Development and psychometric evaluation of the Primary Health Care Engagement (PHCE) Scale: a pilot survey of rural and remote nurses
Bibliographic record
Abstract
AIM: To report the development and psychometric evaluation of a scale to measure rural and remote (rural/remote) nurses' perceptions of the engagement of their workplaces in key dimensions of primary health care (PHC). BACKGROUND: Amidst ongoing PHC reforms, a comprehensive instrument is needed to evaluate the degree to which rural/remote health care settings are involved in the key dimensions that characterize PHC delivery, particularly from the perspective of professionals delivering care. METHODS: This study followed a three-phase process of instrument development and psychometric evaluation. A literature review and expert consultation informed instrument development in the first phase, followed by an iterative process of content evaluation in the second phase. In the final phase, a pilot survey was undertaken and item discrimination analysis employed to evaluate the internal consistency reliability of each subscale in the preliminary 60-item Primary Health Care Engagement (PHCE) Scale. The 60-item scale was subsequently refined to a 40-item instrument. FINDINGS: The pilot survey sample included 89 nurses in current practice who had experience in rural/remote practice settings. Participants completed either a web-based or paper survey from September to December, 2013. Following item discrimination analysis, the 60-item instrument was refined to a 40-item PHCE Scale consisting of 10 subscales, each including three to five items. Alpha estimates of the 10 refined subscales ranged from 0.61 to 0.83, with seven of the subscales demonstrating acceptable reliability (α ⩾ 0.70). The refined 40-item instrument exhibited good internal consistency reliability (α=0.91). The 40-item PHCE Scale may be considered for use in future studies regardless of locale, to measure the extent to which health care professionals perceive their workplaces to be engaged in key dimensions of PHC.
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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 | 0.016 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".