918 resultados para activities of daily living (ADL)


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Objective: During hospitalisation older people often experience functional decline which impacts on their future independence. The objective of this study was to evaluate a multifaceted transitional care intervention including home-based exercise strategies for at-risk older people on functional status, independence in activities of daily living, and walking ability. Methods: A randomised controlled trial was undertaken in a metropolitan hospital in Australia with 128 patients (64 intervention, 64 control) aged over 65 years with an acute medical admission and at least one risk factor for hospital readmission. The intervention group received an individually tailored program for exercise and follow-up care which was commenced in hospital and included regular visits in hospital by a physiotherapist and a Registered Nurse, a home visit following discharge, and regular telephone follow-up for 24 weeks following discharge. The program was designed to improve health promoting behaviours, strength, stability, endurance and mobility. Data were collected at baseline, then 4, 12 and 24 weeks following discharge using the Index of Activities of Daily Living (ADL), Instrumental Index of Activities of Daily Living (IADL), and the Walking Impairment Questionnaire (Modified). Results: Significant improvements were found in the intervention group in IADL scores (p<.001), ADL scores (p<.001), and WIQ scale scores (p<.001) in comparison to the control group. The greatest improvements were found in the first four weeks following discharge. Conclusions: Early introduction of a transitional model of care incorporating a tailored exercise program and regular telephone follow-up for hospitalised at-risk older adults can improve independence and functional ability.

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Children with developmental co-ordination disorder (DCD) face evident motor difficulties in activities of daily living (ADL). Assessment of their capacity in ADL is essential for diagnosis and intervention, in order to limit the daily consequences of the disorder. The aim of this study is to systematically review potential instruments for standardized and objective assessment of children's capacity in ADL, suited for children with DCD. As a first step, databases of MEDLINE, EMBASE, CINAHL and PsycINFO were searched to identify studies that described instruments with potential for assessment of capacity in ADL. Second, instruments were included for review when two independent reviewers agreed that the instruments: (1) are standardized and objective; (2) assess at activity level and comprise items that reflect ADL, and; (3) are applicable to school-aged children that can move independently. Out of 1507 publications, 66 publications were selected, describing 39 instruments. Seven of these instruments were found to fulfil the criteria and were included for review: the Bruininks-Oseretsky Test of Motor Performance-2 (BOT2); the Do-Eat (Do-Eat); the Movement Assessment Battery for Children-2 (MABC2); the school-Assessment of Motor and Process Skills (schoolAMPS); the Tuffts Assessment of Motor Performance (TAMP); the Test of Gross Motor Development (TGMD); and the Functional Independence Measure for Children (WeeFIM). As a third step, for the included instruments, suitability for children with DCD was discussed based on the ADL comprised, ecological validity and other psychometric properties. We concluded that current instruments do not provide comprehensive and ecologically valid assessment of capacity in ADL as required for children with DCD.

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Difficulties in the performance of activities of daily living (ADL) are a key feature of developmental coordination disorder (DCD). The DCDDaily-Q was developed to address children's motor performance in a comprehensive range ADL. The aim of this study was to investigate the psychometric properties of this parental questionnaire. Parents of 218 five to eight year-old children (DCD group: N=25; reference group: N=193) completed the research version of the new DCDDaily-Q and the Movement Assessment Battery for Children-2 (MABC2) Checklist and Developmental Coordination Disorder Questionnaire (DCDQ). Children were assessed with the MABC2 and DCDDaily. Item reduction analyses were performed and reliability (internal consistency and factor structure) and concurrent, discriminant, and incremental validity of the DCDDaily-Q were investigated. The final version of the DCDDaily-Q comprises 23 items that cover three underlying factors and shows good internal consistency (Cronbach's α>.80). Moderate correlations were found between the DCDDaily-Q and the other instruments used (p<.001 for the reference group; p>.05 for the DCD group). Discriminant validity of the DCDDaily-Q was good for DCDDaily-Q total scores (p<.001) and all 23 item scores (p<.01), indicating poorer performance in the DCD group. Sensitivity (88%) and specificity (92%) were good. The DCDDaily-Q better predicted DCD than currently used questionnaires (R2=.88). In conclusion, the DCDDaily-Q is a valid and reliable questionnaire to address children's ADL performance.

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Background Children with developmental coordination disorder (DCD) face evident motor difficulties in daily functioning. Little is known, however, about their difficulties in specific activities of daily living (ADL). Objective The purposes of this study were: (1) to investigate differences between children with DCD and their peers with typical development for ADL performance, learning, and participation, and (2) to explore the predictive values of these aspects. Design. This was a cross-sectional study. Methods In both a clinical sample of children diagnosed with DCD (n=25 [21 male, 4 female], age range=5-8 years) and a group of peers with typical development (25 matched controls), the children’s parents completed the DCDDaily-Q. Differences in scores between the groups were investigated using t tests for performance and participation and Pearson chi-square analysis for learning. Multiple regression analyses were performed to explore the predictive values of performance, learning, and participation. Results Compared with their peers, children with DCD showed poor performance of ADL and less frequent participation in some ADL. Children with DCD demonstrated heterogeneous patterns of performance (poor in 10%-80% of the items) and learning (delayed in 0%-100% of the items). In the DCD group, delays in learning of ADL were a predictor for poor performance of ADL, and poor performance of ADL was a predictor for less frequent participation in ADL compared with the control group. Limitations A limited number of children with DCD were addressed in this study. Conclusions This study highlights the impact of DCD on children’s daily lives and the need for tailored intervention.

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Objective To develop the DCDDaily, an instrument for objective and standardized clinical assessment of capacity in activities of daily living (ADL) in children with developmental coordination disorder (DCD), and to investigate its usability, reliability, and validity. Subjects Five to eight-year-old children with and without DCD. Main measures The DCDDaily was developed based on thorough review of the literature and extensive expert involvement. To investigate the usability (assessment time and feasibility), reliability (internal consistency and repeatability), and validity (concurrent and discriminant validity) of the DCDDaily, children were assessed with the DCDDaily and the Movement Assessment Battery for Children-2 Test, and their parents filled in the Movement Assessment Battery for Children-2 Checklist and Developmental Coordination Disorder Questionnaire. Results 459 children were assessed (DCD group, n = 55; normative reference group, n = 404). Assessment was possible within 30 minutes and in any clinical setting. For internal consistency, Cronbach’s α = 0.83. Intraclass correlation = 0.87 for test–retest reliability and 0.89 for inter-rater reliability. Concurrent correlations with Movement Assessment Battery for Children-2 Test and questionnaires were ρ = −0.494, 0.239, and −0.284, p < 0.001. Discriminant validity measures showed significantly worse performance in the DCD group than in the control group (mean (SD) score 33 (5.6) versus 26 (4.3), p < 0.001). The area under curve characteristic = 0.872, sensitivity and specificity were 80%. Conclusions The DCDDaily is a valid and reliable instrument for clinical assessment of capacity in ADL, that is feasible for use in clinical practice.

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This study determined whether the Functional Independence Measure (FIM) and the Frenchay Activities Index (FAI) could be used together as a more comprehensive score to assess the activities of daily living (ADL) in stroke survivors. Subjects were recruited from stroke patients consecutively admitted to the inpatient neurology or rehabilitation department at a university hospital in southern Taiwan. We interviewed 209 first stroke survivors at least 1 year after stroke onset during their clinical visits, at home, or in long-term care institutions. Combinations of FIM and FAI as a comprehensive assessment of ADL were measured. All items of the FIM and the FAI were included in a non-parametric factor analysis to determine their underlying constructs. Two comprehensive functional independence scores were then computed as functions of the FIM and FAI scores. The distributional characteristics of the comprehensive scores were examined. Approximately 90% of the total variation was explained by three factors. One single factor comprised all the items from FIM, while the FAI items loaded on two other factors, suggesting that FIM supplements FAI without overlap in content. We further demonstrated that the presence of ceiling or floor effects when either the FIM or the FAI was used could be removed using combined scores of the two instruments. The FIM and the FAI assessed different domains with good construct validity. A comprehensive assessment of functional independence obtained by combining the FIM and the FAI scores is potentially more appropriate and useful for clinical and research applications in stroke patients.

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Determining the groups that are most susceptible to developing disability is essential to establishing effective prevention and rehabilitation strategies. The aim of the present study was to determine gender differences in the incidence of disability regarding activities of daily living (ADL) and determinants among elderly residents of Sao Paulo, Brazil. In 2000, 1634 elderly with no difficulties regarding ADL (modified Katz Index) were selected. These activities were reassessed in 2006 and disability was the outcome for the analysis of determinants. The following characteristics were analyzed at baseline: sociodemographic, behavioral, health status, medications, falls, hospitalizations, depressive symptoms, cognition, handgrip, mobility and balance. The incidence density was 42.4/1000 women/year and 17.5/1000 men/year. After adjusting for socioeconomic status and health conditions, women with chronic diseases and social vulnerability continued to have a greater incidence of disability. The following were determinants of the incidence of disability: age and depressive symptoms in both genders; stroke and slowness on the sit-and-stand test among men; and osteoarthritis and sedentary lifestyle among women. Better cognitive performance and handgrip strength were protective factors among men and women, respectively. Adverse clinical and social conditions determine differences between genders regarding the incidence of disability. Decreased mobility and balance and health conditions that affect the central nervous system or lead to impaired cognition disable men more, whereas a sedentary lifestyle, reduction in muscle strength and conditions that affect the osteoarticular system disable women more. (C) 2012 Elsevier Ireland Ltd. All rights reserved.

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In the past decade, several arm rehabilitation robots have been developed to assist neurological patients during therapy. Early devices were limited in their number of degrees of freedom and range of motion, whereas newer robots such as the ARMin robot can support the entire arm. Often, these devices are combined with virtual environments to integrate motivating game-like scenarios. Several studies have shown a positive effect of game-playing on therapy outcome by increasing motivation. In addition, we assume that practicing highly functional movements can further enhance therapy outcome by facilitating the transfer of motor abilities acquired in therapy to daily life. Therefore, we present a rehabilitation system that enables the training of activities of daily living (ADL) with the support of an assistive robot. Important ADL tasks have been identified and implemented in a virtual environment. A patient-cooperative control strategy with adaptable freedom in timing and space was developed to assist the patient during the task. The technical feasibility and usability of the system was evaluated with seven healthy subjects and three chronic stroke patients.

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BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.

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Activities of daily living (ADL) are important for quality of life. They are indicators of cognitive health status and their assessment is a measure of independence in everyday living. ADL are difficult to reliably assess using questionnaires due to self-reporting biases. Various sensor-based (wearable, in-home, intrusive) systems have been proposed to successfully recognize and quantify ADL without relying on self-reporting. New classifiers required to classify sensor data are on the rise. We propose two ad-hoc classifiers that are based only on non-intrusive sensor data. METHODS: A wireless sensor system with ten sensor boxes was installed in the home of ten healthy subjects to collect ambient data over a duration of 20 consecutive days. A handheld protocol device and a paper logbook were also provided to the subjects. Eight ADL were selected for recognition. We developed two ad-hoc ADL classifiers, namely the rule based forward chaining inference engine (RBI) classifier and the circadian activity rhythm (CAR) classifier. The RBI classifier finds facts in data and matches them against the rules. The CAR classifier works within a framework to automatically rate routine activities to detect regular repeating patterns of behavior. For comparison, two state-of-the-art [Naïves Bayes (NB), Random Forest (RF)] classifiers have also been used. All classifiers were validated with the collected data sets for classification and recognition of the eight specific ADL. RESULTS: Out of a total of 1,373 ADL, the RBI classifier correctly determined 1,264, while missing 109 and the CAR determined 1,305 while missing 68 ADL. The RBI and CAR classifier recognized activities with an average sensitivity of 91.27 and 94.36%, respectively, outperforming both RF and NB. CONCLUSIONS: The performance of the classifiers varied significantly and shows that the classifier plays an important role in ADL recognition. Both RBI and CAR classifier performed better than existing state-of-the-art (NB, RF) on all ADL. Of the two ad-hoc classifiers, the CAR classifier was more accurate and is likely to be better suited than the RBI for distinguishing and recognizing complex ADL.

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Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.

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This study describes the discharge destination, basic and instrumental activities of daily living (ADL), community reintegration and generic health status of people after stroke, and explored whether sociodemographic and clinical characteristics were associated with these outcomes. Participants were 51 people, with an initial stroke, admitted to an acute hospital and discharged to the community. Admission and discharge data were obtained by chart review. Follow-up status was determined by telephone interview using the Modified Barthel Index, the Assessment of Living Skills and Resources, the Reintegration to Normal Living Index, and the Short-Form Health Survey (SF-36). At follow up, 57% of participants were independent in basic ADL, 84% had a low risk of experiencing instrumental ADL difficulties, most had few concerns with community reintegration, and SF-36 physical functioning and vitality scores were lower than normative values. At follow up, poorer discharge basic ADL status was associated with poorer instrumental ADL and community reintegration status, and older participants had poorer instrumental ADL, community reintegration and physical functioning. Occupational therapists need to consider these outcomes when planning inpatient and post-discharge intervention for people after stroke.

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This study examined the relationship between normal weight, overweight and obesity class I and II+, and the risk of disability, which is defined as impairment in activities of daily living (ADL). Systematic searching of the literature identified eight cross-sectional studies and four longitudinal studies that were comparable for meta-analysis. An additional four cross-sectional studies and one longitudinal study were included for qualitative review. Results from the meta-analysis of cross-sectional studies revealed a graded increase in the risk of ADL limitations from overweight (1.04, 95% confidence interval [CI] 1.00-1.08), class I obesity (1.16, 95% CI 1.11-1.21) and class II+ obesity (1.76, 95% CI 1.28-2.41), relative to normal weight. Meta-analyses of longitudinal studies revealed a similar graded relationship; however, the magnitude of this relationship was slightly greater for all body mass index categories. Qualitative analysis of studies that met the inclusion criteria but were not compatible for meta-analysis supported the pooled results. No studies identified met all of the pre-defined quality criteria, and subgroup analysis was inhibited due to insufficient comparable studies. We conclude that increasing body weight increases the risk of disability in a graded manner, but also emphasize the need for additional studies using contemporary longitudinal cohorts with large numbers of obese class III individuals, a range of ages and with measured height and weight, and incident ADL questions.

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Background: Decreased ability to perform Activities of Daily Living (ADLs) during hospitalisation has negative consequences for patients and health service delivery. Objective: To develop an Index to stratify patients at lower and higher risk of a significant decline in ability to perform ADLs at discharge. Design: Prospective two cohort study comprising a derivation (n=389; mean age 82.3 years; SD� 7.1) and a validation cohort (n=153; mean age 81.5 years; SD� 6.1). Patients and setting: General medical patients aged = 70 years admitted to three university-affiliated acute care hospitals in Brisbane, Australia. Measurement and main results: The short ADL Scale was used to identify a significant decline in ability to perform ADLs from premorbid to discharge. In the derivation cohort, 77 patients (19.8%) experienced a significant decline. Four significant factors were identified for patients independent at baseline: 'requiring moderate assistance to being totally dependent on others with bathing'; 'difficulty understanding others (frequently or all the time)'; 'requiring moderate assistance to being totally dependent on others with performing housework'; a 'history of experiencing at least one fall in the previous 90 days prior to hospital admission' in addition to 'independent at baseline', which was protective against decline at discharge. 'Difficulty understanding others (frequently or all the time)' and 'requiring moderate assistance to being totally dependent on others with performing housework' were also predictors for patients dependent in ADLs at baseline. Sensitivity, specificity, Positive Predictive Value (PPV), and Negative Predictive Value (NPV) of the DADLD dichotomised risk scores were: 83.1% (95% CI 72.8; 90.7); 60.5% (95% CI 54.8; 65.9); 34.2% (95% CI 27.5; 41.5); 93.5% (95% CI 89.2; 96.5). In the validation cohort, 47 patients (30.7%) experienced a significant decline. Sensitivity, specificity, PPV and NPV of the DADLD were: 78.7% (95% CI 64.3; 89.3); 69.8% (95% CI 60.1, 78.3); 53.6% (95% CI 41.2; 65.7); 88.1% (95% CI 79.2; 94.1). Conclusions: The DADLD Index is a useful tool for identifying patients at higher risk of decline in ability to perform ADLs at discharge.