Factors Influencing Community Participation in Internet Interventions Compared With Research Trials: Observational Study in a Nationally Representative Adult Cohort.
engagement
implementation
internet
mental health
research participation
uptake
Journal
Journal of medical Internet research
ISSN: 1438-8871
Titre abrégé: J Med Internet Res
Pays: Canada
ID NLM: 100959882
Informations de publication
Date de publication:
02 02 2023
02 02 2023
Historique:
received:
04
08
2022
accepted:
30
11
2022
revised:
29
11
2022
entrez:
2
2
2023
pubmed:
3
2
2023
medline:
7
2
2023
Statut:
epublish
Résumé
Digital mental health (DMH) programs can be effective in treating and preventing mental health problems. However, community engagement with these programs can be poor. Understanding the barriers and enablers of DMH program use may assist in identifying ways to increase the uptake of these programs, which have the potential to provide broad-scale prevention and treatment in the community. In this study, we aimed to identify and compare factors that may influence participation in DMH programs in practice and research trials, identify any respondent characteristics that are associated with these factors, and assess the relationship between intentions to use DMH programs and actual uptake. Australian adults aged ≥18 years were recruited from market research panels to participate in the study. The sample was representative of the Australian adult population based on age, gender, and location. Participants completed a cross-sectional web-based survey assessing demographic characteristics, mental health symptom measures, attitudes and use of DMH programs in practice and in research studies, and the factors influencing their use in both settings. Across both research and practice, trust in the organization delivering the service or trial was the top-ranked factor influencing participation, followed by anonymity or privacy and adequate information. There was little variation in rankings across demographic groups, including intentions to use DMH programs or mental health status. Intentions to use DMH programs were a strong predictor of both current (odds ratio 2.50, 99% CI 1.41-4.43; P<.001) and past (odds ratio 2.98, 99% CI 1.71-5.19; P<.001) use behaviors. Efforts to increase the uptake of DMH programs or participation in research trials should focus on clearly communicating the following to users: the legitimacy of the organization delivering the program, security and use of participant data, and effectiveness of DMH programs.
Sections du résumé
BACKGROUND
Digital mental health (DMH) programs can be effective in treating and preventing mental health problems. However, community engagement with these programs can be poor. Understanding the barriers and enablers of DMH program use may assist in identifying ways to increase the uptake of these programs, which have the potential to provide broad-scale prevention and treatment in the community.
OBJECTIVE
In this study, we aimed to identify and compare factors that may influence participation in DMH programs in practice and research trials, identify any respondent characteristics that are associated with these factors, and assess the relationship between intentions to use DMH programs and actual uptake.
METHODS
Australian adults aged ≥18 years were recruited from market research panels to participate in the study. The sample was representative of the Australian adult population based on age, gender, and location. Participants completed a cross-sectional web-based survey assessing demographic characteristics, mental health symptom measures, attitudes and use of DMH programs in practice and in research studies, and the factors influencing their use in both settings.
RESULTS
Across both research and practice, trust in the organization delivering the service or trial was the top-ranked factor influencing participation, followed by anonymity or privacy and adequate information. There was little variation in rankings across demographic groups, including intentions to use DMH programs or mental health status. Intentions to use DMH programs were a strong predictor of both current (odds ratio 2.50, 99% CI 1.41-4.43; P<.001) and past (odds ratio 2.98, 99% CI 1.71-5.19; P<.001) use behaviors.
CONCLUSIONS
Efforts to increase the uptake of DMH programs or participation in research trials should focus on clearly communicating the following to users: the legitimacy of the organization delivering the program, security and use of participant data, and effectiveness of DMH programs.
Identifiants
pubmed: 36729613
pii: v25i1e41663
doi: 10.2196/41663
pmc: PMC9936370
doi:
Types de publication
Observational Study
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e41663Informations de copyright
©Philip Batterham, Amelia Gulliver, Matthew Sunderland, Louise Farrer, Frances Kay-Lambkin, Angelica Trias, Alison Calear. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 02.02.2023.
Références
BMC Psychiatry. 2014 Apr 11;14:109
pubmed: 24725765
Aust N Z J Psychiatry. 2015 Sep;49(9):776-84
pubmed: 25907269
JCO Oncol Pract. 2020 Mar;16(3):e280-e289
pubmed: 32048946
JMIR Ment Health. 2015 Mar 31;2(1):e9
pubmed: 26543915
BJPsych Open. 2016 Jan 28;2(1):67-73
pubmed: 27703756
J Med Internet Res. 2018 Nov 09;20(11):e10113
pubmed: 30413400
J Clin Epidemiol. 2016 Mar;71:35-42
pubmed: 26464194
Front Med (Lausanne). 2021 Feb 23;8:608959
pubmed: 33708777
Arch Intern Med. 2006 May 22;166(10):1092-7
pubmed: 16717171
Evid Based Ment Health. 2018 Aug;21(3):116-119
pubmed: 29871870
J Med Internet Res. 2021 Jan 22;23(1):e22698
pubmed: 33480860
J Med Internet Res. 2009 Apr 24;11(2):e13
pubmed: 19403466
JMIR Ment Health. 2017 Jun 30;4(2):e26
pubmed: 28666976
J Med Internet Res. 2022 May 6;24(5):e34769
pubmed: 35522458
JAMA. 1999 Nov 10;282(18):1737-44
pubmed: 10568646
Psychol Med. 2018 Jun;48(8):1316-1324
pubmed: 28967345
Ann Behav Med. 2010 Aug;40(1):89-98
pubmed: 20652466
Clin J Pain. 2015 Jun;31(6):528-35
pubmed: 24866854
J Med Internet Res. 2012 Jun 22;14(3):e91
pubmed: 22743581
J Health Serv Res Policy. 1999 Apr;4(2):112-21
pubmed: 10387403
J Clin Oncol. 2003 Mar 1;21(5):830-5
pubmed: 12610181
Ethn Dis. 2012 Spring;22(2):226-30
pubmed: 22764647
Internet Interv. 2018 Apr 06;12:181-188
pubmed: 30135782
Internet Interv. 2021 May 05;25:100400
pubmed: 34026569
Int J Methods Psychiatr Res. 2014 Jun;23(2):184-91
pubmed: 24615785
JAMA Psychiatry. 2017 Apr 01;74(4):351-359
pubmed: 28241179
Front Psychiatry. 2018 Dec 04;9:654
pubmed: 30564154
AMIA Annu Symp Proc. 2020 Mar 04;2019:487-493
pubmed: 32308842
J Affect Disord. 2013 Apr 25;146(3):383-9
pubmed: 23084184
J Med Internet Res. 2011 Aug 05;13(3):e52
pubmed: 21821503
J Chronic Dis. 1983;36(10):725-8
pubmed: 6630408
Gen Hosp Psychiatry. 2010 Jul-Aug;32(4):345-59
pubmed: 20633738
Med Care. 2008 Mar;46(3):266-74
pubmed: 18388841
Internet Interv. 2018 Dec 20;15:110-115
pubmed: 30792962
Trials. 2017 Mar 14;18(1):122
pubmed: 28288676
J Med Internet Res. 2016 Jun 20;18(6):e165
pubmed: 27323907
J Med Internet Res. 2021 Jul 27;23(7):e23029
pubmed: 34313595
PLoS Med. 2006 Feb;3(2):e19
pubmed: 16318411
Internet Interv. 2021 Apr 30;25:100398
pubmed: 34026567
Ann Behav Med. 1999 Fall;21(4):339-49
pubmed: 10721442
Soc Psychiatry Psychiatr Epidemiol. 2015 Jan;50(1):77-87
pubmed: 24993290
JMIR Aging. 2021 Jan 6;4(1):e21461
pubmed: 33404509
JMIR Ment Health. 2018 May 15;5(2):e10735
pubmed: 29764797
Australas Psychiatry. 2011 Jun;19(3):259-64
pubmed: 21682626
Psychol Med. 2009 May;39(5):705-12
pubmed: 18812006
Patient Prefer Adherence. 2008 Feb 02;2:97-105
pubmed: 19920949
Diabetes Res Clin Pract. 2014 Jul;105(1):30-9
pubmed: 24862240
J Affect Disord. 2015 May 1;176:9-17
pubmed: 25682378
SAGE Open Med. 2017 Jan 04;5:2050312116686709
pubmed: 28228949
Internet Interv. 2017 Jun 02;9:46-50
pubmed: 30135836
Depress Anxiety. 2012 Jul;29(7):614-20
pubmed: 22495990
JMIR Form Res. 2020 Oct 29;4(10):e22528
pubmed: 33118939
J Ment Health. 2019 Feb;28(1):17-25
pubmed: 28857650