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1.
PLoS One ; 19(5): e0303051, 2024.
Article in English | MEDLINE | ID: mdl-38805418

ABSTRACT

Cardiovascular disease (CVD) is the leading cause of mortality globally, and is the second main cause of mortality in the UK. Four key modifiable behaviours are known to increase CVD risk, namely: tobacco use, unhealthy diet, physical inactivity and harmful use of alcohol. Behaviours that increase the risk of CVD can spread through social networks because individuals consciously and unconsciously mimic the behaviour of others they relate to and admire. Exploiting these social influences may lead to effective and efficient public health interventions to prevent CVD. This project aimed to construct and validate an agent-based model (ABM) of how the four major behavioural risk-factors for CVD spread through social networks in a population, and examine whether the model could be used to identify targets for public health intervention and to test intervention strategies. Previous ABMs have typically focused on a single risk factor or considered very small populations. We created a city-scale ABM to model the behavioural risk-factors of individuals, their social networks (spousal, household, friendship and workplace), the spread of behaviours through these social networks, and the subsequent impact on the development of CVD. We compared the model output (predicted CVD events over a ten year period) to observed data, demonstrating that the model output is realistic. The model output is stable up to at least a population size of 1.2M agents (the maximum tested). We found that there is scope for the modelled interventions targeting the spread of these behaviours to change the number of CVD events experienced by the agents over ten years. Specifically, we modelled the impact of workplace interventions to show that the ABM could be useful for identifying targets for public health intervention. The model itself is Open Source and is available for use or extension by other researchers.


Subject(s)
Cardiovascular Diseases , Humans , Cardiovascular Diseases/epidemiology , Risk Factors , Male , Female , Health Behavior , Middle Aged , Cities
2.
BMJ Open ; 14(4): e076613, 2024 Apr 03.
Article in English | MEDLINE | ID: mdl-38569710

ABSTRACT

OBJECTIVE: The COVID-19 pandemic accelerated changes to clinical research methodology, with clinical studies being carried out via online/remote means. This mixed-methods study aimed to identify which digital tools are currently used across all stages of clinical research by stakeholders in clinical, health and social care research and investigate their experience using digital tools. DESIGN: Two online surveys followed by semistructured interviews were conducted. Interviews were audiorecorded, transcribed and analysed thematically. SETTING, PARTICIPANTS: To explore the digital tools used since the pandemic, survey participants (researchers and related staff (n=41), research and development staff (n=25)), needed to have worked on clinical, health or social care research studies over the past 2 years (2020-2022) in an employing organisation based in the West Midlands region of England (due to funding from a regional clinical research network (CRN)). Survey participants had the opportunity to participate in an online qualitative interview to explore their experiences of digital tools in greater depth (n=8). RESULTS: Six themes were identified in the qualitative interviews: 'definition of a digital tool in clinical research'; 'impact of the COVID-19 pandemic'; 'perceived benefits/drawbacks of digital tools'; 'selection of a digital tool'; 'barriers and overcoming barriers' and 'future digital tool use'. The context of each theme is discussed, based on the interview results. CONCLUSIONS: Findings demonstrate how digital tools are becoming embedded in clinical research, as well as the breadth of tools used across different research stages. The majority of participants viewed the tools positively, noting their ability to enhance research efficiency. Several considerations were highlighted; concerns about digital exclusion; need for collaboration with digital expertise/clinical staff, research on tool effectiveness and recommendations to aid future tool selection. There is a need for the development of resources to help optimise the selection and use of appropriate digital tools for clinical research staff and participants.


Subject(s)
COVID-19 , Pandemics , Humans , Social Support , COVID-19/epidemiology , England , Research Design
3.
Obes Rev ; 20(12): 1771-1780, 2019 12.
Article in English | MEDLINE | ID: mdl-31456340

ABSTRACT

Employees spend a large proportion of their time at work and typically consume a third of their total calories during the working day. Research suggests that the workplace environment can affect employees' eating behaviours, leading to various related health consequences. This systematic review aimed to identify and synthesize the evidence surrounding factors influencing eating behaviours within an office-based workforce. The literature search was restricted to studies published in English between January 2008 and April 2018. A total of 5,017 articles were screened and assessed for eligibility, of which 22 articles (n=23 studies) were included in the review. All included studies were subjected to quality assessment and were summarized into groups (themes) of "factors" affecting any aspect of eating behaviour at work. The findings revealed a number of factors influencing eating behaviours at work relating to the job role, workplace food environment, and social aspects of the office-based workplace. Most of the existing research implies the office-based workplace has a negative influence on eating behaviours. The findings of this review provide an evidence based, comprehensive summary of the possible determinants of eating behaviours in the workplace, which may help researchers to identify factors that are potential targets for intervention.


Subject(s)
Feeding Behavior/psychology , Workplace/psychology , Costs and Cost Analysis , Diet, Healthy/statistics & numerical data , Environment , Food/economics , Food Services/instrumentation , Food Services/statistics & numerical data , Humans , Lunch , Nutritive Value , Snacks , Social Environment , Stress, Psychological/psychology
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