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Cited by 69Digital Mental Health InterventionsMobile Health and mHealth ApplicationsEthics in Clinical Research

Factors Associated With Dropout During Recruitment and Follow-Up Periods of a mHealth-Based Randomized Controlled Trial for Mobile.Net to Encourage Treatment Adherence for People With Serious Mental Health Problems

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Kannisto, Kati Anneli, Korhonen, Joonas, Adams, Clive E, Koivunen, Marita Hannele, Vahlberg, Tero, Välimäki, Maritta Anneli·2017·Journal of Medical Internet Research
DOI 10.2196/jmir.6417PMC PMC5340923
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Abstract

BACKGROUND: Clinical trials are the gold standard of evidence-based practice. Still many papers inadequately report methodology in randomized controlled trials (RCTs), particularly for mHealth interventions for people with serious mental health problems. To ensure robust enough evidence, it is important to understand which study phases are the most vulnerable in the field of mental health care. OBJECTIVE: We mapped the recruitment and the trial follow-up periods of participants to provide a picture of the dropout predictors from a mHealth-based trial. As an example, we used a mHealth-based multicenter RCT, titled "Mobile.Net," targeted at people with serious mental health problems. METHODS: Recruitment and follow-up processes of the Mobile.Net trial were monitored and analyzed. Recruitment outcomes were recorded as screened, eligible, consent not asked, refused, and enrolled. Patient engagement was recorded as follow-up outcomes: (1) attrition during short message service (SMS) text message intervention and (2) attrition during the 12-month follow-up period. Multiple regression analysis was used to identify which demographic factors were related to recruitment and retention. RESULTS: We recruited 1139 patients during a 15-month period. Of 11,530 people screened, 36.31% (n=4186) were eligible. This eligible group tended to be significantly younger (mean 39.2, SD 13.2 years, P<.001) and more often women (2103/4181, 50.30%) than those who were not eligible (age: mean 43.7, SD 14.6 years; women: 3633/6514, 55.78%). At the point when potential participants were asked to give consent, a further 2278 refused. Those who refused were a little older (mean 40.2, SD 13.9 years) than those who agreed to participate (mean 38.3, SD 12.5 years; t1842=3.2, P<.001). We measured the outcomes after 12 months of the SMS text message intervention. Attrition from the SMS text message intervention was 4.8% (27/563). The patient dropout rate after 12 months was 0.36% (4/1123), as discovered from the register data. In all, 3.12% (35/1123) of the participants withdrew from the trial. However, dropout rates from the patient survey (either by paper or telephone interview) were 52.45% (589/1123) and 27.8% (155/558), respectively. Almost all participants (536/563, 95.2%) tolerated the intervention, but those who discontinued were more often women (21/27, 78%; P=.009). Finally, participants' age (P<.001), gender (P<.001), vocational education (P=.04), and employment status (P<.001) seemed to predict their risk of dropping out from the postal survey. CONCLUSIONS: Patient recruitment and engagement in the 12-month follow-up conducted with a postal survey were the most vulnerable phases in the SMS text message-based trial. People with serious mental health problems may need extra support during the recruitment process and in engaging them in SMS text message-based trials to ensure robust enough evidence for mental health care. CLINICALTRIAL: International Standard Randomized Controlled Trial Number (ISRCTN): 27704027; http://www.isrctn.com/ISRCTN27704027 (Archived by WebCite at http://www.webcitation.org/6oHcU2SFp).

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  • Overall, 8 studies saw an effect of age: 2 studies found that people aged ≤50 years engaged more with interventions than older adults.

    “Overall, 8 studies saw an effect of age: 2 studies found that people aged ≤50 years engaged more with interventions than older adults [66,67].”

    From Barriers to and facilitators of user engagement with digital mental health interventions: Systematic review (2021) · cites this paper as [66]

    The Results > Attrition section (page unavailable) reports that older participants were more likely to drop out of the postal follow-up survey. It does not report a ≤50-year cutoff, and it found no statistically significant age difference in dropout during the SMS intervention itself. The age effect therefore concerns follow-up participation, not engagement with the intervention as stated. (LLM, conf=0.88)

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  • Employment status was associated with user engagement: people who worked full time were more likely to use the intervention than people who were retired or unemployed.

    “Other demographic variables associated with user engagement were as follows: (1) employment status, with people who worked full time more likely to use the intervention than people who were retired [66] or unemployed [54,68];”

    From Barriers to and facilitators of user engagement with digital mental health interventions: Systematic review (2021) · cites this paper as [66]

    In Results > Attrition, Table 2 links employment status to dropout from the 12-month postal survey: job seekers and retired participants had higher dropout odds than students. The paper does not compare full-time workers directly with either group, distinguish full-time employment, or show that workers used the SMS intervention more often. Survey participation is not the same outcome as intervention use. (LLM, conf=0.88)

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Research works printed but not linked: 3

  1. [18]Harvey PD Keefe RSE Technology, society, and mental illness: challenges and opportunities for assessment and treatment Innov Clin Neurosci 2012 11 9 11-12 47 50 23346519 PMC3552462 23346519
  2. [27]Attkisson CC Greenfield TK Maruish ME The UCSF Client Satisfaction Scales: I. The Client Satisfaction Questionnaire-8 The Use Of Psychological Testing For Treatment Planning And Outcomes Assessment: Volume 1: General Considerations (3rd Edition) 2004 Mahwah, NJ Lawrence Erlbaum Associates
  3. [33]Vargas-Barón E Planning Policies for Early Childhood Development: Guidelines for Action 2005 2016-07-26 Paris United Nations Educational, Scientific and Cultural Organisation (UNESCO) http://www.unicef.org/ceecis/0611-ECDPolicyGuidelines_en.pdf 29058848

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Authors
Kannisto, K. A., Korhonen, J., Adams, C. E., Koivunen, M. H., Vahlberg, T., & Välimäki, M. A.
Affiliations
  • University of Turku (FI)
  • University of Nottingham (GB)
  • Hong Kong Polytechnic University (HK)
Corresponding author
Kannisto, Kati Anneli
ORCID
Venue
Journal of Medical Internet Research
Publisher
JMIR Publications Inc.
Published
2017-02-21
Volume
19
Issue
2
Pages
e46
ISSN
1438-8871 (ISSN-L)
DOI
10.2196/jmir.6417
PMC
PMC5340923
OpenAlex
W2591428653
Cited by
69
References
35
Citations by year
2026: 2 · 2025: 4 · 2024: 15 · 2023: 6 · 2022: 7 · 2021: 12 · 2020: 11 · 2019: 8 · 2018: 3 · 2017: 1
FWCI
7.18
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Journal of Medical Internet Research (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PolyU Institutional Research Archive (Hong Kong Polytechnic University) (submittedVersion, cc-by)
  • UTUPub (University of Turku) (submittedVersion, cc-by)
  • Nottingham ePrints (University of Nottingham) (submittedVersion, cc-by)
  • PolyU Institutional Research Archive (Hong Kong Polytechnic University) (submittedVersion)
  • Repository@Nottingham (University of Nottingham) (submittedVersion, cc-by)
Funders
  • Suomen Kulttuurirahasto
  • Turun Yliopisto
  • Turun Yliopistollinen Keskussairaala (EVO 13893, 13893)
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics in Clinical Research
Keywords
trial dropout, participant recruitment, participant retention, attrition, severe mental illness, mobile health intervention, predictors of dropout, trial follow-up, patient engagement, trial methodology reporting
MeSH terms
Adult, Mental Disorders, Female, Follow-Up Studies, Humans, Male, Middle Aged, Patient Dropouts, Surveys and Questionnaires, Multicenter Studies as Topic, Randomized Controlled Trials as Topic, Telemedicine, Patient Selection, Medication Adherence, Text Messaging

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