Evaluation and Future Challenges in a Self-Guided Web-Based Intervention With and Without Chat Support for Depression and Anxiety Symptoms During the COVID-19 Pandemic: Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic has had an impact on mental health worldwide. Low- and middle-income countries were largely affected by it. Mexico was one of the most affected countries. Extended periods of lockdowns, isolation, and social distancing, among other factors, highlighted the need to introduce web-based psychological interventions to the Mexican population. In this context, Mental Health COVID-19 emerged as a self-guided web-based intervention (SGWI) aimed at adults to improve mental health during the COVID-19 pandemic. OBJECTIVE: This study aims to assess the efficacy of 2 modalities of a self-guided intervention (with and without chat support) in reducing depression symptoms, generalized anxiety, community posttraumatic stress, widespread fear, anxiety, sleep quality, physiological and affective coping, and suicide ideation. In addition, it aimed to compare the moderating role of coping strategies, acceptance, and satisfaction in participants' symptom reduction. We hypothesize that the self-guided, chat-supported modality will show higher efficacy than the modality without chat support in achieving clinical change and better performance as a moderator of depression symptoms, generalized anxiety, community posttraumatic stress, widespread fear, anxiety, sleep quality, physiological and affective coping, and suicide ideation, as well as an increase in participants' satisfaction and acceptability. METHODS: A randomized controlled trial was conducted. Data were collected from May 2020 to June 2022. We performed intrasubject measures at 4 evaluation periods: pretest, posttest, and follow-up measurements at 3 and 6 months. Differences between intervention groups were assessed through the Mann-Whitney U test for continuous variables and the chi-square test for categorical variables. Changes due to intervention were analyzed using Wilcoxon W test. Moderated regression analysis was performed to test the hypothesized moderating role of coping strategies, usability, and opinion about treatment on clinical change. RESULTS: A total of 36 participants completed the intervention; of these, 5 (14%) were part of the SGWI group, and 31 (86%) were on the SGWI plus chat support (SGWI+C) group, which included a chat service with therapists. The perceived high complexity of the system for the SGWI group had a moderating effect associated with a lack of efficacy of the intervention regarding depression, but not when controlled for sociodemographic variables. A perception of lower helpfulness of the intervention was associated with poorer outcomes. Coping strategies did not show moderating effects. CONCLUSIONS: Enhancing the utility of web-based interventions for reducing clinical symptoms by incorporating a support chat to boost treatment adherence seemed to improve the perception of the intervention's usefulness. Web-based interventions face several challenges, such as eliminating complexities in platform use and increasing the users' perceived utility of the intervention, among other issues identified in the study. TRIAL REGISTRATION: ClinicalTrials.gov NCT04468893; https://clinicaltrials.gov/study/NCT04468893?tab=results. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/23117.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".