Skip to main content

Research Repository

Advanced Search

Dr JAMES GOULDING's Outputs (48)

Food insecurity amongst universal credit claimants: the benefits and nutrition study (BEANS), a cross-sectional online study (2025)
Journal Article
Thomas, M., Rose, P., Coneyworth, L., Harvey, J., Goulding, J., Stone, J., Padley, M., O’Reilly, P., & Welham, S. (2025). Food insecurity amongst universal credit claimants: the benefits and nutrition study (BEANS), a cross-sectional online study. European Journal of Nutrition, 64, Article 115. https://doi.org/10.1007/s00394-025-03596-y

Purpose
Increasing food insecurity (FIS) in the UK presents a major challenge to public health. Universal Credit (UC) claimants are disproportionately impacted by FIS but research on socio-demographic factors and consequent nutritional security is... Read More about Food insecurity amongst universal credit claimants: the benefits and nutrition study (BEANS), a cross-sectional online study.

A mixed methods protocol for an impact and implementation evaluation of the Pharmacy First Services for management of common conditions in England (2025)
Journal Article
Glover, R. E., Lalani, M., Sonnex, K., Allen, T., Anderson, C., Ashiru-Oredope, D., Avery, A., Coupland, C., Elliott, R., Goulding, J., Higgins, H., Johnson, S., Mackenna, B., Muller-Pebody, B., O’Neill, S., Pacho, A., Taylor, A., Thornley, T., & Mays, N. (2025). A mixed methods protocol for an impact and implementation evaluation of the Pharmacy First Services for management of common conditions in England. International Journal of Pharmacy Practice, https://doi.org/10.1093/ijpp/riaf004

Objectives
In response to high levels of demand for primary medical services in England, characterized by longer appointment waiting times and delayed referrals, the Government developed its National Health Service (NHS) Primary Care Recovery Plan.... Read More about A mixed methods protocol for an impact and implementation evaluation of the Pharmacy First Services for management of common conditions in England.

Machine learning on national shopping data reliably estimates childhood obesity prevalence and socio-economic deprivation (2025)
Journal Article
Long, G., Nica-Avram, G., Harvey, J., Lukinova, E., Mansilla, R., Welham, S., Engelmann, G., Dolan, E., Makokoro, K., Thomas, M., Powell, E., & Goulding, J. (2025). Machine learning on national shopping data reliably estimates childhood obesity prevalence and socio-economic deprivation. Food Policy, 131, Article 102826. https://doi.org/10.1016/j.foodpol.2025.102826

Deprivation pushes people to choose cheap, calorie-dense foods instead of nutritious but expensive alternatives. Diseases, such as obesity, cardiovascu-lar disease, and diabetes, resulting from these poor dietary choices place a significant burden on... Read More about Machine learning on national shopping data reliably estimates childhood obesity prevalence and socio-economic deprivation.

Leveraging multiple digital footprint datasets to predict racial, sex-based, and sexual-orientation bias across US states (2024)
Journal Article
Derecki, R., O'Shea, B., & Goulding, J. (2024). Leveraging multiple digital footprint datasets to predict racial, sex-based, and sexual-orientation bias across US states. International Journal of Population Data Science, 9(4), Article 15. https://doi.org/10.23889/ijpds.v9i4.2429

Introduction & Background
Racial, gender, and sexual-orientation biases are pervasive throughout society. Importantly, modern digitally oriented datasets can elucidate important societal variables and potential solutions. One contemporary theory tha... Read More about Leveraging multiple digital footprint datasets to predict racial, sex-based, and sexual-orientation bias across US states.

Predicting Healthy Start Scheme Uptake using Deprivation and Food Insecurity Measures (2024)
Presentation / Conference Contribution
Makokoro, K., Long, G., Harvey, J., Smith, A., Welham, S., Mansilla, R., Lukinova, E., & Goulding, J. (2024, May). Predicting Healthy Start Scheme Uptake using Deprivation and Food Insecurity Measures. Presented at 2nd Digital Footprints Conference: Linking Digital Data for Social Impact, Bristol, UK

Foodinsecurity.london: Developing a food-insecurity prevalence map for London - a machine learning from food-sharing footprints (2024)
Presentation / Conference Contribution
Milligan, G., Nica-Avram, G., Harvey, J., & Goulding, J. (2024, May). Foodinsecurity.london: Developing a food-insecurity prevalence map for London - a machine learning from food-sharing footprints. Presented at 2nd Digital Footprints Conference: Linking Digital Data for Social Impact, Bristol, UK

Introduction & Background
The ability of policymakers to positively transform food environments requires robust empirical evidence that can inform decisions. At present, there is limited data on food-insecurity in the UK that can be used to inform i... Read More about Foodinsecurity.london: Developing a food-insecurity prevalence map for London - a machine learning from food-sharing footprints.

Beyond the Walls: Patterns of Child Labour, Forced Labour, and Exploitation in a New Domestic Workers Dataset (2024)
Journal Article
Trodd, Z., Waite, C., Goulding, J., & Boyd, D. S. (2024). Beyond the Walls: Patterns of Child Labour, Forced Labour, and Exploitation in a New Domestic Workers Dataset. Societies, 14(5), Article 62. https://doi.org/10.3390/soc14050062

The new Domestic Workers Dataset is the largest single set of surveys (n = 11,759) of domestic workers to date. Our analysis of this dataset reveals features about the lives and work of this “hard-to-find” population in India—a country estimated to h... Read More about Beyond the Walls: Patterns of Child Labour, Forced Labour, and Exploitation in a New Domestic Workers Dataset.

An empirical critique of the low income low energy efficiency approach to measuring fuel poverty (2024)
Journal Article
Semple, T., Rodrigues, L., Harvey, J., Figueredo, G., Nica-Avram, G., Gillott, M., Milligan, G., & Goulding, J. (2024). An empirical critique of the low income low energy efficiency approach to measuring fuel poverty. Energy Policy, 186, Article 114014. https://doi.org/10.1016/j.enpol.2024.114014

Fuel poverty is a complex socioenvironmental issue of increasing global significance. In England, fuel poverty is assessed via the Low Income Low Energy Efficiency (LILEE) indicator, yet concerns exist regarding the efficacy of this metric given its... Read More about An empirical critique of the low income low energy efficiency approach to measuring fuel poverty.

Detecting iodine deficiency risks from dietary transitions using shopping data (2024)
Journal Article
Mansilla, R., Long, G., Welham, S., Harvey, J., Lukinova, E., Nica-Avram, G., Smith, G., Salt, D., Smith, A., & Goulding, J. (2024). Detecting iodine deficiency risks from dietary transitions using shopping data. Scientific Reports, 14(1), Article 1017. https://doi.org/10.1038/s41598-023-50180-7

Plant-based product replacements are gaining popularity. However, the long-term health implications remain poorly understood, and available methods, though accurate, are expensive and burdensome, impeding the study of sufficiently large cohorts. To i... Read More about Detecting iodine deficiency risks from dietary transitions using shopping data.

Assessing relative contribution of Environmental, Behavioural and Social factors on Life Satisfaction via mobile app data (2023)
Presentation / Conference Contribution
Milligan, G., Harvey, J., Dowthwaite, L., Vallejos, E. P., Nica-Avram, G., & Goulding, J. (2023, December). Assessing relative contribution of Environmental, Behavioural and Social factors on Life Satisfaction via mobile app data. Presented at 2023 IEEE International Conference on Big Data, Sorrento, Italy

Life satisfaction significantly contributes to wellbe-ing and is linked to positive outcomes for individual people and society more broadly. However, previous research demonstrates that many factors contribute to the life satisfaction of an individua... Read More about Assessing relative contribution of Environmental, Behavioural and Social factors on Life Satisfaction via mobile app data.

Who consumes anthocyanins and anthocyanidins? Mining national retail data to reveal the influence of socioeconomic deprivation and seasonality on polyphenol dietary intake (2023)
Presentation / Conference Contribution
Harvey, J., Long, G., Welham, S., Mansilla, R., Rose, P., Thomas, M., Milligan, G., Dolan, E., Parkes, J., Makokoro, K., & Goulding, J. (2023, December). Who consumes anthocyanins and anthocyanidins? Mining national retail data to reveal the influence of socioeconomic deprivation and seasonality on polyphenol dietary intake. Presented at 2023 IEEE International Conference on Big Data (BigData), Sorrento, Itlay

Anthocyanins are a class of polyphenols that have received widespread recent attention due to their potential health benefits. However, estimating the dietary intake of anthocyanins at a population level is a challenging task, due to the difficulty o... Read More about Who consumes anthocyanins and anthocyanidins? Mining national retail data to reveal the influence of socioeconomic deprivation and seasonality on polyphenol dietary intake.

Assessing the value of integrating national longitudinal shopping data into respiratory disease forecasting models (2023)
Journal Article
Dolan, E., Goulding, J., Marshall, H., Smith, G., Long, G., & Tata, L. J. (2023). Assessing the value of integrating national longitudinal shopping data into respiratory disease forecasting models. Nature Communications, 14, Article 7258. https://doi.org/10.1038/s41467-023-42776-4

The COVID-19 pandemic led to unparalleled pressure on healthcare services. Improved healthcare planning in relation to diseases affecting the respiratory system has consequently become a key concern. We investigated the value of integrating sales of... Read More about Assessing the value of integrating national longitudinal shopping data into respiratory disease forecasting models.

Qualitative Investigation of the Novel Use of Shopping Loyalty Card Data in Medical Decision Making (2023)
Book Chapter
Lang, A., Dolan, E., Tata, L., & Goulding, J. (2023). Qualitative Investigation of the Novel Use of Shopping Loyalty Card Data in Medical Decision Making. In M. Melles, A. Albayrak, & R. H. Goossens (Eds.), Convergence: Breaking Down Barriers Between Disciplines: Proceedings of the International Conference on Healthcare Systems Ergonomics and Patient Safety, HEPS2022. Springer. https://doi.org/10.1007/978-3-031-32198-6_11

This paper describes early results of a small qualitative study investigating the potential impact of shopping loyalty card data (SLCD) in the diagnostic pathway for ovarian cancer. There is early evidence that pharmaceutical products such as pain re... Read More about Qualitative Investigation of the Novel Use of Shopping Loyalty Card Data in Medical Decision Making.

Data donation of individual shopping data to help predict the occurrence of disease: A pilot study linking individual loyalty card and health survey data to investigate COVID-19 (2023)
Presentation / Conference Contribution
Dolan, E., Goulding, J., & Skatova, A. Data donation of individual shopping data to help predict the occurrence of disease: A pilot study linking individual loyalty card and health survey data to investigate COVID-19. Presented at 1st Digital Footprints Conference, University of Bristol

Introduction & Background
Previous studies have found shopping data could increase the predictive accuracy of disease surveillance systems and illuminate behavioural responses in the self-management of symptoms of disease. Yet, accessing individual... Read More about Data donation of individual shopping data to help predict the occurrence of disease: A pilot study linking individual loyalty card and health survey data to investigate COVID-19.

Expert perspectives on how educational technology may support autonomous learning for remote out-of-school children in low-income contexts (2023)
Journal Article
Huntington, B., Goulding, J., & Pitchford, N. J. (2023). Expert perspectives on how educational technology may support autonomous learning for remote out-of-school children in low-income contexts. International Journal of Educational Research Open, 5, Article 100263. https://doi.org/10.1016/j.ijedro.2023.100263

Across Sub-Saharan African, 98 million children are illiterate and innumerate and do not attend school. Educational technologies (EdTech) that promote autonomous learning may ameliorate this learning poverty. Yet, little is known if or how these tech... Read More about Expert perspectives on how educational technology may support autonomous learning for remote out-of-school children in low-income contexts.

Using Shopping Data to Improve the Diagnosis of Ovarian Cancer: Computational Analysis of a Web-Based Survey (2023)
Journal Article
Dolan, E., Goulding, J., Tata, L., & Lang, A. (2023). Using Shopping Data to Improve the Diagnosis of Ovarian Cancer: Computational Analysis of a Web-Based Survey. JMIR Cancer, 9, Article e37141. https://doi.org/10.2196/37141

Background

Shopping data can be analysed using machine learning techniques to study population health. It is unknown if use of such methods can successfully investigate pre-diagnosis purchases linked to self-medication of symptoms of ovarian cance... Read More about Using Shopping Data to Improve the Diagnosis of Ovarian Cancer: Computational Analysis of a Web-Based Survey.

Pedagogical features of interactive apps for effective learning of foundational skills (2023)
Journal Article
Huntington, B., Goulding, J., & Pitchford, N. J. (2023). Pedagogical features of interactive apps for effective learning of foundational skills. British Journal of Educational Technology, 54(5), 1273-1291. https://doi.org/10.1111/bjet.13317

Interactive apps are commonly used to support the acquisition of foundational skills. Yet little is known about how pedagogical features of such apps affect learning outcomes, attainment and motivation—particularly when deployed in lower‐income conte... Read More about Pedagogical features of interactive apps for effective learning of foundational skills.