Evidence map›Paper›PMID 34534509›Full record

ArticleCanadian journal of ophthalmology. Journal canadien d'ophtalmologie2023

Improving the patient decision-making experience for cataract surgery during the COVID-19 era.

Lily Xu, Paul S Mundra, Aseel Anabtawai, Forough Farrokhyar, Brian J Chan

Abstract read
In one paragraph

Article in Canadian journal of ophthalmology. Journal canadien d'ophtalmologie, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Lily XuDepartment of Health Sciences, McMaster University, Hamilton, ON.
Paul S MundraDepartment of Health Sciences, McMaster University, Hamilton, ON.
Aseel AnabtawaiDepartment of Surgery, McMaster University, Hamilton, ON.
Forough FarrokhyarDepartment of Surgery, McMaster University, Hamilton, ON.
Brian J ChanDivision of Surgery, Department of Ophthalmology, McMaster University, Hamilton, ON.. Electronic address: brianjchan19@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo explore whether video-based patient decision aids (VBPDAs) for cataract surgery consultation can enhance a patient's decision-making process while upholding safety regulations during the coronavirus disease 2019 (COVID-19) pandemic.

designSingle-centre consecutive case study.

participants147 patients, with an average age of 70 years, who came in for a cataract surgery consult were enrolled in this study.

methodsAll patients watched part 1 of the VBPDA outlining the process of cataract surgery and the decisions involved. Patients then underwent cataract surgery consultation with an ophthalmologist. Afterward, if the patient was indicated for surgery, part 2 of the VBPDA was played. At the end of the visit, all patients completed a survey assessing the effects of COVID-19 safety precautions on their appointment. In addition, patients who had gone forward with surgery complete the Decisional Conflict Scale (DCS).

resultsFor patients proceeding with cataract surgery, the median DCS score was 9.38 (range, 0-54.69, min-max) on a scale from 0 to 100 (low-high decisional conflict). A DCS score <25 indicates low decisional conflict (n = 76, 68.47%) and a score >25 indicates feeling unsure (n = 35, 31.53%). The DCS also can be separated into various subscales: the informed subscale (median = 8.33; min-max = 0-66.67), values subscale (16.67, 0-58.33), support subscale (8.33, 0-50.00), uncertainty subscale (8.33, 0-83.33), and effective decision subscale (0, 0-37.50).

conclusionOur study found VBPDAs to be an effective tool to enhance the patient decision-making process for cataract surgery during the COVID-19 era.

Indexed as

CataractCataract ExtractionCOVID-19AgedDecision MakingHumansReferral and ConsultationSurveys and Questionnaires

Identifiers

PMID34534509
PMCPMC8384583

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.