Comparing Email Versus Text Messaging as Delivery Platforms for Supporting Patients With Major Depressive Disorder: Noninferiority Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: The prevalence of major depressive disorder (MDD) poses significant global health challenges, with available treatments often insufficient in achieving remission for many patients. Digital health technologies, such as SMS text messaging-based cognitive behavioral therapy, offer accessible alternatives but may not reach all individuals. Email communication presents a secure avenue for health communication, yet its effectiveness compared to SMS text messaging in providing mental health support for patients with MDD remains uncertain. OBJECTIVE: This study aims to compare the efficacy of email versus SMS text messaging as delivery platforms for supporting patients with MDD, addressing a critical gap in understanding optimal digital interventions for mental health care. METHODS: A randomized noninferiority pilot trial was conducted, comparing outcomes for patients receiving 6-week daily supportive messages via email with those receiving messages via SMS text message. This duration corresponds to a minimum of 180 days of message delivery. The supportive messages maintained consistent length and structure across both delivery methods. Participants (N=66) were recruited from the Access 24/7 clinic in Edmonton, Alberta, among those who were diagnosed with MDD. The outcomes were measured at baseline and 6 months after enrollment using the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and the World Health Organization Well-Being Index (WHO-5). RESULTS: Most of the participants were females (n=43, 65%), aged between 26 and 40 years (n=34, 55%), had high school education (n=35, 58%), employed (n=33, 50%), and single (n=24, 36%). Again, most participants had had no history of any major physical illness (n=56, 85%) and (n=61, 92%) responded "No" to having a history of admission for treatment of mood disorders. There was no statistically significant difference in the mean changes in PHQ-9, GAD-7, and WHO-5 scores between the email and SMS text messaging groups (mean difference, 95% CI: -1.90, 95% CI -6.53 to 2.74; 5.78, 95% CI -1.94 to 13.50; and 11.85, 95% CI -3.81 to 27.51), respectively. Both supportive modalities showed potential in reducing depressive symptoms and improving quality of life. CONCLUSIONS: The study's findings suggest that both email and SMS text messaging interventions have equivalent effectiveness in reducing depression symptoms among individuals with MDD. As digital technology continues to evolve, harnessing the power of multiple digital platforms for mental health interventions can significantly contribute to bridging the existing treatment gaps and improving the overall well-being of individuals with depressive conditions. Further research is needed with a larger sample size to confirm and expand upon these findings. TRIAL REGISTRATION: ClinicalTrials.gov NCT04638231; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8552095/.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".