Use of Occupation-Based Measures in LSVT BIG Research: A Case Study.


Journal

OTJR : occupation, participation and health
ISSN: 1938-2383
Titre abrégé: OTJR (Thorofare N J)
Pays: United States
ID NLM: 101144015

Informations de publication

Date de publication:
04 2020
Historique:
pubmed: 16 11 2019
medline: 23 7 2021
entrez: 16 11 2019
Statut: ppublish

Résumé

Parkinson's disease (PD) is a neurodegenerative disorder that results in a variety of motor and nonmotor symptoms that impact occupational performance. To our knowledge, no study has investigated the effect of LSVT BIG using occupational performance outcome measures. The objective of this study was to determine the effects of LSVT BIG on occupational performance with an individual with PD. The participant, a 73-year-old retired female with mild PD, completed the LSVT BIG program. Researchers measured changes in occupational performance using the Canadian Occupational Performance Measure (COPM) and the Performance Assessment of Self-Care Skills (PASS). Results indicated improved client perceptions of occupational performance and satisfaction on the COPM and improved independence and adequacy on the PASS. Despite the positive findings of this study that support the use occupational performance measures to evaluate change within LSVT BIG literature, future research should be conducted to determine causality of identified occupational performance improvements and time course of improvements.

Identifiants

pubmed: 31729929
doi: 10.1177/1539449219886261
doi:

Types de publication

Case Reports Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

131-137

Auteurs

Whitney Henderson (W)

University of Missouri, Columbia, USA.

Anna E Boone (AE)

University of Missouri, Columbia, USA.

Joy Heady (J)

University of Missouri, Columbia, USA.

Micaela Nettleton (M)

University of Missouri, Columbia, USA.

Taylor Wilhelm (T)

University of Missouri, Columbia, USA.

Jaquelyn Bliss (J)

University of Missouri, Columbia, USA.

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Classifications MeSH