Amused, accepted, and used? Attitudes and emotions towards automated vehicles, their relationships, and predictive value for usage intention

Automated vehicles (AVs) have left the laboratories and can be experienced in several projects, e.g. at the premises of a clinic in Germany. With this transition, research on AV attitudes no longer needs to rely on questionnaires with hypothetical scenarios and simulations. Previous research – limited by the unavailability of AVs – has provided ambivalent results regarding age and gender differences in attitudes towards AVs. We present research results about the role of age and gender in connection with attitudes such as acceptance, perceived safety, and trust, as well as intention to use. We additionally demonstrate relationships between those constructs and emotions such as amusement, fear, and surprise. Data were collected from participants (n = 125) after having experienced an AV ride with level 4 automation on two campuses of a clinic in Berlin, Germany. Results reveal strong correlations between all attitudes (0.55 ≤ r ≤ 0.71; p < 0.01) and show acceptance and perceived safety to be solid predictors of intention to use AVs. We also found age to be a significant predictor for usage intention even when other attitudes are considered (β = −0.22; p < 0.01). MANOVA results point to gender differences in all constructs, but with limited confidence (5.40 ≤ F ≤ 18.34; p ≤ 0.02). However, we reject our hypothesis that young men are highly accepting, trusting, and intending to use AVs compared to other combinations of age and gender. We recommend using a mix of attitude, emotion, and behavioural (intention) measures in future research on AVs together with more transparency regarding construct definitions and study materials

Profiles of physical activity biographies in relation to life and aging satisfaction in older adults: longitudinal findings

Background: While there is substantial evidence on the relationship between life satisfaction and present physical activity (PA), less is known about which specific PA biographies are associated with a high quality of life and aging satisfaction. Our objective was to identify classes of PA biographies that may be associated with life and aging satisfaction. Methods: In this longitudinal study, PA biographies were assessed retrospectively as a baseline, followed by assessments of life and aging satisfaction at six and twelve months in 418 adults aged 60–95. Subgroups with different PA biographies were identified using latent class analysis. Results: Four distinct PA biographies emerged: increasingly active (35%; n = 147); consistently active (25%; n = 103); consistently inactive (18%; n = 75); and decreasingly active (22%; n = 94). Being consistently active was related to life satisfaction (β = .17) and consistent inactivity was associated with aging dissatisfaction (β = −.20) when accounting for current PA levels. Conclusions: In addition to current PA, our findings emphasize the value of PA biographies for life and aging satisfaction, which could inform lifespan theories of PA and health promotion

Predicting mortality in the very old: a machine learning analysis on claims data.

Machine learning (ML) may be used to predict mortality. We used claims data from one large German insurer to develop and test differently complex ML prediction models, comparing them for their (balanced) accuracy, but also the importance of different predictors, the relevance of the follow-up period before death (i.e. the amount of accumulated data) and the time distance of the data used for prediction and death. A sample of 373,077 insured very old, aged 75 years or above, living in the Northeast of Germany in 2012 was drawn and followed over 6 years. Our outcome was whether an individual died in one of the years of interest (2013-2017) or not; the primary metric was (balanced) accuracy in a hold-out test dataset. From the 86,326 potential variables, we used the 30 most important ones for modeling. We trained a total of 45 model combinations: (1) Three different ML models were used; logistic regression (LR), random forest (RF), extreme gradient boosting (XGB); (2) Different periods of follow-up were employed for training; 1-5 years; (3) Different time distances between data used for prediction and the time of the event (death/survival) were set; 0-4 years. The mortality rate was 9.15% in mean per year. The models showed (balanced) accuracy between 65 and 93%. A longer follow-up period showed limited to no advantage, but models with short time distance from the event were more accurate than models trained on more distant data. RF and XGB were more accurate than LR. For RF and XGB sensitivity and specificity were similar, while for LR sensitivity was significantly lower than specificity. For all three models, the positive-predictive-value was below 62% (and even dropped to below 20% for longer time distances from death), while the negative-predictive-value significantly exceeded 90% for all analyses. The utilization of and costs for emergency transport as well as emergency and any hospital visits as well as the utilization of conventional outpatient care and laboratory services were consistently found most relevant for predicting mortality. All models showed useful accuracies, and more complex models showed advantages. The variables employed for prediction were consistent across models and with medical reasoning. Identifying individuals at risk could assist tailored decision-making and interventions

Costs for Statutorily Insured Dental Services in Older Germans 2012–2017

Objectives: We assessed the costs of dental services in statutorily insured, very old (geriatric) Germans. Methods: A comprehensive sample of very old (≥75 years) people insured at a large Northeastern statutory insurer was followed over 6 years (2012–2017). We assessed dental services costs for: (1) examination, assessments and advice, (2) operative, (3) surgical, (4) prosthetic, (5) periodontal, (6) preventive and (7) outreach services. Association of utilization with: (1) sex, (2) age, (3) region, (4) social hardship status, (5) International Disease Classification (ICD-10) diagnoses and (6) Diagnoses Related Groups (DRGs) was explored. Results: 404,610 individuals with a mean (standard deviation, SD) age 81.9 (5.4 years) were followed, 173,733 did not survive follow-up. Total mean costs were 129.61 (310.97) euro per capita; the highest costs were for prosthetic (54.40, SD 242.89 euro) and operative services (28.40, SD 68.38 euro), examination/advice (21.15, SD 28.77 euro), prevention (13.31, SD 49.79 euro), surgery (5.91, SD 23.91 euro), outreach (4.81, SD 28.56 euro) and periodontal services (1.64, SD 7.39 euro). The introduction of new fee items for outreach and preventive services between 2012 and 2017 was reflected in costs. Total costs decreased with increasing age, and this was also found for all service blocks except outreach and preventive services. Costs were higher in those with social hardship status, and in Berlin than Brandenburg and Mecklenburg-Western Pomerania. Certain general health conditions were associated with increased or decreased costs. Conclusions: Costs were associated with sex, social hardship status, place of living and general health conditions. Clinical significance: Dental services costs for the elderly in Germany are unequally distributed and, up to a certain age or health status, generated by invasive interventions mainly. Policy makers should incentivize preventive services earlier on and aim to distribute expenses more equally

Informal caregivers during the COVID-19 pandemic perceive additional burden: findings from an ad-hoc survey in Germany

Background: While the relation between care involvement of informal caregivers and caregiver burden is well-known, the additional psychosocial burden related to care involvement during the COVID-19 pandemic has not yet been investigated. Methods: A total of 1000 informal caregivers, recruited offline, participated in a cross-sectional online survey from April 21 to May 2, 2020. Questionnaires were used to assess COVID-19-specific changes in the care situation, negative feelings in the care situation, problems with implementation of COVID-19 measures, concerns/excessive demands, loss of support, change in informal caregivers' own involvement in care and problems with provision, comprehension & practicability of COVID-19 information, and to relate these issues to five indicators of care involvement (i.e., being the main caregiver, high expenditure of time, high level of care, dementia, no professional help). Binomial and multiple regression analyses were applied. Results: Across indicators of care involvement, 25.5-39.7% reported that the care situation rather or greatly worsened during the COVID-19 pandemic, especially for those caring for someone with dementia or those usually relying on professional help. In a multiple regression model, the mean number of involvement indicators met was associated with age (beta = .18; CI .10-.25), excessive demands (beta = .10, CI .00-.19), problems with implementation of COVID-19 measures (beta = .11, CI .04-.19), an increase in caregiving by the informal caregivers themselves (beta = .14, CI .03-.24) as well as with no change in the amount of caregiving (beta = .18, CI .07-.29) and loss of support (beta = -.08, CI -.16-.00). No significant associations with the mean number of involvement indicators met were found for gender, educational level, change in the care situation, negative feelings, and provision, comprehension & practicability of COVID-19 information. Conclusion: Those caregivers who perceived extensive care burden were those who suffered most during the pandemic, calling for structural support by the healthcare system now and in the future

A study based on claims data from a German health insurance fund

Background The objective of this study is to investigate the effect of age on care dependency risk 1 year after stroke. Two research questions are addressed: (1) How strong is the association between age and care dependency risk 1 year after stroke and (2) can this association be explained by burden of disease? Methods The study is based on claims data from a German statutory health insurance fund. The study population was drawn from all continuously insured members with principal diagnoses of ischaemic stroke, hemorrhagic stroke, or transient ischaemic attack in 2007 who survived for 1 year after stroke and who were not dependent on care before their first stroke (n = 2864). Data were collected over a 1-year period. People are considered to be dependent on care if they, due to a physical, mental or psychological illness or disability, require substantial assistance in carrying out activities of daily living for a period of at least 6 months. Burden of disease was assessed by stroke subtype, history of stroke, comorbidities as well as geriatric multimorbidity. Regression models were used for data analysis. Results 21.6 % of patients became care dependent during the observation period. Post-stroke care dependency risk was significantly associated with age. Relative to the reference group (0–65 years), the odds ratio of care dependency was 11.30 (95 % CI: 7.82–16.34) in patients aged 86+ years and 5.10 (95 % CI: 3.88–6.71) in patients aged 76–85 years. These associations were not explained by burden of disease. On the contrary, age effects became stronger when burden of disease was included in the regression model (by between 1.1 and 28 %). Conclusions Our results show that age has an effect on care dependency risk that cannot be explained by burden of disease. Thus, there must be other underlying age- dependent factors that account for the remaining age effects (e.g., social conditions). Further studies are needed to explore the causes of the strong age effects observed

A Population-Based Survey

Background: Chronic conditions are an increasing challenge for individuals and the health care system. Smartphones and health apps are potentially promising tools to change health-related behaviors and manage chronic conditions. Objective: The aim of this study was to explore (1) the extent of smartphone and health app use, (2) sociodemographic, medical, and behavioral correlates of smartphone and health app use, and (3) associations of the use of apps and app characteristics with actual health behaviors. Methods: A population-based survey (N=4144) among Germans, aged 35 years and older, was conducted. Sociodemographics, presence of chronic conditions, health behaviors, quality of life, and health literacy, as well as the use of the Internet, smartphone, and health apps were assessed by questionnaire at home visit. Binary logistic regression models were applied. Results: It was found that 61.25% (2538/4144) of participants used a smartphone. Compared with nonusers, smartphone users were younger, did more research on the Internet, were more likely to work full-time and more likely to have a university degree, engaged more in physical activity, and less in low fat diet, and had a higher health-related quality of life and health literacy. Among smartphone users, 20.53% (521/2538) used health apps. App users were younger, less likely to be native German speakers, did more research on the Internet, were more likely to report chronic conditions, engaged more in physical activity, and low fat diet, and were more health literate compared with nonusers who had a smartphone. Health apps focused on smoking cessation (232/521, 44.5%), healthy diet (201/521, 38.6%), and weight loss (121/521, 23.2%). The most common app characteristics were planning (264/521, 50.7%), reminding (188/521, 36.1%), prompting motivation (179/521 34.4%), and the provision of information (175/521, 33.6%). Significant associations were found between planning and the health behavior physical activity, between feedback or monitoring and physical activity, and between feedback or monitoring and adherence to doctor’s advice. Conclusions: Although there were many smartphone and health app users, a substantial proportion of the population was not engaged. Findings suggest age-related, socioeconomic-related, literacy-related, and health-related disparities in the use of mobile technologies. Health app use may reflect a user’s motivation to change or maintain health behaviors. App developers and researchers should take account of the needs of older people, people with low health literacy, and chronic conditions

Psychosocial burden and associated factors among nurses in care homes during the COVID-19 pandemic: findings from a retrospective survey in Germany

Background: Care homes were hit hard by the COVID-19 pandemic. Although high levels of psychosocial burden (i.e., anxiety, depression and stress) during the pandemic have been described for healthcare workers in hospitals, evidence on the psychosocial burden for nurses in care homes during the pandemic is scarce. Methods: A total of 811 nurses participated in a retrospective online survey between November 2020 and February 2021. Information about the COVID-19 situation (i.e., working demands, COVID-19 cases in their facility, and COVID-19-related burden) of nurses in German care homes during the first wave of the pandemic (March 2020 to June 2020) was gathered. The Stress Scale of the Depression Anxiety and Stress Scales (SDASS-21), the Generalized Anxiety Disorder Scale-2 (GAD-2), the Patients-Health-Questionnaire-2 (PHQ-2), and the Copenhagen Psychosocial Questionnaire (COPSOQ) were used to screen for psychosocial burden. Results: Among nurses, 94.2% stated that working demands since the COVID-19 pandemic increased. Further, 59.1% showed clinically relevant levels of either stress, anxiety, and/or depression. Multiple regression analysis showed significant associations between COVID-19-related burden and qualification (p < .01), dissatisfaction with COVID-19 management of care home manager (p < .05), COVID-19-related anxiety (p < .001), and dementia as a focus of care (p < .05). Stress, depression, and anxiety showed associations with COVID-19 related burden at work (p < .01), COVID-19-related anxiety (p < .001), social support (p < .01), and sense of community (p < .05). Stress was also associated with COVID-19 cases among residents (p < .05), and size of care home (p < .05). Conclusion: Short- and long-term strategies (i.e., psychosocial counseling, mandatory team meetings, more highly qualified nurses, additional training) in the work environment of nursing, in crises, but beyond, should be encouraged to reduce the burden on nursing staff in care homes

I’m curious, I’m open to it, I test it, I trust it! A focus groups study to understand a-priori trust in automated buses

Trust is regarded as one of the main predictors for adopting automated buses (ABs). However, theories about trust (development) in technology generally vary and an in-depths study about trust in ABs specifically is still outstanding. The present study fills this gap by presenting results from focus group interviews to trust (development) in shared automated buses prior to exposure. The objectives of this study are to contrast participants’ naïve concepts of trust with theory and to identify underlying factors influencing a-priori trust in ABs. Results show that the N = 21 focus group participants use different strategies to familiarise themselves with the new technology of ABs, e.g., comparisons with familiar technologies, fundamental tendencies to approach or avoid, additional information seeking, or anthropomorphisation. These strategies largely support existing theories on trust (development) in technology. Differences between naïve interpretations of trust and its theoretical assumptions were found in focus group debates where more control over technology limited uncertainty and led to more trust. While theories suggest control and trust to be incompatible opposites, participants see control as a way to enhance trust. We provide starting points for further theory development and expansion and stress the importance of explanations in emerging technologies for trust and acceptance building

Associations of Health App Use and Perceived Effectiveness in People With Cardiovascular Diseases and Diabetes: Population-Based Survey

Background: Mobile health apps can help to change health-related behaviors and manage chronic conditions in patients with cardiovascular diseases (CVDs) and diabetes mellitus, but a certain level of health literacy and electronic health (eHealth) literacy may be needed. Objective: The aim of this study was to identify factors associated with mobile health app use in individuals with CVD or diabetes and detect relations with the perceived effectiveness of health apps among app users. Methods: The study used population-based Web-based survey (N=1500) among Germans, aged 35 years and older, with CVD, diabetes, or both. A total of 3 subgroups were examined: (1) Individuals with CVD (n=1325), (2) Individuals with diabetes (n=681), and (3) Individuals with CVD and diabetes (n=524). Sociodemographics, health behaviors, CVD, diabetes, health and eHealth literacy, characteristics of health app use, and characteristics of apps themselves were assessed by questionnaires. Linear and logistic regression models were applied. Results: Overall, patterns of factors associated with health app use were comparable in individuals with CVD or diabetes or both. Across subgroups, about every fourth patient reported using apps for health-related purposes, with physical activity and weight loss being the most prominent target behaviors. Health app users were younger, more likely to be female (except in those with CVD and diabetes combined), better educated, and reported more physical activity. App users had higher eHealth literacy than nonusers. Those users who perceived the app to have a greater effectiveness on their health behaviors tended to be more health and eHealth literate and rated the app to use more behavior change techniques (BCTs). Conclusions: There are health- and literacy-related disparities in the access to health app use among patients with CVD, diabetes, or both, which are relevant to specific health care professionals such as endocrinologists, dieticians, cardiologists, or general practitioners. Apps containing more BCTs had a higher perceived effect on people’s health, and app developers should take the complexity of needs into account. Furthermore, eHealth literacy appears to be a requirement to use health apps successfully, which should be considered in health education strategies to improve health in patients with CVD and diabetes