Exploring the Impact of the Caring Contacts Intervention on the Stress and Distress of Veterans and Service Members: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Suicide is a recognized global public health problem that continues to pose substantial challenges in the United States. Veterans and service members are particularly at risk. Caring Contacts is a simple, scalable intervention comprising brief, periodic messages sent over 1 to 2 years that express unconditional care and concern. It reduces suicide risk among individuals with recent suicidal ideation or attempts and has demonstrated acceptability in military and veteran samples, but little is known about the mechanisms of Caring Contacts or its applicability to populations who are not suicidal. OBJECTIVE: We aim to evaluate if receiving Caring Contacts reduces suicide risk among veterans and active service members recruited based on their stress or distress levels, using ecological momentary assessment (EMA) and survey measures of suicidal ideation and cognitions; to examine the experiences of diverse veterans and service members with Caring Contacts; to evaluate if receiving Caring Contacts reduces distress (depression, substance use consequences, hopelessness, defeat, and psychological pain); and to identify the potential mechanisms of action for Caring Contacts (mattering, connectedness, social responsibility, and entrapment). Using EMA, this study will be the first to investigate mechanisms of the Caring Contacts intervention both in real time, as the messages are received, and over the course of 1 year. METHODS: In this randomized controlled trial, veterans or service members (N=510) experiencing stress or distress recruited via social media advertisements will be offered best available resources and randomized into 1 of 3 study conditions: 12 months of Caring Contacts and monthly EMA, 12 months of Caring Contacts without monthly EMA, or 12 months of monthly EMA alone. The individuals in the Caring Contacts conditions will receive 13 messages. A subset of participants from each condition will be asked to complete a qualitative interview after the 12-month follow-up about their study experience. RESULTS: This trial was funded in October 2023; recruitment started in April 2024 and will conclude in May 2025. As of December 2024, we have enrolled 321 participants. Final quantitative data collection will be completed by July 2026, 2 months after the final 12-month follow-up date. Data from the qualitative interviews will be collected until September 2026. Data analysis will occur following data collection, and the results are expected to be published in winter 2027. CONCLUSIONS: This study will be the first randomized controlled trial evaluating the impact of Caring Contacts among service members and veterans who were not recruited based on suicidality. If effective, our findings will demonstrate that Caring Contacts is beneficial for reducing multiple forms of psychological distress and suicide risk. In addition, we will evaluate potential mechanisms explaining the effects of Caring Contacts and assess the utility of EMA as a primary measure of outcome in suicide research trials. TRIAL REGISTRATION: ClinicalTrials.gov NCT06136234; https://clinicaltrials.gov/study/NCT06136234. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/72140.
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 | 0.032 | 0.032 |
| Meta-epidemiology (narrow) | 0.009 | 0.004 |
| Meta-epidemiology (broad) | 0.018 | 0.007 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.083 | 0.013 |
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".