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Abstract: One Third of Plastic and Surgical Patients Have Limited Health Literacy: A Systematic Review and Meta-Analysis

2017· review· en· W2756772260 on OpenAlexaff
Mélissa Roy, Joseph P. Corkum, Steven J. McCabe, Christine B. Novak, Herb von Schroeder, David R. Urbach, Karen Okrainec

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2017
Typereview
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineHealth literacyMEDLINEPsychological interventionData extractionHealth carePopulationFamily medicinePerioperativeMeta-analysisSystematic reviewRandomized controlled trialNursingSurgeryEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Health literacy has been defined as the extent to which patients are able to understand and act upon health information.1 Limited or inadequate health literacy has been shown to have a negative impact on patient satisfaction, clinical outcomes, and risk of hospitalization.2,3 This complex concept is of high importance for surgeons as their patients have to comprehend the nature, risks and benefits of surgical procedures, adhere to strict perioperative rules, and make complex care decisions about interventions or lack thereof.4 The aim of this review was to evaluate the prevalence of reported inadequate health literacy levels and the measurement tools used in the plastic and surgical patient populations. METHODS: A systematic review and meta-analysis was conducted according to the Cochrane guidelines. Relevant studies reporting health literacy measurements in surgical patient populations were identified from MEDLINE and Embase published from inception until January 14th2017. Two-stage screening and data extraction were performed by two independent reviewers. Data on study design, sample size, patient population, health literacy measurement tool, and prevalence of inadequate health literacy were extracted and analyzed. RESULTS: A total of 934 abstracts were screened, 103 articles were reviewed and 57 met inclusion criteria. Five randomized controlled trials, 8 prospective cohorts, 36 cross-sectional studies were included including only 11 (19.0%) studies published before 2010. 18,894 surgical patients were included in these studies and the prevalence of inadequate health literacy was 32.8% (range 2.8–80.7%, 95%CI: 25.9–40.1). Fifteen (26.3%) studies did not present health literacy measurement results. Numerous health literacy measurement tools were used (16 validated, 6 non-validated). Only five studies pertained to the hand surgery and one to the plastic surgery literature. CONCLUSION: Our review demonstrates a high prevalence of limited health literacy within the plastic and overall surgical patient populations. While there is considerable variation in measurement tools currently being used, our review suggests a great need for patient-education and decision-aid tools for surgical patients with limited health literacy. Reference Citations: 1. Nielsen-Bohlman L, Institute of Medicine. Health Literacy: A Prescription to End Confusion. Washington, DC: The National Academies Press; 2004. 2. Berkman ND, Sheridan SL, Donahue KE, Halpern DJ, Viera A, Crotty K, et al. Health literacy interventions and outcomes: an updated systematic review. Evid Report Technology Assess. 2011;199:1–941. 3. Komenaka IK, Nodora JN, Machado L, Hsu CH, Klemens AE, Martinez ME, et al. Health literacy assessment and patient satisfaction in surgical practice. Surgery. 2014;155:374–383. 4. McCaffery KJ, Smith SK, Wolf M. The challenge of shared decision making among patients with lower literacy: a framework for research and development. Med Decis Making. 2010;30:35–44.

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)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.516
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0210.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.241
GPT teacher head0.493
Teacher spread0.252 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations5
Published2017
Admission routes1
Has abstractyes

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