Caring Text Messages for Suicide Prevention in Urban American Indian Youth: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: American Indian (AI) young adults in urban areas have many cultural strengths but also face unique challenges. Cultural norms within their communities strongly emphasize relationships. Previous research has found that receiving occasional positive and nondemanding messages-caring text messages-can be beneficial among people experiencing suicidality. OBJECTIVE: To ameliorate increasing rates of suicide and suicidality among AI young adults, we implemented a caring text message intervention designed to increase social connectedness. METHODS: This 2-arm, double-blinded, randomized controlled trial is being implemented at 2 clinical sites with large AI populations. Partnering with clinics in Albuquerque, New Mexico, and Rapid City, South Dakota, we are recruiting AI adults aged 18-34 years to participate in a caring text message study. During the baseline visit, participants complete several surveys and an interview with study staff to understand their history of suicidal behavior. After completion of the baseline visit, participants are randomized to receive the intervention-approximately 30 caring text messages-or treatment as usual. The text messaging platform selected for this study allows bidirectional messaging; while there is no expectation that participants respond, they can provide feedback or seek additional resources. Participants are followed up at 6 and 12 months postbaseline. At the final 12-month follow-up visit, they complete many of the same surveys and participate in an interview to ascertain suicidality since their initial visit. The primary outcomes of interest are suicide-related behaviors-suicidal ideation, suicide planning, suicide attempt, or thoughts and actions requiring hospitalization. Secondary outcomes include social connectedness and other measures of mental health. We will use an intention-to-treat analysis with logistic and linear regression to calculate odds ratios and risk differences (95% CIs) for binary and continuous outcomes. RESULTS: As of June 2025, the New Mexico site has finished recruitment and follow-up assessments. The South Dakota site is still enrolling participants and has conducted the first follow-up assessments. The project has been well-received by participants. CONCLUSIONS: This randomized controlled trial will evaluate whether a caring text message intervention is effective in reducing suicidality among AI young adults in urban areas. Participants have received the culturally tailored caring text messages. This trial will help establish whether caring text messages are an effective strategy for reducing suicidal behaviors and promoting feelings of connectedness among AI young adults. TRIAL REGISTRATION: ClinicalTrials.gov NCT03136094; http://clinicaltrials.gov/show/NCT03136094. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/71344.
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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 | 0.029 | 0.025 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.085 | 0.010 |
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".