Effectiveness of e-health intervention using smart phone app to reduce anxiety & depressive symptoms among adolescents: A cluster randomized controlled trial. (Study Protocol- NCT05865834)
Bibliographic record
Abstract
Abstract Background: As per World Health Organization, 13% of adolescents worldwide experience a mental disorder. If the increasing burden of mental health issues is not addressed in adolescence, they can culminate into established mental disorders extending to adulthood, impairing overall wellbeing, and limiting opportunities. To cater to mental health issues in adolescents at an early stage, we aim to develop and assess the effectiveness of a smartphone application for the reduction of depression and anxiety symptoms in school-going adolescents aged 12-18 years. Methods A stratified cluster randomized controlled trial will be conducted on 200 students from different schools of Karachi, Pakistan. A two-stage cluster sampling with stratification on school type (government or private) will be employed to select schools and recruit students. The duration of the study will be 1 year. Selected schools will be randomly assigned to either an intervention (mHealth program) or control group (self-reading educational leaflets). PHQ-A, GAD-7, and WHO depression wellbeing scale for assessing depressive symptoms, anxiety symptoms, and wellbeing will be used at baseline, 1 month, and three months. GEE will be used to compare mean scores of depression, anxiety and wellbeing scores between both arms. Discussion: There are hardly any programs in Pakistan that focus on mHealth interventions that are tailored and target anxiety and depression among adolescents. This smartphone application will stimulate autonomous motivation in adolescents by integrating all the components based on the perspectives of Pakistani adolescents. This application by addressing mental health symptoms in adolescents will benefit the community at large by limiting the burden of mental health disorders. Also, this application will improve accessibility especially in adolescents experiencing financial constraints such as lack of money or transportation to attend appointments. Trial registration: Registered in clinicaltrial.gov under the identifier NCT05865834. Date of registration: 18.05.23.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 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".