Effectiveness of an Internet-Based Self-Guided Program to Treat Depression in a Sample of Brazilian Users: Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Depression is undertreated in Brazil. Deprexis is a self-guided internet-based program used to treat depressive symptoms based on empirically supported integrative and cognitive behavioral therapy. Evidence from a meta-analysis supports Deprexis' efficacy in German-speaking countries and the United States, but no study has been conducted using this program in countries with low literacy rates and large social disparities. Furthermore, few studies have investigated whether internet-based interventions ameliorate the psychological processes that might underlie depressive symptomatology, such as low perceived self-efficacy. OBJECTIVE: The main objective of this study was to replicate in Brazil previously reported effects of Deprexis on depressive symptom reduction. Therefore, the main research question was whether Deprexis is effective in reducing depressive symptoms and the general psychological state in Brazilian users with moderate and severe depression in comparison with a control group that does not receive access to Deprexis. A secondary research question was whether the use of Deprexis affects perceptions of self-efficacy. METHODS: We interviewed 312 participants recruited over the internet and randomized 189 participants with moderate to severe depression (according to the Patient Health Questionnaire-9 and a semistructured interview) to an intervention condition (treatment as usual plus immediate access to Deprexis for 90 days, n=94) or to a control condition (treatment as usual and delayed access to Deprexis, after 8 weeks, n=95). RESULTS: Participants from the immediate access group logged in at Deprexis an average of 14.81 (SD 12.16) times. The intention-to-treat analysis using a linear mixed model showed that participants who received Deprexis improved significantly more than participants assigned to the delayed access control group on the primary depression self-assessment measure (Patient Health Questionnaire-9; Cohen d=0.80; P<.001) and secondary outcomes, such as general psychological state measure (Clinical Outcome in Routine Evaluation-Outcome Measurement; Cohen d=0.82; P<.001) and the perceived self-efficacy measure (Cohen d=0.63; P<.001). The intention-to-treat analyses showed that 21% (20/94) of the participants achieved remission compared with 7% (7/95) in the control group (P<.001). The deterioration rates were lower in the immediate access control group. The dropout rate was high, but no differences in demographic and clinical variables were found. Participants reported a medium to high level of satisfaction with Deprexis. CONCLUSIONS: These results replicate previous findings by showing that Deprexis can facilitate symptomatic improvement over 3 months in depressed samples of Brazilian users. From a public health perspective, this is important information to expand the reach of internet-based interventions for those who really need them, especially in countries with less access to mental health care. This extends previous research by showing significant effects on perceived self-efficacy. TRIAL REGISTRATION: Registro Brasileiro de Ensaios Clíncos (ReBec) RBR-6kk3bx UTN U1111-1212-8998; https://ensaiosclinicos.gov.br/rg/RBR-6kk3bx/. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1590/1516-4446-2019-0582.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".