Mobile Phone Intervention to Reduce Youth Suicide in Rural Communities: Field Test
Bibliographic record
Abstract
BACKGROUND: Suicide is a leading cause of death among 10- to 19-year-olds in the United States, with 5% to 8% attempting suicide each year. Suicide risk rises significantly during early adolescence and is higher in rural and underserved communities. School-based universal prevention programs offer a promising way of reducing suicide by providing strategies for emotion regulation and encouraging help-seeking behaviors and youth-adult connectedness. However, such programs frequently run into difficulties in trying to engage a broad range of students. Text messaging is a dominant medium of communication among youths, and studies show both efficacy and uptake in text messaging interventions aimed at adolescents. Text-based interventions may, thus, offer a means for school-based universal prevention programs to engage adolescents who would otherwise be difficult to reach. OBJECTIVE: We field tested Text4Strength, an automated, interactive text messaging intervention that seeks to reach a broad range of early adolescents in rural communities. Text4Strength extends Sources of Strength, a peer-led school suicide prevention program, by encouraging emotion regulation, help-seeking behaviors, and youth-adult connectedness in adolescents. The study tested the appeal and feasibility of Text4Strength and its potential to extend universal school-based suicide prevention. METHODS: We field tested Text4Strength with 42 ninth-grade students. Over 9 weeks, students received 28 interactive message sequences across 9 categories (Sources of Strength introduction, positive friend, mentors, family support, healthy activities, generosity, spirituality, medical access, and emotion regulation strategies). The message sequences included games, requests for advice, questions about students' own experiences, and peer testimonial videos. We measured baseline mental health characteristics, frequency of replies, completion of sequences and video viewing, appeal to students, and their perception of having benefited from the program. RESULTS: Of the 42 participating students, 38 (91%) responded to at least one sequence and 22 (52%) responded to more than a third of the sequences. The proportion of students who completed multistep sequences they had started ranged from 35% (6/17) to 100% (3/3 to 28/28), with responses dropping off when more than 4 replies were needed. With the exception of spirituality and generosity, each of the content areas generated at least a moderate number of student replies from both boys and girls. Students with higher and lower levels of risk and distress interacted with the sequences at similar rates. Contrary to expectations, few students watched videos. Students viewed the intervention as useful-even those who rarely responded to messages. More than 70% found the texts useful (3 items, n range 29-34) and 90% (36) agreed the program should be repeated. CONCLUSIONS: Text4Strength offers a potentially engaging way to extend school-based interventions that promote protective factors for suicide. Text4Strength is ready to be revised, based on findings and student feedback from this field test, and rigorously tested for efficacy.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".