The labor force participation rate for adults aged 55 years and older has increased nearly 10% over the past two and a half decades. As workers age, they frequently experience increased chronic health conditions and impaired sleep, which may negatively influence their self-rated health (SRH) and work performance. This study aimed to examine the associations between nonrestorative sleep (NRS) and work performance (i.e., difficulty concentrating or having lower productivity at work) and associations between demographic and sleep characteristics with SRH in middle-aged workers. We conducted a secondary data analysis among working middle-aged adults 50 to 65 years of age ( N = 392) from the 2008 Sleep in America Poll. Respondents frequently reported impaired sleep such as frequent insomnia symptoms, NRS, and short sleep duration. Nonrestorative sleep was associated with decreased work performance such as trouble organizing work, doing work over due to mistakes, and lower productivity. Nonrestorative sleep and short sleep duration were significantly associated with lower SRH. Strategies for the early detection of impaired sleep and implementation of interventions to improve sleep may improve SRH and work performance in working middle-aged adults.
BackgroundPhysical activity (PA) is a primary factor in reducing the risk of chronic diseases, yet only half of U.S. adults meet recommended levels.ObjectiveTo evaluate a PA self-monitoring pilot intervention using technology in obese adult primary care patients.MethodsThe project had a prospective, single group, pretest/posttest design using an accelerometer with a smartphone app. Obese adult primary care patients (N = 31) were followed over 6 months. Demographic (age, race, sex, marital status, educational level) and PA-relevant (PA, body mass index [BMI], self-efficacy for exercise [SEE]) data were collected at enrollment. PA and BMI were recorded monthly for 6 months. SEE was reassessed at 6 months.ResultsPA and BMI showed gradual improvement; however, changes in PA (p = .130), BMI (p = .326), and SEE (p = .877) at 6 months were not statistically significant. A strong, negative relationship was found between PA and BMI (r = −.727, p < .01). Anecdotal data indicated the smartphone app was acceptable to patients.ConclusionsData-supported clinician-initiated PA self-monitoring with a smartphone app was acceptable and showed favorable trends in improving PA and BMI in obese adult patients.Implications for NursingPrescribing PA self-monitoring using technology may be easily implemented.
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