–508. doi: 10.1192/bjp.bp.106.024737.
    1. Weissman MM, Wickramaratne P, Adams P, Wolk S, Verdeli H, Olfson M. Brief screening for family psychiatric history: the family history screen. Arch Gen Psychiatry. 2000;57(7):675–682. doi: 10.1001/archpsyc.57.7.675.
    1. Andreasen NC, Endicott J, Spitzer RL, Winokur G. The family history method using diagnostic criteria. Reliability and validity. Arch Gen Psychiatry. 1977;34(10):1229–1235. doi: 10.1001/archpsyc.1977.01770220111013.
    1. Axelsson E, Andersson E, Ljótsson B, Wallhed Finn D, Hedman E. The health preoccupation diagnostic interview: inter-rater reliability of a structured interview for diagnostic assessment of DSM-5 somatic symptom disorder and illness anxiety disorder. Cogn Behav Ther. 2016;45(4):259–269. doi: 10.1080/16506073.2016.1161663.
    1. Limburg K, Sattel H, Radziej K, Lahmann C. DSM-5 somatic symptom disorder in patients with vertigo and dizziness symptoms. J Psychosom Res. 2016;91:26–32. doi: 10.1016/j.jpsychores.2016.10.005.
    1. Toussaint A, Murray AM, Voigt K, Herzog A, Gierk B, Kroenke K, et al. Development and validation of the Somatic Symptom Disorder-B Criteria Scale (SSD-12) Psychosom Med. 2016;78(1):5–12. doi: 10.1097/PSY.0000000000000240.
    1. Herzog A, Voigt K, Meyer B, Wollburg E, Weinmann N, Langs G, et al. Psychological and interactional characteristics of patients with somatoform disorders: validation of the Somatic Symptoms Experiences Questionnaire (SSEQ) in a clinical psychosomatic population. J Psychosom Res. 2015;78(6):553–562. doi: 10.1016/j.jpsychores.2015.03.004.
    1. Morin CM, Belleville G, Bélanger L, Ivers H. The Insomnia Severity Index: psychometric indicators to detect insomnia cases and evaluate treatment response. Sleep. 2011;34(5):601–608. doi: 10.1093/sleep/34.5.601.
    1. Krebs EE, Lorenz KA, Bair MJ, Damush TM, Wu J, Sutherland JM, et al. Development and initial validation of the PEG, a three-item scale assessing pain intensity and interference. J Gen Intern Med. 2009;24(6):733–738. doi: 10.1007/s11606-009-0981-1.
    1. Von Korff M, Ormel J, Keefe FJ, et al. Grading the severity of chronic pain. Pain. 1992;50:133–149. doi: 10.1016/0304-3959(92)90154-4.
    1. Leon A, Olfson M, Portera L, Farber L. Assessing impairment in primary care: a psychometric analysis of the Sheehan Disability Scale. Int J Psychiatry Med. 1997;27:93–105. doi: 10.2190/T8EM-C8YH-373N-1UWD.
    1. Motrico E, Moreno-Küstner B, de Dios Luna J, Torres-González F, King M, Nazareth I, et al. Psychometric properties of the List of Threatening Experiences—LTE and its association with psychosocial factors and mental disorders according to different scoring methods. J Affect Disord. 2013;150(3):931–940. doi: 10.1016/j.jad.2013.05.017.
    1. Health Do. Cox A, Bentovim A. Recent life events questionnaire. London: The Stationery Office, Ltd.; 2000. pp. 35–38.
    1. Bernstein DP, Stein JA, Newcomb MD, Walker E, Pogge D, Ahluvalia T, et al. Development and validation of a brief screening version of the Childhood Trauma Questionnaire. Child Abuse Negl. 2003;27(2):169–190. doi: 10.1016/S0145-2134(02)00541-0.
    1. Dube SR, Anda RF, Felitti VJ, Chapman DP, Williamson DF, Giles WH. Childhood abuse, household dysfunction, and the risk of attempted suicide throughout the life span: findings from the Adverse Childhood Experiences Study. JAMA. 2001;286(24):3089–3096. doi: 10.1001/jama.286.24.3089.
    1. Stein MB, Campbell-Sills L, Ursano RJ, Rosellini AJ, Colpe LJ, He F, et al. Childhood maltreatment and lifetime suicidal behaviors among new soldiers in the US Army: results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) J Clin Psychiatry. 2018;79(2):2567. doi: 10.4088/JCP.16m10900.
    1. Williams LM, Debattista C, Duchemin AM, Schatzberg AF, Nemeroff CB. Childhood trauma predicts antidepressant response in adults with major depression: data from the randomized international study to predict optimized treatment for depression. Transl Psychiatry. 2016;6(5):e799. doi: 10.1038/tp.2016.61.
    1. Parker G, Tupling H, Brown L. Parental bonding instrument (PBI) Br J Med Psychol. 1979;52(1):1–10. doi: 10.1111/j.2044-8341.1979.tb02487.x.
    1. Lin LY, Sidani JE, Shensa A, Radovic A, Miller E, Colditz JB, et al. Association between social media use and depression among U.S. young adults. Depress Anxiety. 2016;33(4):323–331. doi: 10.1002/da.22466.
    1. Schuster TL, Kessler RC, Aseltine RH. Supportive interactions, negative interactions, and depressed mood. Am J Community Psychol. 1990;18(3):423–438. doi: 10.1007/BF00938116.
    1. Van Orden KA, Cukrowicz KC, Witte TK, Joiner TE., Jr Thwarted belongingness and perceived burdensomeness: construct validity and psychometric properties of the Interpersonal Needs Questionnaire. Psychol Assess. 2012;24(1):197. doi: 10.1037/a0025358.
    1. Besse RD. Loneliness among college students: examining potential coping strategies and the influence of targeted messages on the likelihood of befriending. Kansas State University; 2016.
    1. Robinson JP, Shaver PR. Measures of social psychological attitudes. Revised. 1973.
    1. (SMART). SMART . Best practices for asking questions about sexual orientation on surveys. The Williams Institute, UCLA School of Law; 2009.
    1. Iwamoto DK, Brady J, Kaya A, Park A. Masculinity and depression: a longitudinal investigation of multidimensional masculine norms among college men. Am J Mens Health. 2018;12(6):1873–1881. doi: 10.1177/1557988318785549.
    1. Thompson E, Jr, Pleck JH, Ferrera DL. Men and masculinities: scales for masculinity ideology and masculinity-related constructs. Sex Roles. 1992;27(11-12):573–607. doi: 10.1007/BF02651094.
    1. Bagby RM, Parker JD, Taylor GJ. The twenty-item Toronto Alexithymia Scale--I. Item selection and cross-validation of the factor structure. J Psychosom Res. 1994;38(1):23–32. doi: 10.1016/0022-3999(94)90005-1.
    1. Judah MR, Grant DM, Mills AC, Lechner WV. Factor structure and validation of the Attentional Control Scale. Cognit Emot. 2014;28(3):433–451. doi: 10.1080/02699931.2013.835254.
    1. Bartholomew K, Horowitz LM. Attachment styles among young adults: a test of a four-category model. J Pers Soc Psychol. 1991;61(2):226–244. doi: 10.1037/0022-3514.61.2.226.
    1. Medrano LA, Trógolo M. Construct validity of the difficulties in emotion regulation scale: further evidence using confirmatory factor analytic approach. Abnorm Behav Psychol. 2016;2:2. doi: 10.4172/2472-0496.1000117.
    1. Garnefski N, Kraaij V. Relationships between cognitive emotion regulation strategies and depressive symptoms: a comparative study of five specific samples. Pers Individ Dif. 2006;40(8):1659–1669. doi: 10.1016/j.paid.2005.12.009.
    1. Tedeschi RG, Calhoun LG. The Posttraumatic Growth Inventory: measuring the positive legacy of trauma. J Trauma Stress. 1996;9(3):455–471. doi: 10.1002/jts.2490090305.
    1. Roberti JW, Harrington LN, Storch EA. Further psychometric support for the 10-item version of the perceived stress scale. JOCC. 2006;9(2):135–147.
    1. Campbell-Sills L, Stein MB. Psychometric analysis and refinement of the Connor-davidson Resilience Scale (CD-RISC): validation of a 10-item measure of resilience. J Trauma Stress. 2007;20(6):1019–1028. doi: 10.1002/jts.20271.
    1. Campbell-Sills L, Kessler RC, Ursano RJ, Sun X, Taylor CT, Heeringa SG, et al. Predictive validity and correlates of self-assessed resilience among U.S. Army soldiers. Depress Anxiety. 2018;35(2):122–131. doi: 10.1002/da.22694.
    1. Stein MB, Kessler RC, Heeringa SG, Jain S, Campbell-Sills L, Colpe LJ, et al. Prospective longitudinal evaluation of the effect of deployment-acquired traumatic brain injury on posttraumatic stress and related disorders: results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) Am J Psychiatry. 2015;172(11):1101–1111. doi: 10.1176/appi.ajp.2015.14121572.
    1. Schlotz W, Yim IS, Zoccola PM, Jansen L, Schulz P. The perceived stress reactivity scale: Measurement invariance, stability, and validity in three countries. Psychol Assess. 2011;23(1):80. doi: 10.1037/a0021148.
    1. Aish AM, Wasserman D, Renberg ES. Does Beck’s Hopelessness Scale really measure several components? Psychol Med. 2001;31(2):367–372. doi: 10.1017/S0033291701003300.
    1. Treynor W, Gonzalez R, Nolen-Hoeksema S. Rumination reconsidered: a psychometric analysis. Cognit Ther Res. 2003;27(3):247–259. doi: 10.1023/A:1023910315561.
    1. Akiskal HS, Mendlowicz MV, Jean-Louis G, Rapaport MH, Kelsoe JR, Gillin JC, et al. TEMPS-A: validation of a short version of a self-rated instrument designed to measure variations in temperament. J Affect Disord. 2005;85(1-2):45–52. doi: 10.1016/j.jad.2003.10.012.
    1. Nakato Y, Inoue T, Nakagawa S, Kitaichi Y, Kameyama R, Wakatsuki Y, et al. Confirmation of the factorial structure of the Japanese short version of the TEMPS-A in psychiatric patients and general adults. Neuropsychiatr Dis Treat. 2016;12:2173–2179. doi: 10.2147/NDT.S97796.
    1. Fossati A, Somma A, Borroni S, Markon KE, Krueger RF. The personality inventory for DSM-5 brief form: evidence for reliability and construct validity in a sample of community-dwelling Italian adolescents. Assessment. 2017;24(5):615–631. doi: 10.1177/1073191115621793.
    1. Aluja A, Jm R, García LF, Angleitner A, Kuhlman M, Zuckerman M. A cross-cultural shortened form of the ZKPQ (ZKPQ-50-cc) adapted to English, French, German, and Spanish languages. Pers Individ Dif. 2006;41(4):619–628. doi: 10.1016/j.paid.2006.03.001.
    1. Zuckerman M, Kuhlman DM, Joireman J, Teta P, Kraft M. A comparison of three structural models for personality: the big three, the big five, and the alternative five. J Pers Soc Psychol. 1993;65(4):757. doi: 10.1037/0022-3514.65.4.757.
    1. John OP, Naumann LP, Soto CJ. Paradigm shift to the integrative big five trait taxonomy. Personal Disord. 2008;3(2):114–158.
    1. Costa PT, McCrae RR. Professional manual: revised NEO personality inventory (NEO-PI-R) and NEO five-factor inventory (NEO-FFI) Odessa: Psychol Assess; 1992. p. 61.
    1. Cyders MA, Littlefield AK, Coffey S, Karyadi KA. Examination of a short English version of the UPPS-P Impulsive Behavior Scale. Addict Behav. 2014;39(9):1372–1376. doi: 10.1016/j.addbeh.2014.02.013.
    1. Mullins-Sweatt SN, Jamerson JE, Samuel DB, Olson DR, Widiger TA. Psychometric properties of an abbreviated instrument of the five-factor model. Assessment. 2006;13(2):119–137. doi: 10.1177/1073191106286748.
    1. Nock MK, Wedig MM, Holmberg EB, Hooley JM. The emotion reactivity scale: development, evaluation, and relation to self-injurious thoughts and behaviors. Behav Ther. 2008;39(2):107–116. doi: 10.1016/j.beth.2007.05.005.
    1. Gosling SD, Rentfrow PJ, Swann WB., Jr A very brief measure of the Big-Five personality domains. J Res Pers. 2003;37(6):504–528. doi: 10.1016/S0092-6566(03)00046-1.
    1. Sato T. The Eysenck Personality Questionnaire Brief Version: factor structure and reliability. J Psychol. 2005;139(6):545–552. doi: 10.3200/JRLP.139.6.545-552.
    1. Pearlin LI, Schooler C. The structure of coping. J Health Soc Behav. 1978;19(1):2–21.
    1. Tambs K, Røysamb E. Selection of questions to short-form versions of original psychometric instruments in MoBa. Nor Epidemiol. 2014;24(1-2):195–201.
    1. Dreer LE, Berry J, Rivera P, Snow M, Elliott TR, Miller D, et al. Efficient assessment of social problem-solving abilities in medical and rehabilitation settings: a Rasch analysis of the Social Problem-Solving Inventory-Revised. J Clin Psychol. 2009;65(7):653–669. doi: 10.1002/jclp.20573.
    1. Langbehn DR, Pfohl BM, Reynolds S, Clark LA, Battaglia M, Bellodi L, et al. The Iowa Personality Disorder Screen: development and preliminary validation of a brief screening interview. J Personal Disord. 1999;13(1):75–89. doi: 10.1521/pedi.1999.13.1.75.
    1. Safran DG, Kosinski M, Tarlov AR, Rogers WH, Taira DH, Lieberman N, et al. The Primary Care Assessment Survey: tests of data quality and measurement performance. Med Care. 1998;36(5):728–739. doi: 10.1097/00005650-199805000-00012.
    1. Chew LD, Bradley KA, Boyko EJ. Brief questions to identify patients with inadequate health literacy. Fam Med. 2004;36(8):588–594.
    1. Norman CD, Skinner HA. eHEALS: The eHealth Literacy Scale. J Med Internet Res. 2006;8(4):e27. doi: 10.2196/jmir.8.4.e27.
    1. McHorney CA, Spain CV, Alexander CM, Simmons J. Validity of the adherence estimator in the prediction of 9-month persistence with medications prescribed for chronic diseases: a prospective analysis of data from pharmacy claims. Clin Ther. 2009;31(11):2584–2607. doi: 10.1016/j.clinthera.2009.11.030.
    1. Unni EJ, Olson JL, Farris KB. Revision and validation of Medication Adherence Reasons Scale (MAR-Scale) Curr Med Res Opin. 2014;30(2):211–221. doi: 10.1185/03007995.2013.851075.
    1. Vik SA, Maxwell CJ, Hogan DB. Measurement, correlates, and health outcomes of medication adherence among seniors. Ann Pharmacother. 2004;38(2):303–312. doi: 10.1345/aph.1D252.
    1. Hatcher RL, Gillaspy JA. Development and validation of a revised short version of the Working Alliance Inventory. Psychother Res. 2006;16(1):12–25. doi: 10.1080/10503300500352500.
    1. Baumann M, Baumann C, Le Bihan E, Chau N. How patients perceive the therapeutic communications skills of their general practitioners, and how that perception affects adherence: use of the TCom-skill GP scale in a specific geographical area. BMC Health Serv Res. 2008;8(1):244. doi: 10.1186/1472-6963-8-244.
    1. Bieber C, Müller KG, Nicolai J, Hartmann M, Eich W. How does your doctor talk with you? Preliminary validation of a brief patient self-report questionnaire on the quality of physician-patient interaction. J Clin Psychol Med Settings. 2010;17(2):125–136. doi: 10.1007/s10880-010-9189-0.
    1. Steidtmann D, Manber R, Arnow BA, Klein DN, Markowitz JC, Rothbaum BO, et al. Patient treatment preference as a predictor of response and attrition in treatment for chronic depression. Depress Anxiety. 2012;29(10):896–905. doi: 10.1002/da.21977.
    1. Milosevic I, Levy HC, Alcolado GM, Radomsky AS. The treatment acceptability/adherence scale: moving beyond the assessment of treatment effectiveness. Cogn Behav Ther. 2015;44(6):456–469. doi: 10.1080/16506073.2015.1053407.
    1. Wisniewski SR, Rush AJ, Balasubramani G, Trivedi MH, Nierenberg AA, Investigators SD. Self-rated global measure of the frequency, intensity, and burden of side effects. J Psychiatr Pract. 2006;12(2):71–79. doi: 10.1097/00131746-200603000-00002.
    1. Curry J, Rohde P, Simons A, Silva S, Vitiello B, Kratochvil C, et al. Predictors and moderators of acute outcome in the Treatment for Adolescents with Depression Study (TADS) J Am Acad Child Adolesc Psychiatry. 2006;45(12):1427–1439. doi: 10.1097/01.chi.0000240838.78984.e2.
    1. Saffer BY, Lanting SC, Koehle MS, Klonsky ED, Iverson GL. Assessing cognitive impairment using PROMIS(®) applied cognition-abilities scales in a medical outpatient sample. Psychiatry Res. 2015;226(1):169–172. doi: 10.1016/j.psychres.2014.12.043.
    1. Byerly MJ, Nakonezny PA, Rush AJ. The Brief Adherence Rating Scale (BARS) validated against electronic monitoring in assessing the antipsychotic medication adherence of outpatients with schizophrenia and schizoaffective disorder. Schizophr Res. 2008;100(1-3):60–69. doi: 10.1016/j.schres.2007.12.470.
    1. Nease DE, Jr, Aikens JE, Klinkman MS, Kroenke K, Sen A. Toward a more comprehensive assessment of depression remission: the Remission Evaluation and Mood Inventory Tool (REMIT) Gen Hosp Psychiatry. 2011;33(3):279–286. doi: 10.1016/j.genhosppsych.2011.03.002.
    1. Bushey MA, Kroenke K, Baye F, Lourens S. Assessing depression improvement with the remission evaluation and mood inventory tool (REMIT) Gen Hosp Psychiatry. 2019;60:44–49. doi: 10.1016/j.genhosppsych.2019.07.007.
    1. Son E, Halbert A, Abreu S, Hester R, Jefferson G, Jennings K, et al. Role of Google Glass in improving patient satisfaction for otolaryngology residents: a pilot study. Clin Otolaryngol. 2017;42(2):433–438. doi: 10.1111/coa.12810.
    1. Faraway JJ. Extending the linear model with R: generalized linear, mixed effects and nonparametric regression models. 2. Boca Raton: CRC Press, Taylor & Francis Group; 2016.
    1. Jiménez FJR. Acceptance and commitment therapy versus traditional cognitive behavioral therapy: a systematic review and meta-analysis of current empirical evidence. Rev Int Psicol Ter Psicol. 2012;12(3):333–358.
    1. van der Laan MJ, Polley EC, Hubbard AE. Super learner. Stat Appl Genet Mol Biol. 2007;6:Article25.
    1. Luedtke AR, van der Laan MJ. Super-learning of an optimal dynamic treatment rule. Int J Biostat. 2016;12(1):305–332. doi: 10.1515/ijb-2015-0052.
    1. Murphy SA. Optimal dynamic treatment regimes. J R Stat Soc Series B Stat Methodol. 2003;65(2):331–355. doi: 10.1111/1467-9868.00389.
    1. Robins JM, editor. Optimal structural nested models for optimal sequential decisions. Proceedings of the second seattle Symposium in Biostatistics: Springer; 2004.
    1. Van Der Laan MJ, Rubin D. Targeted maximum likelihood learning. Int J Biostat. 2006;2(1):19.
    1. Gupta SK. Intention-to-treat concept: a review. Perspect Clin Res. 2011;2(3):109–112. doi: 10.4103/2229-3485.83221.
    1. Robins JM, Rotnitzky A, Zhao LP. Estimation of regression coefficients when some regressors are not always observed. J Am Stat Assoc. 1994;89(427):846–866. doi: 10.1080/01621459.1994.10476818.
    1. Schnitzer ME, Lok JJ, Gruber S. Variable selection for confounder control, flexible modeling and collaborative targeted minimum loss-based estimation in causal inference. Int J Biostat. 2016;12(1):97–115. doi: 10.1515/ijb-2015-0017.
    1. Robins JM, Rotnitzky A. AIDS epidemiology. New York, NY: Springer; 1992. Recovery of information and adjustment for dependent censoring using surrogate markers; pp. 297–331.
    1. Bunouf P, Molenberghs G. Implementation of pattern-mixture models in randomized clinical trials. Pharm Stat. 2016;15(6):494–506. doi: 10.1002/pst.1780.
    1. Stroup WW. Generalized linear mixed models: modern concepts, methods and applications. New York, NY: CRC press; 2012.
    1. Daniels MJ, Jackson D, Feng W, White IR. Pattern mixture models for the analysis of repeated attempt designs. Biometrics. 2015;71(4):1160–1167. doi: 10.1111/biom.12353.
    1. West Virginia State Organization. Depression and Bipolar Support Alliance. . Accessed 30 Oct 2020.
    1. West Virgnia Clinical and Translational Science Institute. West Virginia practice-based research network. . Accessed 30 Oct 2020.
    1. Olfson M, Blanco C, Marcus SC. Treatment of adult depression in the United States. JAMA Intern Med. 2016;176(20):1482–1491. doi: 10.1001/jamainternmed.2016.5057.
    1. Czeisler MÉ, Lane RI, Petrosky E, Wiley JF, Christensen A, Njai R, et al. Mental health, substance use, and suicidal ideation during the COVID-19 pandemic—United States, June 24–30, 2020. MMWR Morb Mortal Wkly Rep. 2020;69(32):1049. doi: 10.15585/mmwr.mm6932a1.
    1. Twenge JM, Joiner TE. US Census Bureau-assessed prevalence of anxiety and depressive symptoms in 2019 and during the 2020 COVID-19 pandemic. Depress Anxiety. 2020;37:954-6.

Source: PubMed

スポンサーと協力者

医学的状態

薬物療法

3
購読する