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Record W2417415120

Patient pain: its influence on primary care physician-patient interaction.

2003· article· en· W2417415120 on OpenAlexaff
Klea D. Bertakis, Rahman Azari, Edward J. Callahan

Bibliographic record

VenuePubMed · 2003
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsCentre for Family Medicine
Fundersnot available
KeywordsMedicinePrimary carePrimary care physicianFamily medicineVisual analogue scaleMEDLINEHealth carePhysical therapy
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Heightened awareness of the importance of appropriate pain management in health care delivery has stimulated researchers to examine the impact of patient pain on medical encounters. In this study, we explored how patient pain might influence the physician-patient interaction during medical visits. METHODS: New adult patients (n = 509) were randomized to see primary care physicians in videotaped visits at a university medical center Self-reported patient pain was measured before the visit using the Visual Analog Scale and the Medical Outcomes Study Short Form-36 (MOS SF-36) pain scale; patient sociodemographics were also measured. Physician practice style during the visit was analyzed with the Davis Observation Code (DOC). RESULTS: Regression analyses revealed that patient pain during the medical visit was associated with the physician spending a greater portion of the visit on technical tasks and a smaller portion on preventive services and other activities designed to encourage the patients' active participation in their own health care. CONCLUSIONS: Patient pain may influence the physician-patient interaction and its outcomes. Primary care physicians should be aware that there may be less focus on patients' active involvement in their own care and less emphasis on providing disease prevention when treating patients who are experiencing pain.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.961
Threshold uncertainty score0.500

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 head0.013
GPT teacher head0.216
Teacher spread0.203 · 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 designOther design
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

Citations17
Published2003
Admission routes1
Has abstractyes

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