Cross-sectional and temporal differences in health-related quality of life of people with and without osteoarthritis: a 10-year prospective study.

OBJECTIVE: To describe the impact of OA on health-related quality of life (HRQoL) in the forms of health state utilities (HSUs) and health-dimension scores, and to compare the longitudinal changes in HRQoL for people with and without OA, using an Australian population-based longitudinal cohort. METHODS: Participants of the Tasmanian Older Adult Cohort with data on OA diagnosis and HRQoL were included [interviewed at baseline (n = 1093), 2.5 years (n = 871), 5 years (n = 760) and 10 years (n = 562)]. HRQoL was assessed using the Assessment of Quality of Life four-dimensions and analysed using multivariable linear mixed regressions. RESULTS: Compared with participants without OA, HSUs for those with OA were 0.07 (95% confidence interval: 0.09, 0.05) units lower on average over 10 years. HSUs for participants with knee and/or hip OA were similar to those with other types of OA at the 2.5 year follow-up and then diverged, with HSUs of the former being up to 0.09 units lower than the latter. Those with OA had lower scores for psychological wellness, independent living and social relationships compared with those without OA. Independent living and social relationships were mainly impacted by knee and/or hip OA, with the effect on the former increasing over time. CONCLUSION: Interventions to improve HRQoL should be tailored to specific OA types, health dimensions, and times. Support for maintaining psychological wellness should be provided, irrespective of OA type and duration. However, support for maintaining independent living could be more relevant to knee and/or hip OA patients living with the disease for longer.

The impact of comorbidities on health-related quality of life of people with osteoarthritis over 10 years.

OBJECTIVE: To investigate the impact of total number and patterns of comorbidities on health-related quality of life (HRQoL) and identify the most prevalent and influential comorbidity patterns in people with OA over 10 years. METHODS: Participants from the Tasmanian Older Adult Cohort aged 50-80 years, with self-reported OA and data on comorbidities and HRQoL were included. Participants were interviewed at baseline (n = 398), 2.5 (n = 304), 5 (n = 269) and 10 years (n = 191). Data on the self-reported presence of 10 chronic comorbidities were collected at baseline. HRQoL was assessed using the Assessment of Quality of Life-4-Dimensions. The long-term impacts of the number and of the nine most prevalent combinations of cardiovascular (CVD), non-OA musculoskeletal (Ms), metabolic and respiratory comorbidities on HRQoL over 10 years were analysed using linear mixed regressions. RESULTS: Compared with comorbidity-free OA participants, the health state utility (HSU) of those with 2 or ≥3 comorbidities was respectively -0.07 and -0.13 units lower over 10 years, largely driven by reduced scores for independent living, social relationships and psychological wellness. Comorbidity patterns including 'CVD+Ms' were most influential, and associated with up to 0.13 units lower HSU, mostly through negative impacts on independent living (up to -0.12), psychological wellness (up to -0.08) and social relationship (up to -0.06). CONCLUSION: Having more comorbidities negatively impacted OA patients' long-term HRQoL. OA patients with CVD and non-OA musculoskeletal conditions had the largest HSU impairment, and therefore optimal management and prevention of these conditions may yield improvements in OA patients' HRQoL.

The habitual characteristic of smart phone use under relevant cues among Chinese college students.

Excessive smartphone use may be habitual behavior induced by cues associated with the phone. Habitual behavior occurs outside of awareness and is characterized by lack of control. It is not like problematic smartphone use (PSU) (Brand et al., 2016), which is used to either limit behavior or produce pleasure and relieve feelings of pain, stress, and failure despite significant harmful consequences. 62 college students participated in experiments to test the effects of visual cues and self-control, which are the important characteristic of habitual behavior in smartphone-related behavior. The results showed that a significantly larger amount of cue-related phone use behavior occurred in the setting where participants (a) had their smartphones in sight and (b) were given no instructions to exert self-control, compared to when neither of the two conditions was imposed. The habitual model is a useful framework for understanding PSU and can help people avoid it with less stress. The results provide substantial implications for reducing the frequency and duration of smartphone use among college populations.

Does health-related quality of life differ between people with relapse onset and progressive onset Multiple Sclerosis?

BACKGROUND: Multiple Sclerosis (MS) can be categorised as relapse onset MS (ROMS) and progressive onset MS (PROMS). We aimed to examine if health-related quality of life (in terms of health state utilities [HSUs] and dimensional scores) differed by onset type, in which health dimensions the differences were most pronounced, and whether these differences remained when stratified by disability severity. METHODS: We estimated HSUs and the unique composite 'super-dimension' and 'individual dimension' scores (crude, age, sex, disease duration and disease modifying therapies use adjusted; and stratified by onset type and disability severity) for a sample of 1577 participants in the Australian MS Longitudinal Study, using the Assessment of Quality of Life (AQoL)-8D. RESULTS: Adjusted mean overall HSU of PROMS was 0.55, 0.07 lower than ROMS. Adjusted mean physical and psychosocial super-dimension scores for PROMS were 0.51 and 0.28, 0.07 and 0.06 lower than for ROMS, respectively. For the individual health dimensions, the largest difference was seen in independent living (-0.12), followed by relationships (-0.07), and self-worth (-0.07). Whilst HSUs and dimensional scores were negatively associated with increasing disability severity in both onset types, estimates by disability severity did not differ between the two cohorts. CONCLUSIONS: Our study provides a comprehensive assessment of the effects of MS onset type on the overall and disability-severity specific HRQoL scores using a detailed preferentially sensitive AQoL-8D instrument. While overall HRQoL was substantially lower in PROMS than in ROMS, the mean HRQoL values for each disability level did not differ by onset type, indicating that future health economic models can use the same HSU inputs for both onset types.