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Record W6973603233 · doi:10.57760/sciencedb.15849

Vision impairment and subsequent daily activity limitation: A systematic review and meta-analysis

2024· dataset· en· W6973603233 on OpenAlexaboutno aff

Bibliographic record

VenueScienceDB · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsActivities of daily livingChecklistAssociation (psychology)Visual impairmentForest plot

Abstract

fetched live from OpenAlex

Table 1. PRISMA 2020 Checklist 4Table 2. MOOSE Checklist 7Supplementary Material 3. Literature search strategy. 9Table 4. A list of the excluded studies and reasons for their exclusion. 13Table 5. Quality assessment and publication bias evaluation of included study using the Newcastle-Ottawa Scale (NOS) 16Figure 1. Forest plot of correlation between vision impairment and difficulties with activity of daily living. 18Figure 2. Forest plot of correlation between vision impairment and difficulties with instrumental activity of daily living. 19Figure 3. Forest plot of the association between vision impairment and difficulties with activity of daily living. 20Figure 4. Forest plot of the association between vision impairment and difficulties with activity of daily living using pooled SMD analysis. 21Figure 5. Forest plot of the association between vision impairment and difficulties with activity of daily living using another pooled SMD analysis. 22Figure 6. Forest plot of the association between vision impairment and difficulties with activity of daily living based on different ADL assessments. 23Figure 7. Sensitivity analysis for the association between vision impairment and difficulties with activity of daily living based on different ADL assessments. 24Figure 8. Forest plot of the association between vision impairment and difficulties with activity of daily living based on severity of vision impairment. 25Figure 9. Forest plot of the association between vision impairment and difficulties with activity of daily living based on different assessments of ADL. 26Figure 10. Forest plot of the association between vision impairment and difficulties with activity of daily living based on different vision impairment characteristics. 27Figure 11. Forest plot of the association between vision impairment and difficulties with instrumental activity of daily living. 28Figure 12. Forest plot of the association between vision impairment and difficulties with instrumental activity of daily living based on different vision assessments. 29Figure 13. Forest plot of the association between vision impairment and difficulties with instrumental activity of daily living based on severity of vision assessments. 30Figure 14. Forest plot of the association between vision impairment and difficulties with instrumental activity of daily living based on different assessments of IADL. 31Figure 15. Sensitivity analysis for the association between vision impairment and difficulties with instrumental activity of daily living based on different vision impairment characteristics. 32Figure 16. Forest plot of the association between vision impairment and difficulties with instrumental activity of daily living based on different vision impairment characteristics. 33Figure 17. Funnel plot for publication bias: ADL difficulties for people with 18-99 years. 34Figure 18. Funnel plot for publication bias: ADL difficulties for people with ≥65 years. 35Figure 19. Funnel plot for publication bias: ADL difficulties for moderate to severe vision impairment 36Figure 20. Funnel plot for publication bias: Self-reported vision impairment and ADL difficulty. 37Figure 21. Funnel plot for publication bias: Objectively measured vision impairment and ADL difficulty. 38Figure 22. Funnel plot for publication bias: Self-reported ADL difficulty and vision impairment 39Figure 23. Funnel plot for publication bias: Objectively-measurement ADL difficulty and vision impairment 40Figure 24. Funnel plot for publication bias: IADL difficulties in people with 18-99 years. 41Figure 25. Funnel plot for publication bias: ADL difficulties IADL difficulties in people with ≥65 years. 42Figure 26. Funnel plot for publication bias: Self-reported IADL difficulty and vision impairment 43Figure 27. Funnel plot for publication bias: Objectively measured IADL difficulty and vision impairment 44Figure 28. Funnel plot for publication bias: IADL difficulties for moderate to severe vision impairment 45Figure 29. Funnel plot for publication bias: Objectively measured vision impairment and IADL difficulty. 46Figure 30. Funnel plot for publication bias: Self-reported vision impairment and ADL difficulty. 47

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)0.020
metaresearch head score (Gemma)0.077
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.077
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0120.024
Bibliometrics0.0100.013
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0300.001

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 head0.070
GPT teacher head0.364
Teacher spread0.293 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreDataset

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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