Daily steps and diet quality, but not sleep, are related to mortality in older Australians

The Effect of a Future-Self Avatar Mobile Health Intervention (FutureMe) on Physical Activity and Food Purchases: Randomized Controlled Trial

BACKGROUND

Insufficient physical activity and unhealthy diets are contributing to the rise in noncommunicable diseases. Preventative mobile health (mHealth) interventions may help reverse this trend, but present bias might reduce their effectiveness. Future-self avatar interventions have resulted in behavior change in related fields, yet evidence of whether such interventions can change health behavior is lacking.

OBJECTIVE

We aimed to investigate the impact of a future-self avatar mHealth intervention on physical activity and food purchasing behavior and examine the feasibility of a novel automated nutrition tracking system. We also aimed to understand how this intervention impacts related attitudinal and motivational constructs.

METHODS

We conducted a 12-week parallel randomized controlled trial (RCT), followed by semistructured interviews. German-speaking smartphone users aged ≥18 years living in Switzerland and using at least one of the two leading Swiss grocery loyalty cards, were recruited for the trial. Data were collected from November 2020 to April 2021. The intervention group received the FutureMe intervention, a physical activity and food purchase tracking mobile phone app that uses a future-self avatar as the primary interface and provides participants with personalized food basket analysis and shopping tips. The control group received a conventional text- and graphic-based primary interface intervention. We pioneered a novel system to track nutrition by leveraging digital receipts from loyalty card data and analyzing food purchases in a fully automated way. Data were consolidated in 4-week intervals, and nonparametric tests were conducted to test for within- and between-group differences.

RESULTS

We recruited 167 participants, and 95 eligible participants were randomized into either the intervention (n=42) or control group (n=53). The median age was 44 years (IQR 19), and the gender ratio was balanced (female 52/95, 55%). Attrition was unexpectedly high with only 30 participants completing the intervention, negatively impacting the statistical power. The FutureMe intervention led to small statistically insignificant increases in physical activity (median +242 steps/day) and small insignificant improvements in the nutritional quality of food purchases (median -1.28 British Food Standards Agency Nutrient Profiling System Dietary Index points) at the end of the intervention. Intrinsic motivation significantly increased (P=.03) in the FutureMe group, but decreased in the control group. Outcome expectancy directionally increased in the FutureMe group, but decreased in the control group. Leveraging loyalty card data to track the nutritional quality of food purchases was found to be a feasible and accepted fully automated nutrition tracking system.

CONCLUSIONS

Preventative future-self avatar mHealth interventions promise to encourage improvements in physical activity and food purchasing behavior in healthy population groups. A full-powered RCT is needed to confirm this preliminary evidence and to investigate how future-self avatars might be modified to reduce attrition, overcome present bias, and promote sustainable behavior change.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04505124; https://clinicaltrials.gov/ct2/show/NCT04505124.

Postoperative physical activity in orthogeriatric patients - new insights with continuous monitoring

BACKGROUND

An early postoperative mobilization shows beneficial effects in terms of complications and long-term mobilization scores in elderly adult fracture patients. The primary objective of this study was to evaluate the overall mobilization of orthogeriatric patients during the postoperative hospital stay based on a continuous accelerometry measurement. Secondly, the collected data was analyzed to detect fracture related differences. We hypothesized that upper extremity fractures come along with higher levels of physical activity compared to fractures of the lower extremity.

METHODS

Thirty-one orthogeriatric patients with proximal femur fractures (PFF) and proximal humerus fractures (PHF) were enrolled consecutively in a maximum care hospital in a prospective study design (level of evidence 2). In the PFF study group 9 patients received hip arthroplasty and 11 patients intramedullary nailing (PFNA) and in the PHF group 10 patients received osteosynthesis of the proximal humerus. All patients worn a waist placed accelerometer during the length of hospitalization to quantify mobilization and physical activity.

RESULTS

The PFF group (n = 21) had a mean age of 80.86 years (SD ± 6.75), the PHF (n = 10) group had a mean age of 75.20 (SD ± 6.86). A significantly higher gait speed was observed in the PHF group of 0.52 m/s (SD ± 0.27) compared to the slower PFF group with 0.29 (SD ± 0.45); p = 0.0403. Quantitative mobility was measured by using the average number of daily steps. This showed a significantly lower number of steps in the PFF group (102.7; SD ± 188.1) compared to the PHF group (413.5; SD ± 287.7; p = 0.0002).

CONCLUSIONS

Our data demonstrates that it is feasible and accepted by the patient to continuously measure the mobility including gait speed and characteristics of orthogeriatric patients using waist worn accelerometry based wearables. Postoperative mobility and gait speed was generally low in both groups. Actions to improve postoperative mobility of orthogeriatric patients are urgently needed. Level Of Evidence Prospective cohort study, Level of Evidence 2.