The effect of the Take Charge intervention on mood, motivation, activation and risk factor management: Analysis of secondary data from the Taking Charge after Stroke (TaCAS) trial

McNaughton, Harry; Weatherall, Mark; McPherson, Kathryn; Fu, Vivian; Taylor, William J.; McRae, Anna; Thomson, Tom; Gommans, John; Green, Geoff; Harwood, Matire; Ranta, Annemarei; Hanger, H. C.; Riley, Judith

doi:10.1177/0269215521993648

Cited by 11 publications

(24 citation statements)

References 30 publications

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“…Take Charge aims to improve a person’s sense of purpose, autonomy, mastery and connectedness. 22 Better connectedness, an improved sense of purpose, as well as improved quality of life may explain the trend to lower rates of institutionalisation. Increased autonomy may contribute to lower rates of personal care service use.…”

Section: Discussionmentioning

confidence: 99%

Economic analysis of the ‘Take Charge’ intervention for people following stroke: Results from a randomised trial

Harwood

et al. 2021

Clin Rehabil

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Objective: To undertake an economic analysis of the Take Charge intervention as part of the Taking Charge after Stroke (TaCAS) study. Design: An open, parallel-group, randomised trial comparing active and control interventions with blinded outcome assessment Setting: Community. Participants: Adults ( n = 400) discharged to community, non-institutional living following acute stroke. Interventions: The Take Charge intervention, a strengths based, self-directed rehabilitation intervention, in two doses (one or two sessions), and a control intervention (no Take Charge sessions). Measures: The cost per quality-adjusted life year (QALY) saved for the period between randomisation (always post hospital discharge) and 12 months following acute stroke. QALYs were calculated from the EuroQol-5D-5L. Costs of stroke-related and non-health care were obtained by questionnaire, hospital records and the New Zealand Ministry of Health. Results: One-year post hospital discharge cost of care was mean (95% CI) $US4706 (3758–6014) for the Take Charge intervention group and $6118 (4350–8005) for control, mean (95% CI) difference $ −1412 (−3553 to +729). Health utility scores were mean (95% CI) 0.75 (0.73–0.77) for Take Charge and 0.71 (0.67–0.75) for control, mean (95% CI) difference 0.04 (0.0–0.08). Cost per QALY gained for the Take Charge intervention was $US −35,296 (=£ −25,524, € −30,019). Sensitivity analyses confirm Take Charge is cost-effective, even at a very low willingness-to-pay threshold. With a threshold of $US5000 per QALY, the probability that Take Charge is cost-effective is 99%. Conclusion: Take Charge is cost-effective and probably cost saving.

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Section: Discussionmentioning

confidence: 99%

Economic analysis of the ‘Take Charge’ intervention for people following stroke: Results from a randomised trial

Harwood

et al. 2021

Clin Rehabil

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“…For example, our measure of impairment was inferred from exercise rates and only partially characterized impairment. Biological, psychological, and socioenvironmental measures are key predictors of health outcomes (39), as well as rehabilitation outcomes for people who have had a stroke (40)(41)(42). Due to the anonymity of the data, our analysis did not include any biopsychosocial measures, and this limits our ability to compare results with other work on stroke.…”

Section: Limitations and Future Workmentioning

confidence: 99%

Using Large-Scale Sensor Data to Test Factors Predictive of Perseverance in Home Movement Rehabilitation: Optimal Challenge and Steady Engagement

et al. 2022

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Persevering with home rehabilitation exercise is a struggle for millions of people in the US each year. A key factor that may influence motivation to engage with rehabilitation exercise is the challenge level of the assigned exercises, but this hypothesis is currently supported only by subjective, self-report. Here, we studied the relationship between challenge level and perseverance using long-term, self-determined exercise patterns of a large number of individuals (N = 2,581) engaging in home rehabilitation with a sensor-based exercise system without formal supervision. FitMi is comprised of two puck-like sensors and a library of 40 gamified exercises for the hands, arms, trunk, and legs that are designed for people recovering from a stroke. We found that individuals showed the greatest perseverance with the system over a 2-month period if they had (1) a moderate level of motor impairment and (2) high but not perfect success during the 1st week at completing the exercise game. Further, a steady usage pattern (vs. accelerating or decelerating use) was associated with more overall exercise, and declines in exercise amount over time were associated with exponentially declining session initiation probability rather than decreasing amounts of exercise once a session was initiated. These findings confirm that an optimized challenge level and regular initiation of exercise sessions predict achievement of a greater amount of overall rehabilitation exercise in a group of users of commercial home rehabilitation technology and suggest how home rehabilitation programs and exercise technologies can be optimized to promote perseverance.

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“…[19][20][21][22][23] While the positive impact of supported self-management in stroke is encouraging, the active ingredients for success or mechanisms of change in such interventions remains unclear. 19 24 Several well-defined supported selfmanagement interventions in stroke exist, for example, Bridges 25 in the UK and Take Charge in New Zealand. 18 24 However, our previous research and anecdotal evidence suggests that the diffusion and delivery of supported selfmanagement in practice requires organisational culture change within the healthcare system, rather than the simple implementation of a discrete and well-defined intervention with specific evaluation outcomes.…”

Section: Strengths and Limitations Of This Studymentioning

confidence: 99%

“…While the positive impact of supported self-management in stroke is encouraging, the active ingredients for success or mechanisms of change in such interventions remains unclear 19 24. Several well-defined supported self-management interventions in stroke exist, for example, Bridges25 in the UK and Take Charge in New Zealand 18 24.…”

Section: Introductionmentioning

confidence: 99%

Supported self-management in community stroke rehabilitation: what is it and how does it work? A protocol for a realist evaluation study

et al. 2022

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IntroductionA growing evidence base demonstrates the effectiveness of supported self-management in stroke for stroke survivors and their families. However, there is significant variation in its implementation in community stroke care and little understanding about how supported self-management works and is delivered across different settings, models used and contexts of community stroke rehabilitation.Methods and analysisUsing a mixed method, realist approach across two phases, this protocol describes a study on community-based supported self-management. The aim is to identify the mechanisms and outcomes of supported self-management in stroke and to understand how supported self-management is implemented in different contexts of community stroke rehabilitation. Phase 1 involves (1) a realist synthesis, (2) a scoping and mapping of current community rehabilitation settings and (3) a Q-methodology study to develop initial programme theories about how community-based supported self-management works, for whom and in what contexts. Phase 2 involves realist informed interviews/focus groups with stroke survivors, community rehabilitation practitioners and team managers from across Scotland to test and refine programme theories and an explanatory model for how supported self-management works across different contexts of community-based stroke rehabilitation.Ethics and disseminationEthical approval and R&D approvals have been granted from East of Scotland Research Ethics Committee (REC reference number: 19/ES/0055) and participating NHS boards. An understanding of how, for whom and in what contexts community-based supported self-management works will help to strengthen its delivery in practice. Such an understanding will enable the design of context-specific recommendations for policy and practice that genuinely reflect the challenges in implementing supported self-management in community stroke care. Results will be disseminated to clinical partners working in community stroke rehabilitation, stroke survivors and families and to policymakers and third sector partners involved in the provision of long-term support for people affected by stroke.PROSPERO registration numberCRD42020166208.

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The effect of the Take Charge intervention on mood, motivation, activation and risk factor management: Analysis of secondary data from the Taking Charge after Stroke (TaCAS) trial

Cited by 11 publications

References 30 publications

Economic analysis of the ‘Take Charge’ intervention for people following stroke: Results from a randomised trial

Economic analysis of the ‘Take Charge’ intervention for people following stroke: Results from a randomised trial

Using Large-Scale Sensor Data to Test Factors Predictive of Perseverance in Home Movement Rehabilitation: Optimal Challenge and Steady Engagement

Supported self-management in community stroke rehabilitation: what is it and how does it work? A protocol for a realist evaluation study

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