Evidence map›Paper›PMID 40811785›Full record

ArticleJMIR mHealth and uHealth2025

Factors Influencing Engagement in a Digital Substance Use Prevention Program: Qualitative Study Using the Capability, Opportunity, Motivation Model and Theoretical Domains Framework.

Nikolai Kiselev, Rebecca Schaffner, Zsofia Csepregi, Andreas Wenger, Raquel Paz Castro, Severin Haug

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Nikolai KiselevSwiss Research Institute for Public Health and Addiction (ISGF), University of Zurich, Konradstrasse 32, Zurich, 8005, Switzerland, 41 444481174.ORCID 0000-0003-0617-0353
Rebecca SchaffnerSwiss Research Institute for Public Health and Addiction (ISGF), University of Zurich, Konradstrasse 32, Zurich, 8005, Switzerland, 41 444481174.ORCID 0009-0009-8689-9427
Zsofia CsepregiSwiss Research Institute for Public Health and Addiction (ISGF), University of Zurich, Konradstrasse 32, Zurich, 8005, Switzerland, 41 444481174.ORCID 0009-0003-7577-6110
Andreas WengerSwiss Research Institute for Public Health and Addiction (ISGF), University of Zurich, Konradstrasse 32, Zurich, 8005, Switzerland, 41 444481174.ORCID 0000-0003-4818-4681
Raquel Paz CastroSwiss Research Institute for Public Health and Addiction (ISGF), University of Zurich, Konradstrasse 32, Zurich, 8005, Switzerland, 41 444481174.ORCID 0000-0003-4451-900X
Severin HaugSwiss Research Institute for Public Health and Addiction (ISGF), University of Zurich, Konradstrasse 32, Zurich, 8005, Switzerland, 41 444481174.ORCID 0000-0002-6539-5045

Funding

Swiss National Science Foundation 10001C_204412/1
6 · The paper itself

Abstract

Background: Digital interventions are promising for the prevention of substance use in young people. However, engagement with these interventions is often insufficient, and their full potential remains unrealized. Given the established link between engagement in digital interventions and their effectiveness, understanding user factors that influence involvement in eHealth and mobile health (mHealth) interventions is essential. Objective: This study aimed to identify factors influencing user engagement in a mobile phone-based life skills training program for substance use prevention among adolescents and to collect suggestions for program optimization. Methods: A qualitative study was conducted with 171 participants of the mHealth prevention SmartCoach (Pathmate Technologies) program. The program provided individualized text messages to foster life skills for 4 months and proved to be effective in preventing the onset of cigarette and cannabis use. Semistructured phone interviews were conducted with program participants to explore factors associated with program engagement and to gather suggestions for program optimization. Interviews were recorded, transcribed, and analyzed using thematic analysis with both inductive and deductive coding. The capability, opportunity, and motivation model of behavior change (COM-B) model and Theoretical Domains Framework (TDF) were used to assess behavioral influences. Results: Key factors positively influencing program engagement included the timing of text messages, social influences and support, engaging and helpful content, and rewards (points and prizes). Conversely, barriers to engagement were identified as forgetfulness, short response time limits, limited time resources, lack of interest, concerns related to personal disclosure, and difficulty identifying with the challenge task type (posting). Suggestions for optimization included implementing reminders, providing better guidance for using tips, allowing personalization of message timing and content, extending time limits for tasks, and reducing the concerns related to personal disclosure. Conclusions: The study confirms the critical role of timing, content relevance, and social support in enhancing engagement with digital interventions. Specific recommendations for optimizing the SmartCoach program were derived, highlighting the importance of reminders, personalization, and addressing concerns related to personal disclosure.

Indexed as

MotivationPatient ParticipationSubstance-Related DisordersAdolescentAdultFemaleHumansInterviews as TopicMaleQualitative ResearchTelemedicineText MessagingYoung AdultadolescentcannabiscigaretteCOM-B modeldigital interventiondrug useengagementengagement optimizationmHealthmobile healthpreventionprogram engagementqualitative studySmartCoachsocial influencessocial supportsubstance usesubstance use preventionteenagertexttheoretical domains frameworktraining program

Identifiers

PMID40811785
PMCPMC12352799

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.