Impacts of child welfare worker and clientele characteristics on attitudes toward trauma informed-care
Bibliographic record
Abstract
Background: There is increasing recognition of the need to integrate trauma-informed care (TIC) into child welfare practices, given the high rates of trauma experiences among children and youth across these settings. The implementation of TIC is facilitated by various elements, including worker attitudes, yet further research is needed to illuminate the factors that influence child welfare workers’ positive regard for TIC. Objectives: This study aims to explore the relationship between child welfare worker attitudes regarding TIC with workers’ and clients’ individual characteristics. Methods: N = 418 child welfare workers from 11 agencies completed two measures: a demographic questionnaire as well as the French translated version of the ARTIC-35 questionnaire comprised of five subscales. Linear mixed effects models were run for each ARTIC subscale, examining how child and worker factors affect attitudes toward TIC. Results: Participants indicated relatively positive attitudes toward TIC. Managerial staff in offender units scored higher on the subscale regarding their beliefs about the causes underlying child behaviors and on the subscale regarding beliefs about the secondary effects of trauma, than their counterparts in protection units serving boys. Managers scored higher than frontline staff on worker self-efficacy, response to problem behavior, and on-the-job behavior subscales. Workers with a community college degree—and not a university degree–indicated greater sense of self-efficacy. Conclusions: This study points to the importance of paying attention to the characteristics of both workers and clients that may influence inclination toward TIC principles, as a means to build effective integration of this approach in child-serving settings.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".