Determinants of Change in Stroke-Specific Quality of Life After Distributed Constraint-Induced Therapy

Research Design

The research design involved decision analyses (i.e., CHAID) for one group, before and after the dCIT intervention. The research ethics committees of the participating sites approved the study, and all participants gave informed consent.

Participants

We obtained data from 74 participants enrolled in dCIT studies investigating the effects of UE motor rehabilitation therapy (Lin, Chang, et al., 2009; Wu et al., 2007). These patients, who were consecutively screened and recruited from four stroke rehabilitation units, completed the SS–QOL before and after the dCIT intervention.

The inclusion criteria were as follows: hemiplegia, first stroke and ≥1 mo after stroke onset, no cognitive deficiency (Mini-Mental State Examination [MMSE; Folstein, Folstein, & McHugh, 1975] score ≥23) and able to understand the questionnaires, voluntary movement (Brunnstrom stage >3) for the proximal part of the affected UE, and no excessive spasticity in the joints of the affected UE (Modified Ashworth Scale [Bohannon & Smith, 1987] score ≤ 2).

Instruments

We measured QOL outcomes with the SS–QOL (Williams, Weinberger, Harris, & Biller, 1999), a self-report assessment that includes 12 stroke-specific subscales with 49 items. The SS–QOL attempts to capture the domains of stroke-specific QOL that are insufficiently assessed with generic QOL measures. The 12 subscales, which are unidimensional, are Energy, Family Role, Language, Mobility, Mood, Personality, Self-Care, Social Roles, Thinking, Upper Extremity Function, Vision, and Work–Productivity. Participants responded to each item on a 5-point Likert scale. Domain scores are the averages of the item scores, and the total score is the average of the domain scores. All summary scores therefore range from 1 to 5. Higher scores indicate better function.

Reliability was established for each domain, with Cronbach’s αs ranging from .73 to .89. Construct validity was established by correlating the SS–QOL scores to scores on the Short Form 36-Item Health Survey (Ware & Sherbourne, 1992), Beck Depression Inventory (Beck, Ward, Mendelson, Mock, & Erbaugh, 1961), National Institutes of Health Stroke Scale (Brott et al., 1989), and Barthel Index (Mahoney & Barthel, 1965) (r ²s = .3–.5; Williams, Weinberger, Harris, Clark, & Biller, 1999). Validity (rs = .25–.88) and test–retest reliability (intraclass correlations [ICCs] = .53–.96) of the SS–QOL have been established in many cultures (Boosman, Passier, Visser-Meily, Rinkel, & Post, 2010; Ewert & Stucki, 2007; Lima et al., 2008; Lin et al., 2010; Muus et al., 2007).

Procedures

Occupational therapists screened patients, recruited eligible participants, and delivered the intervention to patients. Screening tests included a demographic survey and the MMSE. All clinical measures were administered to study participants by a blinded rater before and immediately after the intervention. After pretesting, the therapists provided a 3-wk intervention for each participant.

Data Collection

Within 1 wk before and 1 wk after the 3-wk dCIT intervention, three blinded raters administered the four standardized measurements (FMA, FIM, NEADL, and SS–QOL). Approximately 1 hr was needed to finish these measurements. The raters were trained under the supervision of senior occupational therapists and followed the standardized written instructions that were provided by the study investigators. The interrater reliability between the raters of each SS–QOL domain was high (ICCs ≥ .84).

Data Analysis

The sample used in this study included the participants who received the dCIT intervention. We used SPSS software (Version 19.0; IBM SPSS Statistics Inc., Chicago) for data entry and generation of descriptive statistics. CHAID analysis was used to identify the predictors that were most strongly linked with each SS–QOL domain. The advantage of using CHAID is that it offers concrete information about the predictors. Therefore, we also used CHAID to further identify the best specific scores of the predictors that distinguished the SS–QOL domains. The α level for all statistical tests was .05.

Energy Domain

Side of lesion was the indicator most strongly associated with Energy outcomes, separating the sample into two groups (Figure 1A). SS–QOL Energy domain scores improved significantly more among participants with a right-sided lesion than among those with a left-sided lesion. The subgroup with a right-sided lesion was further differentiated into two groups by the time since stroke: those who were >17 mo poststroke had more improvement than those who were <17 mo poststroke.

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Figure 1.

Chi-square automatic interaction detector diagram showing the factors predictive of outcomes for four domains of the Stroke-Specific Quality of Life Scale (A) Energy; (B) Family Roles; (C) Mobility, according to the NEADL scale; and (D) Mood, according to the NEADL scale.

The misclassification risk estimate of the original sample on the SS–QOL Energy domain scores was .176. The average misclassification risk estimate of the validation samples was .240.

Family Roles Domain

Time since stroke was the indicator most strongly associated with Family Roles outcomes, separating the sample into two groups (Figure 1B). Family Roles domain scores improved significantly more among participants who were >10 mo poststroke than among participants who were ≤10 mo poststroke.

The misclassification risk estimate of the original sample on the SS–QOL Family Role scores was .139. The average misclassification risk estimate of the validation samples was .177.

Mobility Domain

NEADL score was the indicator most strongly associated with mobility outcomes in the SS–QOL Mobility domain scores, separating the sample into two groups (Figure 1C). Participants with NEADL scores of ≤11 improved significantly more than those whose scores were >11.

The misclassification risk estimate of the original sample on the SS–QOL Mobility scores was .106. The average misclassification risk estimate of the validation samples was .139.

Mood Domain

Age was the indicator most strongly associated with Mood domain outcomes, separating the sample into two groups (Figure 1D). Participants >68 yr old showed significantly greater improvement in SS–QOL Mood domain scores than did participants ≤68 yr old. Those ≤68 yr old were further differentiated by their NEADL scores into two subgroups. Patients whose NEADL scores were >20 had a better outcome than those who whose NEADL scores were ≤20.

The misclassification risk estimate of the original sample on the SS–QOL Mood scores was .065. The average misclassification risk estimate of the validation samples was .095.

Effect of Side of Stroke on the SS–QOL Energy Domain

SS–QOL Energy domain scores improved significantly more among participants with a right-sided brain lesion (left hemiparesis) than among those with a left-sided brain lesion (right hemiparesis). This result is similar to those of Byl et al. (2003), who found that stroke survivors with right-sided brain damage had advantages after functional independence training. Because 70 participants in our study were right-handed, those with a right-sided brain lesion exhibited deficits in the nondominant (left) hand. After dCIT, the left hand could assist the right dominant hand, and participants performed tasks without a strong feeling of being tired. People with a left-sided brain lesion, however, may require the affected right-dominant hand, which is primarily responsible for activity performance, to expend great effort in doing complicated activities. Therefore, even though the affected right-dominant hand showed some improvement after dCIT, stroke survivors still felt exhausted and frustrated when engaging in activities using the affected right-dominant hand.

Participants in the right-sided lesion subgroups were further differentiated into two groups by time since stroke. Patients who were >17 mo poststroke experienced more improvement in the SS–QOL Energy domain than those who were <17 mo poststroke. One study showed that 52% of patients with disabling ischemic stroke recovered within 18 mo (Hankey et al., 2007). Stroke patients with onset >17 mo ago may have recovered maximally and did not need to spend a lot of time in bed, nor did they feel tired in performing daily life activities. These changes in recovery as a result of dCIT were reflected in self-perceived energy consumption for task performance.

Influence of Time Since Stroke on the SS–QOL Family Role Domain

Family Role domain scores improved significantly more among participants who were >10 mo poststroke than among those ≤10 mo poststroke. Patients with onset >10 mo ago have usually received a period of standard rehabilitation treatment, and the opportunity for spontaneous recovery to occur is attenuated (Wolf et al., 2006). Neurologic status and motor reorganization might tend to be more stable after 10 mo. Participants with onset >10 mo ago might have better capacity after receiving dCIT to apply these learned motor skills to daily life and family life than patients with onset <10 mo ago; therefore, they will have greater opportunities to engage in a family role.

Effect of IADLs on the SS–QOL Mobility Domain

Participants with NEADL scores of ≤11 of the total 22 points improved significantly more in SS–QOL Mobility domain scores than those with NEADL scores >11 points. This finding suggests that stroke patients with lower capabilities in extended ADL performance before treatment had more room to improve than those who had higher capabilities in extended ADL performance before treatment. The four NEADL domains are Mobility, Kitchen, Domestic, and Leisure. The NEADL Mobility domain, along with some other NEADL domains, is related to the SS–QOL Mobility domain, resulting in the NEADL being a significant predictor for the Mobility outcome on the SS–QOL.

Evidence Regarding Age and IADLs on the SS–QOL Mood Domain

SS–QOL Mood domain scores improved significantly more among participants who were >68 yr old than among those ≤68 yr old. Older age is related to increasing subjective well-being among stroke patients (Wyller, Holmen, Laake, & Laake, 1998). People who are >68 yr old may have fewer expectations for potential improvement from dCIT; if true, they may be more easily satisfied with improvement after dCIT than younger people.

However, people who were <68 yr old and had lower IADL abilities (NEADL scores <20) were located in the unfavorable outcome end of the SS–QOL Mood domain, indicating that these two risk factors deteriorated mood outcome after the intervention. The explanation might be that stroke survivors who are <68 yr old might have more desire and expectations for performing IADLs. Poor IADL ability (NEADL score <20) may have impeded them from achieving their expectations, even after training, thus negatively affecting their mood outcome. This study lends support to the findings of previous studies that IADL is related to HRQOL and life satisfaction (Hartman-Maeir et al., 2007; Sveen et al., 2004).

Gender, cognitive status (as measured by the MMSE), motor ability (as measured by the FMA), and daily functional ability (as measured by the FIM) did not appear to be predictors of SS–QOL scores in this study sample. Our findings were consistent with those of a previous study (Jönsson, Lindgren, Hallström, Norrving, & Lindgren, 2005) that showed that gender and levels of cognitive and motor function were not determinants of any changes in the HRQOL domains. An unexpected finding was that change in FIM scores was not significantly related to change in SS–QOL scores. Use of different potential predictors and measurement tools for HRQOL outcome (e.g., the SS–QOL and SIS) in the research literature might account for this discrepancy. Unlike the SIS, the SS–QOL involves Energy, Family Role, Social Role, and Work–Productivity domains, which may be closely related to IADL and which the FIM is not sensitive in detecting. The SIS and SS–QOL both contain the ADL–IADL domain; however, this domain in the SIS includes some items, such as bladder and bowel control, that are more specific and basic than items on the SS–QOL. The FIM might better predict the basic ADL items on the SIS than the general and complex ones on the SS–QOL.

Even though the SS–QOL scores improved after treatment, the eight predictors that we tested only predicted 4 of the 12 domains. No specific predictors were identified in the SS–QOL domains of Language, Personality, Self-Care, Social Roles, Thinking, Upper Extremity Function, Vision, and Work–Productivity. Contrary to our intuition, we found no significant predictors for the Upper Extremity Function, Self-Care, and Work–Productivity domains. These three domains involve increasingly complicated physical activities that require finer motor control and bilateral arm movement. A close examination of the items in the SS–QOL Upper Extremity Function domain suggested that the questions related to daily functional tasks, such as “Did you have trouble putting on socks?” or “Did you have trouble opening a jar?” may require bilateral arm function. The dCIT regimen focuses on mass practice of the affected arm, and the possible benefits of motor ability after dCIT may not have translated into self-perceived improvement in functional tasks performed with both arms. In addition, participants were close to age 60, and returning to work may not have been a primary goal for rehabilitation, resulting in no notable improvement in the Work–Productivity domain.