The Action Project Method Applied in Nursing Home Settings
Bibliographic record
Abstract
Abstract The action-project method (APM), developed in counselling psychology and used in various disciplines, has been shown to be useful for understanding major life transitions in different contexts. We argue that the APM is beneficial for studying the impact of nursing home (NH) home admission and daily life of residents and their families/friends. The APM enables researchers to explore how residents and their families/friends experience NH-life at individual and supraindividual levels of analysis. We applied the APM to solicit the views of residents and individuals close to them to understand their priorities for quality care. The APM data collection consisted of three stages. First, a resident and family member or other caregiver met with the interviewer who initiated a conversation about their experience in the NH. The interviewer then left the room but video-recorded the conversation. Second, the interviewer met with each participant to review the video with each participant offering reflection on the original conversation. These sessions were also recorded. Following transcription and analysis of the conversations, 3 lay-language narratives were created: 1 for each individual and 1 for the pair. Third, participants reviewed their own and the pair’s narrative for additional comments. The APM offers a means to give a voice to NH residents and allows for people to talk about their experiences without the presence of a researcher. By using the APM, researchers can break down individual actions of participants and how these actions come together to form the project of navigating care in NHs.
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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 | 0.092 | 0.073 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".