The Use of Data From Wearable Technology to Co-develop School-specific Physical Activity Interventions

NCT04905615 | Completed

• 1 other identifier: EP 1920 009
• Study Type: interventional
• Target: 228
• Locations: 1 country
• Sites: 1

Brief Summary

Increasing physical activity is vital for children's physical and mental health. It is important to address inactivity early and engage children in positive behaviours which can be sustained throughout life. Teachers are well placed to understand and influence in-school factors impacting children's physical activity. As wearable technologies continue to improve and become more accessible, they offer the opportunity to engage schools in the data collection process, as well as providing them with the capacity to monitor strategies designed to improve physical activity. This study is a within-subject, pre-post, co-developed intervention design.

Conditions

Physical Activity

Keywords

Physical Activity; Primary School Children; Wearable Technology; Data Driven Intervention; School-based Intervention; Co-design

Outcome Measures

Primary Outcomes (1)

• Step Count

  Changes in step counts from baseline

  2-weeks baseline, compared to 2-weeks intervention period in each school

Secondary Outcomes (3)

• Moderate to Vigorous Physical Activity (MVPA)

  2-weeks baseline, compared to 2-weeks intervention period in each school

• Qualitative Data

  Interviews conducted at the end of each 2-week period with each class teacher.

• Pupil Demographics and Physical Activity Measures

  4 weeks

Study Arms (2)

Baseline Measures

NO INTERVENTION

The first two-weeks within each school children's baseline physical activity data will be collected. Children will be blinded to the data, receiving no feedback. Teachers will be instructed not to change normal school practices or encourage children's physical activity.

Data-Driven Strategy Based Intervention

EXPERIMENTAL

During the following 2-weeks teachers will be implementing strategies to improve their class' physical activity. These are individualised strategies which will be co-developed during semi-structured interviews where teachers will discuss data visualisations with the researcher which depicts their class' physical activity over the 2-week baseline period. Teachers will then implement these strategies over the subsequent 2-weeks. During this time teachers are able to share the physical activity data with their pupils if they wish.

Other: Data-driven and teacher led school based strategies.

Interventions

Data-driven and teacher led school based strategies. OTHER

The intervention is individualised to each school, depending on the teacher led strategies which are data-informed

Data-Driven Strategy Based Intervention

Eligibility Criteria

• Age: 9 Years - 11 Years
• Gender Eligibility Details: Teachers input the gender pupils identify with into the physical activity data collection software.
• Healthy Volunteers: Yes
• Age Groups: Child (0-17)

You may qualify if:

• Any pupil from the each respective UK-based school and class. Pupils in years 5 to 6 (aged 9-11 years old).

Sponsors & Collaborators

• University of Bath: lead
• Economic and Social Research Council, United Kingdom: collaborator
• University of Bristol: collaborator
• Loughborough University: collaborator

Study Sites (1)

University of Bath

Bath, Banes, BA2, United Kingdom

Location

MeSH Terms

Conditions

Motor Activity

Condition Hierarchy (Ancestors)

Behavior

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NON RANDOMIZED
• Masking: NONE
• Purpose: PREVENTION
• Intervention Model: FACTORIAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: May 24, 2021
• First Posted: May 27, 2021
• Study Start: April 19, 2021
• Primary Completion: November 29, 2021
• Study Completion: November 29, 2021
• Last Updated: October 6, 2022

Record last verified: 2022-10

Locations

GB (1)