Evidence map›Paper›PMID 21545445›Full record

ArticleSociology of health & illness2011

An interactional approach to conceptualising small talk in medical interactions.

Pamela L Hudak, Douglas W Maynard

Abstract read
In one paragraph

Article in Sociology of health & illness, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Pamela L HudakDepartment of Medicine, St Michael's Hospital, Toronto, Ontario, Canada. plhudak@gmail.com
Douglas W Maynard

Funding

INFORMED DECISION MAKING IN OLDER PATIENTS AND SURGEONSR01AG018781 · NIA · NATIONAL OPINION RESEARCH CENTER · PI LEVINSON, WENDY · 2001 to 2004
$1.9M
Exploring Racial Differences in CommunicationR03HS015579 · AHRQ · NATIONAL OPINION RESEARCH CENTER · PI HUDAK, PAMELA L · 2006 to 2006
$100k
AHRQ HHS R03 HS015579AHRQ HHS #R03 HS015579-01A1NIA NIH HHS #R01 AG018781NIA NIH HHS R01 AG018781
6 · The paper itself

Abstract

In medical interactions, it may seem straightforward to identify 'small talk' as casual or social talk superfluous to the institutional work of dealing with patients' medical concerns. Such a broad characterisation is, however, extremely difficult to apply to actual talk, and more specificity is necessary to pursue analyses of how small talk is produced and what it achieves for participants in medical interactions. We offer an approach to delineating a subgenre of small talk called topicalised small talk (TST), derived on the basis of conversation analytically-informed analyses of routine consultations involving orthopaedic surgeons and older patients. TST is a line of talk that is referentially independent from their institutional identities as patients or surgeons, oriented instead to an aspect of the personal biography of one (or both), or to some neutral topic available to interactants in any setting (e.g. weather). Importantly, TST is an achievement of both patient and surgeon in that generation and pursuit of topic is mutually accomplished. In an exploratory but systematic analysis, when this approach was applied to a purposive sample of surgeon-patient interactions, TST was much more prevalent in visits with White than African American patients. Accounts for possible ethnic differences in TST are suggested.

Indexed as

CommunicationConcept FormationPhysician-Patient RelationsFemaleHumansMaleMiddle Aged

Identifiers

PMID21545445
PMCPMC3609551

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.