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Record W4221124544 · doi:10.3390/traumacare2020010

Exploration of Trauma-Oriented Retreats: Quantitative Changes in Mental Health Measures for Canadian Military Members, Veterans and Royal Canadian Mounted Police with Posttraumatic Stress Disorder and Moral Injury

2022· article· en· W4221124544 on OpenAlexaffabout
Lorraine Smith‐MacDonald, Ashley Pike, Chelsea Jones, Suzette Brémault‐Phillips

Bibliographic record

VenueTrauma Care · 2022
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMoral injuryAngerPsychological resilienceMental healthAnxietyClinical psychologyMedicinePsychiatryLongitudinal studyTraumatic stressDepression (economics)PsychologyPsychotherapist

Abstract

fetched live from OpenAlex

Background: Military members, veterans, and public safety personnel have been noted to have a higher risk of exposure to potentially traumatic events and potentially morally injurious events resulting in operational stress injuries (OSI) such as posttraumatic stress disorder (PTSD) and moral injury (MI). Treatments that can quickly and effectively address these conditions are desperately needed. The purpose of this research was to identify the impact of participation in a non-evidence-based trauma-oriented retreat for the above populations experiencing PTSD and MI. Methods: This study was an embedded mixed-methods longitudinal study with parallel repeated quantitative measures designed to evaluate outcomes at 1, 3, 6, and 12 months after completion of the retreat. Results: Analysis showed a statistically significant reduction in self-reported symptoms of PTSD, anxiety, stress, depression, MI, anger, and emotional dysregulation pre/post-retreat, and an increase in resilience. Self-reported longitudinal results did not see a change in symptom scores, with participants continuing to maintain their clinical diagnoses post-retreat. Conclusions: The results from this study illustrate that trauma-oriented retreats may be a complementary treatment modality for OSI-related conditions but should not be seen as a first-line treatment option. Program evaluation, determination of the evidence-based nature of retreats, and standardization are yet needed.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.066
GPT teacher head0.364
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2022
Admission routes2
Has abstractyes

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