Abstract
Background:
Recent systematic reviews and meta-analyses on the effects of interventions to prevent obesity in children aged 5 to 18 years identified over 200 randomised trials. Interventions targeting diet, activity (including physical activity and sedentary behaviours) and both diet and activity appear to have small but beneficial effects, on average. However, these effects varied between studies and might be explained by variation in characteristics of the interventions, for example by the extent to which the children enjoyed the intervention or whether they aim to modify behaviour through education or physical changes to the environment. Here we develop a novel analytic framework to identify key intervention characteristics considered likely to explain differential effects.
Objectives:
To describe the development of the analytic framework, including the involvement of school-aged children, parents, teachers and other stakeholders, and to present the content of the finalised analytic framework and the results of the coding of the interventions.
Design and methods:
We first conducted a literature review to find out from the existing literature what different types of characteristics of interventions we should be thinking about, and why. This information helped us to develop a comprehensive map (called a logic model) of these characteristics. We then used this logic model to develop a list of possible intervention characteristics. We held a series of workshops with children, parents, teachers and public health professionals to refine the list into a coding scheme. We then used this to code the characteristics of each intervention in all the trials which aimed to prevent obesity in children aged 5 to 18 years.
Findings:
Our finalised analytic framework included 25 questions across 12 characteristics. These addressed aspects such as the setting of the intervention (e.g. at school, at home or in the community), mode of delivery (e.g. to individuals or to groups children), whether the intervention targeted diet and/or activity, complexity (e.g. focused on a single swap of juice for water or aimed to change all aspects the diet), intensity, flexibility, choice, mechanism of action (e.g. through participation, education, change in the social environment, change in the physical environment), resonance (e.g. credibility of the person delivering the intervention), commercial involvement and the ‘fun-factor’ (as perceived by children). We coded 255 interventions from 210 randomised trials.
Conclusions:
Our evidence-based analytic framework, refined by consulting with stakeholders, allowed us to code 255 interventions aiming to prevent obesity in children aged 5 to 18 years. Our confidence in the validity of the framework and coding results is increased by our rigorous methods and, especially, the involvement of children at multiple stages.
Future work:
Future work will include the development of a statistical methods for the synthesis and its application to the data coded according to the analytic framework.
Limitations:
The coding results depend on the level of detail provided to describe the interventions and the applicability of the analytic framework may be limited by demographic profile of the children and young people involved in the project.
Recent systematic reviews and meta-analyses on the effects of interventions to prevent obesity in children aged 5 to 18 years identified over 200 randomised trials. Interventions targeting diet, activity (including physical activity and sedentary behaviours) and both diet and activity appear to have small but beneficial effects, on average. However, these effects varied between studies and might be explained by variation in characteristics of the interventions, for example by the extent to which the children enjoyed the intervention or whether they aim to modify behaviour through education or physical changes to the environment. Here we develop a novel analytic framework to identify key intervention characteristics considered likely to explain differential effects.
Objectives:
To describe the development of the analytic framework, including the involvement of school-aged children, parents, teachers and other stakeholders, and to present the content of the finalised analytic framework and the results of the coding of the interventions.
Design and methods:
We first conducted a literature review to find out from the existing literature what different types of characteristics of interventions we should be thinking about, and why. This information helped us to develop a comprehensive map (called a logic model) of these characteristics. We then used this logic model to develop a list of possible intervention characteristics. We held a series of workshops with children, parents, teachers and public health professionals to refine the list into a coding scheme. We then used this to code the characteristics of each intervention in all the trials which aimed to prevent obesity in children aged 5 to 18 years.
Findings:
Our finalised analytic framework included 25 questions across 12 characteristics. These addressed aspects such as the setting of the intervention (e.g. at school, at home or in the community), mode of delivery (e.g. to individuals or to groups children), whether the intervention targeted diet and/or activity, complexity (e.g. focused on a single swap of juice for water or aimed to change all aspects the diet), intensity, flexibility, choice, mechanism of action (e.g. through participation, education, change in the social environment, change in the physical environment), resonance (e.g. credibility of the person delivering the intervention), commercial involvement and the ‘fun-factor’ (as perceived by children). We coded 255 interventions from 210 randomised trials.
Conclusions:
Our evidence-based analytic framework, refined by consulting with stakeholders, allowed us to code 255 interventions aiming to prevent obesity in children aged 5 to 18 years. Our confidence in the validity of the framework and coding results is increased by our rigorous methods and, especially, the involvement of children at multiple stages.
Future work:
Future work will include the development of a statistical methods for the synthesis and its application to the data coded according to the analytic framework.
Limitations:
The coding results depend on the level of detail provided to describe the interventions and the applicability of the analytic framework may be limited by demographic profile of the children and young people involved in the project.
| Original language | English |
|---|---|
| Journal | Public Health Research |
| Publication status | Accepted/In press - 16 May 2025 |
