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Record W1553131882

Secondary Traumatic Stress: The Hidden Trauma in Child and Youth Counsellors

2009· article· en· W1553131882 on OpenAlexaff
Michelle Linda Bloom

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2009
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsCompassion fatigueTraumatic stressClinical psychologyMedicinePsychology
DOInot available

Abstract

fetched live from OpenAlex

The current research study was conducted to establish evidence based research identifying Secondary Traumatic Stress (STS) in Child and Youth Counsellors (CYCs). 161 CYCs participated in an online survey responding to both demographic questions and Bride’s (1999) Secondary Traumatic Stress Scale (STSS). Data analysis included both descriptive and inferential testing. Scoring of the STSS revealed that 66.1% of the CYCs sampled experienced some level of STS. The overall mean score is 33.65 suggesting that CYCs experienced a mild level of STS. An independent group t-test indicated that CYC’s who were exposed to children and youth’s traumatic experience 1 to 3 times a week did not differ in the level of STS from CYC’s who were exposed to children and Youth’s traumatic experience over 4 times a week. A correlation analysis revealed a weak but positive relationship between the years of experience in the field of Child and Youth Care and the level of Secondary Traumatic Stress. Recommendations include educators incorporating this study in the teaching of STS to future CYCs; prevention and self care practices in the symptoms of STS. In addition, future research is needed to verify the current findings.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.971
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.242
Teacher spread0.226 · 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 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

Citations1
Published2009
Admission routes1
Has abstractyes

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