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Record W2067504026 · doi:10.1080/15325020500358225

Development of the Coping Strategies Inventory for Trauma Counselors

2005· article· en· W2067504026 on OpenAlexaff
TED BOBER, Cheryl Regehr, Yanqiu Zhou

Bibliographic record

VenueJournal of Loss and Trauma · 2005
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsUniversity of TorontoOntario Medical Association
Fundersnot available
KeywordsCoping (psychology)PsychologyClinical psychologyApplied psychology

Abstract

fetched live from OpenAlex

There is increasing awareness about the negative consequences of counseling traumatized people. Emanating from qualitative research and clinical reflections, suggestions are frequently made regarding self-care strategies to reduce the impact. However, no tools exist for measuring these strategies to determine the effectiveness of engaging in self-care behaviors. This study evaluates the Coping Strategies Inventory which measures beliefs and behaviors regarding coping in trauma counselors. Items were derived from the practice literature and a focus group with experienced therapists. A factor analysis was conducted with a sample of 259 trauma therapists and 71 hospital workers. Results demonstrated a consistent factor structure with adequate internal reliability. The CSI may thus be useful in research on vicarious trauma and for self-appraisal of counselors.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.057
GPT teacher head0.346
Teacher spread0.289 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations44
Published2005
Admission routes1
Has abstractyes

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