Direct and indirect effects of mindfulness, PTSD, and depression on self-stigma of mental illness in OEF/OIF veterans.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Two of the most common and costly mental health diagnoses among military veterans who served in the post-9/11 conflicts in Afghanistan and Iraq are posttraumatic stress disorder (PTSD) and depression, but over half of veterans who screen positive for these problems do not seek treatment. A key barrier is self-stigma of mental illness. Mindfulness has shown promise as an explanatory variable in the context of mental health symptoms and self-stigma, but these associations are underexplored in the veterans' literature. This study examines direct and indirect effects among mindfulness, PTSD and depression, and self-stigma in post-9/11-era military veterans. METHOD: A sample of 577 veterans from 3 large American cities completed surveys capturing mindfulness, symptoms of PTSD and depression, and self-stigma. A structural equation modeling approach was used to examine direct and indirect effects among study variables. RESULTS: Mindfulness was associated with less PTSD and depression and indirectly with less self-stigma through the PTSD pathway. PTSD was associated with more depression and self-stigma, and depression was not significantly associated with self-stigma. CONCLUSION: PTSD is strongly associated with self-stigma in military veterans, many of whom do not seek mental health treatment. Findings show that mindfulness is a promising intervention target for reducing symptoms of PTSD directly and reducing associated self-stigma of mental illness indirectly. Additional investigation of links between mindfulness, PTSD and depressive symptoms, and self-stigma in military veterans is warranted. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it