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Record W4206035896 · doi:10.1177/20101058211068601

Communication Vulnerability within Singapore’s Healthcare Environment

2021· article· en· W4206035896 on OpenAlexaboutno aff
Teck Wah William Go, Hoi Tong Mok, Sanchalika Acharyya, Darlin C. Suelo, Eu Chin Ho

Bibliographic record

VenueProceedings of Singapore Healthcare · 2021
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHealth careVulnerability (computing)PerceptionQuarter (Canadian coin)Health communicationPatient satisfactionNursingFamily medicineMedical emergencyPsychologyCommunication

Abstract

fetched live from OpenAlex

Communication difficulties can, and often do, create barriers between patients and healthcare workers (HCWs). We examined the perceptual differences between patients and caregivers; and HCWs with regards to their perceived communication vulnerabilities and identified communication needs in a tertiary hospital. A survey was conducted in selected outpatient settings among patients, their caregivers and HCWs, in a cross-sectional study. Respondents rated the reasons and frequency of encountering the communication difficulties during a hospital visit. Fifty-four percent of patients and caregivers cited poor hearing in the presence of noise, while HCWs cited patient’s poor vision (87%) as their primary communication barrier that requires improvement. Majority of HCWs (90%) had encountered patients who presented multiple communication barriers a quarter of the time. A third of HCWs felt that such encounters were especially challenging during communication, with very limited strategies available to deal with such communication vulnerable individuals. Patients, caregivers and HCWs universally experience communication challenges, even if their perceived barriers to communication happen to differ. Such perceptual difference between patients and HCWs may lead to inconsistent use of communication strategies by HCWs, potentially compromising patient’s healthcare needs. Nonetheless, the onus is on healthcare providers to bridge this communication gap to improve patient care.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.106
GPT teacher head0.384
Teacher spread0.278 · 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 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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

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