Delivering an Online Cognitive Behavioral Therapy Program to Address Mental Health Challenges Faced by Correctional Workers and Other Public Safety Personnel: Protocol for a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Public safety personnel have regular and often intense exposure to potentially traumatic events at work, especially workplace violence in the case of correctional workers. Subsequently, correctional workers are at higher risk of developing mental health problems such as posttraumatic stress disorder. Public safety personnel are up to 4 times more likely to experience suicidal ideation, suicidal attempts, and death by suicide compared to the general population. Despite this high prevalence, help-seeking behaviors from public safety personnel are low due to stigma and irregular work hours limiting access to care. Innovative treatments are needed to address these challenges. OBJECTIVE: This study will investigate the efficacy of an electronically delivered cognitive behavioral therapy (e-CBT) program tailored to correctional workers' mental health problems. METHODS: This study is composed of 4 phases. In phase 1, we will interview correctional workers individually and in focus groups to identify personal, social, and cultural factors affecting their mental health and barriers to care. Phase 2 will use the information gathered from the interviews to develop gender- and diagnosis-specific e-CBT modules. These will be presented to a new group of participants who will provide further feedback on their usability and accessibility. In phase 3, we will randomly assign participants to either an e-CBT or treatment as usual arm. The program will be evaluated with validated symptomatology questionnaires and interviews. Phase 4 will use this additional information to fine-tune the e-CBT modules for a larger-scale randomized controlled trial design comparing the e-CBT program to in-person CBT. All e-CBT modules will be delivered through a secure online platform. RESULTS: The study received ethics approval in December 2020, and participant recruitment began in March 2021. Participant recruitment has been conducted through targeted advertisements and physician referrals. To date, there have been 15 participants recruited for Phase 1, and it is expected to conclude in July 2021, with phase 2 beginning in September 2021. Complete data collection and analysis from all phases are expected to conclude by July 2023. Linear and binomial regression (for continuous and categorical outcomes, respectively) will be conducted along with interpretive qualitative methods. CONCLUSIONS: If proven efficacious and feasible, this e-CBT program can provide a high-quality and clinically validated resource to address the mental health problems of correctional workers. Additionally, findings can contribute to the development of innovative treatments for other public safety professions. TRIAL REGISTRATION: ClinicalTrials.gov NCT04666974; https://www.clinicaltrials.gov/ct2/show/NCT04666974. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30845.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.047 | 0.009 |
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".