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Record W4410380523 · doi:10.1186/s12913-025-12830-6

Shifting the focus of child and youth wellbeing programs from crisis to prevention: a mixed methods study of the role of First Nations’ community-controlled organisations

2025· article· en· W4410380523 on OpenAlexaboutno aff
Janya McCalman, Merissa Nona, Mandy Edwards, Ruth Fagan, Vicki Saunders, Alexandra van Beek, Sandra Campbell, Mary Anne Furst, Luis Salvador‐Carulla

Bibliographic record

VenueBMC Health Services Research · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilMedical Research Council
KeywordsNursing researchHealth informaticsHealth administrationPublic healthMedicineFocus groupFocus (optics)Quality of Life ResearchSocial policyHealth services researchEnvironmental healthNursingEconomic growthPolitical scienceSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Australian governments and the First Nations Coalition of Peaks, through the Closing the Gap reforms, have committed to build the Aboriginal and Torres Strait Islander community-controlled sector and increase decision making by community-controlled services. This paper describes a First Nations-led place-based research program with community-controlled health and youth service partners in Far North Queensland to understand and map the regional child and youth wellbeing service system and co-design strategies to improve service provision. METHODS: This mixed-method research was conducted through a First Nations-led approach that is both place-based and systems focused. Following research planning workshops with community-controlled health and youth service partners, 47 staff members from 27 Cairns and Yarrabah intersectoral child and youth-wellbeing organisations were interviewed in 2021-22 to map the characteristics of their services. Their responses were coded using a modified version of the internationally validated Description and Evaluation of Services and DirectoriEs for Long Term Care (DESDE-LTC) mapping tool to determine the characteristics of whole system intersectoral services. Forty-four participants then attended co-design workshops in each place to discuss the results and identify further priorities. RESULTS: A high 68% of the main types of care were crisis-related services (focused on child protection, youth justice, mental illness, homelessness, illness/injury, and disengagement from education), with just a third (32%) focused on prevention/early intervention. Despite clear leadership from community-controlled services, only 23% of the main types of care were delivered by community-controlled organisations, with 51% delivered by mainstream non-government organisations, and 26% by government departments. Funding agreements drove the characteristics of services, with community-controlled organisations providing a higher proportion of the more complex crisis-oriented services, whilst non-government organisations received funding for preventive programs. Service providers prioritised a need for greater investment in prevention and early intervention, with community control of decision making considered critical to improving the appropriateness of care. CONCLUSIONS: These findings speak to the recent national commitment to increase decision making by Aboriginal and/or Torres Strait Islander community-controlled services. The recommendations of north Queensland regional service providers can inform improvements in the Closing the Gap reforms, and hence in the systems that support the wellbeing of First Nations children, youth and families.

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)0.037
metaresearch head score (Gemma)0.026
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.193

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0060.004
Scholarly communication0.0040.003
Open science0.0020.005
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 head0.044
GPT teacher head0.443
Teacher spread0.399 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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