Behavior-Change Intervention Targeting Physical Function, Walking, and Disability After Dysvascular Amputation: A Randomized Controlled Pilot Trial

Christiansen, Cory L.; Miller, Matthew J.; Murray, Aisling; Stephenson, Ryan O.; Stevens‐Lapsley, Jennifer E.; Hiatt, William R.; Schenkman, Margaret

doi:10.1016/j.apmr.2018.04.011

Cited by 42 publications

(108 citation statements)

References 51 publications

(42 reference statements)

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“…66,67 For example, conventional rehabilitation interventions may improve physical function, but unless low self-efficacy and/or motivation are addressed with rehabilitation, increased physical activity following dysvascular LLA may not be achieved. 7,[68][69][70][71][72][73][74] Our results support the use of interventions targeting improved chronic disease self-management to improve daily step counts for people with dysvascular LLA. Chronic disease self-management interventions largely seek to enhance self-efficacy and motivation for positive health behaviors (eg, physical activity, medication adherence) by developing psychosocial skills known to positively influence health outcomes.…”

Section: Discussionsupporting

confidence: 60%

“…Although cardiovascular disease and low pre‐amputation walking time are not modifiable following dysvascular LLA, personal factors associated with these variables (eg, self‐efficacy, motivation) may be particularly important for interventions to improve physical activity . For example, conventional rehabilitation interventions may improve physical function, but unless low self‐efficacy and/or motivation are addressed with rehabilitation, increased physical activity following dysvascular LLA may not be achieved …”

Section: Discussionmentioning

confidence: 99%

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Physical Function and Pre‐Amputation Characteristics Explain Daily Step Count after Dysvascular Amputation

Miller¹,

Cook

Kline³

et al. 2019

PM&R

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Background People with dysvascular lower limb amputation (LLA) achieve one‐third of the recommended steps per day and experience severe disability. Although physical function improves with rehabilitation after dysvascular LLA, physical activity remains largely unchanged, and factors contributing to limited daily step count are unknown. Objectives To identify factors that contribute to daily step count after dysvascular LLA. Design Cross‐sectional, secondary data analysis. Setting Outpatient rehabilitation facilities. Participants Fifty‐eight patients with dysvascular major LLA (age: 64 ± 9 years, body mass index: 30 ± 8 kg/m2, male: 95%, transtibial LLA: 95%). Methods Data were collected by a blinded assessor after dysvascular LLA. Candidate explanatory variables included (1) demographics, (2) LLA characteristics, (3) comorbidities and health behaviors, and (4) physical function. Variables with univariate associations with log steps/day (transformed due to non‐normality) were included in a multiple linear regression model using backward elimination to identify factors that explained significant variability in log steps/day. Primary Outcome Measure The primary outcome, daily step count, was measured with accelerometer‐based activity monitors worn by participants for 10 days. Results Participants took an average (± SD) of 1450 ± 1309 steps/day. After backward elimination, the final model included four variables explaining 62% of the overall daily step count (P < .0001): 2‐minute walk distance (32%), assistive device use (11%), cardiovascular disease (10%), and pre‐amputation walking time (11%). Conclusions Average daily step count of 1450 steps/day reflects the lowest category of sedentary behavior. Physical function, cardiovascular disease, and pre‐amputation walking time explain 62% of daily step count after dysvascular LLA. Although physical rehabilitation commonly focuses on improving physical function, interventions to increase daily step count after dysvascular LLA should also consider chronic disease and health behaviors that predate LLA. Level of Evidence III.

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Section: Discussionsupporting

confidence: 60%

Section: Discussionmentioning

confidence: 99%

Physical Function and Pre‐Amputation Characteristics Explain Daily Step Count after Dysvascular Amputation

Miller¹,

Cook

Kline³

et al. 2019

PM&R

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“…[16][17][18] Home-based behavior change intervention to promote exercise, walking activity, and disease self-management has been piloted in people recovering from nontraumatic transtibial amputation, resulting in increased daily step count. 19 However, the intervention did not focus solely on physical activity. In addition, the previous trial was implemented within the first 6 months after amputation and physical activity progression was potentially limited due to the need for some participants to resolve wound and incision healing issues from the amputation.…”

Section: Introductionmentioning

confidence: 99%

Biobehavioral Intervention Targeting Physical Activity Behavior Change for Older Veterans after Nontraumatic Amputation: A Randomized Controlled Trial

Christiansen

Miller

Kline

et al. 2020

PM&R

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Background: Lower-limb amputation (LLA) due to non-traumatic vascular etiology is linked to extremely low physical activity and high disability. Objective: To test the feasibility of a biobehavioral intervention designed to promote physical activity. Design: A randomized, single-blind feasibility trial with a crossover design. Setting: Veterans Administration Medical Center. Participants: Military veterans (age: 65.7 [7.8] years; mean [standard deviation]) with nontraumatic lower-limb amputation (LLA), randomized to two groups: GROUP1 (n = 16) and GROUP2 (n = 15). Both groups had similar baseline amputation characteristics (level of amputation and time since amputation). Interventions: Twelve weekly, 30-minute telehealth sessions of physical activity behavior-change intervention, with GROUP1 participating in weeks 1-12 and GROUP2 in weeks 13-24. GROUP1 noncontact phase in weeks 13-24 and GROUP2 attention control telehealth phase in weeks 1-12. Main Outcome Measures: Feasibility (participant retention, dose goal attainment, intervention acceptability [Intrinsic Motivation Inventory [IMI] Interest and Enjoyment scale], safety) and signal of efficacy (free-living physical activity [accelerometer-based average daily step count], Late Life Function and Disability Index-Disability Scale [LLFDI-DS]). Results: Participant retention rate was high (90%), with three participants lost to follow-up during the intervention period. Dose goal attainment was low, with only 10% of participants achieving an a priori walking dose goal. Intervention was rated as acceptable, with mean IMI Interest and Enjoyment score (5.8) statistically higher than the null value of 5.0 (P = .002). There were no between-group differences in adverse event rates (falls: P = .19, lower extremity wounds: P = .60). There was no signal of efficacy for change in average daily step count (d = −0.15) or LLFDI-DS (d = −0.22 and 0.17 for frequency and limitations scales, respectively). Conclusions: Telehealth delivered biobehavioral intervention resulted in acceptable participant retention, low dose goal attainment, high participant acceptability, and low safety risk, while having no signal of efficacy (physical activity, disability) for people with nontraumatic LLA.

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“…Only one intervention study was identified from the set of upper-limb studies and this used a log of grasping events to explore the effect of sensory feedback on use over time. 71 The lifestyle interventions for lower-limb prosthesis users were aimed at promoting physical activity, 67,69,81 providing rehabilitation 86 or providing massage. 80 These all showed positive outcomes, from increased daily step counts 67 to weight loss 81 and decreased pain levels.…”

Section: Figure 1 Flow Chart Of Selection and Sorting Methodsmentioning

confidence: 99%

“…71 The lifestyle interventions for lower-limb prosthesis users were aimed at promoting physical activity, 67,69,81 providing rehabilitation 86 or providing massage. 80 These all showed positive outcomes, from increased daily step counts 67 to weight loss 81 and decreased pain levels. 101 Of the 17 papers that compared activity levels of lower-limb prosthesis users to clinical scores, most compared the recorded physical activity to the K-level scores and found good correlation.…”

Section: Figure 1 Flow Chart Of Selection and Sorting Methodsmentioning

confidence: 99%

Technology for monitoring everyday prosthesis use: a systematic review

Chadwell¹,

Diment²,

Amigo³

et al. 2020

Preprint

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BackgroundUnderstanding how prostheses are used in everyday life is central to the design, provision and evaluation of prosthetic devices and associated services. This paper reviews the scientific literature on methodologies and technologies that have been used to assess the daily use of both upper- and lower-limb prostheses. It discusses the types of studies that have been undertaken, the technologies used to monitor physical activity, the benefits of monitoring daily living and the barriers to long-term monitoring.MethodsA systematic literature search was conducted in PubMed, Web of Science, Scopus, CINAHL and EMBASE of studies that monitored the activity of prosthesis-users during daily-living.Results60 lower-limb studies and 9 upper-limb studies were identified for inclusion in the review. The first studies in the lower-limb field date from the 1990s and the number has increased steadily since the early 2000s. In contrast, the studies in the upper-limb field have only begun to emerge over the past few years. The early lower-limb studies focused on the development or validation of actimeters, algorithms and/or scores for activity classification. However, most of the recent lower-limb studies used activity monitoring to compare prosthetic components. The lower-limb studies mainly used step-counts as their only measure of activity, focusing on the amount of activity, not the type and quality of movements. In comparison, the small number of upper-limb studies were fairly evenly spread between development of algorithms, comparison of everyday activity to clinical scores, and comparison of different prosthesis user populations. Most upper-limb papers reported the degree of symmetry in activity levels between the arm with the prosthesis and the intact arm.ConclusionsActivity monitoring technology used in conjunction with clinical scores and user feedback, offers significant insights into how prostheses are used and whether they meet the user’s requirements. However, the cost, limited battery-life and lack of availability in many countries mean that using sensors to understand the daily use of prostheses and the types of activity being performed has not yet become a feasible standard clinical practice. This review provides recommendations for the research and clinical communities to advance this area for the benefit of prosthesis users.

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Behavior-Change Intervention Targeting Physical Function, Walking, and Disability After Dysvascular Amputation: A Randomized Controlled Pilot Trial

Abstract: The behavior-change intervention demonstrates promise for increasing walking activity for people with dysvascular transtibial amputation (TTA). The efficacy of implementing such intervention in the scope of conventional TTA rehabilitation should be further studied.

Cited by 42 publications

References 51 publications

Physical Function and Pre‐Amputation Characteristics Explain Daily Step Count after Dysvascular Amputation

Physical Function and Pre‐Amputation Characteristics Explain Daily Step Count after Dysvascular Amputation

Biobehavioral Intervention Targeting Physical Activity Behavior Change for Older Veterans after Nontraumatic Amputation: A Randomized Controlled Trial

Technology for monitoring everyday prosthesis use: a systematic review

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