MétaCan
Menu
Back to cohort
Record W2301777715 · doi:10.18438/b8rk73

Evaluation of Self-Ratings for Health Information Behaviour Skills Requires More Heterogeneous Sample, but Finds that Public Library Print Collections and Health Information Literacy of Librarians Needs Improvement

2016· article· en· W2301777715 on OpenAlexvenueno aff
Carol Perryman

Bibliographic record

VenueEvidence Based Library and Information Practice · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsnot available
Fundersnot available
KeywordsHealth literacyInformation literacyMedicineTest (biology)Public healthEthnic groupMedical educationInformation seekingInformation needsGerontologySample (material)Scale (ratio)Family medicinePsychologyHealth careNursingLibrary scienceSociologyPedagogy

Abstract

fetched live from OpenAlex

A Review of:
 Yi, Y. J. (2015). Consumer health information behavior in public libraries: A qualitative study. The Library Quarterly: Information, Community, Policy, 85(1), 45-63. http://dx.doi.org/10.1086/679025 
 
 Abstract
 
 Objective – To understand public library users’ perceptions of ability to locate, evaluate, and use health information; to identify barriers experienced in finding and using health information; and to compare self-ratings of skills to an administered instrument.
 
 Design – Mixed methods.
 
 Setting – Main library and two branches of one public library system in Florida.
 
 Subjects – 20 adult library users purposively selected from 131 voluntary respondents to a previously conducted survey (Yi, 2014) based on age range, ethnicity, gender, and educational level. Of the 20, 13 were female; 11 White, 8 Black, 1 Native American; most had attained college or graduate school education levels (9 each), with 2 having graduated from high school. 15 respondents were aged 45 or older. 
 
 Methods – Intensive interviews conducted between April and May 2011 used critical incident technique to inquire about a recalled health situation. Participants responded to questions about skill self-appraisal, health situation severity, information seeking and assessment behaviour, use of information, barriers, and outcome. Responses were compared to results of the short form of the Test of Functional Health Literacy in Adults (S-TOFHLA) test, administered to participants. 
 
 Main Results – On a scale of 100, participants’ S-TOFHLA scores measured at high levels of proficiency, with 90% rating 90 points or above. Self-ratings of ability to find health information related to recalled need were ”excellent” (12 participants) or “good” (8 participants). Fourteen participants did not seek library assistance; 12 began their search on the Internet, 5 searched the library catalogue, and 3 reported going directly to the collection. Resource preferences were discussed, although no frequency descriptions were provided. 90% of participants self-rated their ability to evaluate the quality of health information as “good” or “excellent.” Participants selected authority, accuracy, and currency as the most important criteria of quality evaluation; however, other important criteria such as editorial review of content were not mentioned. Participants rated their ability to use health information as either “excellent” (17) or “good” (3). 
 
 Conclusion – Use of health information enabled health behaviour change for participants, although conflicting information tended to increase anxiety. Barriers to success in all areas of inquiry include difficulties with terminology, collection limitations, asking a librarian for assistance, and lack of awareness of resources. Librarians should improve their health literacy skills in order to advise on all aspects of health information seeking, evaluation, and use. Collaborative efforts are suggested, such as special libraries and public library efforts, and health professional workshops or seminars offered to public library patrons.

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)0.008
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.796
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.419
Open science0.0000.000
Research integrity0.0000.000
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 head0.058
GPT teacher head0.405
Teacher spread0.348 · 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.

Study designOther design
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

Citations3
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueEvidence Based Library and Information PracticeSame topicHealth Literacy and Information AccessibilityFrench-language works237,207