Text4Hope: An e-Mental Health Tool for Mitigating Psychological Symptoms among Young Adults
Bibliographic record
Abstract
Introduction Chronic stress, anxiety, and depression can interfere with young adults’ everyday function, academic achievement, and interpersonal relationships. Interventions aimed at preventing the deterioration or possibly onset of these mental disorders among young people are timely. Objectives To assess the impact of a supportive text messaging program (Text4Hope) on the psychological well-being of young adults. Methods This study adopted both longitudinal and naturalistic controlled trial designs. Longitudinal study: compared baseline and 6th week outcomes in the same group of young adult subscribers. Naturalistic controlled study: compared clinical parameters in two groups of Text4Hope young adult subscribers: (i) intervention group (IG), subscribers who received once-daily supportive text messages for 6-weeks and completed 6th-week evaluation between 26 April and 12 July 2020, and (ii) control group (CG), subscribers who joined Text4Hope the same time frame, completed a baseline survey and were yet to receive text messages. The prevalence and severity of moderate-high stress, anxiety, and depression was measured using standardized scales. Inferential statistics, including the t-test, McNemar test, chi-square, and binary logistic regression analyses, were used to evaluate the differences in the prevalence and severity of the psychological symptoms. Results Longitudinal study: subscribers who completed both the baseline and 6th-week surveys, had significant reduction in the prevalence of moderate-high stress (8%) and likely GAD (20%) from baseline to six weeks. The largest reduction in mean scores was for the GAD-7 scale (18.4%). Naturalistic study: significantly lower prevalence for likely Moderate Depressive Disorder (25.2%) and suicidal thoughts/thoughts of self-harm (48.4%), with a small effect size in the IG compared to CG. Image: Conclusions TheText4Hope program has been demonstrated as an effective e-mental health tool for mental health support for young adult subscribers. This is particularly encouraging, as young adults have already adapted to SMS text messaging and texting. Therefore, this mode of intervention can be used to supplement existing treatments for psychological problems impacting young adults. In addition, the cost effectiveness and easy scalability of supportive text message interventions mean that policymakers and governments can quickly implement similar programs as part of national youth suicide prevention strategies. Disclosure of Interest None Declared
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.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".