The Action Project Method Applied in Nursing Home Settings
Bibliographic record
Abstract
The Action-Project Method (A-PM) is a qualitative research approach used to understand the actions and experiences co-constructed by individuals. We applied the A-PM in a nursing home (NH) setting with the aim to explore how NH residents and the people closest to them describe their priorities for care and act on these priorities. Due to the health of residents, the demands on staff and family members, and general issues around scheduling, applying the A-PM in the setting required adaptations. The core focus of this article is on the necessary adaptations to apply the A-PM in a NH setting. (1) The A-PM is typically longitudinal with multiple data collection cycles; however, given the circumstances surrounding the residents’ health and the highly structured institutional setting, we opted for a single round of data collection. (2) During recruitment, three residents asked to participate alone, which we accommodated to acknowledge their experiences. (3) The setting posed challenges to data collection such as ensuring privacy and avoiding interruptions, but these challenges often reinforced participants’ experiences. With the necessary adaptations the A-PM in NHs gives voice to participants while contextualizing that within their core relationships.
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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 | 0.077 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.027 | 0.003 |
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".