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2023· article· en· W6961315020 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFigshare · 2023
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPsidium guajava Extracts and Applications
Canadian institutionsnot available
Fundersnot available
KeywordseHealthChecklistHealth literacyLiteracyHealth careThe InternetScale (ratio)Quality (philosophy)MEDLINE

Abstract

fetched live from OpenAlex

<div><p>Introduction</p><p>Electronic health has the potential benefit to the health system by improving health service quality efficiency effectiveness and reducing the cost of care. Having good e-health literacy level is considered essential for improving healthcare delivery and quality of care as well as empowers caregivers and patients to influence control care decisions. Many studies have done on eHealth literacy and its determinants among adults, however, inconsistent findings from those studies were found. Therefore, this study was conducted to determine the pooled magnitude of eHealth literacy and to identify associated factors among adults in Ethiopia through systematic review and meta-analysis.</p><p>Method</p><p>Search of PubMed, Scopus, and web of science, and Google Scholar was conducted to find out relevant articles published from January 2028 to 2022. The Newcastle-Ottawa scale tool was used to assess the quality of included studies. Two reviewers extracted the data independently by using standard extraction formats and exported in to Stata version11 for meta-analysis. The degree of heterogeneity between studies was measured using I2 statistics. The publication bias between studies also checked by using egger test. The pooled magnitude of eHealth literacy was performed using fixed effect model.</p><p>Result</p><p>After go through 138 studies, five studies with total participants of 1758 were included in this systematic review and Meta-analysis. The pooled estimate of eHealth literacy in Ethiopia was found 59.39% (95%CI: 47.10–71.68). Perceived usefulness (AOR = 2.46; 95% CI: 1.36, 3.12),educational status(AOR = 2.28; 95% CI: 1.11, 4.68), internet access (AOR = 2.35; 95% CI: 1.67, 3.30), knowledge on electronic health information sources(AOR = 2.60; 95% CI: 1.78, 3.78), electronic health information sources utilization (AOR = 2.55; 95%CI: 1.85, 3.52), gender (AOR = 1.82; 95% CI: 1.38, 2.41) were identified significant predictors of e-health literacy.</p><p>Conclusion and recommendation</p><p>This systematic review and meta-analysis found that more than half of study participants were eHealth literate. This finding recommends that creating awareness about importance of eHealth usefulness and capacity building to enhance and encouraging to use electronic sources and availability of internet has para amount to solution to increase eHealth literacy level of study participants.</p></div>

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.492
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.6430.320

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 head0.318
GPT teacher head0.501
Teacher spread0.183 · 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