Primary health care reform, dilemmatic space and risk of burnout among health workers
Bibliographic record
Abstract
Health system changes may increase primary health care workers' dilemmatic space, created when reforms contravene professional values. Dilemmatic space may be a risk factor for burnout. This study partnered with six Australian primary health care services (in South Australia: four state government-managed services including one Aboriginal health team and one non-government organisation and in Northern Territory: one Aboriginal community-controlled service) during a period of change and examined workers' dilemmatic space and incidence of burnout. Dilemmatic space and burnout were assessed in a survey of 130 staff across the six services (58% response rate). Additionally, 63 interviews were conducted with practitioners, managers, regional executives and health department staff. Dilemmatic space occurred across all services and was associated with higher rates of self-reported burnout. Three conditions associated with dilemmatic space were (1) conditions inherent in comprehensive primary health care, (2) stemming from service provision for Aboriginal and Torres Strait Islander peoples and (3) changes wrought by reorientation to selective primary health care in South Australia. Responses to dilemmatic space included ignoring directives or doing work 'under the radar', undertaking alternative work congruent with primary health care values outside of hours, or leaving the organisation. The findings show that comprehensive primary health care was contested and political. Future health reform processes would benefit from considering alignment of changes with staff values to reduce negative effects of the reform and safeguard worker wellbeing.
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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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".