BACKGROUND: Depression in later life is a common mental disorder with a prevalence rate of between 3% and 35% for minor depression and approximately 2% for Major Depressive Disorder (MDD). The most common treatment modalities for MDD are antidepressant medication and psychological interventions. Recently, Behavioral Activation (BA) has gained renewed attention as an effective treatment modality in MDD. Although BA is considered an easy accessible intervention for both patients and health care workers (such as nurses), there is no research on the effectiveness of the intervention in inpatient depressed elderly.The aim of study, described in the present proposal, is to examine the effects of BA when executed by nurses in an inpatient population of elderly persons with MDD. METHODS/DESIGN: The study is designed as a multi-center cluster randomized controlled trial. BA, described as The Systematic Activation Method (SAM) will be compared with Treatment as Usual (TAU). We aim to include ten mental health care units in the Netherlands that will each participate as a control unit or an experimental unit. The patients will meet the following criteria: (1) a primary diagnosis of Major Depressive Disorder (MDD) according to the DSM-IV criteria; (2) 60 years or older; (3) able to read and write in Dutch; (4) have consented to participate via the informed consent procedure. Based on an effect size d = 0.7, we intend to include 51 participants per condition (n = 102). The SAM will be implemented within the experimental units as an adjunctive therapy to Treatment As Usual (TAU). All patients will be assessed at baseline, after eight weeks, and after six months. The primary outcome will be the level of depression measured by means of the Beck Depression Inventory (Dutch version). Other assessments will be activity level, mastery, costs, anxiety and quality of life. DISCUSSION: To our knowledge this is the first study to test the effect of Behavioral Activation as a nursing intervention in an inpatient elderly population. This research has been approved by the medical research ethics committee for health-care settings in the Netherlands (No. NL26878.029.09) and is listed in the Dutch Trial Register (NTR No.1809).
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Background: COPD self-management is a complex behavior influenced by many factors. Despite scientific evidence that better disease outcomes can be achieved by enhancing self-management, many COPD patients do not respond to self-management interventions. To move toward more effective self-management interventions, knowledge of characteristics associated with activation for self-management is needed. The purpose of this study was to identify key patient and disease characteristics of activation for self-management. Methods: An explorative cross-sectional study was conducted in primary and secondary care in patients with COPD. Data were collected through questionnaires and chart reviews. The main outcome was activation for self-management, measured with the 13-item Patient Activation Measure (PAM). Independent variables were sociodemographic variables, self-reported health status, depression, anxiety, illness perception, social support, disease severity, and comorbidities. Results: A total of 290 participants (age: 67.2±10.3; forced expiratory volume in 1 second predicted: 63.6±19.2) were eligible for analysis. While poor activation for self-management (PAM-1) was observed in 23% of the participants, only 15% was activated for self-management (PAM-4). Multiple linear regression analysis revealed six explanatory determinants of activation for self-management (P,0.2): anxiety (β: -0.35; -0.6 to -0.1), illness perception (β: -0.2; -0.3 to -0.1), body mass index (BMI) (β: -0.4; -0.7 to -0.2), age (β: -0.1; -0.3 to -0.01), Global Initiative for Chronic Obstructive Lung Disease stage (2 vs 1 β: -3.2; -5.8 to -0.5; 3 vs 1 β: -3.4; -7.1 to 0.3), and comorbidities (β: 0.8; -0.2 to 1.8), explaining 17% of the variance. Conclusion: This study showed that only a minority of COPD patients is activated for self-management. Although only a limited part of the variance could be explained, anxiety, illness perception, BMI, age, disease severity, and comorbidities were identified as key determinants of activation for self-management. This knowledge enables health care professionals to identify patients at risk of inadequate self-management, which is essential to move toward targeting and tailoring of self-management interventions. Future studies are needed to understand the complex causal mechanisms toward change in self-management
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Self-efficacy and outcome expectations regarding client activation determine professionals’ level of actively engaging clients during daily activities. The Client Activation Self-Efficacy and Outcome Expectation Scales for nurses and domestic support workers (DSWs) were developed to measure these concepts. This study aimed to assess their psychometric properties. Cross-sectional data from a sample of Dutch nurses (n=150) and DSWs (n=155) were analysed. Descriptive statistics were used to examine floor and ceiling effects. Construct validity was assessed by testing research-based hypotheses. Internal consistency was determined with Cronbach’s alpha. The scales for nurses showed a ceiling effect. There were no floor or ceiling effects in the scales for domestic support workers. Three out of five hypotheses could be confirmed (construct validity). For all scales, Cronbach’s alpha coefficients exceeded 0.70. In conclusion, all scales had moderate construct validity and high internal consistency. Further research is needed concerning their construct validity, testretest reliability and sensitivity to change.
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A substantial proportion of chronic disease patients do not respond to self-management interventions, which suggests that one size interventions do not fit all, demanding more tailored interventions. To compose more individualized strategies, we aim to increase our understanding of characteristics associated with patient activation for self-management and to evaluate whether these are disease-transcending. A cross-sectional survey study was conducted in primary and secondary care in patients with type-2 Diabetes Mellitus (DM-II), Chronic Obstructive Pulmonary Disease (COPD), Chronic Heart Failure (CHF) and Chronic Renal Disease (CRD). Using multiple linear regression analysis, we analyzed associations between self-management activation (13-item Patient Activation Measure; PAM-13) and a wide range of socio-demographic, clinical, and psychosocial determinants. Furthermore, we assessed whether the associations between the determinants and the PAM were disease-transcending by testing whether disease was an effect modifier. In addition, we identified determinants associated with low activation for self-management using logistic regression analysis. We included 1154 patients (53% response rate); 422 DM-II patients, 290 COPD patients, 223 HF patients and 219 CRD patients. Mean age was 69.6±10.9. Multiple linear regression analysis revealed 9 explanatory determinants of activation for selfmanagement: age, BMI, educational level, financial distress, physical health status, depression, illness perception, social support and underlying disease, explaining a variance of 16.3%. All associations, except for social support, were disease transcending. This study explored factors associated with varying levels of activation for self-management. These results are a first step in supporting clinicians and researchers to identify subpopulations of chronic disease patients less likely to be engaged in self-management. Increased scientific efforts are needed to explain the greater part of the factors that contribute to the complex nature of patient activation for self-management.
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This paper presents the results of an evaluation of a technology-supported leisure game for people with dementia in relation to the stimulation of social behavior.
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Background: Physical inactivity is common during hospitalization. Physical activity has been described in different inpatient populations but never across a hospital. Purpose: To describe inpatient movement behavior and associated factors throughout a single university hospital. Methods: A prospective observational study was performed. Patients admitted to clinical wards were included. Behavioral mapping was undertaken for each participant between 9AM and 4PM. The location, physical activity, daily activity, and company of participants were described. Barriers to physical activity were examined using linear regression analyses. Results: In total, 345 participants from 19 different wards were included. The mean (SD) age was 61 (16) years and 57% of participants were male. In total, 65% of participants were able to walk independently. On average participants spent 86% of observed time in their room and 10% of their time moving. A physiotherapist or occupational therapist was present during 1% of the time, nursing staff and family were present 11% and 13%, respectively. Multivariate regression analysis showed the presence of an intravenous line (p = .039), urinary catheter (p = .031), being female (p = .034), or being dependent on others for walking (p = .016) to be positively associated with the time spent in bed. Age > 65, undergoing surgery, receiving encouragement by a nurse or physician, reporting a physical complaint or pain were not associated with the time spent in bed (P > .05). Conclusion: As family members and nursing staff spend more time with patients than physiotherapists or occupational therapists, increasing their involvement might be an important next step in the promotion of physical activity.
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The historically developed practice of learning to play a music instrument from notes instead of by imitation or improvisation makes it possible to contrast two types of skilled musicians characterized not only by dissimilar performance practices, but also disparate methods of audiomotor learning. In a recent fMRI study comparing these two groups of musicians while they either imagined playing along with a recording or covertly assessed the quality of the performance, we observed activation of a right-hemisphere network of posterior superior parietal and dorsal premotor cortices in improvising musicians, indicating more efficient audiomotor transformation. In the present study, we investigated the detailed performance characteristics underlying the ability of both groups of musicians to replicate music on the basis of aural perception alone. Twenty-two classically trained improvising and score-dependent musicians listened to short, unfamiliar two-part excerpts presented with headphones. They played along or replicated the excerpts by ear on a digital piano, either with or without aural feedback. In addition, they were asked to harmonize or transpose some of the excerpts either to a different key or to the relative minor. MIDI recordings of their performances were compared with recordings of the aural model. Concordance was expressed in an audiomotor alignment score computed with the help of music information retrieval algorithms. Significantly higher alignment scores were found when contrasting groups, voices, and tasks. The present study demonstrates the superior ability of improvising musicians to replicate both the pitch and rhythm of aurally perceived music at the keyboard, not only in the original key, but also in other tonalities. Taken together with the enhanced activation of the right dorsal frontoparietal network found in our previous fMRI study, these results underscore the conclusion that the practice of improvising music can be associated with enhanced audiomotor transformation in response to aurally perceived music.
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BACKGROUND: Although enhancing physical activity (PA) is important to improve physical and/or cognitive recovery, little is known about PA of patients admitted to an inpatient rehabilitation setting. Therefore, this study assessed the quantity, nature and context of inpatients PA admitted to a rehabilitation center. METHODOLOGY/PRINICIPAL FINDINGS: Prospective observational study using accelerometry & behavioral mapping. PA of patients admitted to inpatient rehabilitation was measured during one day between 7.00-22.00 by means of 3d-accelerometery (Activ8; percentage of sedentary/active time, number of sedentary/active bouts (continuous period of ≥1 minute), and active/sedentary bout lengths and behavioral mapping. Behavioral mapping consisted of observations (every 20 minutes) to assess: type of activity, body position, social context and physical location. Descriptive statistics were used to describe PA on group and individual level. At median the 15 patients spent 81% (IQR 74%-85%) being sedentary. Patients were most sedentary in the evening (maximum sedentary bout length minutes of 69 (IQR 54-95)). During 54% (IQR 50%-61%) of the observations patients were alone) and in their room (median 50% (IQR 45%-59%)), but individual patterns varied widely. CONCLUSION/SIGNIFICANCE: The results of this study enable a deeper understanding of the daily PA patterns of patients admitted for inpatient rehabilitation treatment. PA patterns of patients differ in both quantity, day structure, social and environmental contexts. This supports the need for individualized strategies to support PA behavior during inpatient rehabilitation treatment.
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This study provides an illustration of a research design complementary to randomized controlled trial to evaluate program effects, namely, participatory peer research (PPR). The PPR described in current study was carried out in a small sample (N = 10) of young adults with mild intellectual disabilities (MID) and severe behavioral problems. During the PPR intervention, control and feedback to individuals is restored by training them to become participant-researchers, who collaborate in a small group of people with MID. Their research is aimed at the problems the young adults perceive and/or specific subjects of their interest. The study was designed as a multiple case study with an experimental and comparison group. Questionnaires and a semistructured interview were administered before and after the PPR project. Results of Reliable Change Index (RCI) analyses showed a decrease in self-serving cognitive distortions in the PPR group, but not in the comparison group. These results indicate that PPR helps to compensate for a lack of adequate feedback and control, and in turn may decrease distorted thinking and thereby possibly later challenging behavior.
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BACKGROUND: Research suggests that cancer rehabilitation reduces fatigue in survivors of cancer. To date, it is unclear what type of rehabilitation is most beneficial.OBJECTIVE: This randomized controlled trial compared the effect on cancer-related fatigue of physical training combined with cognitive behavioral therapy with physical training alone and with no intervention.DESIGN: In this multicenter randomized controlled trial, 147 survivors of cancer were randomly assigned to a group that received physical training combined with cognitive-behavioral therapy (PT+CBT group, n=76) or to a group that received physical training alone (PT group, n=71). In addition, a nonintervention control group (WLC group) consisting of 62 survivors of cancer who were on the waiting lists of rehabilitation centers elsewhere was included.SETTING: The study was conducted at 4 rehabilitation centers in the Netherlands.PATIENTS: All patients were survivors of cancer.INTERVENTION: Physical training consisting of 2 hours of individual training and group sports took place twice weekly, and cognitive-behavioral therapy took place once weekly for 2 hours.MEASUREMENTS: Fatigue was assessed with the Multidimensional Fatigue Inventory before and immediately after intervention (12 weeks after enrollment). The WLC group completed questionnaires at the same time points.RESULTS: Baseline fatigue did not differ significantly among the 3 groups. Over time, levels of fatigue significantly decreased in all domains in all groups, except in mental fatigue in the WLC group. Analyses of variance of postintervention fatigue showed statistically significant group effects on general fatigue, on physical and mental fatigue, and on reduced activation but not on reduced motivation. Compared with the WLC group, the PT group reported significantly greater decline in 4 domains of fatigue, whereas the PT+CBT group reported significantly greater decline in physical fatigue only. No significant differences in decline in fatigue were found between the PT+CBT and PT groups.CONCLUSIONS: Physical training combined with cognitive-behavioral therapy and physical training alone had significant and beneficial effects on fatigue compared with no intervention. Physical training was equally effective as or more effective than physical training combined with cognitive-behavioral therapy in reducing cancer-related fatigue, suggesting that cognitive-behavioral therapy did not have additional beneficial effects beyond the benefits of physical training.
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