IMPORTANCE Cancer-related fatigue (CRF) remains one of the most prevalent and troublesome adverse events experienced by patients with cancer during and after therapy. OBJECTIVE To perform a meta-analysis to establish and compare the mean weighted effect sizes (WESs) of the 4 most commonly recommended treatments for CRF—exercise, psychological, combined exercise and psychological, and pharmaceutical—and to identify independent variables associated with treatment effectiveness. DATA SOURCES PubMed, PsycINFO, CINAHL, EMBASE, and the Cochrane Library were searched from the inception of each database to May 31, 2016. STUDY SELECTION Randomized clinical trials in adults with cancer were selected. Inclusion criteria consisted of CRF severity as an outcome and testing of exercise, psychological, exercise plus psychological, or pharmaceutical interventions. DATA EXTRACTION AND SYNTHESIS Studies were independently reviewed by 12 raters in 3 groups using a systematic and blinded process for reconciling disagreement. Effect sizes (Cohen d) were calculated and inversely weighted by SE. MAIN OUTCOMES AND MEASURES Severity of CRF was the primary outcome. Study quality was assessed using a modified 12-item version of the Physiotherapy Evidence-Based Database scale (range, 0–12, with 12 indicating best quality). RESULTS From 17 033 references, 113 unique studies articles (11525 unique participants; 78% female; mean age, 54 [range, 35–72] years) published from January 1, 1999, through May 31, 2016, had sufficient data. Studies were of good quality (mean Physiotherapy Evidence-Based Database scale score, 8.2; range, 5–12) with no evidence of publication bias. Exercise (WES, 0.30; 95% CI, 0.25–0.36; P < .001), psychological (WES, 0.27; 95% CI, 0.21–0.33; P < .001), and exercise plus psychological interventions (WES, 0.26; 95% CI, 0.13–0.38; P < .001) improved CRF during and after primary treatment, whereas pharmaceutical interventions did not (WES, 0.09; 95% CI, 0.00–0.19; P = .05). Results also suggest that CRF treatment effectiveness was associated with cancer stage, baseline treatment status, experimental treatment format, experimental treatment delivery mode, psychological mode, type of control condition, use of intention-to-treat analysis, and fatigue measures (WES range, −0.91 to 0.99). Results suggest that the effectiveness of behavioral interventions, specifically exercise and psychological interventions, is not attributable to time, attention, and education, and specific intervention modes may be more effective for treating CRF at different points in the cancer treatment trajectory (WES range, 0.09–0.22). CONCLUSIONS AND RELEVANCE Exercise and psychological interventions are effective for reducing CRF during and after cancer treatment, and they are significantly better than the available pharmaceutical options. Clinicians should prescribe exercise or psychological interventions as first-line treatments for CRF.

BACKGROUND: Burnout affects nearly half of all U.S. nurses and physicians, and has been linked to poor outcomes such as worse patient safety. The most common measure of burnout is the well-validated Maslach Burnout Inventory (MBI). However, the MBI is proprietary and carries licensing fees, posing challenges to routine or repeated assessment. OBJECTIVE: To compare a non-proprietary, single-item burnout measure to a single item from the MBI Emotional Exhaustion (MBI:EE) subscale that has been validated as a standalone burnout measure. DESIGN: Cross-sectional online survey. PARTICIPANTS: A sample of primary care providers (PCPs), registered nurses, clinical associates (e.g., licensed practical nurses (LPNs), medical technicians), and administrative clerks in the Veterans Health Administration surveyed in 2012. MAIN METHODS: We compared a validated one-item version of the MBI:EE and a non-proprietary single-item burnout measure used in the Physician Work Life Study. We calculated kappa statistics, sensitivity and specificity, positive predictive (PPV) and negative predictive values (NPV), and area under the receiver operator curve (AUC). We conducted analyses stratified by occupation to determine the stability of the correlation between the two measures. KEY RESULTS: We analyzed responses from 5,404 participants, including 1,769 providers and 1,380 registered nurses. The prevalence of burnout was 36.7 % as measured on the single MBI:EE item and 38.5 % as measured on the non-proprietary single-item measure. Relative to the MBI:EE, the non-proprietary single-item measure had a correlation of 0.79, sensitivity of 83.2 %, specificity of 87.4 %, and AUC of 0.93 (se=0.004). Results were similar when stratified by respondent occupation. CONCLUSIONS: A non-proprietary single-item measure served as a reliable substitute for the MBI:EE across occupations. Because it is non-proprietary and easy to interpret, it has logistical advantages over the one-item MBI.

The authors conducted 4 studies to construct a multidimensional measure of perceptions of organization personality. Results of the first 2 studies suggest that (a) 5 broad factors are sufficient to capture the structure of organization personality perceptions, (b) real-world organizations differ on personality profiles, and (c) personality trait inferences are related to organizational attraction. Results of a 3rd study suggest that personality trait inferences assessed in 1 sample are related lo ratings of organizational attractiveness by a 2nd sample. Finally, results of a 4th study suggest that the measure is sensitive to experimental manipulations of organizational descriptions. Implications and suggestions for the use of this measure in future research are discussed.

Objective Mobile Health (mHealth) approaches can support the rehabilitation of individuals with psychiatric conditions. In the current article, we describe the development of a smartphone illness self-management system for people with schizophrenia. Methods The research was conducted with consumers and practitioners at a community-based rehabilitation agency. Stage 1: 904 individuals with schizophrenia or schizoaffective disorder completed a survey reporting on their current use of mobile devices and interest in mHealth services. Eight practitioners completed a survey examining their attitudes and expectations from an mHealth intervention, and identified needs and potential obstacles. Stage 2: A multidisciplinary team incorporated consumer and practitioner input and employed design principles for the development of e-resources for people with schizophrenia to produce an mHealth intervention. Stage 3: 12 consumers participated in laboratory usability sessions. They performed tasks involved in operating the new system, and provided “think aloud” commentary and post-session usability ratings. Results 570 (63%) of survey respondents reported owning a mobile device and many expressed interest in receiving mHealth services. Most practitioners believed that consumers could learn to use and would benefit from an mHealth intervention. In response, we developed a smartphone system that targets medication adherence, mood regulation, sleep, social functioning, and coping with symptoms. Usability testing revealed several design vulnerabilities, and the system was adapted to address consumer needs and preferences accordingly. Conclusions and Implications for Practice Through a comprehensive development process, we produced an mHealth illness self-management intervention that is likely to be used successfully, and is ready for deployment and systemic evaluation in real-world conditions.