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Record W3014089200 · doi:10.1080/08870446.2020.1743293

The experience of care coordination for people living with multimorbidity at risk of hospitalisation: an interpretative phenomenological analysis

2020· article· en· W3014089200 on OpenAlexfundno aff
Annette Peart, Christopher Barton, Virginia Lewis, Grant Russell

Bibliographic record

VenuePsychology and Health · 2020
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsInterpretative phenomenological analysisContext (archaeology)Intervention (counseling)PsychologyQualitative researchPerceptionNursingPhenomenology (philosophy)Health careMultimorbidityLived experienceMedicineSociologyPsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

Objective: There is growing interest in improving the care of people living with multimorbidity who require care coordination to help manage their health and reduce risk of hospitalisation. There has been limited past research exploring experiences of care for people living with multimorbidity. This qualitative study sought to explore the care experience of people enrolled in a care coordination intervention.Design: We interviewed 23 people living with multimorbidity enrolled in a care coordination intervention to examine their perceptions of the care experience. We used interpretative phenomenological analysis to identify themes from participants’ perspectives of involvement in their care, using information to make decisions, and the meanings they made of their care experiences.Results: We identified three master themes of the participants’ experience of care: Needing expert guidance, Circle of care, and I want to be spoken to like a person. We discuss these findings in the context of the recent literature on person-centred care.Conclusion: Understanding participants’ experience of care reinforces the need for person-centred approaches. These findings suggest care coordination offered to people living with multimorbidity can be implemented through practical support and information alongside establishing a relationship of trust.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.140

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.068
GPT teacher head0.416
Teacher spread0.347 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2020
Admission routes1
Has abstractyes

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