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Identifying Unmet Needs in Major Depressive Disorder Using a Computer-Assisted Alternative to Conventional Thematic

Michelle A Worthington^1,2, Richard H Christie¹, Aaron J Masino^1,3

¹AiCure, New York, NY, United States.

JMIR Formative Research

|March 1, 2024

Summary

A hybrid qualitative analysis method offers a faster way to find unmet clinical needs for digital health tools. This approach helps develop practical tools to improve patient health outcomes.

Keywords:

consumer health informatics interview major depressive disorder medical informatics applications needs assessment psychiatry and psychology

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Area of Science:

Digital Health
Qualitative Research
Clinical Needs Assessment

Background:

Developing clinically relevant digital health tools requires understanding stakeholder needs.
Conventional qualitative data analysis is time-consuming and resource-intensive.
A time-efficient method for identifying target needs in digital tool development is needed.

Purpose of the Study:

To develop an accessible, simple, and time-efficient alternative to conventional thematic analysis for qualitative data.
To identify key themes from psychiatrist interviews for digital tool development targeting unmet clinical needs.

Main Methods:

Conducted 10 semistructured interviews with US psychiatrists treating major depressive disorder.
Used a hybrid analytical approach combining computer-assisted text analysis with deductive analysis.
Identified word frequencies, content categories, and themes related to unmet needs in care management.

Main Results:

Identified key areas of interest for clinicians in major depressive disorder care.
Revealed potential targets for digital tool development based on identified needs.

Conclusions:

A hybrid approach (computer-assisted + deductive) is time-efficient for identifying unmet needs for digital tool development.
This method aids in creating practical digital tools to improve patient health outcomes.