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Record W3037370546 · doi:10.2147/ppa.s257454

<p>Experiences and Views of Medicine Information Among the General Public in Thailand</p>

2020· article· en· W3037370546 on OpenAlexaboutno aff
Kamonphat Wongtaweepkij, Janet Krska, Juraporn Pongwecharak, Narumol Jarernsiripornkul

Bibliographic record

VenuePatient Preference and Adherence · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFamily medicineQuarter (Canadian coin)Public healthAlternative medicineHealth professionalsBonferroni correctionHealth careNursing

Abstract

fetched live from OpenAlex

PURPOSE: Written and electronic medicine information are important for improving patient knowledge and safe use of medicines. Written medicine information in Thailand is mostly in the form of printed package inserts (PIs), designed for health professionals, with few medicines having patient information leaflets (PILs). The aim of this study was to determine practices, needs and expectations of Thai general public about written and electronic medicine information and attitudes towards PILs. PATIENTS AND METHODS: Cross-sectional survey, using self-completed questionnaires, was distributed directly to members of the general public in a large city, during January to March 2019. It explored experiences of using information, expectations, needs and attitudes, the latter measured using a 10-item scale. Differences between sub-groups were assessed, applying the Bonferroni correction to determine statistical significance. RESULTS: Of the total 851 questionnaires distributed, 550 were returned (64.2%). The majority of respondents (88%) had received PIs, but only a quarter (26.2%) had received PILs. Most respondents (78.5%) had seen medicine information in online form. High educational level and income increased the likelihood of receiving PILs and electronic information. The majority of respondents (88.5%) perceived PILs as useful, but 70% considered they would still need information about medicines from health professionals. Indication, drug name and precautions were the most frequently read information in PIs and perceived as needed in PILs. Three-quarters of respondents would read electronic information if it were available, with more who had received a PIL having previously searched for such information compared to those who had not. All respondents had positive overall attitudes towards PILs. CONCLUSION: Experiences of receiving PILs and electronic medicine information in Thailand are relatively limited. However, the general public considered PILs as a useful source of medicine information. Electronic medicine information was desired and should be developed to be an additional source of information for consumers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.138
GPT teacher head0.387
Teacher spread0.249 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations10
Published2020
Admission routes1
Has abstractyes

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