Participatory action as a research method with public health nurses
Bibliographic record
Abstract
AIM: This article explores and describes participatory action research (PAR) as a preferred method in addressing nursing practice issues. This is the first study that used PAR with public health nurses (PHNs) in Canada to develop a professional practice model. BACKGROUND: Participatory action research is a sub-category of action research that incorporates feminist and critical theory with foundations in the field of social psychology. For nurses, critical analysis of long-established beliefs and practices through PAR contributes to emancipatory knowledge regarding the impact of traditional hierarchies on their practice. DESIGN: This study used participatory action, a non-traditional but systematic research method, which assisted participants to develop a solution to a long-standing organizational issue. METHOD: The stages of generating concerns, participatory action, acting on concerns, reflection and evaluation were implemented from 2012 - 2013 in an urban Canadian city, to develop a professional practice model for PHNs. FINDINGS: Four sub-themes specific to PAR are discussed. These are "participatory action research engaged PHNs in development of a professional practice model;" "the participatory action research cycles of "Look, Think, Act" expanded participants' views;" "participatory action research increased awareness of organizational barriers;" and "participatory action research promoted individual empowerment and system transformation." CONCLUSIONS: This study resulted in individual and system change that may not have been possible without the use of PAR. The focus was engagement of participants and recognition of their lived experience, which facilitated PHNs' empowerment, leadership and consciousness-raising.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".