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Record W4318933993 · doi:10.2196/40466

Internet Use for Obtaining Medicine Information: Cross-sectional Survey

2023· article· en· W4318933993 on OpenAlexvenueno aff
Trine Strand Bergmo, Vilde Sandsdalen, Unn Sollid Manskow, Lars Småbrekke, Marit Waaseth

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsnot available
FundersInnovative Medicines InitiativeEuropean CommissionEuropean Federation of Pharmaceutical Industries and Associations
KeywordsThe InternetNorwegianPharmacyOddsFamily medicineCross-sectional studyMedical prescriptionMedicineInternet privacyPsychologyNursingWorld Wide WebInternal medicineLogistic regression

Abstract

fetched live from OpenAlex

BACKGROUND: The internet is increasingly being used as a source of medicine-related information. People want information to facilitate decision-making and self-management, and they tend to prefer the internet for ease of access. However, it is widely acknowledged that the quality of web-based information varies. Poor interpretation of medicine information can lead to anxiety and poor adherence to drug therapy. It is therefore important to understand how people search, select, and trust medicine information. OBJECTIVE: The objectives of this study were to establish the extent of internet use for seeking medicine information among Norwegian pharmacy customers, analyze factors associated with internet use, and investigate the level of trust in different sources and websites. METHODS: This is a cross-sectional study with a convenience sample of pharmacy customers recruited from all but one community pharmacy in Tromsø, a medium size municipality in Norway (77,000 inhabitants). Persons (aged ≥16 years) able to complete a questionnaire in Norwegian were asked to participate in the study. The recruitment took place in September and October 2020. Due to COVID-19 restrictions, social media was also used to recruit medicine users. RESULTS: A total of 303 respondents reported which sources they used to obtain information about their medicines (both prescription and over the counter) and to what extent they trusted these sources. A total of 125 (41.3%) respondents used the internet for medicine information, and the only factor associated with internet use was age. The odds of using the internet declined by 5% per year of age (odds ratio 0.95, 95% CI 0.94-0.97; P=.048). We found no association between internet use and gender, level of education, or regular medicine use. The main purpose reported for using the internet was to obtain information about side effects. Other main sources of medicine information were physicians (n=191, 63%), pharmacy personnel (n=142, 47%), and medication package leaflets (n=124, 42%), while 36 (12%) respondents did not obtain medicine information from any sources. Note that 272 (91%) respondents trusted health professionals as a source of medicine information, whereas 58 (46%) respondents who used the internet trusted the information they found on the internet. The most reliable websites were the national health portals and other official health information sites. CONCLUSIONS: Norwegian pharmacy customers use the internet as a source of medicine information, but most still obtain medicine information from health professionals and packet leaflets. People are aware of the potential for misinformation on websites, and they mainly trust high-quality sites run by health authorities.

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)0.029
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0290.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0000.009
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.005

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 head0.505
GPT teacher head0.645
Teacher spread0.140 · 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; both teacher heads agree on what is shown here.

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

Citations24
Published2023
Admission routes1
Has abstractyes

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