StudiCare procrastination - Randomized controlled non-inferiority trial of a persuasive design-optimized internet- and mobile-based intervention with digital coach targeting procrastination in college students.
Digital guidance
Internet- and mobile-based cognitive behavioral therapy
Persuasive System Design
Procrastination
Journal
BMC psychology
ISSN: 2050-7283
Titre abrégé: BMC Psychol
Pays: England
ID NLM: 101627676
Informations de publication
Date de publication:
12 Sep 2023
12 Sep 2023
Historique:
received:
28
02
2023
accepted:
05
09
2023
medline:
14
9
2023
pubmed:
13
9
2023
entrez:
12
9
2023
Statut:
epublish
Résumé
Academic procrastination is widespread among college students. Procrastination is strongly negatively correlated with psychological well-being, thus early interventions are needed. Internet- and mobile-based cognitive behavioral therapy (iCBT) could provide a low-threshold treatment option. Human guidance seems to be a decisive mechanism of change in iCBT. Persuasive design optimization of iCBT and guidance by a digital coach might represent a resource-saving alternative. The study evaluated the non-inferiority of a digital coach in comparison to human guidance with regard to the primary outcome procrastination. The iCBT StudiCare procrastination was optimized by principles of the Persuasive System Design (PSD). A total of 233 college students were randomly assigned to either StudiCare procrastination guided by a digital coach (intervention group, IG) or by a human eCoach (control group, CG). All participants were assessed at baseline, 4-, 8- and 12-weeks post-randomization. Symptom change and between-group differences were assessed with latent growth curve models and supported by effect size levels. The non-inferiority margin was set at Cohen's d = - 0.3. The primary outcome procrastination measured by the Irrational Procrastination scale (IPS) significantly decreased across groups (γ = - 0.79, p < .001, Cohen's d = -0.43 to -0.89) from baseline to 12-weeks post-randomization. There were no significant differences between groups (γ = -0.03, p = .84, Cohen's d = -0.03 to 0.08). Regarding symptoms of depression, no significant time x group effect was found (γ = 0.26, p = .09; Cohen's d = -0.15 to 0.21). There was also no significant time x group effect on the improvement of symptoms of anxiety (γ = 0.25, p = .09). However, Cohen's ds were above the non-inferiority margin 8-weeks (Cohen's d = 0.51) and 12-weeks post-randomization (Cohen's d = 0.37), preferring the CG. Of the IG, 34% and of the CG, 36% completed 80% of the modules. The PSD optimized version of StudiCare procrastination is effective in reducing procrastination. The digital coach was not inferior to human guidance. Guidance by a digital coach in iCBT against procrastination for college students could be a resource-saving alternative to human guidance. The trial was registered at the WHO International Clinical Trials Registry Platform via the German Clinical Trial Register (ID: DRKS00025209, 30/04/2021).
Sections du résumé
BACKGROUND
BACKGROUND
Academic procrastination is widespread among college students. Procrastination is strongly negatively correlated with psychological well-being, thus early interventions are needed. Internet- and mobile-based cognitive behavioral therapy (iCBT) could provide a low-threshold treatment option. Human guidance seems to be a decisive mechanism of change in iCBT. Persuasive design optimization of iCBT and guidance by a digital coach might represent a resource-saving alternative. The study evaluated the non-inferiority of a digital coach in comparison to human guidance with regard to the primary outcome procrastination.
METHODS
METHODS
The iCBT StudiCare procrastination was optimized by principles of the Persuasive System Design (PSD). A total of 233 college students were randomly assigned to either StudiCare procrastination guided by a digital coach (intervention group, IG) or by a human eCoach (control group, CG). All participants were assessed at baseline, 4-, 8- and 12-weeks post-randomization. Symptom change and between-group differences were assessed with latent growth curve models and supported by effect size levels. The non-inferiority margin was set at Cohen's d = - 0.3.
RESULTS
RESULTS
The primary outcome procrastination measured by the Irrational Procrastination scale (IPS) significantly decreased across groups (γ = - 0.79, p < .001, Cohen's d = -0.43 to -0.89) from baseline to 12-weeks post-randomization. There were no significant differences between groups (γ = -0.03, p = .84, Cohen's d = -0.03 to 0.08). Regarding symptoms of depression, no significant time x group effect was found (γ = 0.26, p = .09; Cohen's d = -0.15 to 0.21). There was also no significant time x group effect on the improvement of symptoms of anxiety (γ = 0.25, p = .09). However, Cohen's ds were above the non-inferiority margin 8-weeks (Cohen's d = 0.51) and 12-weeks post-randomization (Cohen's d = 0.37), preferring the CG. Of the IG, 34% and of the CG, 36% completed 80% of the modules.
CONCLUSIONS
CONCLUSIONS
The PSD optimized version of StudiCare procrastination is effective in reducing procrastination. The digital coach was not inferior to human guidance. Guidance by a digital coach in iCBT against procrastination for college students could be a resource-saving alternative to human guidance.
TRIAL REGISTRATION
BACKGROUND
The trial was registered at the WHO International Clinical Trials Registry Platform via the German Clinical Trial Register (ID: DRKS00025209, 30/04/2021).
Identifiants
pubmed: 37700387
doi: 10.1186/s40359-023-01312-1
pii: 10.1186/s40359-023-01312-1
pmc: PMC10496391
doi:
Types de publication
Randomized Controlled Trial
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
273Informations de copyright
© 2023. BioMed Central Ltd., part of Springer Nature.
Références
Klingsieck KB, Procrastination. Eur Psychol. 2013;18:24–34. https://doi.org/10.1027/1016-9040/a000138 .
doi: 10.1027/1016-9040/a000138
Harriott J, Ferrari JR. Prevalence of procrastination among samples of adults. Psychol Rep. 1996;78:611–6. https://doi.org/10.2466/pr0.1996.78.2.611 .
doi: 10.2466/pr0.1996.78.2.611
Ferrari JR, Ozer BU, Demir A. Chronic procrastination among turkish adults: exploring decisional, avoidant, and arousal styles. J Soc Psychol. 2009;149:402–8. https://doi.org/10.3200/SOCP.149.3.402-408 .
doi: 10.3200/SOCP.149.3.402-408
pubmed: 19537606
Mahasneh AM, Bataineh OT, Al-Zoubi ZH. The relationship between academic procrastination and parenting styles among jordanian undergraduate University students. TOPSYJ. 2016;9:25–34. https://doi.org/10.2174/1874350101609010025 .
doi: 10.2174/1874350101609010025
Ozer BU, Demir A, Ferrari JR. Exploring academic procrastination among turkish students: possible gender differences in prevalence and reasons. J Soc Psychol. 2009;149:241–57. https://doi.org/10.3200/SOCP.149.2.241-257 .
doi: 10.3200/SOCP.149.2.241-257
pubmed: 19425360
Schouwenburg HC. Procrastination in academic settings: general introduction. In: Schouwenburg HC, Lay CH, Pychyl TA, Ferrari JR, editors. Counseling the procrastinator in academic settings. 1st ed. Washington, DC: American Psychological Association; 2004. pp. 3–17. https://doi.org/10.1037/10808-001 .
doi: 10.1037/10808-001
Ferrari JR. Procrastination as self-regulation failure of performance: effects of cognitive load, self‐awareness, and time limits on ‘working best under pressure’. Eur J Pers. 2001;15:391–406. https://doi.org/10.1002/per.413 .
doi: 10.1002/per.413
Yan B, Zhang X. What research has been conducted on Procrastination? Evidence from a systematical bibliometric analysis. Front Psychol. 2022;13:809044. https://doi.org/10.3389/fpsyg.2022.809044 .
doi: 10.3389/fpsyg.2022.809044
pubmed: 35185729
pmcid: 8847795
Dietz F, Hofer M, Fries S. Individual values, learning routines and academic procrastination. Br J Educ Psychol. 2007;77:893–906. https://doi.org/10.1348/000709906X169076 .
doi: 10.1348/000709906X169076
pubmed: 17971288
Hen M, Goroshit M. General and Life-Domain Procrastination in highly educated adults in Israel. Front Psychol. 2018;9:1173. https://doi.org/10.3389/fpsyg.2018.01173 .
doi: 10.3389/fpsyg.2018.01173
pubmed: 30022965
pmcid: 6039828
Wypych M, Matuszewski J, Dragan W. Roles of Impulsivity, Motivation, and emotion regulation in procrastination - path analysis and comparison between students and non-students. Front Psychol. 2018;9:891. https://doi.org/10.3389/fpsyg.2018.00891 .
doi: 10.3389/fpsyg.2018.00891
pubmed: 29922205
pmcid: 5996249
Harris NN, Sutton RI. Task procrastination in organizations: a framework for research. Hum Relat. 1983;36:987–95. https://doi.org/10.1177/001872678303601102 .
doi: 10.1177/001872678303601102
Tice D, Baumeister RF. Longitudinal study of procrastination, performance, stress, and Health: the costs and benefits of Dawdling. Psychol Sci. 1997;8:454–8. https://doi.org/10.1111/j.1467-9280.1997.tb00460.x .
doi: 10.1111/j.1467-9280.1997.tb00460.x
Constantin K, English MM, Mazmanian D. Anxiety, Depression, and Procrastination among students: rumination plays a larger mediating role than worry. J Rat-Emo Cognitive-Behav Ther. 2017. https://doi.org/10.1007/s10942-017-0271-5 .
doi: 10.1007/s10942-017-0271-5
Steel P, Brothen T, Wambach C. Procrastination and personality, performance, and mood. Pers Indiv Differ. 2001;30:95–106. https://doi.org/10.1016/S0191-8869(00)00013-1 .
doi: 10.1016/S0191-8869(00)00013-1
Sirois FM, Tosti N. Lost in the moment? An investigation of Procrastination, Mindfulness, and well-being. J Rat-Emo Cognitive-Behav Ther. 2012;30:237–48. https://doi.org/10.1007/s10942-012-0151-y .
doi: 10.1007/s10942-012-0151-y
van Eerde W, Klingsieck KB. Overcoming procrastination? A meta-analysis of intervention studies. Educational Res Rev. 2018;25:73–85. https://doi.org/10.1016/j.edurev.2018.09.002 .
doi: 10.1016/j.edurev.2018.09.002
Andersson G, Titov N, Dear BF, Rozental A, Carlbring P. Internet-delivered psychological treatments: from innovation to implementation. World Psychiatry. 2019;18:20–8. https://doi.org/10.1002/wps.20610 .
doi: 10.1002/wps.20610
pubmed: 30600624
pmcid: 6313242
Rozental A, Forsell E, Svensson A, Andersson G, Carlbring P. Internet-based cognitive-behavior therapy for procrastination: a randomized controlled trial. J Consult Clin Psychol. 2015;83:808–24. https://doi.org/10.1037/ccp0000023 .
doi: 10.1037/ccp0000023
pubmed: 25939016
Eckert M, Ebert DD, Lehr D, Sieland B, Berking M. Does SMS-Support make a difference? Effectiveness of a two-week online-training to overcome procrastination. A Randomized Controlled Trial. Front Psychol. 2018;9:1103. https://doi.org/10.3389/fpsyg.2018.01103 .
doi: 10.3389/fpsyg.2018.01103
pubmed: 30026713
pmcid: 6042057
Lukas CA, Berking M. Reducing procrastination using a smartphone-based treatment program: a randomized controlled pilot study. Internet Interventions. 2018;12:83–90. https://doi.org/10.1016/j.invent.2017.07.002 .
doi: 10.1016/j.invent.2017.07.002
pubmed: 30135772
Küchler A-M, Albus P, Ebert DD, Baumeister H. Effectiveness of an internet-based intervention for procrastination in college students (StudiCare Procrastination): study protocol of a randomized controlled trial. Internet Interventions. 2019;17:100245. https://doi.org/10.1016/j.invent.2019.100245 .
doi: 10.1016/j.invent.2019.100245
pubmed: 31080750
pmcid: 6500923
Küchler AM, Albus P, Ebert DD, Baumeister H. Studicare Procrastination Effectiveness and feasibility of an internet-based intervention for college students - preliminary results presented at the european Congress of psychology; July 3, 2019.
Baumeister H, Reichler L, Munzinger M, Lin J. The impact of guidance on internet-based mental health interventions — a systematic review. Internet Interventions. 2014;1:205–15. https://doi.org/10.1016/j.invent.2014.08.003 .
doi: 10.1016/j.invent.2014.08.003
Mohr DC, Cuijpers P, Lehman K. Supportive accountability: a model for providing human support to enhance adherence to eHealth interventions. J Med Internet Res. 2011;13:e30. https://doi.org/10.2196/jmir.1602 .
doi: 10.2196/jmir.1602
pubmed: 21393123
pmcid: 3221353
Furukawa TA, Suganuma A, Ostinelli EG, Andersson G, Beevers CG, Shumake J, et al. Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual participant data. The Lancet Psychiatry. 2021;8:500–11. https://doi.org/10.1016/S2215-0366(21)00077-8 .
doi: 10.1016/S2215-0366(21)00077-8
pubmed: 33957075
pmcid: 8838916
Oinas-Kukkonen H, Harjumaa M. Persuasive Systems Design: key issues, process model, and System features. CAIS. 2009. https://doi.org/10.17705/1CAIS.02428 .
doi: 10.17705/1CAIS.02428
Kelders SM, Kok RN, Ossebaard HC, van Gemert-Pijnen JEWC. Persuasive system design does matter: a systematic review of adherence to web-based interventions. J Med Internet Res. 2012;14:e152. https://doi.org/10.2196/jmir.2104 .
doi: 10.2196/jmir.2104
pubmed: 23151820
pmcid: 3510730
Orji R, Moffatt K. Persuasive technology for health and wellness: state-of-the-art and emerging trends. Health Inf J. 2018;24:66–91. https://doi.org/10.1177/1460458216650979 .
doi: 10.1177/1460458216650979
Titov N, Andrews G, Choi I, Schwencke G, Johnston L. Randomized Controlled Trial of web-based treatment of Social Phobia without Clinician Guidance. Aust N Z J Psychiatry. 2009;43:913–9. https://doi.org/10.1080/00048670903179160 .
doi: 10.1080/00048670903179160
Heim E, Rötger A, Lorenz N, Maercker A. Working alliance with an avatar: how far can we go with internet interventions? Internet Interventions. 2018;11:41–6. https://doi.org/10.1016/j.invent.2018.01.005 .
doi: 10.1016/j.invent.2018.01.005
pubmed: 30135758
pmcid: 6084819
Provoost S, Lau HM, Ruwaard J, Riper H. Embodied conversational agents in clinical psychology: a scoping review. J Med Internet Res. 2017;19:e151. https://doi.org/10.2196/jmir.6553 .
doi: 10.2196/jmir.6553
pubmed: 28487267
pmcid: 5442350
Kelders SM, Bohlmeijer ET, Pots WTM, van Gemert-Pijnen JEWC. Comparing human and automated support for depression: fractional factorial randomized controlled trial. Behav Res Ther. 2015;72:72–80. https://doi.org/10.1016/j.brat.2015.06.014 .
doi: 10.1016/j.brat.2015.06.014
pubmed: 26196078
Piaggio G, Elbourne DR, Pocock SJ, Evans SJW, Altman DG. Reporting of noninferiority and equivalence randomized trials: extension of the CONSORT 2010 statement. JAMA. 2012;308:2594–604. https://doi.org/10.1001/jama.2012.87802 .
doi: 10.1001/jama.2012.87802
pubmed: 23268518
Schulz KF, Altman DG, Moher D. CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. BMJ. 2010;340:c332. https://doi.org/10.1136/bmj.c332 .
doi: 10.1136/bmj.c332
pubmed: 20332509
pmcid: 2844940
Svartdal F, Pfuhl G, Nordby K, Foschi G, Klingsieck KB, Rozental A, et al. On the measurement of procrastination: comparing two Scales in six european countries. Front Psychol. 2016;7:1307. https://doi.org/10.3389/fpsyg.2016.01307 .
doi: 10.3389/fpsyg.2016.01307
pubmed: 27630595
pmcid: 5005418
D’Agostino RB, Massaro JM, Sullivan LM. Non-inferiority trials: design concepts and issues - the encounters of academic consultants in statistics. Stat Med. 2003;22:169–86. https://doi.org/10.1002/sim.1425 .
doi: 10.1002/sim.1425
pubmed: 12520555
Rozental A, Forsström D, Lindner P, Nilsson S, Mårtensson L, Rizzo A, et al. Treating procrastination using cognitive behavior therapy: a pragmatic randomized controlled trial comparing treatment delivered via the internet or in groups. Behav Ther. 2018;49:180–97. https://doi.org/10.1016/j.beth.2017.08.002 .
doi: 10.1016/j.beth.2017.08.002
pubmed: 29530258
Gladstone BP, Vach W. Choice of non-inferiority (NI) margins does not protect against degradation of treatment effects on an average–an observational study of registered and published NI trials. PLoS ONE. 2014;9:e103616. https://doi.org/10.1371/journal.pone.0103616 .
doi: 10.1371/journal.pone.0103616
pubmed: 25080093
pmcid: 4117500
Funder DC, Ozer DJ, Corrigendum. Evaluating effect size in Psychological Research: sense and nonsense. Adv Methods Practices Psychol Sci. 2020;3:509. https://doi.org/10.1177/2515245920979282 .
doi: 10.1177/2515245920979282
Schäfer T, Schwarz MA. The meaningfulness of Effect Sizes in Psychological Research: differences between sub-disciplines and the impact of potential biases. Front Psychol. 2019;10:813. https://doi.org/10.3389/fpsyg.2019.00813 .
doi: 10.3389/fpsyg.2019.00813
pubmed: 31031679
pmcid: 6470248
Höcker A, Engberding M, Rist F. Prokrastination Ein Manual zur Behandlung des pathologischen Aufschiebens. Göttingen: Hogrefe; 2013.
Haycock LA, McCarthy P, Skay CL. Procrastination in College students: the role of self-efficacy and anxiety. J Couns Dev. 1998;76:317–24. https://doi.org/10.1002/j.1556-6676.1998.tb02548.x .
doi: 10.1002/j.1556-6676.1998.tb02548.x
Kocovski NL, Endler NS. Self-Regulation: social anxiety and depression. J Appl Biobehav Res. 2000;5:80–91. https://doi.org/10.1111/j.1751-9861.2000.tb00065.x .
doi: 10.1111/j.1751-9861.2000.tb00065.x
Gallego J, Aguilar-Parra JM, Cangas AJ, Langer ÁI, Mañas I. Effect of a mindfulness program on stress, anxiety and depression in university students. Span J Psychol. 2015;17:E109. https://doi.org/10.1017/sjp.2014.102 .
doi: 10.1017/sjp.2014.102
pubmed: 26055051
Breedvelt JJF, Amanvermez Y, Harrer M, Karyotaki E, Gilbody S, Bockting CLH, et al. The Effects of Meditation, yoga, and mindfulness on Depression, anxiety, and stress in Tertiary Education students: a Meta-analysis. Front Psychiatry. 2019;10:193. https://doi.org/10.3389/fpsyt.2019.00193 .
doi: 10.3389/fpsyt.2019.00193
pubmed: 31068842
pmcid: 6491852
Idrees AR, Kraft R, Pryss R, Reichert M, Nguyen T, Stenzel L, Baumeister H. Backend Concept of the eSano eHealth Platform for Internet-and Mobile-based Interventions. 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob). 2022:88–93. IEEE.
Steel P. Arousal, avoidant and decisional procrastinators: do they exist? Personality and individual differences. 2010;48:926–34. https://doi.org/10.1016/j.paid.2010.02.025 .
Kroenke K, Strine TW, Spitzer RL, Williams JBW, Berry JT, Mokdad AH. The PHQ-8 as a measure of current depression in the general population. J Affect Disord. 2009;114:163–73. https://doi.org/10.1016/j.jad.2008.06.026 .
doi: 10.1016/j.jad.2008.06.026
pubmed: 18752852
Spitzer RL, Kroenke K, Williams JBW, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166:1092–7. https://doi.org/10.1001/archinte.166.10.1092 .
doi: 10.1001/archinte.166.10.1092
pubmed: 16717171
Cohen S, Williamson G. Perceived stress in a probability sample of the United States. In: S. Spacapan & S. Oskamp, editor. The social psychology of health. 1988. pp. 31–68.
Jerusalem M, Schwarzer R. SWE - Skala zur Allgemeinen Selbstwirksamkeitserwartung. ZPID (Leibniz Institute for Psychology) – Open Test Archive; 2003.
Schulz U, Schwarzer R. Soziale Unterstützung bei der Krankheitsbewältigung: die Berliner Social Support Skalen (BSSS). Diagnostica. 2003;49:73–82. https://doi.org/10.1026//0012-1924.49.2.73 .
doi: 10.1026//0012-1924.49.2.73
Christensen H, Griffiths KM, Farrer L. Adherence in internet interventions for anxiety and depression. J Med Internet Res. 2009;11:e13. https://doi.org/10.2196/jmir.1194 .
doi: 10.2196/jmir.1194
pubmed: 19403466
pmcid: 2762797
Gómez Penedo JM, Babl AM, Grosse Holtforth M, Hohagen F, Krieger T, Lutz W, et al. The Association of Therapeutic Alliance with Long-Term Outcome in a guided internet intervention for Depression: secondary analysis from a Randomized Control Trial. J Med Internet Res. 2020;22:e15824. https://doi.org/10.2196/15824 .
doi: 10.2196/15824
pubmed: 32207689
pmcid: 7139432
Kaiser J, Hanschmidt F, Kersting A. The association between therapeutic alliance and outcome in internet-based psychological interventions: a meta-analysis. Comput Hum Behav. 2021;114:106512. https://doi.org/10.1016/j.chb.2020.106512 .
doi: 10.1016/j.chb.2020.106512
Gómez Penedo JM, Berger T, Grosse Holtforth M, Krieger T, Schröder J, Hohagen F, et al. The Working Alliance Inventory for guided internet interventions (WAI-I). J Clin Psychol. 2020;76:973–86. https://doi.org/10.1002/jclp.22823 .
doi: 10.1002/jclp.22823
pubmed: 31240727
Rozental A, Kottorp A, Forsström D, Månsson K, Boettcher J, Andersson G, et al. The negative Effects Questionnaire: psychometric properties of an instrument for assessing negative effects in psychological treatments. Behav Cogn Psychother. 2019;47:559–72. https://doi.org/10.1017/S1352465819000018 .
doi: 10.1017/S1352465819000018
pubmed: 30871650
Schrepp M, Hinderks A, Thomaschewski J. Design and evaluation of a short version of the user experience questionnaire (UEQ-S). IJIMAI. 2017;4:103. https://doi.org/10.9781/ijimai.2017.09.001 .
doi: 10.9781/ijimai.2017.09.001
R Core Team. R: A language and environment for statistical computing. 2021. https://www.R-project.org/ .
McNeish D. Thanks coefficient alpha, we’ll take it from here. Psychol Methods. 2018;23:412–33. https://doi.org/10.1037/met0000144 .
doi: 10.1037/met0000144
pubmed: 28557467
Lee T, Shi D. A comparison of full information maximum likelihood and multiple imputation in structural equation modeling with missing data. Psychol Methods. 2021;26:466–85. https://doi.org/10.1037/met0000381 .
doi: 10.1037/met0000381
pubmed: 33507765
Lei P-W, Wu Q. Estimation in structural equation modeling. In: Hoyle RH, editor. Handbook of structural equation modeling. The Guilford Press; 2012. pp. 164–80.
McArdle JJ. Latent variable modeling of differences and changes with longitudinal data. Annu Rev Psychol. 2009;60:577–605. https://doi.org/10.1146/annurev.psych.60.110707.163612 .
doi: 10.1146/annurev.psych.60.110707.163612
pubmed: 18817479
Putnick DL, Bornstein MH. Measurement Invariance Conventions and reporting: the state of the art and future directions for Psychological Research. Dev Rev. 2016;41:71–90. https://doi.org/10.1016/j.dr.2016.06.004 .
doi: 10.1016/j.dr.2016.06.004
pubmed: 27942093
pmcid: 5145197
Moshagen M, Erdfelder E. A new strategy for testing structural equation models. Struct Equ Modeling. 2016;23(1):54–60. https://doi.org/10.1080/10705511.2014.950896 .
Browne MW, Cudeck R. Alternative Ways of assessing Model Fit. Sociol Methods Res. 1992:230–58.
Bentler PM. Comparative fit indexes in structural models. Psychol Bull. 1990;107:238–46. https://doi.org/10.1037/0033-2909.107.2.238 .
doi: 10.1037/0033-2909.107.2.238
pubmed: 2320703
Savalei V. On the computation of the RMSEA and CFI from the Mean-And-Variance Corrected Test Statistic with Nonnormal Data in SEM. Multivar Behav Res. 2018;53:419–29. https://doi.org/10.1080/00273171.2018.1455142 .
doi: 10.1080/00273171.2018.1455142
Bentler PM. EQS structural equations program manual. Volume Vol 6. Multivariate software; 1995.
Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equation Modeling: Multidisciplinary J. 1999;6:1–55. https://doi.org/10.1080/10705519909540118 .
doi: 10.1080/10705519909540118
Rosseel Y. lavaan: an R Package for Structural equation modeling. J Stat Softw. 2012;48:1–36. https://doi.org/10.18637/jss.v048.i02 .
doi: 10.18637/jss.v048.i02
van Buuren S, Groothuis-Oudshoorn K. Mice: multivariate imputation by chained equations in R. J Stat Softw. 3;45:1–67. https://doi.org/10.18637/jss.v045.i03 .
Mayring P. Qualitative content analysis. Forum Qualitative Social Research. 2000. https://doi.org/10.1093/acprof:oso/9780190215491.003.0004 .
doi: 10.1093/acprof:oso/9780190215491.003.0004
Dear BF, Staples LG, Terides MD, Karin E, Zou J, Johnston L, et al. Transdiagnostic versus disorder-specific and clinician-guided versus self-guided internet-delivered treatment for generalized anxiety disorder and comorbid disorders: a randomized controlled trial. J Anxiety Disord. 2015;36:63–77. https://doi.org/10.1016/j.janxdis.2015.09.003 .
doi: 10.1016/j.janxdis.2015.09.003
pubmed: 26460536
Moshe I, Terhorst Y, Philippi P, Domhardt M, Cuijpers P, Cristea I, et al. Digital interventions for the treatment of depression: a meta-analytic review. Psychol Bull. 2021;147:749–86. https://doi.org/10.1037/bul0000334 .
doi: 10.1037/bul0000334
pubmed: 34898233
Musiat P, Johnson C, Atkinson M, Wilksch S, Wade T. Impact of guidance on intervention adherence in computerised interventions for mental health problems: a meta-analysis. Psychol Med. 2022;52:229–40. https://doi.org/10.1017/S0033291721004621 .
doi: 10.1017/S0033291721004621
pubmed: 34802474
Schmidt ID, Forand NR, Strunk DR. Predictors of Dropout in Internet-Based cognitive behavioral therapy for Depression. Cognit Ther Res. 2019;43:620–30. https://doi.org/10.1007/s10608-018-9979-5 .
doi: 10.1007/s10608-018-9979-5
pubmed: 32879540
Schulte-Strathaus J, Rauschenberg C, Baumeister H, Reininghaus U. 25. Ecological momentary interventions in public mental health provision. In: C. Montag & H. Baumeister. Digital phenotyping and mobile sensing. 2022. pp. 427–439.
Johansson O, Michel T, Andersson G, Paxling B. Experiences of non-adherence to internet-delivered cognitive behavior therapy: a qualitative study. Internet Interventions. 2015;2:137–42. https://doi.org/10.1016/j.invent.2015.02.006 .
doi: 10.1016/j.invent.2015.02.006
Zalaznik D, Strauss AY, Halaj A, Barzilay S, Fradkin I, Katz BA, et al. Patient alliance with the program predicts treatment outcomes whereas alliance with the therapist predicts adherence in internet-based therapy for panic disorder. Psychother Res. 2021;31:1022–35. https://doi.org/10.1080/10503307.2021.1882712 .
doi: 10.1080/10503307.2021.1882712
pubmed: 33567994
Bendig E, Erb B, Schulze-Thuesing L, Baumeister H. Die nächste generation: Chatbots in der klinischen Psychologie und Psychotherapie zur Förderung mentaler gesundheit – ein scoping-review. Verhaltenstherapie. 2019;29:266–80. https://doi.org/10.1159/000499492 .
doi: 10.1159/000499492
Bendig E, Erb B, Meißner D, Bauereiß N, Baumeister H. Feasibility of a Software agent providing a brief intervention for self-help to uplift psychological wellbeing (SISU). A single-group pretest-posttest trial investigating the potential of SISU to act as therapeutic agent. Internet Interventions. 2021;24:100377. https://doi.org/10.1016/j.invent.2021.100377 .
doi: 10.1016/j.invent.2021.100377
pubmed: 33816127
pmcid: 8005771
Ibrahim ENM, Jamali N, Suhaimi AIH. Exploring gamification design elements for mental health support. IJATEE. 2021;8:114–25. https://doi.org/10.19101/IJATEE.2020.S1762123 .
doi: 10.19101/IJATEE.2020.S1762123
Wozney L, Huguet A, Bennett K, Radomski AD, Hartling L, Dyson M, et al. How do eHealth Programs for adolescents with Depression Work? A Realist Review of Persuasive System Design Components in Internet-Based psychological therapies. J Med Internet Res. 2017;19:e266. https://doi.org/10.2196/jmir.7573 .
doi: 10.2196/jmir.7573
pubmed: 28793983
pmcid: 5569246
Fuhr K, Schröder J, Berger T, Moritz S, Meyer B, Lutz W, et al. The association between adherence and outcome in an internet intervention for depression. J Affect Disord. 2018;229:443–9. https://doi.org/10.1016/j.jad.2017.12.028 .
doi: 10.1016/j.jad.2017.12.028
pubmed: 29331706
Ilardi SS, Craighead WE. The role of nonspecific factors in cognitive-behavior therapy for depression. Clin Psychol Sci Pract. 1994;1:138–56. https://doi.org/10.1111/j.1468-2850.1994.tb00016.x .
doi: 10.1111/j.1468-2850.1994.tb00016.x
Rozental A, Forsell E, Svensson A, Andersson G, Carlbring P. Internet-based cognitive—behavior therapy for procrastination: a randomized controlled trial. J Consult Clin Psychol. 2015;83:808–24. https://doi.org/10.1037/ccp0000023 .
doi: 10.1037/ccp0000023
pubmed: 25939016
Manea L, Gilbody S, McMillan D. Optimal cut-off score for diagnosing depression with the Patient Health Questionnaire (PHQ-9): a meta-analysis. CMAJ. 2012;184:E191–6. https://doi.org/10.1503/cmaj.110829 .
doi: 10.1503/cmaj.110829
pubmed: 22184363
pmcid: 3281183
Plummer F, Manea L, Trepel D, McMillan D. Screening for anxiety disorders with the GAD-7 and GAD-2: a systematic review and diagnostic metaanalysis. Gen Hosp Psychiatry. 2016;39:24–31. https://doi.org/10.1016/j.genhosppsych.2015.11.005 .
doi: 10.1016/j.genhosppsych.2015.11.005
pubmed: 26719105
Beswick G, Rothblum ED, Mann L. Psychological antecedents of student procrastination. Australian Psychol. 1988;23:207–17. https://doi.org/10.1080/00050068808255605 .
doi: 10.1080/00050068808255605
Cuijpers P, Turner EH, Koole SL, van Dijke A, Smit F. What is the threshold for a clinically relevant effect? The case of major depressive disorders. Depress Anxiety. 2014;31:374–8. https://doi.org/10.1002/da.22249 .
doi: 10.1002/da.22249
pubmed: 24677535
Harrer M, Adam SH, Baumeister H, Cuijpers P, Karyotaki E, Auerbach RP, et al. Internet interventions for mental health in university students: a systematic review and meta-analysis. Int J Methods Psychiatr Res. 2019;28:e1759. https://doi.org/10.1002/mpr.1759 .
doi: 10.1002/mpr.1759
pubmed: 30585363
Curran PJ, Obeidat K, Losardo D. Twelve frequently asked questions about growth curve modeling. J Cogn Dev. 2010;11:121–36. https://doi.org/10.1080/15248371003699969 .
doi: 10.1080/15248371003699969
pubmed: 21743795
pmcid: 3131138
Weisel KK, Zarski A-C, Berger T, Krieger T, Moser CT, Schaub MP, et al. User experience and Effects of an individually tailored Transdiagnostic Internet-Based and Mobile-Supported intervention for anxiety Disorders: mixed-methods study. J Med Internet Res. 2020;22:e16450. https://doi.org/10.2196/16450 .
doi: 10.2196/16450
pubmed: 32936085
pmcid: 7527916
Küchler A-M, Kählke F, Vollbrecht D, Peip K, Ebert DD, Baumeister H, Effectiveness. Acceptability, and mechanisms of change of the internet-based intervention StudiCare Mindfulness for College students: a Randomized Controlled Trial. Mindfulness. 2022;13:2140–54. https://doi.org/10.1007/s12671-022-01949-w .
doi: 10.1007/s12671-022-01949-w
Küchler A-M, Schultchen D, Dretzler T, Moshagen M, Ebert DD, Baumeister H. A Three-Armed Randomized Controlled Trial to evaluate the effectiveness, Acceptance, and negative Effects of StudiCare Mindfulness, an internet- and Mobile-Based intervention for College students with no and on demand Guidance. Int J Environ Res Public Health. 2023. https://doi.org/10.3390/ijerph20043208 .
doi: 10.3390/ijerph20043208
pubmed: 36833903
pmcid: 9965996
Kählke F, Berger T, Schulz A, Baumeister H, Berking M, Auerbach RP, et al. Efficacy of an unguided internet-based self-help intervention for social anxiety disorder in university students: a randomized controlled trial. Int J Methods Psychiatr Res. 2019;28:e1766. https://doi.org/10.1002/mpr.1766 .
doi: 10.1002/mpr.1766
pubmed: 30687986
pmcid: 6877166
Rozental A, Forsström D, Tangen JA, Carlbring P. Experiences of undergoing internet-based cognitive behavior therapy for procrastination: a qualitative study. Internet Interventions. 2015;2:314–22. https://doi.org/10.1016/j.invent.2015.05.001 .
doi: 10.1016/j.invent.2015.05.001
Rosenman R, Tennekoon V, Hill LG. Measuring bias in self-reported data. Int J Behav Healthc Res. 2011;2:320–32. https://doi.org/10.1504/IJBHR.2011.043414 .
doi: 10.1504/IJBHR.2011.043414
pubmed: 25383095
pmcid: 4224297