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Information bias in the Canadian occupational performance measure: A qualitative study
Tatsunori Sawada1, Kounosuke Tomori1, Kanta Ohno1
1Major of Occupational Therapy, Department of Rehabilitation, School of Health Sciences, Tokyo University of Technology, Ota-ku, Tokyo, Japan.
This study reveals that client biases can influence scores in the Canadian Occupational Performance Measure (COPM). Understanding these 15 sources of bias can improve client-therapist collaboration in occupational therapy.
Area of Science:
- Occupational therapy outcomes measurement
- Client-centered practice
- Qualitative research methodology
Background:
- The Canadian Occupational Performance Measure (COPM) is a key tool for assessing outcomes in client-centered occupational therapy.
- Understanding potential biases in COPM assessments is crucial for accurate outcome measurement.
- Client perspectives on the initial COPM assessment can reveal sources of information bias.
Purpose of the Study:
- To explore clients' views and experiences during their initial COPM assessment.
- To identify potential information biases that may influence COPM scores.
- To enhance the validity and reliability of COPM assessments through client insights.
Main Methods:
- Qualitative thematic analysis of semi-structured interviews with clients.
- Study conducted at a typical Japanese rehabilitation hospital.
- Involved 20 clients (13 men, 7 women, aged 19-84 years).
Main Results:
- 19 out of 20 clients exhibited potential information bias in their COPM scores.
- Identified 15 distinct sources of bias, categorized into three domains: occupational area selection, performance/satisfaction scoring, and future scoring interference.
- Examples include misunderstanding client-centeredness, hopeful scoring, and ceiling effects.
Conclusions:
- This research highlights significant potential sources of bias impacting COPM scores.
- Awareness of these biases can lead to improved client-therapist collaboration during COPM assessments.
- Findings support refining the COPM process to minimize bias and enhance outcome measurement accuracy.
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