MoveMentor-examining the effectiveness of a machine learning and app-based digital assistant to increase physical activity in adults: protocol for a randomised controlled trial.

Background: Physical inactivity is prevalent, leading to a high burden of disease and large healthcare costs. Thus, there is a need for affordable, effective and scalable interventions. However, interventions that are affordable and scalable are beset with modest effects and engagement.

Impact of Iterative Development and Beta-Testing on the Usability and Acceptability of a Novel Just-in-Time Adaptive Digital Physical Activity Intervention.

Background: The search for cost-effective population-based physical activity interventions continues. Therefore, we developed a novel just-in-time adaptive digital assistant supported by machine learning (ie, MoveMentor). Beta-testing is essential to evaluate both technical performance and user acceptance.

Perceptions and expectations of an artificially intelligent physical activity digital assistant - A focus group study.

Artificially intelligent physical activity digital assistants that use the full spectrum of machine learning capabilities have not yet been developed and examined. This study aimed to explore potential users' perceptions and expectations of using such a digital assistant. Six 90-min online focus group meetings (n = 45 adults) were conducted.

Increasing physical activity using an just-in-time adaptive digital assistant supported by machine learning: A novel approach for hyper-personalised mHealth interventions.

Objective: Physical inactivity is a leading modifiable cause of death and disease worldwide. Population-based interventions to increase physical activity are needed. Existing automated expert systems (e.

Quality of Life Outcomes in Community-based Mental Health Consumers: Comparisons with Population Norms and Changes over Time.

Quality of life is shown to be lower in people diagnosed with mental illness in comparison to the general population. The aim of this study is to examine the Quality of life in a subset of people accessing mental health services in a regional Queensland Centre. Thirty-seven people accessing mental health services completed the SF36 Health Survey on three occasions.

Lessons Learned From the Trial of a Cardiometabolic Health Nurse.

Purpose: This paper examines the findings from an exit interview with a cardiometabolic health nurse (CHN) following a 26-week trial.

Design And Methods: The CHN participated in a semi-structured exit interview following completion of the 26-week trial. Applied thematic analysis was used to identify themes contained in the resultant transcript.