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Record W2092970199 · doi:10.1080/09503153.2013.786695

Multiprofessional Views on Older Patients’ Participation in Care Planning Meetings in a Hospital Context

2013· article· en· W2092970199 on OpenAlexaff
Sarah Donnelly, Janet Carter-Anand, Suzanne Cahill, Brenda Mehigan, Desmond O’Neill

Bibliographic record

VenuePractice · 2013
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsTrinity College
Fundersnot available
KeywordsMultidisciplinary approachContext (archaeology)Citizen journalismFocus groupResource (disambiguation)NursingPatient participationHealth careMedicinePsychologyPublic relationsSociologyPolitical science

Abstract

fetched live from OpenAlex

Care planning meetings (CPMs; sometimes referred to as family meetings) for older patients involve group decision-making between the multidisciplinary team, the older person and their family. However, service user participation is challenged by the inequity of knowledge and power between participants, together with organisational and resource pressures for timely discharge. The effective use and perhaps, potential misuse of communication strategies within CPMs is of ethical concern to all participants. Habermas’ essential critique of participatory communication provides insight as to how older people’s involvement can be either enabled or blocked by healthcare professionals (HCPs) depending on their use of communication strategies. Seven discipline-specific mini-focus groups provided an opportunity for HCPs to reflect on the participation of patients over 65 and their families in CPMs. Findings explore HCPs’ understanding of older patients involvement based on key dimensions of communicative participation, namely, mutuality, inclusiveness, patient centredness and clear outcomes. Whilst the benefits of collaborative decision-making were confirmed, legitimate concerns as to the quality of participatory practices, limited attention to group work processes and the exclusion of older patients with cognitive impairment were identified.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.184
GPT teacher head0.487
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations25
Published2013
Admission routes1
Has abstractyes

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