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Multiple sclerosis and fibromyalgia syndrome may spur substantial disability for those affected. Using structural equation modeling, this secondary analysis examined predictors of disability in women with multiple sclerosis (n = 118) and fibromyalgia syndrome (n = 197) recruited for separate wellness studies. Greater functional limitations, lower economic adequacy, less social support, and higher depressive symptoms predicted greater disability in both groups. The final multigroup model showed good fit [chi][superscript 2] [(111, n = 315) = 135.92, comparative fit index = 0.99, root mean square error of approximation = 0.03] and identified similarities and differences across groups.

Structural equation modeling (SEM), a popular statistical technique for analysis of multivariate data in the social sciences, is increasingly being used in the behavioral and clinical sciences. SEM is appropriate for posing complex models that evaluate the direct and indirect influence of several variables on one or more outcome variables. A biosocial model of disability, the Disablement Process Model, lends itself to evaluation by SEM. Using SEM, this study examined predictors of disability (Age, Education, Duration of Illness, and Economic Adequacy Functional Limitations, Depressive Symptoms, and Social Support) separately in women with multiple sclerosis (MS) and women with fibromyalgia syndrome (FMS) and compared the respective models across groups. Data were analyzed with Analysis of Moment Structures (Amos) 7.0. Problems identified in initial confirmatory model testing included collateral correlated errors, a negative error variance, and poor performance of the disability indicators. After specifying well-fitting confirmatory models for each group, a structural model for the larger FMS group was estimated. Model refinement resulted in the reversal of the path between Depressive Symptoms and Social Support. Further model revisions were based on comparative lit statistics and theoretical logic. The structural model developed from the FMS sample required minimal changes to fit the MS sample. The multisample model explained greater variance in disability in women with FMS than in women with MS. Social support and depressive symptoms mediated the effect of functional limitations on disability. Interventions that target modifiable characteristics, such as depression and social support, may improve outcomes such as disability. Keywords: structural equation modeling; disability fibromyalgia; multiple sclerosis; depression; social support

This study examined predictors of continued employment among persons with multiple sclerosis (MS) participating in a 7-year longitudinal study of health promotion and quality of life in MS. Participants for the present study were a subset (n=176) of a larger sample of persons with MS (N=621) who participated in the longitudinal study between the years 1996 to 2003, were employed at Time 1, and were younger than age 55. At Time 1 (1996), all participants were employed, and 75% of the sample reported full-time employment. At Time 7 (2003), only 55% reported continued employment. Forward stepwise multiple logistic regression analysis revealed that years of education, functional limitations related to MS, and health-promoting behaviors explained approximately 10.2% of the variance in employment status over time ([R.sup.2] = .102). The article discusses the importance of considering work-environmental factors in addition to disease and demographic factors in the prediction of employment outcomes for persons with MS., Multiple Sclerosis (MS) is one of the most prevalent neurologic diseases in the world and most often (90% of cases) manifests in people between the ages of 15-50 years (LaRocca, [...]

The purpose of this systematic review and meta-analysis was to determine the effects of supervised resistance and/or aerobic training physical activity interventions on performance-based measures of physical functioning among community-dwelling older adults, and to identify factors impacting intervention effectiveness. Diverse search strategies were used to identify eligible studies. Standardized mean difference effect sizes (d, ES) were synthesized using a random effects model. Moderator analyses were conducted using subgroup analyses and meta-regression. Twenty-eight studies were included. Moderator analyses were limited by inconsistent reporting of sample and intervention characteristics. The overall mean ES was 0.45 (k = 38, p ≤ .01), representing a clinically meaningful reduction of 0.92 s in the Timed Up and Go for treatment versus control. More minutes per week (p < .01) and longer intervention session duration (p < .01) were associated with larger effects. Interventions were especially effective among frail participants (d = 1.09). Future research should clearly describe sample and intervention characteristics and incorporate frail populations. [ABSTRACT FROM AUTHOR]

This qualitative study investigated individual and situational factors influencing physical activity (PA) practices of elders in residential-care/assisted-living (RC/ AL) communities. This article describes the results of focus-group interviews involving 47 residents across 6 RC/AL settings. Thematic analysis revealed 6 themes: staying active, past PA experiences, value of PA, barriers to PA, strategies to facilitate PA, and support needs to promote PA. Staying active meant walking indoors and out, attending chair-exercise programs, performing professionally prescribed home exercises, and using available exercise equipment. Past PA experiences shaped current preferences and practices. Participants agreed that exercise helped maintain physical functioning but recounted cognitive and situational barriers to PA. Lack of dedicated exercise space and short corridors hampered efforts to stay active. Participants wished for individualized home exercise programs and supervised exercise sessions. Future research should examine the extent to which the physical environment and PA programming in RC/AL communities affect elders' PA. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to identify predictors of 6-month physical function and 12-month relocation or death in 272 residents of 34 residential care/assisted communities. Method: Measures collected at baseline, 6, and 12 months included health and demographic characteristics; self-reported pain, fatigue, and depressive symptoms; exercise self-efficacy, barriers, and expectations; attitudes on aging; performance-based physical function and physical activity; and community demographics, programs, and policies. GLIMMIX procedures for regression analyses with community as a random effect were run. Results: Better baseline physical function and grip strength, female sex, and residential care community predicted better 6-month physical function. At 12 months, 25.6% had relocated or died. The odds of 12-month relocation or death for 1-point increase in physical function score was 0.84 and for 1-point increase in depression score was 1.16. Discussion: Targets to promote longer tenure in residential care/assisted living include programs to ameliorate functional decline and depression screening and treatment. [ABSTRACT FROM AUTHOR]

This study examined the relationships between individual and environmental factors and physical activity, and between physical activity and functional limitations and disability in residential care/assisted living (RC/AL) residents. Participants completed questionnaires and physical performance tests, and wore the Fitbit Motion Tracker® to capture physical activity. Model fit was analyzed using two-level path models with residents nested within RC/AL settings. Model parameters were estimated using the MPlus robust maximum likelihood method. A multilevel model with good fit (root mean square error of approximation = 0.07, comparative fit index [CFI] = 0.91) showed that persons with greater exercise self-efficacy were more physically active, and persons who were more physically active had better physical function and less disability. Setting-level factors did not significantly correlate with physical activity or disability. Although environmental factors may influence physical activity behavior, only individual factors were associated with physical activity in this sample of RC/AL residents. [ABSTRACT FROM AUTHOR]

The purpose of these meta-analyses was to quantitatively synthesize the effectiveness of simulation on student nurses’ and registered nurses’ ability to recognize and manage clinical deterioration in the acute care setting. A search of the literature resulted in 22 reports and 19 studies meeting inclusion criteria. Four random-effects analyses were conducted to examine two-group posttest and single-group pre–posttest intervention effect sizes for knowledge and performance. A total of 41 effect sizes were calculated from the data extracted. The standardized mean difference (d) for two-group posttest knowledge was d = 0.964 (p = .001) and for performance was d = 1.382 (p ≤ .001). The standardized mean difference for single-group pre–posttest knowledge was d = 1.231 (p ≤ .001) and performance was d = 1.610 (p ≤ .001). Findings indicate that simulation-based interventions have a positive effect on knowledge and performance. As simulation is increasingly used as a teaching modality in nursing, further research should aim to test standardized simulation-based education programs. [ABSTRACT FROM AUTHOR]

Environmentally embedded (nonwearable) sensor technology is in continuous use in elder housing to monitor a new set of ‘vital signs' that continuously measure the functional status of older adults, detect potential changes in health or functional status, and alert healthcare providers for early recognition and treatment of those changes. Older adult participants' respiration, pulse, and restlessness are monitored as they sleep. Gait speed, stride length, and stride time are calculated daily, and automatically assess for increasing fall risk. Activity levels are summarized and graphically displayed for easy interpretation. Falls are detected when they occur and alerts are sent immediately to healthcare providers, so time to rescue may be reduced. Automated health alerts are sent to healthcare staff, based on continuously running algorithms applied to the sensor data, days and weeks before typical signs or symptoms are detected by the person, family members, or healthcare providers. Discovering these new functional status ‘vital signs', developing automated methods for interpreting them, and alerting others when changes occur have the potential to transform chronic illness management and facilitate aging in place through the end of life. Key findings of research in progress at the University of Missouri are discussed in this viewpoint article, as well as obstacles to widespread adoption. [ABSTRACT FROM AUTHOR]

The author reflects on the advancement of depression research in nursing home residents in the U.S. She mentions that nursing home residents have various chronic conditions which include mental depression and its recognition remains to be a problem. The author cites a study that targets training in depression for workers in the nursing homes which she considers the first step toward improving depression detection.

This paper describes the evolution of an early illness warning system used by an interdisciplinary team composed of clinicians and engineers in an independent living facility. The early illness warning system consists of algorithms which analyze resident activity patterns obtained from sensors embedded in residents' apartments. The engineers designed an automated reasoning system to generate clinically relevant alerts which are sent to clinicians when significant changes occur in the sensor data, for example declining activity levels. During January 2010 through July 2010, clinicians and engineers conducted weekly iterative review cycles of the early illness warning system to discuss concerns about the functionality of the warning system, to recommend solutions for the concerns, and to evaluate the implementation of the solutions. A total of 45 concerns were reviewed during this period. Iterative reviews resulted in greater efficiencies and satisfaction for clinician users who were monitoring elder activity patterns.