Measuring partnership synergy and functioning: Multi-stakeholder collaboration in primary health care
Bibliographic record
Abstract
In primary health care, multi-stakeholder partnerships between clinicians, policy makers, academic representatives and other stakeholders to improve service delivery are becoming more common. Literature on processes and approaches that enhance partnership effectiveness is growing. However, evidence on the performance of the measures of partnership functioning and the achievement of desired outcomes is still limited, due to the field's definitional ambiguity and the challenges inherent in measuring complex and evolving collaborative processes. Reliable measures are needed for external or self-assessment of partnership functioning, as intermediate steps in the achievement of desired outcomes. We adapted the Partnership Self-Assessment Tool (PSAT) and distributed it to multiple stakeholders within five partnerships in Canada and Australia. The instrument contained a number of partnership functioning sub-scales. New sub-scales were developed for the domains of communication and external environment. Partnership synergy was assessed using modified Partnership Synergy Processes and Partnership Synergy Outcomes sub-scales, and a combined Partnership Synergy scale. Ranking by partnership scores was compared with independent ranks based on a qualitative evaluation of the partnerships' development. 55 (90%) questionnaires were returned. Our results indicate that the instrument was capable of discriminating between different levels of dimensions of partnership functioning and partnership synergy even in a limited sample. The sub-scales were sufficiently reliable to have the capacity to discriminate between individuals, and between partnerships. There was negligible difference in the correlations between different partnership functioning dimensions and Partnership Synergy sub-scales. The Communication and External Environment sub-scales did not perform well metrically. The adapted partnership assessment tool is suitable for assessing the achievement of partnership synergy and specific indicators of partnership functioning. Further development of Communication and External Environment sub-scales is warranted. The instrument could be applied to assess internal partnership performance on key indicators across settings, in order to determine if the collaborative process is working well.
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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 | 0.086 | 0.123 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".