RAISe‐ing awareness: Person‐centred care in coercive mental health care environments—A scoping review and framework development
Bibliographic record
Abstract
WHAT IS KNOWN ON THE SUBJECT?: In mental healthcare environments, there are times when people are forced into care (i.e. to take medications or be hospitalized) when they may not want it. It is difficult to understand how person-centred care (i.e. supporting patients to lead decisions about their care) can occur within coercive settings. There is a gap in the literature about this topic as few studies have explored it. WHAT THIS PAPER ADDS TO EXISTING KNOWLEDGE?: This paper examines the research publicly available to better understand if person-centred care can exist at times when people are forced into mental health care. The paper develops a conceptual framework, RAISe (Relationship, Agency, Information, Safe environment), for understanding this matter in order to help people apply this concept in practice In certain situations, with caring and respectful approaches, with and for patients, it is possible to provide person-centred care at times when mental health care is forced. RAISe identifies ways in which this can be done by clinicians while working with people. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: These person-centred approaches need to be applied across mental health systems so that people in forced mental healthcare scenarios continue to experience dignity and respect. This is particularly important for nurses who are often the ones providing direct care to patients in these environments. ABSTRACT: Introduction Person-centred care (PCC) is founded on a theoretical premise that the person who the care issue pertains to directs the decisions relating to them. This can raise ethical challenges when mental health care is forced. Aim This paper reports on how PCC is provided in coercive mental healthcare environments and its outcomes, where reported. Method A scoping review methodology was utilized to search the literature in English until December 2019 (inclusive). Results Twenty articles were included in the review. The information found was diverse and addressed different aspects of PCC in coercive mental healthcare environments. Discussion Overall, this area is understudied. Despite ethical challenges, there are opportunities to provide PCC in coercive mental healthcare environments. A novel conceptual framework, RAISe (Relationship, Agency, Information, Safe environment), is presented to assist in applying PCC in these environments. Further research investigating how to employ these practices across systems should occur. Implications for Practice This review acknowledges the challenges of providing PCC in coercive mental healthcare environments, while suggesting that this type of care can still be delivered in general as well as specific ways. This is especially relevant for nurses who provide direct care within these environments.
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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 | 0.028 | 0.072 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.024 | 0.025 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".