Royal Far West's Allied Health Telehealth Services for Children Post‐Bushfires
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effectiveness of Royal Far West allied health telehealth services to support the health and well-being of children affected by the bushfires. SETTING: In response to the 2019/2020 Black Summer bushfires, Royal Far West (RFW) implemented the Community Recovery Services (CRS) targeting the health and well-being of affected children. One component of the CRS was the delivery of allied health telehealth services to children. PARTICIPANTS: One hundred and thirty-five children participated in occupational therapy, psychology and/or speech pathology telehealth. Forty-eight parents/carers completed a telehealth satisfaction survey. DESIGN: Measures used to determine effectiveness included child and parent/carer satisfaction surveys, the Canadian Occupational Performance Measure (COPM), the Goal Attainment Scale (GAS) and the Strengths and Difficulties Questionnaire (SDQ). RESULTS: The children overwhelmingly stated that they felt listened to (89%), enjoyed telehealth sessions (84%) and learned new ways to cope with their feelings (87%). Parents/carers reported that children had developed effective emotional regulation and coping strategies. COPM outcomes indicated the children demonstrated statistically significant large improvements in their self-perceived performance of and satisfaction with their identified goals, p < 0.001. The GAS outcomes indicated that 86% of children attained or exceeded their set goals. A statistically significant improvement in children's mental health outcomes post-telehealth was found, as measured by the SDQ (p < 0.05). CONCLUSION: Occupational therapy, psychology and speech pathology telehealth sessions contributed to positive health and well-being outcomes for children affected by the bushfires. The findings support the implementation of RFW's five key principles for telehealth services: (1) Access to a multidisciplinary team; (2) Practical resources; (3) Flexible delivery; (4) Providing in-person session to support telehealth and (5) Take a 'whole of child' approach. Innovative telehealth offered children in geographically remote areas access to effective allied health support post-disaster that was not readily available in their local communities.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
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".