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Introduction: The COVID-19 pandemic forced people to give up their daily routines and adjust to new circumstances. This might have affected health-related quality of life (HRQOL). We aimed to compare HRQOL during the first COVID-19 wave in 2020 to HRQOL before the pandemic and to identify determinants of HRQOL during the pandemic in Switzerland. Methods: We conducted a cross-sectional online survey during the pandemic (between May and July 2020; CoWELL sample; convenience sample). Before the pandemic (2015–2016), we had conducted a cross-sectional paper-based survey among a representative random sample of the Swiss general population (SGP sample). In both samples, we assessed physical and mental HRQOL (Short Form-36) and socio-demographic characteristics. In the CoWELL sample, we additionally assessed health- and COVID-19-related characteristics. Data were analysed using linear regressions. Results: The CoWELL sample included 1581 participants (76% women; mean age = 43 years, SD = 14 years) and the SGP sample 1209 participants (58% women, mean age = 49 years, SD = 15 years). Adjusted for sex, age, and education, the CoWELL sample reported higher physical HRQOL (PCS, +5.8 (95% CI: 5.1, 6.6), p < 0.001) and lower mental HRQOL (MCS, −6.9 (−7.8, −6.0), p < 0.001) than the SGP sample. In the CoWELL sample, especially persons with lower health literacy, who had no support network or who have had COVID-19, reported lower HRQOL. Discussion: Aspects unique to the COVID-19 pandemic affected HRQOL. Vulnerable persons such as those having had COVID-19, less support opportunities, and with lower health literacy are especially prone to impaired HRQOL during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Purpose: The Patient-Reported Outcomes Measurement Information System® (PROMIS®) was designed to develop, validate, and standardize item banks to measure key domains of physical, mental, and social health in chronic conditions. This paper reports the calibration and validation testing of the PROMIS Self-Efficacy for Managing Chronic Conditions measures.Methods: PROMIS Self-Efficacy for Managing Chronic Conditions item banks comprise five domains, Self-Efficacy for Managing: Daily Activities, Symptoms, Medications and Treatments, Emotions, and Social Interactions. Banks were calibrated in 1087 subjects from two data sources: 837 patients with chronic neurologic conditions (epilepsy, multiple sclerosis, neuropathy, Parkinson disease, and stroke) and 250 subjects from an online Internet sample of adults with general chronic conditions. Scores were compared with one legacy scale: Self-Efficacy for Managing Chronic Disease 6-Item scale (SEMCD6) and five PROMIS short forms: Global Health (Physical and Mental), Physical Function, Fatigue, Depression, and Anxiety.Results: The sample was 57% female, mean age = 53.8 (SD = 14.7), 76% white, 21% African American, 6% Hispanic, and 76% with greater than high school education. Full-item banks were created for each domain. All measures had good internal consistency and correlated well with SEMCD6 (r  = 0.56-0.75). Significant correlations were seen between the Self-Efficacy measures and other PROMIS short forms (r  > 0.38).Conclusions: The newly developed PROMIS Self-Efficacy for Managing Chronic Conditions measures include five domains of self-efficacy that were calibrated across diverse chronic conditions and show good internal consistency and cross-sectional validity. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to estimate the comorbidity of mental disorders and chronic physical conditions and to describe the impact of these conditions on health-related quality of life (HRQoL) in a sample of older primary care (PC) attendees by gender.Methods: Cross-sectional survey, conducted in 77 PC centres in Catalonia (Spain) on 1192 patients over 65 years old. Using face-to-face interviews, we assessed HRQoL (SF-12), mental disorders (SCID and MINI structured clinical interviews), chronic physical conditions (checklist), and disability (Sheehan disability scale). We used multivariate quantile regressions to model which factors were associated with the physical component summary-short form 12 and mental component summary-short form 12.Result: The most frequent comorbidity in both men and women was mood disorder with chronic pain and arthrosis. Mental disorders mainly affected 'mental' QoL, while physical disorders affected 'physical' QoL. Mental disorders had a greater impact on HRQoL than chronic physical conditions, with mood and adjustment disorders being the most disabling conditions. There were some gender differences in the impact of mental and chronic physical conditions on HRQoL. Anxiety disorders and pain had an impact on HRQoL but only in women. Respiratory diseases had an effect on the MCS in women, but only affected the PCS in men.Conclusions: Mood and adjustment disorders had the greatest impact on HRQoL. The impact profile of mental and chronic physical conditions differs between genders. Our results reinforce the need for screening for mental disorders (mainly depression) in older patients in PC. [ABSTRACT FROM AUTHOR]

Purpose: To derive EQ-5D-5L Spanish population norms based on a national representative sample adjusted by age, gender and region.Methods: A representative sample of the Spanish general population (n = 21,007) was used in a cross-sectional study. The source of data was the Spanish National Health Survey 2011-2012. All socio-demographic factors and clinical characteristics were carried to a descriptive analysis. All variables were stratified by region, gender and age-group.Results: The utility value 1 is the most repeated (62%) in this representative population sample. This study showed a deterioration of health states as age increases. Overall, men reported better health status than women. In relation to ceiling effect by regions, there was little difference with the highest scores. Conversely, the lowest score corresponds to Galicia.Conclusions: The paper reports EQ-5D-5L normative data for Spanish general population, based on a national representative sample adjusted by region, gender and age-group. These results may serve as reference data of the population health status. A regional difference in health status could be observed, which might suggest that policies aiming to reduce regional inequalities are important. [ABSTRACT FROM AUTHOR]