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Record W2032573502 · doi:10.1097/sga.0b013e3181b85c66

Assessing the Quality of Care in a Regional Integrated Viral Hepatitis Clinic in British Columbia

2009· article· en· W2032573502 on OpenAlexafffundabout
Tracy Christianson, Donna Moralejo

Bibliographic record

VenueGastroenterology Nursing · 2009
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsThompson Rivers University
FundersBritish Columbia Centre for Disease Control
KeywordsCourtesyMedicineFamily medicineNursingCoping (psychology)Psychiatry

Abstract

fetched live from OpenAlex

Four regional viral hepatitis clinics in British Columbia provide accessible integrated care and services but have not been evaluated. The purpose of this cross-sectional study was to assess clients' perceptions of the quality of care and services received, what aspects of care were important, and what the effect of care was on their ability to cope. Clients who had received care at one of the clinics were surveyed by using two self-administered questionnaires. The Hepatitis C Virus Questionnaire asked clients to rate five aspects of care related to general clinic, physician, and nurse services. The open-ended questions of the Aspects of Care Questionnaire explored clients' perceptions of the aspects of care considered to be the most and least helpful. The response rate was 55% (115 of 210). The highest rated items were with the professional aspects of care, whereas the lowest rated were with the educational items. Only 46.3% of the clients felt that the clinic staff taught them the necessary skills to cope with their disease. The results showed that the courtesy, continuity of care, and educational aspects of care had significant differences by age, antiviral treatment status, genotype, and gender (p < .05). Although the clients valued the professional aspects of care, findings highlight the need for improved communication, follow-up, and education about coping and managing hepatitis C. Results will be helpful for improving integrated service delivery.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.047
GPT teacher head0.406
Teacher spread0.359 · 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 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

Citations5
Published2009
Admission routes3
Has abstractyes

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