‘Getting Everyone on the Same Page’: Long‐Term‐Care Nurses' Experiences With Advance Care Planning
Bibliographic record
Abstract
INTRODUCTION: Much of the literature examining the experiences of advance care planning (ACP) in long-term care (LTC) has been from the perspectives of residents and their families. Largely absent from the literature are the perspectives of LTC nurses, who are key members of the healthcare team most involved with LTC residents/families and well positioned to facilitate the ACP process. The purpose of this study was to develop an inductively derived empirical model to address this gap in empirical knowledge. METHODS: A constructivist grounded theory (CGT) methodology was used in this study of 25 nurses working in 18 different LTC facilities in central Canada. Data were collected using a demographic questionnaire; in-depth, semi-structured, audio-recorded and face-to-face/telephone interviews; field notes; and memos. Descriptive statistics and specific CGT coding procedures were used to analyse the data. RESULTS: The basic social process that emerged from the data was that of nurses trying to identify an ACP level and craft a corresponding care plan that they believed would optimise residents' comfort in LTC during both acute medical events and at the end-of-life (EOL). The empirically derived theoretical model that captured the experiences, processes and strategies of nurses to address the identified social process was orchestrating comfort: getting everyone on the same page. This model encompassed two main processes, downgrading and upgrading ACP levels, and two preconditions, piecing together the big picture and selling the big picture. CONCLUSIONS: Ensuring comfort for LTC residents at the end-of-life or during acute events by getting everyone on the same page is a complex process. The ability of nurses to downgrade or upgrade the ACP level to orchestrate comfort for LTC residents involves many factors related to the resident, family, healthcare providers and the context in which the ACP discussions take place. IMPLICATIONS OF PRACTICE: Providing ACP/dementia information in LTC admission packages and through informational sessions can raise family awareness of these topics and dementia's complications. Clinical rotations in LTC facilities for medical, nursing, and paramedic students could also improve their understanding of the sector's complexities.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".