Return on Data: Personalizing Consumer Guidance in Data Exchanges

Consumers routinely supply personal data to technology companies in exchange for services. Yet, the relationship between the utility (U) consumers gain and the data (D) they supply — “return on data” (ROD) — remains largely unexplored. Expressed as a ratio, ROD = U / D. While lawmakers strongly advocate protecting consumer privacy, they tend to overlook ROD. Are the benefits of the services enjoyed by consumers, such as social networking and predictive search, commensurate with the value of the data extracted from them? How can consumers compare competing data-for-services deals? Currently, the legal frameworks regulating these transactions, including privacy law, aim primarily to protect personal data

Older adults' evaluations of the standard and modified pedometer-based Green Prescription

INTRODUCTION: The Green Prescription is a primary care programme designed to increase physical activity in individuals with low activity levels. Older adults tend to engage in insufficient physical activity to obtain health-related gain. AIM: To examine participants’ ratings of the Healthy Steps intervention and to assess how participants rated the use of a pedometer-based Green Prescription in aiding their physical activity. METHODS: In total, 330 community-dwelling older adults who have low levels of activity were randomised to receive either a standard time-based Green Prescription or a modified pedometer-based Green Prescription. Post-intervention, 259 participants completed the participant evaluation questionnaire via postal survey. Data were analysed using descriptive statistics and Chi-squared analyses. RESULTS: The standard components of the Green Prescription (general practitioner consultations and telephone counselling) received similar and higher ratings across both allocation groups than the use of print materials. A pedometer-based Green Prescription was rated as being helpful in aiding physical activity. DISCUSSION: This study supports the importance of general practitioners’ initial role in prescribing physical activity for older adults and of ongoing telephone support for longer-term adherence. Incorporating a pedometer can be effective in helping low-active older adults initiate and maintain regular physical activity

Active lifestyles related to excellent self-rated health and quality of life: cross sectional findings from 194,545 participants in The 45 and Up Study

Background: Physical activity and sitting time independently contribute to chronic disease risk, though little work has focused on aspirational health outcomes. The purpose of this study was to examine associations between physical activity, sitting time, and excellent overall health (ExH) and quality of life (ExQoL) in Australian adults. Methods: The 45 and Up Study is a large Australian prospective cohort study (n = 267,153). Present analyses are from 194,545 participants (48% male; mean age = 61.6 ± 10.7 yrs) with complete baseline questionnaire data on exposures, outcomes, and potential confounders (age, income, education, smoking, marital status, weight status, sex, residential remoteness and economic advantage, functional limitation and chronic disease). The Active Australia survey was used to assess walking, moderate, and vigorous physical activity. Sitting time was determined by asking participants to indicate number of hours per day usually spent sitting. Participants reported overall health and quality of life, using a five-point scale (excellent—poor). Binary logistic regression models were used to analyze associations, controlling for potential confounders. Results: Approximately 16.5% of participants reported ExH, and 25.7% reported ExQoL. In fully adjusted models, physical activity was positively associated with ExH (AOR = adjusted odds ratio for most versus least active = 2.22, 95% CI = 2.20, 2.47; P[subscript trend] < 0.001) and ExQoL (AOR for most versus least active = 2.30, 95% CI = 2.12, 2.49; P[subscript trend]  < 0.001). In fully adjusted models, sitting time was inversely associated with ExH (AOR for least versus most sitting group = 1.13, 95% CI = 1.09, 1.18; P[subscript trend]  < 0.001) and ExQoL (AOR for least versus most sitting group = 1.13, 95% CI = 1.10, 1.17; P[subscript trend]  < 0.001). In fully adjusted models, interactions between physical activity and sitting time were not significant for ExH (P = 0.118) or ExQoL (P = 0.296). Conclusions: Physical activity and sitting time are independently associated with excellent health and quality of life in this large diverse sample of Australian middle-aged and older adults. These findings bolster evidence informing health promotion efforts to increase PA and decrease sitting time toward the achievement of better population health and the pursuit of successful aging

Physical activity and physical function in older adults: the 45 and up study

OBJECTIVES: To determine the strength of the relationship between physical activity and physical function in older adults. DESIGN: Cross-sectional. SETTING: The 45 and Up Study baseline questionnaire, New South Wales, Australia. PARTICIPANTS: Ninety-one thousand three hundred seventy-five Australian men and women aged 65 and older from the 45 and Up Study. MEASUREMENTS: Physical activity engagement (Active Australia Survey), physical function (Medical Outcomes Study Physical Functioning), psychological distress (Kessler- 10), and self-reported age, smoking history, education, height, and weight were all measured. RESULTS: Higher levels of physical activity were associated with better physical function in older adults (correlation coefficient = 0.166, P < .001). Participants engaging in higher levels of physical activity had progressively lower likelihoods of functional limitation (middle tertile: odds ratio (OR) = 0.39, 95% confidence interval (CI) = 0.38– 0.41; highest tertile: OR = 0.28, 95% CI = 0.27–0.29). This relationship remained significant, but weakened slightly, when adjusted for age, sex, body mass index, smoking history, psychological distress, and educational attainment (middle tertile: adjusted OR (AOR) = 0.48, 95% CI = 0.46–0.50; highest tertile: AOR = 0.36, 95% CI = 0.34–0.37). CONCLUSION: There is a significant, positive relationship between physical activity and physical function in older adults, with older adults who are more physically active being less likely to experience functional limitation than their more-sedentary counterparts. Level of engagement in physical activity is an important predictor of physical function in older adults