<p>Dataset.</p>

Muhammed Ayas published a dataset on figshare in April 2026 containing results from a descriptive cross-sectional online questionnaire. The data includes responses from 235 participants, primarily health-sciences students and faculty, assessing their recognition of audiology's professional scope in hearing and balance care. A composite scope-of-practice recognition outcome was derived, and logistic regression identified predictors of full recognition.

Use Cases

• Analyze predictors of full scope-of-practice recognition based on logistic regression results.
• Compare recognition rates for hearing-loss diagnosis versus balance-disorder care based on scenario-based classification tasks.
• Model interprofessional role conceptualization during training based on multidisciplinary vignette responses.
• Examine associations between audiology awareness and scope recognition based on the reported odds ratio.

Strengths

• Dataset is openly licensed under CC-BY-4.0.
• Specific participant count (235) and response rates (e.g., 90.0% for hearing-loss diagnosis) are provided.
• Analysis includes a derived composite outcome and logistic regression with a reported odds ratio (OR 1.80).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data reflects a specific sample of health-sciences students and faculty, which may limit generalizability to practicing clinicians.

Provenance

Source

figshare, author Muhammed Ayas.

Collection Method

Descriptive cross-sectional online questionnaire administered to health-sciences students and faculty.

Time Range

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Freshness

Last updated 2026-04-09 17:30:39; freshness should be verified.

Geography

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