| Title |
WHO disability assessment schedule 2.0 is related to upper and lower extremity disease-specific quality of life
|
|---|---|
| Published in |
Quality of Life Research, May 2018
|
| DOI | 10.1007/s11136-018-1869-5 |
| Pubmed ID | |
| Authors |
Jun-Il Yoo, Jin-Sung Park, Rock-Beum Kim, Ae-Rim Seo, Young-Jin Park, Mi-Ji Kim, Ki Soo Park |
| Abstract |
We evaluated whether two disease-specific quality of life instruments (Disabilities of the Arm, Shoulder and Hand, DASH and Western Ontario & McMaster Universities Osteoarthritis Index, WOMAC) reflect a patient's perception of general disability using the WHO Disability Assessment Schedule 2.0 (WHODAS 2.0) and determined whether disability components are explained by upper and lower extremity HRQOL. We recruited 421 participants, 50 years or older without stroke, cancer, or history of surgery for musculoskeletal disease, who participated in the NAMGARAM Cohort. Upper extremity HRQOL was determined with the DASH score and lower extremity HRQOL with the WOMAC; as a measure of disability, we obtained WHODAS 2.0 component. Multiple regression modeling was used to assess the relative contributions made by upper and lower extremity HRQOL to disability. When adjusted for covariates, the DASH total score was correlated with getting around (β = 0.217, p < 0.001) and social participation (β = 0.226, p < 0.001), and the WOMAC total score was correlated with getting around (β = 0.363, p < 0.001), life activation (β = 0.363, p < 0.001), and social participation (β = 0.301, p < 0.001). QOL significantly correlated with upper extremity disorders (β = 0.081, p = 0.018) or lower extremity disorders (β = 0.095 p = 0.004). We found that in a community-based population, perceived activity limitation and social participation were associated with upper and lower extremity HRQOL. Since the WHODAS 2.0 does not target a specific disease (as opposed to DASH and WOMAC), it can be used to compare disabilities caused by different diseases. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 60 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 13% |
| Student > Bachelor | 7 | 12% |
| Student > Ph. D. Student | 7 | 12% |
| Student > Postgraduate | 4 | 7% |
| Student > Doctoral Student | 4 | 7% |
| Other | 5 | 8% |
| Unknown | 25 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 11 | 18% |
| Medicine and Dentistry | 9 | 15% |
| Psychology | 3 | 5% |
| Economics, Econometrics and Finance | 2 | 3% |
| Agricultural and Biological Sciences | 2 | 3% |
| Other | 4 | 7% |
| Unknown | 29 | 48% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 July 2020.
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#7,042,297
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Outputs of similar age from Quality of Life Research
#23
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