P070 Cultural determinants of Sleep Health for First Nations adolescents: Perspectives of Service Providers in Remote Communities
Bibliographic record
Abstract
Abstract Background Despite established links between sleep and mental health across the general population, sleep health within a First Nations context is less understood. Moreover, there remains a dearth of culturally responsive approaches for Australian First Nations communities, including adolescents. This qualitative study explores the cultural determinants of First Nations adolescents’ sleep health, drawing on yarning sessions with service providers in remote Northern Queensland (NQ) communities as part of the Let’s Yarn About Sleep Project. Methods Ten yarning sessions were conducted with health and wellbeing and education service providers (N= 27; 23 female; 12 Indigenous) in remote NQ. First Nations community researchers reviewed the data and the Lowitja Cultural Determinants of Health and Wellbeing Framework was used to culturally ground the work and thematically organise First Nations adolescents’ sleep health narratives. Results Preliminary analysis revealed Family, Kinship and Community; and Self-determination and Leadership as key cultural determinants to First Nations adolescents’ sleep health. Participants emphasised there is no ‘one-size-fits-all’ approach, suggesting sleep health programs should be guided by place-based, culturally sensitive, First Nations-led, methods sensitive to myriad determinants of sleep health. Discussion Adopting a strengths-based approach, this study sought to situate First Nations adolescents’ sleep health within a rights-based, First Nations-led framework. Findings suggest future sleep health initiatives must privilege First Nations voices and be guided by a holistic health and wellbeing concept, encompassing place-based, culturally responsive and First Nations-led local service delivery. This study advocates for upstream determinants of health to guide future sleep health research, practice and policy.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".