Priorities and approaches to investigating Asian youth health: perspectives of young Asian New Zealanders
Bibliographic record
Abstract
INTRODUCTION: The proportion of young people in New Zealand identifying with Asian ethnicities has increased considerably. Despite some prevalent health concerns, Asian youth are less likely than non-Asian peers to seek help. As preparatory research towards a more nuanced approach to service delivery and public policy, this qualitative study aimed to identify young Asian New Zealanders' perspectives on best approaches to investigate health issues of priority concern to them. METHODS: Three semi-structured focus group discussions were conducted with 15 Asian youth leaders aged 18-24 years. Using an inductive approach for thematic analysis, key themes were identified and analysed. FINDINGS: Study participants considered ethno-cultural identity, racism and challenges in integration to play significant roles influencing the health of Asian youth (especially mental health) and their access to health services. While emphasising the importance of engaging young Asians in research and service development so that their needs and aspirations are met, participants also highlighted the need for approaches that are cognisant of the cultural, contextual and intergenerational dimensions of issues involved in promoting youth participation. CONCLUSION: Research that engages Asian youth as key agents using methods that are sensitive to their cultural and sociological contexts can inform more responsive health services and public policy. This is of particular relevance in primary health care where culturally competent services can mitigate risks of unmet health needs and social isolation.
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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 | 0.014 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.010 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".