Text Message Feedback to Support Mindfulness Practice in People With Depressive Symptoms: A Pilot Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: It has been shown that mindfulness practice can be helpful in preventing relapse from depression. However, practicing mindfulness regularly at home is often a challenge for people with depression. Mobile phone text messaging (short message service, SMS) may be a feasible approach to assist regular mindfulness home practice. OBJECTIVE: The aim of this study was to evaluate the feasibility of text message-based feedback to support mindfulness practice in people with depressive symptoms after inpatient psychiatric treatment. METHODS: Participants received a manualized group introduction to three mindfulness exercises during inpatient treatment and were randomized at hospital discharge. All participants were asked to practice the exercises daily during the 4-month follow-up period. Only participants allocated to the intervention group received reinforcing feedback via mobile phone text messages after reporting their mindfulness practice via text message. Participation rates and satisfaction with the interventions were evaluated, and effects on relevant outcomes were explored. RESULTS: Of the 176 eligible inpatients invited to participate, 65.9% (116/176) attended the introductory mindfulness group at least once, 33.0% (58/176) were willing to participate in the study, and 41 were randomized. The majority 85% (35/41) of these participants completed the study. Among the participants allocated to the intervention group (n=21), 81% (17/21) used the text message support at least once. The average number of text messages sent during the intervention period was 14 (SD 21, range 0-91). Satisfaction rates were high. Preliminary analyses of the effects of the intervention yielded mixed results. CONCLUSIONS: Findings indicate that text messaging following inpatient treatment is feasible for some, but not for all people with depressive symptoms. Modest use of the text messaging intervention and its mixed effects imply that dose and ingredients of the intervention should be increased for this group of patients in a future full-size RCT. Such a larger study should also include a process evaluation to investigate moderators of the effect of mindfulness practice and text message feedback on clinical outcome. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number (ISRCTN): 58808893; http://www.controlled-trials.com/ISRCTN58808893 (Archived by Webcite at http://www.webcitation.org/6pmrDRnGt).
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".