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Record W7057784163

The Likelihood of Seeking Information on OTC Medicines

2023· dissertation· en· W7057784163 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2023
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsDescriptive statisticsRanking (information retrieval)Intraclass correlationScale (ratio)Product (mathematics)Sample (material)
DOInot available

Abstract

fetched live from OpenAlex

Over-the-counter medicines have been reported as safe medicines by Canadians, yet there are concerns about their misuse and adverse drug reactions. Previous evidence shows that users of these medicines obtain information from sources such as professionals, relatives, friends, news and print media, and product labels. However, little is known about how likely and extensively consumers would seek information relative to other consumer products. The study purposed to explore the likelihood and extent of seeking information about OTC medicines relative to common consumer products, as a surrogate of the importance consumers place on such medication. The study was cross-sectional and descriptive in design. Common consumer products (10 non-drug and five OTC medicines) and 15 OTC medicines were selected for comparative purposes. Saskatchewan residents were asked to rate these products on a scale of 1 to 10 for the likelihood and extent of information-searching and product familiarity. Impressions of effectiveness and safety of OTC medicines were also provided on the same scale. A scale was developed to measure consumer Propensity to Self-Medicate. Test-retest reliability was estimated using Pearson correlation coefficients (r), Intraclass Correlation Coefficients (ICC) and Paired Sample t-tests. Descriptive and inferential analyses of the findings were undertaken. A total of 575 responses were gathered, for a response rate of 19.2 percent. The mean age of respondents was 63.0 years and 61.6 percent were female. The likelihood respondents will search for information about OTC medicines had a similar rating to common consumer products, ranking less than televisions, coffee makers, and bike helmets, but more than body lotion, sunglasses, and red wine. Product familiarity ranged from 5.8 for headache medicines down to 3.9 for red wine (10-point scale). A moderate rating was given to the perception of safety and effectiveness for the 15 OTC medicines. Product effectiveness ranged from 7.3 for headache medicines to Athlete’s Foot creams at 5.1. Product safety for adult cough syrups was slightly higher than such products for children. Factors motivating self-medication among respondents are associated with their perception on Purchase Involvement, Self-Efficacy, Awareness of Care Needed during Self-Medication, and Perceived Usefulness of OTC Medications. The tendency to self-medicate was higher among women and the elderly. Given the potential for OTC medicines to help resolve symptoms, but also do harm, sufficient care must be undertaken when deciding to use one. While the likelihood to search for information on OTC medicines was similar to rather mundane consumer products, it is too early to consider the two groups as possessing similar levels of importance to the public. But it is concerning. There is a plethora of information currently available to consumers on such medicines; motivating them to access it may need attention. The development of a Propensity to Self-Medicate scale was exploratory and novel, and may be relevant in future research for different population settings and contexts

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)0.002
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.027
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.005
GPT teacher head0.184
Teacher spread0.179 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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