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Record W4288041082 · doi:10.3390/healthcare10081391

Patient-Reported Experiences and Satisfaction with Rural Outreach Clinics in New South Wales, Australia: A Cross-Sectional Study

2022· article· en· W4288041082 on OpenAlexaff
Md Irteja Islam, Claire O’Neill, Hibah Kolur, Sharif Bagnulo, Richard Colbran, Alexandra Martiniuk

Bibliographic record

VenueHealthcare · 2022
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsUniversity of TorontoQueen's University
FundersNational Health and Medical Research Council
KeywordsOutreachCross-sectional studyFamily medicinePatient satisfactionMedicineLogistic regressionRural healthRural areaHealth careNursingInternal medicine

Abstract

fetched live from OpenAlex

Introduction: Many studies have been conducted on how physicians view outreach health services, yet few have explored how rural patients view these services. This study aimed to examine the patient experience and satisfaction with outreach health services in rural NSW, Australia and the factors associated with satisfaction. Methods: A cross-sectional study was conducted among patients who visited outreach health services between December 2020 and February 2021 across rural and remote New South Wales, Australia. Data on patient satisfaction were collected using a validated questionnaire. Both bivariate (chi-squared test) and multivariate analyses (logistic regression) were performed to identify the factors associated with the outcome variable (patient satisfaction). Results: A total of 207 participants were included in the study. The mean age of respondents was 58.6 years, and 50.2% were men. Ninety-three percent of all participants were satisfied with the outreach health services. Respectful behaviours of the outreach healthcare practitioners were significantly associated with the higher patient satisfaction attending outreach clinics. Conclusions: The current study demonstrated a high level of patient satisfaction regarding outreach health services in rural and remote NSW, Australia. Further, our study findings showed the importance of collecting data about patient satisfaction to strengthen outreach service quality.

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)0.001
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.172
GPT teacher head0.475
Teacher spread0.303 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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