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Record W2605344818 · doi:10.1177/1049732317707726

Experience of Touch in Health Care: A Meta-Ethnography Across the Health Care Professions

2017· review· en· W2605344818 on OpenAlexaff
Martina Kelly, Lara Nixon, Caitlin McClurg, Albert Scherpbier, Nigel King, Tim Dornan

Bibliographic record

VenueQualitative Health Research · 2017
Typereview
Languageen
FieldSocial Sciences
TopicPsychology of Social Influence
Canadian institutionsUniversity of Calgary
FundersArnold P. Gold Foundation
KeywordsEthnographyHealth carePsychologyNursingHealth professionsMedicineSociologyPolitical scienceAnthropology

Abstract

fetched live from OpenAlex

Touch mediates health professionals' interactions with patients. Different professionals have reported their practices but what is currently lacking is a well-theorized, interprofessional synthesis. We systematically searched eight databases, identified 41 studies in seven professions-nursing (27), medicine (4), physiotherapy (5), osteopathy (1), counseling (2), psychotherapy (1), dentistry (1)-and completed a meta-ethnographic line-of-argument synthesis. This found that touch is caring, exercises power, and demands safe space. Different professions express care through the medium of touch in different ways. They all, however, expect to initiate touch rather than for patients to do so. Various practices negotiate boundaries that define safe spaces between health care professions and patients. A metaphor-the waltz-integrates the practice of touch. Health care professionals connect physically with patients in ways that form strong relationships between them while "dance steps" help manage the risk that is inherent in such an intimate form of connection.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.046
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.910
GPT teacher head0.808
Teacher spread0.102 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreReview

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

Citations100
Published2017
Admission routes1
Has abstractyes

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