Posts Tagged quality of life
[ARTICLE] Effects of Virtual Reality Exercise Program on Balance, Emotion and Quality of Life in Patients with Cognitive Decline
[Abstract] The feasibility and impact of a yoga pilot programme on the quality-of-life of adults with acquired brain injury – CNS
OBJECTIVE: This pilot study measured the feasibility and impact of an 8-week yoga programme on the quality-of-life of adults with acquired brain injury (ABI).
METHODS: Thirty-one adults with ABI were allocated to yoga (n = 16) or control (n = 15) groups. Participants completed the Quality of Life After Brain Injury (QOLIBRI) measure pre- and post-intervention; individuals in the yoga group also rated programme satisfaction. Mann-Whitney/Wilcoxon and the Wilcoxon Signed Rank tests were used to evaluate between- and within-group differences for the total and sub-scale QOLIBRI scores, respectively.
RESULTS: No significant differences emerged between groups on the QOLIBRI pre- or post-intervention. However, there were significant improvements on overall quality-of-life and on Emotions and Feeling sub-scales for the intervention group only. The overall QOLIBRI score improved from 1.93 (SD = 0.27) to 2.15 (SD = 0.34, p = 0.01). The mean Emotions sub-scale increased from 1.69 (SD = 0.40) to 2.01 (SD = 0.52, p = 0.01), and the mean Feeling sub-scale from 2.1 (SD = 0.34) to 2.42 (SD = 0.39, p = 0.01).
CONCLUSION: Adults with ABI experienced improvements in overall quality-of-life following an 8-week yoga programme. Specific improvements in self-perception and negative emotions also emerged. High attendance and satisfaction ratings support the feasibility of this type of intervention for people with brain injury.
[ARTICLE] Visual Impairment Following Stroke – The Impact on Quality of Life: A Systematic Review – Full Text PDF
Background: The visual impairments caused by stroke have the potential to affect the ability of an individual to perform activities of daily living. An individual with visual impairment may also have reduced level of independence. The purpose of this review was to investigate the impact on quality of life from stroke related visual impairment, using subjective patient reported outcome measures.
Methods: A systematic search of the literature was performed. The inclusion criteria required studies to have adult participants (aged 18 years or over) with a diagnosis of a visual impairment directly resulting from a stroke. Studies which included visual impairment as a result of other intracranial aetiology, were included if over half of the participants were stroke survivors. Multiple scholarly online databases and registers of published, unpublished and ongoing trials were searched, in addition articles were hand searched. MESH terms and alternatives in relation to stroke and visual conditions were used. Study selection was performed by two authors independently. Data was extracted by one author and verified by a second. The quality of the evidence was assessed using a quality appraisal tool and reporting guidelines.
Results: This review included 11 studies which involved 5646 participants, the studies used a mixture of generic and vision-specific instruments. The seven instruments used by the included studies were the EQ-5D, LIFE-H, SF-36, NEI VFQ-25, VA LV VFQ-48, SRA-VFP and DLTV.
Conclusion: A reduction in quality of life was reported by all studies in stroke survivors with visual impairment. Some studies used generic instruments, therefore making it difficult to extract the specific impact of the visual impairment as opposed to the other deficits caused by stroke. The majority of studies (8/11) primarily had participants with visual field loss. This skew towards visual field loss and no studies investigating the impact ocular motility prevented a comparison of the effects on quality of life due to different visual impairments caused by stroke. In order to fully understand the impact of visual impairment following stroke on quality of life, further studies need to use an appropriate vision-specific outcome measure and include all types of visual impairment which can result from a stroke.
[Abstract] Caregiver-mediated exercises for improving outcomes after stroke (Cochrane review) [with consumer summary]
BACKGROUND: Stroke is a major cause of long-term disability in adults. Several systematic reviews have shown that a higher intensity of training can lead to better functional outcomes after stroke. Currently, the resources in inpatient settings are not always sufficient and innovative methods are necessary to meet these recommendations without increasing healthcare costs. A resource efficient method to augment intensity of training could be to involve caregivers in exercise training. A caregiver-mediated exercise programme has the potential to improve outcomes in terms of body function, activities, and participation in people with stroke. In addition, caregivers are more actively involved in the rehabilitation process, which may increase feelings of empowerment with reduced levels of caregiver burden and could facilitate the transition from rehabilitation facility (in hospital, rehabilitation centre, or nursing home) to home setting. As a consequence, length of stay might be reduced and early supported discharge could be enhanced.
OBJECTIVES: To determine if caregiver-mediated exercises (CME) improve functional ability and health-related quality of life in people with stroke, and to determine the effect on caregiver burden.
SEARCH METHODS: We searched the Cochrane Stroke Group Trials Register (October 2015), CENTRAL (the Cochrane Library, 2015, issue 10), Medline (1946 to October 2015), Embase (1980 to December 2015), CINAHL (1982 to December 2015), SPORTDiscus (1985 to December 2015), three additional databases (two in October 2015, one in December 2015), and six additional trial registers (October 2015). We also screened reference lists of relevant publications and contacted authors in the field.
SELECTION CRITERIA: Randomised controlled trials comparing CME to usual care, no intervention, or another intervention as long as it was not caregiver-mediated, aimed at improving motor function in people who have had a stroke.
DATA COLLECTION AND ANALYSIS: Two review authors independently selected trials. One review author extracted data, and assessed quality and risk of bias, and a second review author cross-checked these data and assessed quality. We determined the quality of the evidence using GRADE. The small number of included studies limited the pre-planned analyses.
MAIN RESULTS: We included nine trials about CME, of which six trials with 333 patient-caregiver couples were included in the meta-analysis. The small number of studies, participants, and a variety of outcome measures rendered summarising and combining of data in meta-analysis difficult. In addition, in some studies, CME was the only intervention (CME-core), whereas in other studies, caregivers provided another, existing intervention, such as constraint-induced movement therapy. For trials in the latter category, it was difficult to separate the effects of CME from the effects of the other intervention. We found no significant effect of CME on basic ADL when pooling all trial data post intervention (4 studies; standardised mean difference (SMD) 0.21, 95% confidence interval (CI) -0.02 to 0.44; p = 0.07; moderate-quality evidence) or at follow-up (2 studies; mean difference (MD) 2.69, 95% CI -8.18 to 13.55; p = 0.63; low-quality evidence). In addition, we found no significant effects of CME on extended ADL at post intervention (two studies; SMD 0.07, 95% CI -0.21 to 0.35; p = 0.64; low-quality evidence) or at follow-up (2 studies; SMD 0.11, 95% CI -0.17 to 0.39; p = 0.45; low-quality evidence). Caregiver burden did not increase at the end of the intervention (2 studies; SMD -0.04, 95% CI -0.45 to 0.37; p = 0.86; moderate-quality evidence) or at follow-up (1 study; MD 0.60, 95% CI -0.71 to 1.91; p = 0.37; very low-quality evidence). At the end of intervention, CME significantly improved the secondary outcomes of standing balance (3 studies; SMD 0.53, 95% CI 0.19 to 0.87; p = 0.002; low-quality evidence) and quality of life (1 study; physical functioning MD 12.40, 95% CI 1.67 to 23.13; p = 0.02; mobility MD 18.20, 95% CI 7.54 to 28.86; p = 0.0008; general recovery MD 15.10, 95% CI 8.44 to 21.76; p < 0.00001; very low-quality evidence). At follow-up, we found a significant effect in favour of CME for Six-Minute Walking Test distance (1 study; MD 109.50 m, 95% CI 17.12 to 201.88; p = 0.02; very low-quality evidence). We also found a significant effect in favour of the control group at the end of intervention, regarding performance time on the Wolf Motor Function test (2 studies; MD -1.72, 95% CI -2.23 to -1.21; p < 0.00001; low-quality evidence). We found no significant effects for the other secondary outcomes (ie, patient: motor impairment, upper limb function, mood, fatigue, length of stay and adverse events; caregiver: mood and quality of life). In contrast to the primary analysis, sensitivity analysis of CME-core showed a significant effect of CME on basic ADL post intervention (2 studies; MD 9.45, 95% CI 2.11 to 16.78; p = 0.01; moderate-quality evidence). The methodological quality of the included trials and variability in interventions (eg, content, timing, and duration), affected the validity and generalisability of these observed results.
AUTHORS’ CONCLUSIONS: There is very low- to moderate-quality evidence that CME may be a valuable intervention to augment the pallet of therapeutic options for stroke rehabilitation. Included studies were small, heterogeneous, and some trials had an unclear or high risk of bias. Future high-quality research should determine whether CME interventions are (cost-)effective.
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The purpose of this study was to develop a computational method to identify potential predictors for quality of life (QOL) after post stroke rehabilitation.
Five classifiers were trained by five personal factors and nine functional outcome measures by 10-fold cross-validation. The classifier with the highest cross-validated accuracy was considered to be the optimal classifier for QOL prediction.
Particle Swarm-Optimized Support Vector Machine (PSO-SVM) showed highest accuracy in predicting QOL in stroke patients and was adopted as the optimal classifier. Potential predictors were assessed by PSO-SVM with feature selection. The early outcomes of Quality of Movement scale of the Motor Activity Log (MAL_QOM) and the Stroke Impact Scale (SIS) were identified to be the most predictive outcome predictors for QOL.
The approach provides the medical team another possibility to improve the accuracy in predicting QOL in stroke patients. Therapists could determine the therapies for stroke patients more accurately and efficiently to enhance the quality of life after stroke.
Stroke remains a leading cause of death and disability in the developed world . After stroke, the effects of stroke and post stroke rehabilitation are usually assessed by health professional ratings and performance tests [2–4]. However, real life of stroke survivors is affected in multiple ways and may not be described completely by only health and functional status. It is possible that a treatment succeeds in enhancing physical function recovery however induces psychosocial problems [5,6]. In this case, quality of life (QOL) may actually be degraded after poststroke rehabilitation. The WHO suggests that a comprehensive view of quality of life includes not only physical health, but also psychological health, social relationships, and environmental quality . Therefore, to obtain a comprehensive view of the effects after stroke, life quality should also be considered when assessing a person’s health and functioning.
In recent years, assessment of QOL in stroke has become increasingly common. Many recent rehabilitation therapies have been reported to be effective in restoring upper limb motor function after stroke but showed varied effects in QOL [7–10]. Different rehabilitation therapies may benefit different subgroups of the stroke population and cause different effects to QOL. Identifying key predictors of QOL may assist therapists to determine an optimal therapy, which can not only improve physical function but also maximize QOL for a specific subgroup of stroke survivors. Decision making of rehabilitation strategies may be more efficient and complete with identifying predominant predictors of QOL.
Only three studies examined predictors of QOL [5,11,12]. In these three studies, the predictive ability of multiple factors was examined, including demographic factors, vascular risk factors, clinical scales and neuropsychological assessment, and lesion characteristics. However, general predictors of outcomes of QOL were hard to determine because of the heterogeneity among these studies. Both physical and psychological factors were reported to be important in predicting QOL after stroke [5,11,12]. Although stroke rehabilitation gains in QOL are important, the question of which patients may benefit most in QOL from specific therapies has not been widely addressed, and statistical approaches to reveal such associations and predictors may not be optimal [13,14]. However, possible predictors related to QOL performance outcome after rehabilitation remained less discussed. More studies are needed to clarify the predictive ability of diverse QOL predictors in stroke patients.
Practical implementation of outcome predictors in clinical use was also constrained by the complexity of the algorithms. Developing prognostic algorithm based on existing and simple algorithms may reduce the complexity in clinical implementation, increase the use of prognostic model, and further improve the efficiency of rehabilitation therapy. Traditionally, studies examined outcome predictors used regression analysis to discriminate the most predictive factors from others [15–18]. However, the results of regression analysis can only explained the variance of the outcome in percentage. Computational methods can provide another aspect of outcome prediction. The results of regression statistical method showed that the factors were predictors for the outcome measure model, and the model only explained how percentage of the variance in the outcome measure scores. However, the results of computational classifier methods can provide accuracy and more application related to the predictors.
It has been applied in predicting clinical outcome in cancer patients and showed high accuracy and efficiency [19,20]. Using classifiers could improve the accuracy in predicting QOL. Hopefully, predominant predictors could also be better identified. That’s why we try to utilize a computational classifier method to identify potential predictors for quality of life (QOL) after post stroke rehabilitation.
[ARTICLE] A systematic review of active video games on rehabilitative outcomes among older patients – Full Text
Although current research supports the use of active video games (AVGs) in rehabilitation, the evidence has yet to be systematically reviewed or synthesized. The current project systematically reviewed literature, summarized findings, and evaluated the effectiveness of AVGs as a therapeutic tool in improving physical, psychological, and cognitive rehabilitative outcomes among older adults with chronic diseases.
Seven databases (Academic Search Complete, Communication & Mass Media Complete, ERIC, PsycINFO, PubMed, SPORTDiscus, and Medline) were searched for studies that evaluated the effectiveness of AVG-based rehabilitation among older patients. The initial search yielded 946 articles; after evaluating against inclusion criteria and removing duplicates, 19 studies of AVG-based rehabilitation remained.
Most studies were quasiexperimental in design, with physical functioning the primary outcome investigated with regard to the use of AVGs in rehabilitation. Overall, 9 studies found significant improvements for all study outcomes, whereas 9 studies were mixed, with significant improvements on several study outcomes but no effects observed on other outcomes after AVG-based treatments. One study failed to find any benefits of AVG-based rehabilitation.
Findings indicate AVGs have potential in rehabilitation for older patients, with several randomized clinical trials reporting positive effects on rehabilitative outcomes. However, existing evidence is insufficient to support the advantages of AVGs over standard therapy. Given the limited number of studies and concerns with study design quality, more research is warranted to make more definitive conclusions regarding the ability of AVGs to improve rehabilitative outcomes in older patients.
Findings favored active video games (AVGs) in balance and falls efficacy promotion.
Across all age groups, AVGs were used most often for balance rehabilitation.
AVG-based physical functioning rehabilitation common in middle-aged/older adults
Falls efficacy was the only similar psychological outcome across all ages/studies.
Larger samples/more psychological rehabilitative outcomes needed in future studies.
A meta-analysis on Active Video Games (AVG) as a rehabilitative tool does not appear to be available. This meta-analytic review synthesizes the effectiveness of AVGs on patients’ rehabilitative outcomes. Ninety-eight published studies on AVGs and rehabilitation were obtained in late 2015 with 14 meeting the following inclusion criteria: 1) data-based English articles; 2) randomized-controlled trials investigating AVG’s effect on rehabilitative outcome(s); and 3) ≥ 1 comparison present in each study. Data extraction for comparisons was completed for three age categories: 1) youth/young adults (5–25 years-old); 2) middle-aged adults (40–65 years-old); and 3) older adults (≥ 65 years-old). Comprehensive Meta-Analysis software calculated effect size (ES; Hedge’s g). Comparison group protocols often employed another non-AVG experimental treatment. Control group protocols implemented standard care. AVGs demonstrated a large positive effect on balance control over control among youth/young adults (ES = 0.81, p < 0.01). Further, AVGs resulted in small positive effects on middle-aged adults’ balance control over control (ES = 0.143, p = 0.48) and comparison (ES = 0.14, p = 0.53), with similar results in older adults compared to control (ES = 0.16, p = 0.27). Notably, AVG’s effect on balance control versus comparison among older adults was small yet negative (ES = − 0.12, p = 0.63). AVGs were also used to enhance general physical functioning (GPF) among middle-aged and older adults. Versus control and comparison, AVGs had no effect on middle-aged adults’ GPF (ES = − 0.054 and − 0.046, respectively) or older adults’ GPF (ES = 0.04 and 0.002, respectively). Finally, AVGs had a moderate effect on older adults’ falls efficacy versus control (ES = 0.61, p < 0.05). Findings favor AVGs for youth/young adult balance control rehabilitation and falls efficacy promotion in older adults.
[Abstract] Effect of Underwater Exercise on Lower-Extremity Function and Quality of Life in Post-Stroke Patients: A Pilot Controlled Clinical Trial. – PubMed
To date, controlled clinical trials evaluating the efficacy of underwater exercise in improving the lower-extremity function and quality of life (QOL) in post-stroke patients have yet to be conducted. The purpose of the present study was to determine whether repeated underwater exercise enhances the therapeutic effect of conventional therapy for post-stroke patients.
This was a pilot controlled clinical trial.
The study took place in a research facility attached to a rehabilitation hospital.
This prospective trial included 120 consecutive post-stroke inpatients with hemiplegic lower limbs (Brunnstrom stage 3-6). Patients were assigned to either an experimental or a control group. Patients in the experimental group received both repeated underwater exercise and conventional rehabilitation therapy.
The underwater exercise consisted of 30-min training sessions in a pool with a water temperature of 30-31°C in which patients followed the directions and movements of trained staff. Training sessions were conducted once a day on 2 days of the week for a total of 24 times. Patients in the control group received only the conventional therapy.
The 10-Minute Walk Test (10MWT), the Modified Ashworth Scale, and the 36-Item Short Form Health Survey were the outcome measures used. Lower-extremity function and QOL were assessed before and upon completion of the 12-week program.
Improvements in 10MWT results and spasticity parameters were greater in the experimental group than they were in the control group (p < 0.01). Significant differences between the groups were observed in magnitudes of changes of all QOL parameters (p < 0.01).
Combining conventional therapy with repeated underwater exercise may improve both lower-extremity function and QOL in post-stroke patients.
[ARTICLE] Comparison of Two Post-Stroke Rehabilitation Programs: A Follow-Up Study among Primary versus Specialized Health Care – Full Text HTML
To compare home-based rehabilitation (RITH) and standard outpatient rehabilitation in a hospital setting, in terms of improving the functional recovery and quality of life of stroke patients.
Study Design and Setting
This was a prospective cohort study in Andalusia (Spain).
One hundred and forty-five patients completed the outcome data.
Daily activities were measured by the Barthel index, Canadian Neurological Scale (to assess mental state), Tinetti scale (balance and gait), and Short Form Health Survey-36 (SF-36 to compare the quality of life).
No statistically significant differences were found between the two groups regarding the clinical characteristics of patients in the initial measurement, except for age and mental state (younger and with greater neurological impairment in the hospital group). After physical therapy, both groups showed statistically significant improvements from baseline in each of the measures. These improvements were better in RITH patients than in the hospital patients on all functionality scales with a smaller number of sessions.
Home rehabilitation is at least as effective as the outpatient rehabilitation programs in a hospital setting, in terms of recovery of functionality in post-stroke patients. Overall quality of life is severely impaired in both groups, as stroke is a very disabling disease that radically affects patients’ lives.
OBJECTIVE: The aim of this study was to assess the quality of life (QoL) of
traumatic brain injury (TBI) patients and to explore its predictive factors.
MATERIAL/PATIENTS AND METHODS: This is a descriptive and analytical
cross-sectional study, including 27 TBI patients followed in the physical
medicine and rehabilitation department (PMR). The collected data were: age,
educational level, marital status, initial Glosgow score and intensive care unit
length of stay. The assessment of the QoL was based on two scales, the first one was specific: Quality of Life after Brain Injury (QOLIBRI), while the second was generic: the SF-36. We had assessed memory disorders by the mini mental state (MMS) and functional capacity by The Functional Independence Measure (FIM). The handicap was assessed by Go Outcome Scale (GOS). Possible correlations between QoL and the different variables were explored.
RESULTS: The mean age of patients was 32.19 years. For QOLIBRI scale, the overall average score was 48.03%, the most affected dimensions were the feelings and social relations. Regarding the SF-36 scale, impaired QoL was found in 74% of these patients, the overall average score was 43.02. A significant correlation was found between QOLIBRI and mental composite score of the SF-36 (P=0.012). Memory disorder was significantly correlated with QoL (P=0.037). There were no statistically significant correlations between QoL and the other variables.
DISCUSSION-CONCLUSION: Memory disorder was the main predictive factor of impaired quality of life of traumatic brain injury patients; however, there was no correlation between handicap and QoL. This alteration of QOL has clinical implications and highlights the necessity of more efforts to optimize the rehabilitation interventions.