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Beyond surface characteristics: a new health text-specific readability measurement
Hyeoneui Kim1, Sergey Goryachev, Graciela Rosemblat
1Decision Systems Group, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
A new health-specific readability tool accurately assesses medical texts. Unlike general formulas, it correctly identifies electronic health records as the most difficult material, improving health communication.
Area of Science:
- Health communication
- Medical informatics
- Natural language processing
Background:
- Assessing the readability of health materials is crucial for consumer understanding and effective personal health records.
- General readability formulas may not accurately reflect the complexity of medical and consumer health content.
Purpose of the Study:
- To develop and pilot a novel health-specific readability measure.
- To evaluate the performance of this new measure against general readability formulas using diverse health-related texts.
Main Methods:
- A new readability tool was created, focusing on semantic, syntactic features, and text unit length.
- The tool was applied to four text types: consumer health, electronic health records, health news, and biomedical journals.
- Results were compared with three established general readability formulas.
Main Results:
- General formulas underestimated the difficulty of electronic health records, grouping them with consumer health texts.
- The developed health-specific measure identified electronic health records as the most challenging document type.
- Correlations between the new method and general formulas for other text types were strong (r ≈ 0.81–0.85, p < .0001).
Conclusions:
- The health-specific readability tool offers a more accurate assessment for medical materials, particularly electronic health records.
- This improved accuracy can aid in creating more understandable health information resources.
- The tool shows promise for enhancing the clarity and accessibility of diverse health-related content.
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