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Record W1528706188 · doi:10.18438/b8r30m

Time, Cost, Information Seeking Skills and Format of Resources Present Barriers to Information Seeking by Primary Care Practitioners in a Research Environment

2007· article· en· W1528706188 on OpenAlexvenueno aff
Martha Ingrid Preddie

Bibliographic record

VenueEvidence Based Library and Information Practice · 2007
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsnot available
Fundersnot available
KeywordsInformation seekingPopulationFamily medicinePrimary careDescriptive statisticsQuality (philosophy)Information needsHealth careMedicineNursingSample (material)Medical educationPsychologyLibrary scienceComputer science

Abstract

fetched live from OpenAlex

Objective – To determine the information seeking behaviors of primary care practitioners in order to inform future efforts towards the design of information services that would support quality in primary care. Design – A cross-sectional survey. Setting – A primary care practice based research network (PBRN) of caregivers who serve a broad population while simultaneously studying and disseminating innovations aimed at improvements in quality, efficiency and/or safety of primary health care in the United States. Subjects – All primary care practitioners in the PBRN including family practitioners, general practitioners, nurse practitioners and physician assistants. Methods – A questionnaire comprising twenty-six questions was distributed to 116 practitioners. Practitioners attached to academic centres (who were also members of the PBRN) were excluded in order “to achieve a sample of practices more representative of the primary care practising population” (208). Descriptive data were collected and analyzed. SPSS v11.5 was used for statistical analyses. Main results – There was a response rate of 51% (59 of 116). Fifty-eight percent of the respondents stated that they sought information (excluding drug dosing or drug interactions information) to support patient care several times a week. Sixty-eight per cent sought this information while the patient waited. Almost half of the respondents had access to a small medical library (48%) or a hospital library (46%), while 21% used a university medical library. Approximately 14% had no immediate access to a medical library. Almost 60% of practitioners stated that they had an e-mail account. Thirty-four percent agreed that the use of e-mail to communicate with patients enhanced medical practice, while 24% disagreed. There was frequent prescribing of Internet-based consumer health information to patients by only 16% of the practitioners, while Internet support groups were frequently recommended by 5%. The main barriers to information seeking were lack of time (76%), cost (33%), information seeking skills (25%), and format of information sources (22%). The use of EBM resources was fairly low, while there was a high preference for ready reference and interpersonal sources. When compared with print information resources, the use of online resources was moderate. A significant correlation was found between use of online sources and use of print sources, namely, that practitioners who used online sources more frequently, also sought information from print sources more frequently, with the inverse being true for those who sought information less frequently from either electronic or print sources. Conclusion – Primary care practitioners in this rural PBRN used print and interpersonal sources more than online sources. Practitioners who are more likely to use print sources are also more likely to seek online information. Librarians working in PBRN environments will need to identify interventions that address barriers such as time, cost, and information-seeking skills.

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)0.007
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.993
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.040
GPT teacher head0.404
Teacher spread0.364 · 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.

Study designObservational
DomainMethods
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

Citations8
Published2007
Admission routes1
Has abstractyes

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