Involving End Users in Adapting a Spanish Version of a Web-Based Mental Health Clinic for Young People in Colombia: Exploratory Study Using Participatory Design Methodologies
Bibliographic record
Abstract
BACKGROUND: Health information technologies (HITs) hold enormous promise for improving access to and providing better quality of mental health care. However, despite the spread of such technologies in high-income countries, these technologies have not yet been commonly adopted in low- and middle-income countries. People living in these parts of the world are at risk of experiencing physical, technological, and social health inequalities. A possible solution is to utilize the currently available HITs developed in other counties. OBJECTIVE: Using participatory design methodologies with Colombian end users (young people, their supportive others, and health professionals), this study aimed to conduct co-design workshops to culturally adapt a Web-based Mental Health eClinic (MHeC) for young people, perform one-on-one user-testing sessions to evaluate an alpha prototype of a Spanish version of the MHeC and adapt it to the Colombian context, and inform the development of a skeletal framework and alpha prototype for a Colombian version of the MHeC (MHeC-C). METHODS: This study involved the utilization of a research and development (R&D) cycle including 4 iterative phases: co-design workshops; knowledge translation; tailoring to language, culture, and place (or context); and one-on-one user-testing sessions. RESULTS: A total of 2 co-design workshops were held with 18 users-young people (n=7) and health professionals (n=11). Moreover, 10 users participated in one-on-one user-testing sessions-young people (n=5), supportive others (n=2), and health professionals (n=3). A total of 204 source documents were collected and 605 annotations were coded. A thematic analysis resulted in 6 themes (ie, opinions about the MHeC-C, Colombian context, functionality, content, user interface, and technology platforms). Participants liked the idea of having an MHeC designed and adapted for Colombian young people, and its 5 key elements were acceptable in this context (home page and triage system, self-report assessment, dashboard of results, booking and video-visit system, and personalized well-being plan). However, to be relevant in Colombia, participants stressed the need to develop additional functionality (eg, phone network backup; chat; geolocation; and integration with electronic medical records, apps, or electronic tools) as well as an adaptation of the self-report assessment. Importantly, the latter not only included language but also culture and context. CONCLUSIONS: The application of an R&D cycle that also included processes for adaptation to Colombia (language, culture, and context) resulted in the development of an evidence-based, language-appropriate, culturally sensitive, and context-adapted HIT that is relevant, applicable, engaging, and usable in both the short and long term. The resultant R&D cycle allowed for the adaptation of an already available HIT (ie, MHeC) to the MHeC-C-a low-cost and scalable technology solution for low- and middle-income countries like Colombia, which has the potential to provide young people with accessible, available, affordable, and integrated mental health care at the right time.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".