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Record W2884106197 · doi:10.1111/medu.13684

How can tomorrow's doctors be more caring? A phenomenological investigation

2018· article· en· W2884106197 on OpenAlexafffund
Hannah Gillespie, Martina Kelly, Gerard Gormley, Nigel King, Drew Gilliland, Tim Dornan

Bibliographic record

VenueMedical Education · 2018
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsUniversity of Calgary
FundersQueen's UniversityQueen's University Belfast
KeywordsHermeneutic phenomenologyNarrativeLived experiencePhenomenology (philosophy)Qualitative researchPhenomenonPsychologyContext (archaeology)NursingMedical educationMedicineSocial psychologyPsychotherapistEpistemologySociology

Abstract

fetched live from OpenAlex

CONTEXT: Peabody's maxim 'the secret of the care of the patient is in caring for the patient' inspired generations of doctors to relate humanely to patients. Since then, phrases such as 'managed care' have impersonalised caring. The term 'patient-centred' was introduced to re-personalise caring. Ironically, however, such terms have been defined by professionals' preconceptions rather than patients' experiences. Using patients' experiences of doctors being (un)caring to guide doctors' learning could reinvigorate caring. Interpretive phenomenology provides qualitative research tools with which to do this. METHODS: Ten patients, purposively selected to have broad experiences of primary, secondary and tertiary health care, consented to participate. To stay close to their lived experiences, participants first drew 'Pictor' diagrams to represent relationships between themselves and professionals during remembered experiences of (un)caring. A researcher then used the depictions to structure in-depth, one-to-one explorations of the lived experience of caring. Verbatim transcripts were analysed using template analysis. To remain very close to patients' experiences, the researchers assembled a narrative description of the phenomenon of caring using participants' own words. RESULTS: Caring doctors were genuine. They allowed their own individuality to interact with patients' individuality. This made participants feel recognised as individuals, not just diseases. Caring doctors listened and spoke carefully, encouraged expressions of emotion, were accessible and responsive, and formed relationships. These factors empowered participants to be actively involved in their own care. Little things like smiling, shaking hands, admitting uncertainty, asking a colleague for advice and calling a participant unexpectedly at home showed that doctors were prepared to 'go above and beyond'. This was caring. CONCLUSIONS: These findings provide medical educators with an interpretation of caring that is truly patient-centred. Coupling technical proficiency with human qualities - being genuinely empathic and respectful - within doctor-patient relationships is the essence of caring.

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)0.006
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.338
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.324
Teacher spread0.297 · 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 designNot applicable
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

Citations39
Published2018
Admission routes2
Has abstractyes

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