User journey method: a case study for improving digital intervention use measurement
Abstract Background Many digital mental health interventions meet low levels of use. However, current use measurement methods do not necessarily help identify which intervention elements are associated with dropout, despite this information potentially facilitating iterative intervention development...
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BMC
2025-04-01
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| Series: | BMC Health Services Research |
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| Online Access: | https://doi.org/10.1186/s12913-025-12641-9 |
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| author | Lauri Lukka Maria Vesterinen Antti Salonen Vilma-Reetta Bergman Paulus Torkki Satu Palva J. Matias Palva |
| author_facet | Lauri Lukka Maria Vesterinen Antti Salonen Vilma-Reetta Bergman Paulus Torkki Satu Palva J. Matias Palva |
| author_sort | Lauri Lukka |
| collection | DOAJ |
| description | Abstract Background Many digital mental health interventions meet low levels of use. However, current use measurement methods do not necessarily help identify which intervention elements are associated with dropout, despite this information potentially facilitating iterative intervention development. Here, we suggest improving the comprehensiveness of intervention use measurement with the user journey method, which evaluates every intervention element to identify intervention-specific use barriers. Methods We applied user journey method in a clinical trial that investigated the efficacy of a novel game-based intervention, Meliora, for adult Major Depressive Disorder. We modelled the intervention for its four technological (Recruitment, Website, Questionnaires, Intervention Software) and two interpersonal elements (Assessment, Support). We then applied the user journey method to measure how many users proceeded from one element to the next combining social media analytics, website use data, signup data, clinical subject coordinator interview data, symptom questionnaire data, and behavioral intervention use data. These measurements were complemented with the qualitative analysis of the study discovery sources and email support contacts. Results Recruitment: The intervention recruitment reached at least 145,000 Finns, with social media, word-of-mouth, and news and web sources being the most effective recruitment channels. Website: The study website received 16,243 visitors, which led to 1,007 sign-ups. Assessment: 895 participants were assessed and 735 were accepted. Intervention Software: 498 participants were assigned to the active intervention or comparator, of whom 457 used them at least once: on average, for 17.3 h (SD = 20.4 h) on 19.7 days (SD = 20.7 d) over a period of 38.9 days (SD = 31.2 d). The 28 intervention levels were associated with an average dropout rate of 2.6%, with two sections exhibiting an increase against this baseline. 150 participants met the minimum adherence goal of 24 h use. Questionnaires: 116 participants completed the post-intervention questionnaire. Support: 313 signed-up participants contacted the researchers via email. Conclusion The user journey method allowed for the comprehensive evaluation of the six intervention elements, and enabled identifying use barriers expediting iterative intervention development and implementation. Trial registration ClinicalTrials.gov, NCT05426265. Registered 28 June 2022, https://clinicaltrials.gov/ct2/show/NCT05426265 . |
| format | Article |
| id | doaj-art-b56a0ed968ae4b32a3a73162ea22b8f4 |
| institution | OA Journals |
| issn | 1472-6963 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Health Services Research |
| spelling | doaj-art-b56a0ed968ae4b32a3a73162ea22b8f42025-08-20T01:53:07ZengBMCBMC Health Services Research1472-69632025-04-0125111510.1186/s12913-025-12641-9User journey method: a case study for improving digital intervention use measurementLauri Lukka0Maria Vesterinen1Antti Salonen2Vilma-Reetta Bergman3Paulus Torkki4Satu Palva5J. Matias Palva6Department of Neuroscience and Biomedical Engineering, School of Science, Aalto UniversityNeuroscience Center, Helsinki Institute of Life Science, University of HelsinkiDepartment of Neuroscience and Biomedical Engineering, School of Science, Aalto UniversityDepartment of Neuroscience and Biomedical Engineering, School of Science, Aalto UniversityDepartment of Public Health, University of HelsinkiNeuroscience Center, Helsinki Institute of Life Science, University of HelsinkiDepartment of Neuroscience and Biomedical Engineering, School of Science, Aalto UniversityAbstract Background Many digital mental health interventions meet low levels of use. However, current use measurement methods do not necessarily help identify which intervention elements are associated with dropout, despite this information potentially facilitating iterative intervention development. Here, we suggest improving the comprehensiveness of intervention use measurement with the user journey method, which evaluates every intervention element to identify intervention-specific use barriers. Methods We applied user journey method in a clinical trial that investigated the efficacy of a novel game-based intervention, Meliora, for adult Major Depressive Disorder. We modelled the intervention for its four technological (Recruitment, Website, Questionnaires, Intervention Software) and two interpersonal elements (Assessment, Support). We then applied the user journey method to measure how many users proceeded from one element to the next combining social media analytics, website use data, signup data, clinical subject coordinator interview data, symptom questionnaire data, and behavioral intervention use data. These measurements were complemented with the qualitative analysis of the study discovery sources and email support contacts. Results Recruitment: The intervention recruitment reached at least 145,000 Finns, with social media, word-of-mouth, and news and web sources being the most effective recruitment channels. Website: The study website received 16,243 visitors, which led to 1,007 sign-ups. Assessment: 895 participants were assessed and 735 were accepted. Intervention Software: 498 participants were assigned to the active intervention or comparator, of whom 457 used them at least once: on average, for 17.3 h (SD = 20.4 h) on 19.7 days (SD = 20.7 d) over a period of 38.9 days (SD = 31.2 d). The 28 intervention levels were associated with an average dropout rate of 2.6%, with two sections exhibiting an increase against this baseline. 150 participants met the minimum adherence goal of 24 h use. Questionnaires: 116 participants completed the post-intervention questionnaire. Support: 313 signed-up participants contacted the researchers via email. Conclusion The user journey method allowed for the comprehensive evaluation of the six intervention elements, and enabled identifying use barriers expediting iterative intervention development and implementation. Trial registration ClinicalTrials.gov, NCT05426265. Registered 28 June 2022, https://clinicaltrials.gov/ct2/show/NCT05426265 .https://doi.org/10.1186/s12913-025-12641-9AcceptabilityDepressionDigital interventionsEvaluation methodsEngagementImplementation |
| spellingShingle | Lauri Lukka Maria Vesterinen Antti Salonen Vilma-Reetta Bergman Paulus Torkki Satu Palva J. Matias Palva User journey method: a case study for improving digital intervention use measurement BMC Health Services Research Acceptability Depression Digital interventions Evaluation methods Engagement Implementation |
| title | User journey method: a case study for improving digital intervention use measurement |
| title_full | User journey method: a case study for improving digital intervention use measurement |
| title_fullStr | User journey method: a case study for improving digital intervention use measurement |
| title_full_unstemmed | User journey method: a case study for improving digital intervention use measurement |
| title_short | User journey method: a case study for improving digital intervention use measurement |
| title_sort | user journey method a case study for improving digital intervention use measurement |
| topic | Acceptability Depression Digital interventions Evaluation methods Engagement Implementation |
| url | https://doi.org/10.1186/s12913-025-12641-9 |
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