Jennifer M. Badham

Dr. Jennifer M. Badham

Department of Sociology, Durham University, UK
orcid

Research Focus & Metrics

Academic Career Length

27Years (2000-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 September 2019 in PLOS Medicine
Verified
Journal Article
Open access
PDF file
RHRuth Hunter
Ruth Hunter
KHKayla de la Haye
Kayla de la Haye
JMJennifer M. Murray
Jennifer M. Murray
Jennifer M. BadhamJennifer M. Badham
Jennifer M. Badham
TVThomas W. Valente
Thomas W. Valente
FKFrank Kee
Frank Kee
There has been a growing interest in understanding the effects of social networks on health-related behaviour, with a particular backdrop being the emerging prominence of complexity or systems science in public health. Social network interventions specifically use or alter the characteristics of social networks to generate, accelerate, or maintain health behaviours. We conducted a systematic review and meta-analysis to investigate health behaviour outcomes of social network interventions. We searched eight databases and two trial registries from 1990 to May 28, 2019, for English-language reports of randomised controlled trials (RCTs) and before-and-after studies investigating social network interventions for health behaviours and outcomes. Trials that did not specifically use social networks or that did not include a comparator group were excluded. We screened studies and extracted data from published reports independently. The primary outcome of health behaviours or outcomes at ≤6 months was assessed by random-effects meta-analysis. Secondary outcomes included those measures at >6–12 months and >12 months. This study is registered with the International Prospective Register of Systematic Reviews, PROSPERO: CRD42015023541. We identified 26,503 reports; after exclusion, 37 studies, conducted between 1996 and 2018 from 11 countries, were eligible for analysis, with a total of 53,891 participants (mean age 32.4 years [SD 12.7]; 45.5% females). A range of study designs were included: 27 used RCT/cluster RCT designs, and 10 used other study designs. Eligible studies addressed a variety of health outcomes, in particular sexual health and substance use. Social network interventions showed a significant intervention effect compared with comparator groups for sexual health outcomes. The pooled odds ratio (OR) was 1.46 (95% confidence interval [CI] 1.01–2.11; I2 = 76%) for sexual health outcomes at ≤6 months and OR 1.51 (95% CI 1.27–1.81; I2 = 40%) for sexual health outcomes at >6–12 months. Intervention effects for drug risk outcomes at each time point were not significant. There were also significant intervention effects for some other health outcomes including alcohol misuse, well-being, change in haemoglobin A1c (HbA1c), and smoking cessation. Because of clinical and measurement heterogeneity, it was not appropriate to pool data on these other behaviours in a meta-analysis. For sexual health outcomes, prespecified subgroup analyses were significant for intervention approach (p < 0.001), mean age of participants (p = 0.002), and intervention length (p = 0.05). Overall, 22 of the 37 studies demonstrated a high risk of bias, as measured by the Cochrane Risk of Bias tool. The main study limitations identified were the inclusion of studies of variable quality; difficulty in isolating the effects of specific social network intervention components on health outcomes, as interventions included other active components; and reliance on self-reported outcomes, which have inherent recall and desirability biases. Our findings suggest that social network interventions can be effective in the short term (6 months) for sexual health outcomes. Intervention effects for drug risk outcomes at each time point were not significant. There were also significant intervention effects for some other health outcomes including alcohol misuse, well-being, change in HbA1c, and smoking cessation.

1 June 2019 in Environmental Modelling & Software
Verified
Journal Article
Closed access
Jennifer M. BadhamJennifer M. Badham
Jennifer M. Badham
SESondoss Elsawah
Sondoss Elsawah
JGJoseph Guillaume
Joseph Guillaume
SHSerena (Chen) Hamilton
Serena (Chen) Hamilton
RHRandall Hunt
Randall Hunt
GBGabriele Bammer
Gabriele Bammer

1 November 2018 in Health & Place
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Journal Article
Open access
Jennifer M. BadhamJennifer M. Badham
Jennifer M. Badham
ECEdmund Chattoe-Brown
Edmund Chattoe-Brown
NGNigel Gilbert
Nigel Gilbert
ZCZaid Chalabi
Zaid Chalabi
FKFrank Kee
Frank Kee
RHRuth F. Hunter
Ruth F. Hunter
Managing non-communicable diseases requires policy makers to adopt a whole systems perspective that adequately represents the complex causal architecture of human behaviour. Agent-based modelling is a computational method to understand the behaviour of complex systems by simulating the actions of entities within the system, including the way these individuals influence and are influenced by their physical and social environment. The potential benefits of this method have led to several calls for greater use in public health research. We discuss three challenges facing potential modellers: model specification, obtaining required data, and developing good practices. We also present steps to assist researchers to meet these challenges and implement their agent-based model.

1 August 2019 in Environmental Modelling & Software
Verified
Journal Article
Closed access
SHSerena (Chen) Hamilton
Serena (Chen) Hamilton
BFBaihua Fu
Baihua Fu
JGJoseph Guillaume
Joseph Guillaume
Jennifer M. BadhamJennifer M. Badham
Jennifer M. Badham
Sondoss ElsawahSondoss Elsawah
Sondoss Elsawah
FZFateme Zare
Fateme Zare

1 February 2010 in Theoretical Population Biology
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Journal Article
Closed access
Jennifer M. BadhamJennifer M. Badham
Jennifer M. Badham
RSRob Stocker
Rob Stocker

17 November 2019 in Pilot and Feasibility Studies
Verified
Journal Article
Open access
PDF file
RCRekesh Corepal
Rekesh Corepal
PBPaul Best
Paul Best
RORoisin O’nEill
Roisin O’nEill
FKFrank Kee
Frank Kee
Jennifer M. BadhamJennifer M. Badham
Jennifer M. Badham
RHRuth Hunter
Ruth Hunter
Background: Inactive lifestyles are becoming the norm and creative approaches to encourage adolescents to be more physically active are needed. Little is known about how gamification techniques can be used in physical activity interventions for young people. Such approaches may stimulate interest and encourage physical activity behaviour. The study investigated the feasibility of implementing and evaluating a physical activity intervention for adolescents which included gamification techniques within schools. We tested recruitment and retention strategies for schools and participants, the use of proposed outcome measures, and explored intervention acceptability.Methods: This school-based feasibility study of a randomised cluster trial recruited adolescents aged 12–14 years (n = 224) from five schools (three intervention; two control) in Belfast, Northern Ireland. The 22-week intervention (The StepSmart Challenge) informed by self-determination theory and incorporating gamification strategies involved a school-based pedometer competition. Outcomes, measured at baseline, and post-intervention (at 22 weeks post-baseline and 52 weeks post-baseline) included daily minutes of moderate to vigorous physical activity (MVPA) (measured using ActiGraph accelerometer), mental wellbeing (Warwick-Edinburgh Mental Wellbeing Scale), social support for physical activity, time preference (for delayed and larger rewards or immediate and smaller rewards), pro-social behaviour (Strengths and Difficulties Questionnaire (SDQ)) and the influence of social networks. The intervention’s acceptability was explored in focus groups.Results: We invited 14 schools to participate; eight showed interest in participating. We recruited the first five who responded; all five completed the trial. Of the 236 pupils invited, 224 participated (94.9%): 84.8% (190/224) provided valid MVPA (minutes/day) at baseline and 57.2% (123/215) at 52 weeks. All other outcomes were well completed apart from the SDQ (65% at baseline). Qualitative data highlighted that participants and teachers found The StepSmart Challenge to be an acceptable intervention.Conclusions: The level of interest and high recruitment and retention rates provide support for the feasibility of this trial. The intervention, incorporating gamification strategies and the recruitment methods, using parental opt-out procedures, were acceptable to participants and teachers. Teachers also suggested that the implementation of The StepSmart Challenge could be embedded in a lifelong learning approach to health within the school curriculum. As young people’s lives become more intertwined with technology, the use of innovative gamified interventions could be one approach to engage and motivate health behavioural change in this population.Trial registration: NCT02455986(date of registration: 28 May 2015).