Lifestyles aimed at reducing dementia risk typically combine physical and cognitive training, nutritional adaptations, and, potentially, an augmentation in social interactions. Interventions at the population level are essential but should be complemented by individual efforts. For efficacy, lasting changes to an individual's lifestyle are needed, necessitating robust motivation and volition. Acting in accordance with one's values is assumed to be rewarding, leading to improved motivation and volition, and produces stable behaviour–outcome relationships. To this end, future preventive endeavours might first evaluate an individual's extant lifestyle, preferences, and values, including considerations of age-related changes to ensure these values remain a motivational source. Digital technology can support lifestyle goals and be targeted to support an individual's values. A digital platform could implement situation-specific, sensing-based feedback to alert users to a target situation (eg, opportunity for exercise) coupled with (smartphone-based) feedback on the extent of accomplished behavioural change to support individually set goals and facilitate their adjustment depending on whether these goals are achieved. This use of the motivational impetus of values, coupled with interpersonal techniques, such as motivational interviewing and SMART goal setting, in combination with sensor technology and just-in-time adaptive interventions, is assumed to hold high potential for dementia prevention.
The expected increase of dementia prevalence in the coming decades will mainly be in low-income and middle-income countries and in people with low socioeconomic status in high-income countries. This study aims to reduce dementia risk factors in underserved populations at high-risk using a coach-supported mobile health (mHealth) intervention.
This open-label, blinded endpoint, hybrid effectiveness–implementation randomised controlled trial (RCT) investigated whether a coach-supported mHealth intervention can reduce dementia risk in people aged 55–75 years of low socioeconomic status in the UK or from the general population in China with at least two dementia risk factors. The primary effectiveness outcome was change in cardiovascular risk factors, ageing, and incidence of dementia (CAIDE) risk score from baseline to after 12–18 months of intervention. Implementation outcomes were coverage, adoption, sustainability, appropriateness, acceptability, fidelity, feasibility, and costs assessed using a mixed-methods approach. All participants with complete data on the primary outcome, without imputation of missing outcomes were included in the analysis (intention-to-treat principle). This trial is registered with ISRCTN, ISRCTN15986016, and is completed.
Between Jan 15, 2021, and April 18, 2023, 1488 people (601 male and 887 female) were randomly assigned (734 to intervention and 754 to control), with 1229 (83%) of 1488 available for analysis of the primary effectiveness outcome. After a mean follow-up of 16 months (SD 2·5), the mean CAIDE score improved 0·16 points in the intervention group versus 0·01 in the control group (mean difference –0·16, 95% CI –0·29 to –0·03). 1533 (10%) invited individuals responded; of the intervention participants, 593 (81%) of 734 adopted the intervention and 367 (50%) of 734 continued active participation throughout the study. Perceived appropriateness (85%), acceptability (81%), and fidelity (79%) were good, with fair overall feasibility (53% of intervention participants and 58% of coaches), at low cost. No differences in adverse events between study arms were found.
A coach-supported mHealth intervention is modestly effective in reducing dementia risk factors in those with low socioeconomic status in the UK and any socioeconomic status in China. Implementation is challenging in these populations, but those reached actively participated. Whether this intervention will result in less cognitive decline and dementia requires a larger RCT with long follow-up.
EU Horizon 2020 Research and Innovation Programme and the National Key R&D Programmes of China.
For the Mandarin translation of the abstract see Supplementary Materials section.