Literature DB >> 33315834

Readiness to Change is Related to Real-World Walking and Depressive Symptoms in Chronic Stroke.

Allison Miller1, Tamara Wright, Henry Wright, Elizabeth Thompson, Ryan T Pohlig, Darcy S Reisman.   

Abstract

BACKGROUND AND
PURPOSE: The transtheoretical model is a health behavior model used to understand an individual's readiness to change their behavior. This study aims to apply the transtheoretical model in understanding a person with stroke's readiness to change their activity level, as it relates to physical capacity, physical health, depressive symptoms, self-efficacy, and daily stepping activity.
METHODS: This was a cross-sectional analysis of baseline data from a clinical trial. Participants' readiness to change their activity levels was measured via self-report and daily stepping activity was measured using a step activity monitor. Robust regression (M-estimation with robust standard errors) was used to test the relationship between readiness to change and measures of physical capacity (6-minute walk test, self-selected walking speed), physical health (body mass index, age-adjusted Charlson Comorbidity Index), depressive symptoms (Patient Health Questionnaire-9), self-efficacy (Activities-Specific Balance Confidence Scale), and daily stepping (steps per day).
RESULTS: A total of 274 individuals were included in the analysis. Adjusted for age, readiness to change was positively related to daily stepping (β = 0.29, P < 0.001) and negatively related to depressive symptoms (β = -0.13, P = 0.01). Readiness to change was not significantly associated with measures of physical capacity, physical health, or self-efficacy. DISCUSSION: These results suggest that individuals with stroke in the later stages of change may demonstrate greater daily stepping activity and lower depressive symptoms compared with those in earlier stages.
CONCLUSIONS: Understanding the relationship between readiness to change, daily stepping, and depressive symptoms will help clinicians implement appropriate stage-specific intervention strategies and facilitate greater improvement in activity levels.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A333).

Entities:  

Mesh:

Year:  2021        PMID: 33315834      PMCID: PMC7739270          DOI: 10.1097/NPT.0000000000000345

Source DB:  PubMed          Journal:  J Neurol Phys Ther        ISSN: 1557-0576            Impact factor:   4.655


  57 in total

1.  Participation in community walking following stroke: subjective versus objective measures and the impact of personal factors.

Authors:  Cynthia A Robinson; Anne Shumway-Cook; Marcia A Ciol; Deborah Kartin
Journal:  Phys Ther       Date:  2011-10-14

2.  Using step activity monitoring to characterize ambulatory activity in community-dwelling older adults.

Authors:  James T Cavanaugh; Kim L Coleman; Jean M Gaines; Linda Laing; Miriam C Morey
Journal:  J Am Geriatr Soc       Date:  2007-01       Impact factor: 5.562

3.  Predicting home and community walking activity in people with stroke.

Authors:  George D Fulk; Chelsea Reynolds; Sumona Mondal; Judith E Deutsch
Journal:  Arch Phys Med Rehabil       Date:  2010-10       Impact factor: 3.966

4.  Consumer-Based Physical Activity Monitor as a Practical Way to Measure Walking Intensity During Inpatient Stroke Rehabilitation.

Authors:  Tara D Klassen; Jennifer A Semrau; Sean P Dukelow; Mark T Bayley; Michael D Hill; Janice J Eng
Journal:  Stroke       Date:  2017-08-07       Impact factor: 7.914

5.  Screening for poststroke depression using the patient health questionnaire.

Authors:  Janneke M de Man-van Ginkel; Floor Gooskens; Vera P M Schepers; Marieke J Schuurmans; Eline Lindeman; Thóra B Hafsteinsdóttir
Journal:  Nurs Res       Date:  2012 Sep-Oct       Impact factor: 2.381

6.  Inflated perceptions of physical activity after stroke: pairing self-report with physiologic measures.

Authors:  Barbara Resnick; Kathleen Michael; Marianne Shaughnessy; Eun Shim Nahm; Susan Kobunek; John Sorkin; Denise Orwig; Andrew Goldberg; Richard F Macko
Journal:  J Phys Act Health       Date:  2008-03

7.  Classification of walking handicap in the stroke population.

Authors:  J Perry; M Garrett; J K Gronley; S J Mulroy
Journal:  Stroke       Date:  1995-06       Impact factor: 7.914

Review 8.  How many steps/day are enough? For older adults and special populations.

Authors:  Catrine Tudor-Locke; Cora L Craig; Yukitoshi Aoyagi; Rhonda C Bell; Karen A Croteau; Ilse De Bourdeaudhuij; Ben Ewald; Andrew W Gardner; Yoshiro Hatano; Lesley D Lutes; Sandra M Matsudo; Farah A Ramirez-Marrero; Laura Q Rogers; David A Rowe; Michael D Schmidt; Mark A Tully; Steven N Blair
Journal:  Int J Behav Nutr Phys Act       Date:  2011-07-28       Impact factor: 6.457

9.  Stroke incidence and association with risk factors in women: a 32-year follow-up of the Prospective Population Study of Women in Gothenburg.

Authors:  Ann Blomstrand; Christian Blomstrand; Nashmil Ariai; Calle Bengtsson; Cecilia Björkelund
Journal:  BMJ Open       Date:  2014-10-28       Impact factor: 2.692

10.  The Use of Wearable Activity Trackers Among Older Adults: Focus Group Study of Tracker Perceptions, Motivators, and Barriers in the Maintenance Stage of Behavior Change.

Authors:  Anastasia Kononova; Lin Li; Kendra Kamp; Marie Bowen; R V Rikard; Shelia Cotten; Wei Peng
Journal:  JMIR Mhealth Uhealth       Date:  2019-04-05       Impact factor: 4.773

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  1 in total

1.  A machine learning approach to identifying important features for achieving step thresholds in individuals with chronic stroke.

Authors:  Allison E Miller; Emily Russell; Darcy S Reisman; Hyosub E Kim; Vu Dinh
Journal:  PLoS One       Date:  2022-06-17       Impact factor: 3.752

  1 in total

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