Systematic Review on Socioeconomic Factors in Medical School Access and Progression

Pin-Hsiang Huang's systematic review and meta-analysis examines the impact of financial and economic disadvantage on student selection and progression in medical schools. The study, hosted on Jeehp Dataverse, includes research from PubMed, Scopus, ERIC, Embase, ProQuest, and EBSCO covering 2005 to 2025. It employed an active machine-learning screening process and assessed risk of bias using the Risk of Bias Instrument.

Use Cases

• Conducting meta-analyses on socioeconomic disadvantage based on the described binary effect sizes and random-effects model.
• Modeling the relationship between parental income/occupation and medical school outcomes based on the socioeconomic indicators mentioned.
• Assessing risk of bias in educational research based on the application of the Risk of Bias Instrument described.
• Training machine learning models for study screening based on the active machine-learning process used in selection.

Strengths

• Systematic methodology using an active machine-learning screening process for study selection.
• Risk of bias was formally assessed using the Risk of Bias Instrument.
• Analysis includes a defined time range of literature from 2005 to 2025.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect publication bias inherent to systematic reviews of academic literature.

Provenance

Source

Jeehp Dataverse

Collection Method

Systematic review and meta-analysis of studies from PubMed, Scopus, ERIC, Embase, ProQuest, and EBSCO.

Time Range

2005–2025

Freshness

Last updated 2026-05-06 20:52:57; freshness should be verified.

Geography

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