Text Messaging Versus Email Messaging to Support Patients With Major Depressive Disorder: Protocol for a Randomized Hybrid Type II Effectiveness-Implementation Trial (Preprint)
Bibliographic record
Abstract
BACKGROUND Major depressive disorder (MDD) accounts for 40.5% of disability-adjusted life years caused by mental and substance use disorders. Barriers such as stigma and financial and physical access to care have been reported, highlighting the need for innovative, accessible, and cost-effective psychological interventions. The effectiveness of supportive SMS text messaging in alleviating depression symptoms has been proven in clinical trials, but this approach can only help those with mobile phones. OBJECTIVE This paper presents the protocol for a study that will aim to evaluate the feasibility, comparative effectiveness, and user satisfaction of daily supportive email messaging as an effective strategy compared to daily supportive text messaging as part of the treatment of patients with MDD. METHODS This trial will be carried out using a hybrid type II implementation-effectiveness design. This design evaluates the effectiveness of an implementation strategy or intervention, while also evaluating the implementation context associated with the intervention. Patients with MDD receiving usual care will be randomized to receive either daily supportive email messaging or daily supportive text messaging of the same content for 6 months. The Patient Health Questionnaire-9, the Generalized Anxiety Disorder-7, and the 5-item World Health Organization Well-Being Index will be used to evaluate the effectiveness of both strategies. The implementation evaluation will be guided by the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework, as well as the Consolidated Framework for Implementation Research. All outcome measures will be analyzed using descriptive and inferential statistics. Qualitative data will be analyzed using thematic analysis. RESULTS Data collection for this trial began in April 2021. We expect the study results to be available within 18 months of study commencement. The results will shed light on the feasibility, acceptability, and effectiveness of using automated emails as a strategy for delivering supportive messages to patients with MDD in comparison to text messaging. CONCLUSIONS The outcome of this trial will have translational impact on routine patient care and access to mental health, as well as potentially support mental health policy decision-making for health care resource allocation. CLINICALTRIAL ClinicalTrials.gov NCT04638231; https://clinicaltrials.gov/ct2/show/NCT04638231 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/29495
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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 | 0.024 | 0.025 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.070 | 0.009 |
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".