Perceived Barriers to Prescribing PrEP, Logistic Regression Model

A multivariable logistic regression model predicting perceived barriers to prescribing PrEP, based on a sample of 102 observations. The dataset was authored by Deborah G. Smith and is available on figshare under a CC-BY-4.0 license.

Use Cases

• Train logistic regression models based on the multivariable analysis described.
• Analyze factors influencing PrEP prescribing decisions based on the described barrier variables.
• Benchmark predictive models for healthcare provider behavior based on the 102-observation sample.

Strengths

• The dataset is explicitly described as a multivariable logistic regression model, indicating a structured statistical analysis.
• The sample size is specified as 102 observations.
• The dataset is openly licensed under CC-BY-4.0.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Freshness

Last updated 2026-05-26 17:26:11; freshness should be verified.