Participants’ and Nurses’ Experiences With a Digital Intervention for Patients With Depressive Symptoms and Comorbid Hypertension or Diabetes in Peru: Qualitative Post–Randomized Controlled Trial Study
Bibliographic record
Abstract
BACKGROUND: Depression is one of the most prevalent mental disorders and a leading cause of disability, disproportionately affecting specific groups, such as patients with noncommunicable diseases. Over the past decade, digital interventions have been developed to provide treatment for these patients. CONEMO (Emotional Control in Spanish) is an 18-session psychoeducational digital intervention delivered through a smartphone app and minimally supported by a nurse. CONEMO demonstrated effectiveness in reducing depressive symptoms through a randomized controlled trial (RCT) among patients with diabetes, hypertension, or both, in Lima, Peru. However, in addition to clinical outcomes, it is important to explore users' experiences, satisfaction, and perceptions of usability and acceptability, which can affect their engagement with the intervention. OBJECTIVE: This study aimed to explore the RCT participants' experiences with CONEMO in Peru, complemented with information provided by the nurses who monitored them. METHODS: In 2018, semistructured interviews were conducted with a sample of 29 (13.4%) patients from the 217 patients who participated in the CONEMO intervention in Peru and the 3 hired nurses who supported its delivery. Interviewees were selected at random based on their adherence to the digital intervention (0-5, 10-14, and 15-18 sessions completed), to include different points of view. Content analysis was conducted to analyze the interviews. RESULTS: Participants' mean age was 64.4 (SD 8.5) years, and 79% (23/29) of them were women. Most of the interviewed participants (21/29, 72%) stated that CONEMO fulfilled their expectations and identified positive changes in their physical and mental health after using it. Some of these improvements were related to their thoughts and feelings (eg, think differently, be more optimistic, and feel calmer), whereas others were related to their routines (eg, go out more and improve health-related habits). Most participants (19/29, 66%) reported not having previous experience with using smartphones, and despite experiencing some initial difficulties, they managed to use CONEMO. The most valued features of the app were the videos and activities proposed for the participant to perform. Most participants (27/29, 93%) had a good opinion about the study nurses and reported feeling supported by them. A few participants provided suggestions to improve the intervention, which included adding more videos, making the sessions' text simple, extending the length of the intervention, and improving the training session with long explanations. CONCLUSIONS: The findings of this qualitative study provide further support and contextualize the positive results found in the CONEMO RCT, including insights into the key features that made the intervention effective and engaging. The participants' experience with the smartphone and CONEMO app reveal that it is feasible to be used by people with little knowledge of technology. In addition, the study identified suggestions to improve the CONEMO intervention for its future scale-up. TRIAL REGISTRATION: ClinicalTrials.gov NCT03026426; https://clinicaltrials.gov/ct2/show/NCT03026426.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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 source (direct Gemma or distilled Codex), 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".