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Record W2264944417

Attachment and compassion fatigue among American and Israeli mental health clinicians working with traumatized victims of terrorism.

2005· article· en· W2264944417 on OpenAlexaff
Christine Racanelli

Bibliographic record

VenuePubMed · 2005
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsCanadian Mental Health Association
Fundersnot available
KeywordsCompassion fatigueBurnoutMental healthClinical psychologyPsychologyAnxietyMediationCompassionPsychiatryMedicine
DOInot available

Abstract

fetched live from OpenAlex

This study compared the construct of compassion fatigue with the role of attachment as a potential mediator among mental health clinicians working with victims of terrorism in the New York metropolitan region of the United States and Israel. Differences between clinicians practicing within Israel (n = 31) and New York (n = 35), in terms of their symptoms of compassion fatigue, compassion satisfaction, and "burnout," were not significant, as measured by multivariate analyses of variance. Based upon nonsignificant differences, mediational statistical tests could not be run; thus, mediation did not hold. The data failed to support a significant difference between compassion fatigue and attachment avoidance or anxiety. However, data collection resulted in attenuated scores for compassion fatigue and compassion satisfaction within both study groups of clinicians and moderate to average scores for burnout. Israeli clinicians had significantly more avoidant attachment dimensions than their New York cohorts. The strongest predictors of compassion satisfaction were (a) low attachment anxiety and (b) sufficient clinical experience related to treating victims of trauma. The strongest predictors of burnout were (a) minimal clinical experience, (b) minimal experience working with trauma victims, and (c) greater avoidant attachment dimensions.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.278
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.059
GPT teacher head0.376
Teacher spread0.317 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations26
Published2005
Admission routes1
Has abstractyes

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