Randomized controlled pilot trial of supportive text messages for patients with depression
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Depression is projected to be the primary cause of disability worldwide by 2030. In a recent survey, the most commonly cited unmet need among 42.4% of depressed Albertans was the lack of sufficient, accessible, and affordable counselling. Our aim was to test the efficacy of a supportive text messaging mobile health intervention in improving treatment outcomes in depressed patients. METHODS: We performed a single-rater-blinded randomized trial involving 73 patients with Major Depressive Disorder. Patients in the intervention group (n = 35) received twice-daily supportive text messages for 3 months while those in the control group (n = 38) received a single text message every fortnight thanking them for participating in the study. The primary outcome of this study was: "Mean changes in the BDI scores from baseline". RESULTS: After adjusting for baseline BDI scores, a significant difference remained in the 3 month mean BDI scores between the intervention and control groups: (20.8 (SD = 11.7) vs. 24.9 (SD = 11.5), F (1, 60) = 4.83, p = 0.03, ηp2 = 0.07). The mean difference in the BDI scores change was significant with an effect size (Cohen's d) of 0.67. Furthermore, after adjusting for baseline scores, a significant difference remained in the 3 month mean self-rated VAS scores (EQ-5D-5 L scale) between the intervention and control groups, 65.7 (SD = 15.3) vs. 57.4 (SD = 22.9), F (1, 60) =4.16, p = 0.05, ηp2 = 0.065. The mean difference in change mean self-rated VAS scores was also statistically significant with an effect size (Cohen's d) of 0.51. CONCLUSIONS: Our findings suggest that supportive text messages are a potentially useful psychological intervention for depression, especially in underserved populations. Further studies are needed to explore the implications of our findings in larger clinical samples. TRIAL REGISTRATION: ClinicalTrials.gov NCT02327858 . Registered 24 December 2014.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it