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Record W2017734942 · doi:10.1016/s0886-3350(03)00234-7

Informed consent for cataract surgery: What patients do and do not understand

2003· article· en· W2017734942 on OpenAlexaff
Daniel Scanlan, Farhan Asif Siddiqui, Gail Perry, Cindy Hutnik

Bibliographic record

VenueJournal of Cataract & Refractive Surgery · 2003
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsWestern University
Fundersnot available
KeywordsInformed consentTerminologyRecallMedicineCataract surgeryAutonomyOutcome (game theory)SurgeryFamily medicinePhysical therapyPsychologyAlternative medicine

Abstract

fetched live from OpenAlex

PURPOSE: To determine patients' understanding and opinions about the usefulness of the informed consent (IC) document for cataract surgery and evaluate the deterioration in the effectiveness of verbal and written IC over time. SETTING: Academic tertiary care center. METHODS: Multiple-choice questionnaires addressing specific information about cataract surgery were distributed to patients. The questionnaires covered topics such as treatment, risk, and outcome probabilities (assessed preoperatively and postoperatively); terminology commonly used in IC; and patients' opinions about IC. Scores were calculated and compared using paired and unpaired t tests. RESULTS: Twenty-six patients thought that their legal autonomy would be waived by signing a consent form. Patients who took part in a standardized discussion of IC before testing scored 73.4% versus 23.4% in a control group who received no IC counseling (P<.001). Patient recall of outcome probabilities significantly decreased between preoperative and postoperative testing (61.2% to 44.0%) when IC was given verbally but improved to 75.0% when patients were given written information to take home. CONCLUSIONS: Patients about to consent to cataract surgery had a reasonable grasp of basic terminology. A standardized IC discussion was effective in educating patients. Patients considered IC to be important and expected all pertinent information to be communicated. Patient recall of outcome probabilities was poorer than that of nonnumeric facts; however, memory decay may be slowed by providing supporting take-home literature.

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)0.002
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0000.001
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 head0.285
GPT teacher head0.432
Teacher spread0.147 · 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 designObservational
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

Citations46
Published2003
Admission routes1
Has abstractyes

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