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Background: Serious injuries and fatalities among vulnerable road users on two wheeled motorised vehicles have increased across Australia and internationally in the past decade yet fallen for motor vehicle occupants. Almost half of all reported motorcycle injury crashes cause serious injury or death, nearly double that of motor vehicle police-reported crashes. This study explores associations with sociodemographic and pre-injury health characteristics and health outcomes after a road traffic injury; aiming to compare motorcyclists with other road users and inform recovery care. Methods: An inception cohort study recruited 1854 individuals aged > 17 years, injured following land-transport crashes in New South Wales, Australia (July 2013–November 2016). Interviews conducted at baseline, 6-and 12-months post-injury elicited demographic, socioeconomic, and self-reported health conditions. Results: Primary analysis involved 1854 participants who were recruited at baseline as three distinct road user groups; 628 (33.9%) motorcyclists, 927 (50%) vehicle occupants and 299 (16.1%) bicyclists. At baseline, injury patterns differed significantly between road user groups; motorcyclists were more than twice as likely to sustain lower extremity injury (p < 0.001); to have more severe injury severity scores (p < 0.001) and longer hospital stays versus vs vehicle occupants and bicyclists (< 0.001) across these measures. Injured motorcyclists were predominantly male (88.1%, p < 0.001), were younger on average (38 years) than bicyclists (41.5 years), had lower income and education levels, and poorer pre-injury physical health than other road user groups. Despite these differences, at 12 months post-injury motorcyclists had better physical health (SF12-PCS 2.07 (0.77, 3.36), p = 0.002) and reported lower pain scores (− 0.51 (− 0.83, − 0.2), p < 0.001) than vehicle occupants. Motorcyclists displayed less evidence of psychological distress than vehicle occupants, but more than bicyclist

Purpose: People with age-related macular degeneration (AMD) experience high rates of depression, but rarely engage in or have access to tailored mental wellbeing programmes. This qualitative study investigated the perspectives of those primarily with late AMD on mental health and mental wellbeing programmes. Methods: Twenty-eight people with late AMD in at least one eye, and one person with early AMD in both eyes, aged 56–87 years (mean age 78 years) attending a private eye clinic between December 2019 and January 2020 in Sydney, New South Wales, Australia, participated. Individual semi-structured interviews were conducted and analysed deductively using content analysis, following the individual level factors for health promotion interventions in the behaviour change wheel: Capability (Physical & Psychological), Opportunity (Physical & Social), and Motivation (Reflective & Automatic). Results: Six major themes were identified: Capability: (1) Impact of vision loss on mobility and leisure pursuits; (2) Adjustment to living with vision loss; Opportunity: (3) Program considerations for those with AMD; (4) Stigma and self-perception of vision loss and mental health; Motivation: (5) Accumulation of vision-related issues as a barrier to participation; (6) Examples of others living with vision loss. General personal factors relevant to delivery of a programme in this age group were also identified: Comorbidities; Limitations using technology; Isolation; Financial concerns and Beliefs that undesired effects of aging are inevitable. Conclusions: Complex individual, environmental and social factors influence the perspectives of people with late AMD on mental health, and potential participation in mental wellbeing programmes. These factors should be considered when developing and implementing mental wellbeing programmes to improve the emotional and functional rehabilitation outcomes for people with AMD.

BACKGROUND: In current approaches to vision screening in the community, a simple and efficient process is needed to identify individuals who should be referred to tertiary eye care centres for vision loss related to eye diseases. The emergence of deep learning technology offers new opportunities to revolutionise this clinical referral pathway. We aimed to assess the performance of a newly developed deep learning algorithm for detection of disease-related visual impairment. METHODS: In this proof-of-concept study, using retinal fundus images from 15 175 eyes with complete data related to best-corrected visual acuity or pinhole visual acuity from the Singapore Epidemiology of Eye Diseases Study, we first developed a single-modality deep learning algorithm based on retinal photographs alone for detection of any disease-related visual impairment (defined as eyes from patients with major eye diseases and best-corrected visual acuity of <20/40), and moderate or worse disease-related visual impairment (eyes with disease and best-corrected visual acuity of <20/60). After development of the algorithm, we tested it internally, using a new set of 3803 eyes from the Singapore Epidemiology of Eye Diseases Study. We then tested it externally using three population-based studies (the Beijing Eye study [6239 eyes], Central India Eye and Medical study [6526 eyes], and Blue Mountains Eye Study [2002 eyes]), and two clinical studies (the Chinese University of Hong Kong's Sight Threatening Diabetic Retinopathy study [971 eyes] and the Outram Polyclinic Study [1225 eyes]). The algorithm's performance in each dataset was assessed on the basis of the area under the receiver operating characteristic curve (AUC). FINDINGS: In the internal test dataset, the AUC for detection of any disease-related visual impairment was 94·2% (95% CI 93·0-95·3; sensitivity 90·7% [87·0-93·6]; specificity 86·8% [85·6-87·9]). The AUC for moderate or worse disease-related visual impairment was 93·9% (95% CI 92·2

Abstract Background Serious injuries and fatalities among vulnerable road users on two wheeled motorised vehicles have increased across Australia and internationally in the past decade yet fallen for motor vehicle occupants. Almost half of all reported motorcycle injury crashes cause serious injury or death, nearly double that of motor vehicle police-reported crashes. This study explores associations with sociodemographic and pre-injury health characteristics and health outcomes after a road traffic injury; aiming to compare motorcyclists with other road users and inform recovery care. Methods An inception cohort study recruited 1854 individuals aged > 17 years, injured following land-transport crashes in New South Wales, Australia (July 2013–November 2016). Interviews conducted at baseline, 6-and 12-months post-injury elicited demographic, socioeconomic, and self-reported health conditions. Results Primary analysis involved 1854 participants who were recruited at baseline as three distinct road user groups; 628 (33.9%) motorcyclists, 927 (50%) vehicle occupants and 299 (16.1%) bicyclists. At baseline, injury patterns differed significantly between road user groups; motorcyclists were more than twice as likely to sustain lower extremity injury (p < 0.001); to have more severe injury severity scores (p < 0.001) and longer hospital stays versus vs vehicle occupants and bicyclists (< 0.001) across these measures. Injured motorcyclists were predominantly male (88.1%, p < 0.001), were younger on average (38 years) than bicyclists (41.5 years), had lower income and education levels, and poorer pre-injury physical health than other road user groups. Desp