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Artificial Intelligence and Physical Activity Among People From Ethnic Minority Groups

Understanding and Identifying the Potential of Artificial Intelligence Powered Digital Physical Activity and Lifestyle Interventions Among People From Ethnic Minority Groups: a Mixed Methods Study

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05779696
Acronym
AI-ACTIV-E
Enrollment
300
Registered
2023-03-22
Start date
2023-04-01
Completion date
2024-03-31
Last updated
2023-05-16

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Physical Inactivity

Keywords

Physical activity, Artificial intelligence, Ethnic health

Brief summary

Despite the high interest in physical activity, many individuals lack the necessary experience in being active and therefore have low levels of knowledge and confidence to become and stay active. For effective lifestyle changes to occur, information must be tailored to the individual's health, goals, motivations, and overall ability. Lifestyle interventions, for example those designed to increase physical activity, are only effective when adapted to the physical, social, and psychological needs of the patient and progressed at rate appropriate for their development by specialist health professional. In the context of ethnic minority health, information must also be culturally adapted, sensitive to religious needs, and accessible to those where English is not proficient. Behavioural digital health interventions have been moderately successful in increasing physical activity, although opportunities for further improvement remain to be discussed. New technologies involving the use of artificial intelligence (AI) are growing, and allow the dissemination of individualised and tailored advice and information. Whilst a few AI-driven physical activity-based applications exist, they are not widely used, particularly amongst people from ethnic minority groups where both physical activity and digital health literacy is poor. Research has identified that whilst many people would be receptive to using health chatbots, hesitancy regarding this technology is likely to compromise engagement. In particular, user perspectives, motivation and capabilities need to be taken into account when developing and assessing the effectiveness of health chatbots. Guidance suggests that developing health chatbots should focus on issues of digital literacy, linguistic and cultural issues, privacy concerns, and personalization. As such, any development needs to involve user-driven co-creation techniques and involving community partners to increase the probability that it will ultimately be effective. Aims Aim 1 Gain a new understanding of barriers and facilitators to digital physical activity interventions and AI-delivered healthcare in people from ethnic minority groups through an online survey Aim 2 To conduct a series of focus groups to explore participants understanding and identifying barriers and facilitators to digital physical activity interventions. In particular to: i)Better understand general barriers and facilitators (focus on access and provision of education, and physical, environmental, cultural and psycho-social barriers) to physical activity; ii)Explore current and future usage of digital-based resources to facilitate physical activity behaviour; iii)Investigate views of use of AI in digital-based healthcare applications (e.g., trust in such applications)

Interventions

This is a non-intervention study.

Sponsors

University of Leicester
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
CROSS_SECTIONAL

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum

Inclusion criteria

Inclusion * Participants must be over 18 years old; * Participants must be able to a computer/mobile device to access the survey or video conference software (Zoom, as used by the Centre of Ethnic Health Research) * Participants can come from a range of cultural communities and religious groups; * Participants do not need to have any prior knowledge to participate in the virtual focus groups or the survey. Exclusion \- No specific

Exclusion criteria

.

Design outcomes

Primary

MeasureTime frameDescription
Feelings towards chatbots and artificial intelligence12 monthsBespoke questions via online survey. Questions answered on a Likert scale between 1 and 7; with 1 being 'disagree completely' and 7 being 'agree completely'

Countries

United Kingdom

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026