MétaCan
Menu
Back to cohort
Record W1991042912 · doi:10.1177/1078155207082017

Impact on patient satisfaction with a structured counselling approach on natural health products

2008· article· en· W1991042912 on OpenAlexaff
Suzanne C. Malfair Taylor, Mário L de Lemos, Dennis Jang, J. -P. De Man, Dawn Annable, Saira Mithani, Leela John, Thanh Vu, Robin K O’Brien

Bibliographic record

VenueJournal of Oncology Pharmacy Practice · 2008
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsMedicinePatient satisfactionFamily medicinePharmacyWorkloadIntervention (counseling)Breast cancerPhysical therapyCancerNursingInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: Natural health products (NHP) are commonly used by cancer patients. The provision of better information on NHP may improve the patient satisfaction and quality of life. We report the impact on patient satisfaction by routine counselling on NHP. METHODS: Patients visiting the pharmacy of a comprehensive cancer centre for the first time were recruited before (control) and after (intervention) the introduction of routine structured counselling on NHP by pharmacists. The primary endpoint was patient satisfaction. Overall cost and cost per improvement in satisfaction were estimated. RESULTS: 265 patients completed the questionnaires. The average age was about 60 years old, with roughly equal number of men and women. Breast and genitor-urinary cancers made up about 80% of the patients. Nearly 45% of patients had some college or university education. The scores for overall satisfaction and each subscale were all increased in the intervention group. This was statistically significant regarding information on NHP. Counselling was associated with an increase of about 9 minutes of counselling time and a mean additional cost of CDN$7.49 per patient. CONCLUSION: We found increased patient satisfaction with routine counselling on NHP. There was only minimal increase in workload and cost for each counselling section.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.501
Threshold uncertainty score0.503

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 head0.083
GPT teacher head0.442
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

Citations9
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Oncology Pharmacy PracticeSame topicComplementary and Alternative Medicine StudiesFrench-language works237,207