Development and Evaluation of a Child Welfare Trauma-Informed Care Beliefs Scale
Bibliographic record
Abstract
This dissertation includes four manuscripts that detail the development and evaluation of the Trauma-Informed Care Beliefs Scale-Comprehensive (TIBS-C). A scale that measures child welfare carer beliefs about trauma-informed care (TIC) practices. The TIC literature lacks psychometric scales that measure TIC beliefs for carers, who play an integral role in supporting young people. Existing TIC literature indicates that favourable TIC beliefs in carers are associated with improved outcomes for young people, carers, and agencies. Furthermore, implementation science indicates that beliefs may be a predictor of behaviour. However, research showing this in child welfare tends to use scales with unknown psychometric properties. The study reported in the first manuscript, the Trauma-Informed Care Beliefs Scale-Brief (TIBS-B) presented in Chapter 2, reanalysed data from a previous study, using Rasch methodology to develop a brief tool, from which a later and more comprehensive scale could be developed. This study identified several limitations, including bias responses related to item wording and response format. The subsequent process of scale development aimed to address these limitations. The results of the Rasch analyses, however, indicated a good fit and sound psychometric properties for the final 13-item scale of the TIBS-B. The TIBS-B can be used in research and practice when time prevents the TIBS-C from being completed. Chapter 3 presents a comprehensive scoping review on 32 published TIC studies. The aim of this review was to address the theoretical limitations of the study presented in Chapter 2 and help in the development of a more comprehensive scale measuring TIC beliefs. The review indicated that better TIC practices resulted in reduced psychopathology of young people, more stable placements, fewer reports of maltreatment in care, improved carer confidence, and reduced carer stress. The review provided further evidence to support the relationship between favourable TIC beliefs and positive outcomes for young people. The review was used to identify the three main carer-related TIC constructs to be included in the TIBS-C. The constructs were trauma-informed strategies for carers to use with their young person, knowledge of the impact of trauma on young people, and carer self-care and self-reflection strategies to prevent burnout and compassion fatigue. The manuscript presented in Chapter 4, used the studies presented in Chapters 2 and 3 to create 61 candidate items. These were presented to 719 participants who were active carers from Australia, the United States of America (US), Canada, the United Kingdom (UK), and the Republic of Ireland. The resulting data was analysed with Rasch analyses and identified a final scale of 35 items with sound psychometric properties, good internal reliability consistency, unidimensionality, and no differential item functioning (e.g., age or gender). Chapter 5 presents the manuscript that evaluated the construct validity of the TIBS-C. Participants (N = 255) from Australia, the US, Canada, the UK, and the Republic of Ireland completed the TIBS-C carer functioning, carer experience, and psychopathology measures (in relation to the young person they were caring for). The results demonstrated good construct validity, with high TIBS-C scores being associated with carer compassion, TIC knowledge, reduced carer stress, and high psychopathology in young people. Chapter 6 summarises the results of each chapter, the strengths, limitations, future directions, and clinical and practice utility of the TIBS-C.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".