بازیابی بعد از سکته مغزی: نقش آموزش خود مدیریتی

Current stroke rehabilitation tends to focus on the bio-medical course of disability, often responding to psychological and social issues only when they have been implicated in crises. Although this situation is costly, little evidence exists in relation to how psychological and social outcomes can be facilitated or how psychosocial decline can be prevented. In the area of adjustment following traumatic injury, there has been some suggestion that rehabilitation should focus on the expansion of resources, skills and self-efficacy as this will enable individuals to cope more effectively with their medical condition and circumstances. The current study was a longitudinal randomised controlled trial involving 100 people with stroke, 58 of whom were randomly allocated to an intervention based on the notion of psychosocial skill expansion. All were patients of a major hospital in Queensland, Australia. An existing self-management intervention (The Chronic Disease Self-Management Course, Lorig et al., 2001) was used to operationalise the concept of psychosocial skill expansion. The control group reported declines in functioning during the first year following stroke in the areas of family roles, activities of daily living, self-care and work productivity, that were not reported by the intervention group. Although the groups had reached similar levels by one year post-stroke, this intervention may have a protective function, presumably by improving capacity to manage the functional requirements of daily life. However, the intervention did not appear to have its impact through self-efficacy, as was expected, and failed to influence outcomes such as mood or social participation. Nevertheless, the intervention warrants further investigation, given that it appears to improve rehabilitation outcomes, at least in the short-term.

Stroke is a major health problem in Australia, with high incidence rates of approximately 40,000 each year (Davis & Donnan, 1999). The annual cost of acute medical rehabilitation for people with stroke can reach $40,000 per individual, representing an enormous investment in the recovery of this population (Kirsner, 1997). Despite this expense, dissatisfaction with rehabilitation is common following stroke, and psychosocial outcomes tend to remain problematic for many years (Thomas & Parry, 1996). Recovery from stroke is complex and multidimensional (Dowswell, Lawler, Dowswell, Young, & Hearn, 2000). Indeed, research in the area of chronic illness has confirmed that any recovery process can be viewed in terms of three complex and unique pathways (Robinson, 1990), namely bio-medical, social and psychological. The bio-medical pathway represents the physical course of an illness and focuses on medical diagnosis, prognosis and functional outcomes. The purpose of treatment within this bio-medical area is to restore an impaired individual to his or her former condition (Newsome & Kendall, 1996). In contrast, the psychological and social pathways represent the way in which individuals perceive their circumstances and how they are perceived by others. Although the physical, psychological and social aspects of recovery are likely to be inter-linked, the relationship between these factors is poorly understood (Dowswell et al., 2000). In relation to stroke, the bio-medical pathway is likely to involve a sharp decline followed by a period of rapid improvement and stabilisation. In contrast, psychological and social pathways are more likely to follow one of two “regressive” patterns—either a continual and gradual decline over time or an extremely rapid and dramatic decline at a particular point. Although no common path of recovery has been found following stroke (Burton, 2000), some research has suggested that within the first few months, the extent and/or permanence of disability is likely to become apparent, leading to psychological turmoil (Kendall & Buys, 1998; Mackenzie & Chang, 2002). Individuals are likely to be initially overwhelmed by stroke and unable to comprehend their situation (Watson & Quinn, 1998). Similarly, the social interest of family members and friends is likely to be intense in the early stages of any injury or illness, artificially inflating the sense of being supported (Kendall & Terry, 1996). Within several months of returning home from hospital, however, social support networks tend to diminish, leaving individuals isolated at a time when support is most critical to stroke outcome (Robinson, Murata, & Shimoda, 1999). This sense of social isolation may compound the overwhelming nature of the condition, leading to psychological difficulties and potentially catastrophic outcomes (Godfrey, Partridge, Knight, & Bishara, 1993). Research has suggested that by 1 or 2 years post-stroke, psychological and social outcomes are likely to have stabilised (Hafsteinsdóttir & Grypdonck, 1997), although problems can still remain evident for many years (Jones, Charlesworth, & Hendra, 2000). It is important to note that the utility of such linear and time-dependent models of adjustment has been queried on the grounds that recovery processes are more likely to be cyclical and embedded in socially constructed contexts (Kendall & Buys, 1998). Nevertheless, knowledge about how bio-medical, psychological and social trajectories can differ from each other and interact is likely to be useful (Mackenzie & Chang, 2002). It is particularly important to acknowledge the fact that biologically-based rehabilitation will not necessarily influence the psychosocial well-being of individuals and, conversely, psychosocial difficulties may impede physical recovery. Indeed, Robinson (1990) argued that bio-medical recovery can be best facilitated if social and psychological needs are recognised and addressed appropriately, a claim that has received some support in the literature (Frank et al., 1998). Despite this recognition, some investigations continue to focus on only the physical course of disabilities and diseases. Current rehabilitation remains firmly based in the bio-medical trajectory, leaving gaps in the provision of psychological and social services and accelerating the decline into regressive psychological and social pathways (Catalano, Dickson, Kendall, Kuipers, & Posner, 2003). Unfortunately, the rehabilitation system tends to respond to psychological and social issues in a post hoc and atheoretical manner, often as a result of crises or after a cycle of deterioration has become entrenched (Jochims, 1995). Consequently, it is pertinent to address psychosocial issues at an early point in the recovery process, thereby preventing decline and positioning individuals on a “progressive” pathway. Indeed, psychosocial rehabilitation has been characterised as a process of creating opportunities, facilitating positive perceptions of one's future, re-establishing goals and valued social roles and enabling individuals to assert personal control over their bio-medical condition (Newsome & Kendall, 1996). Even though adjustment may decline initially in response to the trauma of a sudden-onset illness or disability, it is important that this pattern is redirected before it becomes entrenched (Robinson, 1990). Although facilitating a progressive adjustment pattern would appear to be the ultimate goal of rehabilitation, the methods of facilitating such an outcome have not been well articulated. Given that stroke exposes individuals and families to a range of stressful circumstances, it is possible that theories of stress and coping may offer some guidance on this issue (e.g. Lazarus & Folkman, 1984). In these theories, stressful events are defined as those that are appraised by the individual as being threatening or harmful and unable to be managed successfully. Once an event has been appraised as stressful, the theory suggests that coping responses will be implemented. These coping responses will then determine the course of psychological and social recovery. Lazarus and his colleagues (Lazarus, 1990; Lazarus, 1993; Lazarus & Folkman, 1984) proposed that positive appraisal and effective coping will be facilitated through access to sufficient personal or environmental “coping resources”, such as social support, family cohesion, financial security, self-esteem and community services. It is suggested that these factors encourage individuals to perceive their circumstances as less threatening and more able to be managed successfully, leading to better adjustment (Kendall & Terry, 1996). Lazarus and Folkman (1984) also noted that the adjustment process is recursive, in that positive outcomes enhance coping resources, which then facilitate better outcomes (i.e., a progressive trajectory). In contrast, poor outcomes become future stressors, depleting coping resources and interfering with the coping process, leading to a downward spiral or regressive trajectory following stroke (Watson & Quinn, 1998). The Lazarus and Folkman (1984) theory indicates that psychological and social interventions should be based on two major premises: (1) early intervention, presumably to prevent regressive trajectories; (2) the development of sufficient coping resources, presumably to support progressive trajectories. One intervention that has been used to develop coping resources in relation to people with chronic conditions is the Stanford University model of self-management training, the Chronic Disease Self-Management (CDSM) course (Lorig et al., 2001). This model of self-management involves a group education format that encourages people with chronic conditions to (1) engage in activities that promote health and wellbeing, such as adopting healthy behaviours (e.g. exercise and healthy eating), (2) minimise the negative influence of their illness on their lives, (3) manage the negative emotional impact of their symptoms and (4) take an active role in their own health by developing partnerships with health professionals. Lorig and Holman (2003) claimed that successful self-management is based on five core skills. First, self-management requires the development of problem-solving skills (i.e., problem definition, generation of possible solutions, implementation of a solution and evaluation of the outcome) to ensure that difficult situations can be addressed. Second, self-management requires people to make day-to-day decisions about their condition on the basis of sound knowledge and information about health, symptoms and treatment. Third, self-management requires the ability to find and utilise appropriate resources, including support. Fourth, self-management requires the capacity to make informed choices about one's own treatment in partnership with healthcare providers, rather than being passive recipients of healthcare. Finally, self-management involves taking action to change behaviour and master new skills. Thus, coping, action planning and goal-setting are important components of the course. These core skills are thought to contribute to participants’ confidence in managing their health and the perception that they can control their environment (i.e., self-efficacy). Presumably through increased self-efficacy, behaviours are changed and health status is altered in a positive direction. There is considerable anecdotal evidence that self-management is associated with positive outcomes for people with chronic conditions, both in terms of physical and psychological well-being (Lorig & Holman, 2003). This evidence has led to the widespread delivery of the CDSM course within the Australian health system. However, its application in the stroke population has been minimal. Given the chronic nature of post-stroke disability, the course is likely to offer an important psychosocial dimension to current rehabilitation. The purpose of the current study was to conduct a longitudinal randomised controlled trial to examine the utility of the CDSM course as a way of promoting progressive psychosocial recovery pathways among people with stroke. The course was implemented early in the rehabilitation process (i.e., within the first few months of discharge) to maximise its capacity to alter the recovery pathway.

Given that not all intervention group participants had attended the same number of sessions, a “dosage” variable could have been introduced into the study. Thus, prior to examining the results, it was necessary to examine the impact of attendance at the course sessions. In previous studies, attendance at four or more sessions has been used as an indicator to distinguish full attendees from partial attendees (Foster et al., 2003). Of the 58 intervention participants, 37 had attended four or more sessions, with most of these having attended the full course. When full attendees and partial attendees were compared on self-efficacy and the SSQOL outcome variables, no significant differences emerged at any time. This finding indicates that level of attendance did not alter the impact of the intervention on participants. Table 2 presents the mean scores and standard deviations on self-efficacy across the two groups at each point in time. Given that the intervention is purported to have its greatest impact through self-efficacy, analyses were conducted using this variable as a dependent variable. It was apparent that the control and intervention groups differed significantly in self-efficacy levels across all times, F (1, 93)=9.45, p=.003p=.003, including pre-intervention. Specifically, the control group demonstrated lower levels of self-efficacy than the intervention group. There was no interaction between group and time and no main effect for time. Thus, it would seem that self-efficacy in the control group was consistently lower than the intervention group and did not change over time for either group. Table 2. Means and standard deviations for self-efficacy over time Group Time M SD Control 1 61.45 14.93 2 62.68 15.73 3 60.88 20.44 4 61.68 18.16 Treatment 1 68.46 15.31 2 67.88 12.25 3 68.80 13.29 4 69.42 15.16 Table options However, self-efficacy showed significant positive main effects on all SSQOL outcome variables: language, F (3, 150.24)=30.13, p<.01p<.01; energy, F (3, 157.47)=80.89, p<.01p<.01; mobility, F (3, 124.30)=33.52, p<.01p<.01; mood, F (3, 176.37)=118.61, p<.001p<.001; vision, F (3, 148.07)=6.20, p<.05p<.05; fine motor tasks, F (1, 115.23)=24.58, p<.001p<.001; self-care, F (1, 254.56)=37.94, p<.001p<.001; personality, F (3, 133.87)=0.49, ns; thinking, F (3, 148.97)=28.92, p<.01p<.01; social roles, F (3, 148.37)=87.39, p<.001p<.001; family roles, F (1, 267.17)=98.42, p<.001p<.001; work productivity, F (1, 272.44)=49.48, p<.001p<.001. This finding confirms the importance of self-efficacy in the determination of outcomes following stroke, irrespective of any interventions. Given its significant impact on the SSQOL variables, the self-efficacy scale was included as a covariate in the remaining analyses. Table 3 and Table 4 present the mean scores and standard deviations on SSQOL subscales across the two groups at each point in time. The effect of most interest in determining outcomes was the interaction between treatment condition and time, as a significant interaction would indicate the presence of a different trajectory of adjustment over time for the treatment group. Given that a number of analyses were being run on the same data set, the alpha level for significance was adjusted to p<.01p<.01. Bonferroni corrections to alpha were also applied for comparing levels of independent variables within an analysis when overall significance had been obtained. Table 3. Means (standard deviations) for SSQOL physical sub-scales over time Sub-scale Group Time 1 Time 2 Time 3 Time 4 Vision Control 13.59 (2.32) 13.79 (2.14) 13.72 (2.14) 13.70 (2.46) Treatment 14.02 (1.77) 13.88 (1.93) 14.13 (1.65) 13.98 (2.04) Language Control 21.90 (3.79) 21.71 (3.50) 21.84 (3.46) 21.32 (4.04) Treatment 21.96 (3.88) 22.18 (3.62) 22.52 (2.81) 22.18 (3.52) Mobility Control 23.10 (6.83) 23.40 (5.56) 23.26 (6.75) 23.61 (6.03) Treatment 23.69 (5.82) 24.02 (5.47) 25.39 (4.68) 24.87 (5.15) Fine Motor Tasks Control 20.23 (4.77) 19.26 (5.50) 19.31 (5.49) 20.79 (4.62) Treatment 20.46 (4.50) 21.24 (3.94) 21.41 (4.36) 21.49 (4.09) Energy Control 8.07 (3.88) 8.46 (3.95) 8.87 (3.82) 9.64 (3.36) Treatment 9.08 (3.85) 9.92 (3.86) 10.00 (3.65) 9.91 (3.72) Table options Table 4. Means (standard deviations) for SSQOL psychological sub-scales over time Subscale Group Time 1 Time 2 Time 3 Time 4 Thinking Control 9.34 (3.93) 9.83 (3.49) 9.55 (3.41) 9.86 (3.59) Treatment 9.91 (3.92) 10.36 (3.39) 10.02 (3.93) 10.09 (4.13) Personality Control 10.00 (3.70) 9.89 (3.65) 9.39 (3.60) 10.54 (3.67) Treatment 10.33 (4.01) 10.14 (4.07) 10.87 (3.33) 10.16 (3.74) Mood Control 17.76 (4.82) 17.31 (5.75) 17.94 (5.75) 18.46 (4.86) Treatment 18.59 (5.41) 19.24 (5.19) 19.61 (4.80) 19.64 (4.81) Work productivity Control 9.67 (4.09) 9.37 (4.73) 10.00 (4.35) 11.14 (3.36) Treatment 10.07 (3.62) 11.06 (3.68) 11.80 (3.27) 11.62 (3.67) Social roles Control 13.71 (5.59) 14.11 (4.64) 14.09 (6.25) 14.89 (5.79) Treatment 14.59 (5.92) 16.35 (5.76) 16.04 (5.53) 17.40 (6.22) Family roles Control 10.71 (3.77) 10.00 (4.02) 9.90 (4.30) 11.37 (2.95) Treatment 10.31 (4.00) 11.19 (3.55) 11.47 (3.65) 11.67 (3.50) Self-Care Control 19.59 (5.34) 19.38 (6.11) 19.81 (5.24) 21.22 (4.45) Treatment 20.98 (4.65) 21.92 (3.79) 22.48 (2.84) 22.20 (3.41) Table options Significant interaction effects were obtained for several SSQOL scales, even after self-efficacy was entered as a covariate. A significant interaction was obtained between treatment group and time for family roles and fine motor tasks. A trend towards significance (i.e., p=.05p=.05) was also identified in relation to work productivity and self-care. Each of these findings is presented in more detail below.