Claire Timon

Dr. Claire Timon


Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

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

Representative Publications

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13 December 2016 in Nutrition Research Reviews
Verified
Journal Article
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PDF file
CTClaire Timon
Claire Timon
RBRinske van Den Barg
Rinske van Den Barg
RBRichard J. Blain
Richard J. Blain
LKLaura Kehoe
Laura Kehoe
KEKatie Evans
Katie Evans
EGEileen Gibney
Eileen Gibney
Technology-based dietary assessment offers solutions to many of the limitations of traditional dietary assessment methodologies including cost, participation rates and the accuracy of data collected. The 24-h dietary recall (24HDR) method is currently the most utilised method for the collection of dietary intake data at a national level. Recently there have been many developments using web-based platforms to collect food intake data using the principles of the 24HDR method. This review identifies web- and computer-based 24HDR tools that have been developed for both children and adult population groups, and examines common design features and the methods used to investigate the performance and validity of these tools. Overall, there is generally good to strong agreement between web-based 24HDR and respective reference measures for intakes of macro- and micronutrients.

11 May 2017 in Journal of Medical Internet Research
Verified
Journal Article
Open access
CTClaire Timon
Claire Timon
RBRichard J Blain
Richard J Blain
BMBreige McNulty
Breige McNulty
LKLaura Kehoe
Laura Kehoe
KEKatie Evans
Katie Evans
EGEileen Gibney
Eileen Gibney
Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

7 February 2025 in Nutrients
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Journal Article
Open access
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COCathal O'Hara
Cathal O'Hara
GKGráinne Kent
Gráinne Kent
AFAngela Flynn
Angela Flynn
EGEileen Gibney
Eileen Gibney
CTClaire Timon
Claire Timon
Background/Objectives: Advances in artificial intelligence now allow combined use of large language and vision models; however, there has been limited evaluation of their potential in dietary assessment. This study aimed to evaluate the accuracy of ChatGPT-4 in estimating nutritional content of commonly consumed meals using meal photographs derived from national dietary survey data. Methods: Meal photographs (n = 114) were uploaded to ChatGPT and it was asked to identify the foods in each meal, estimate their weight, and estimate the nutrient content of the meals for 16 nutrients for comparison with the known values using precision, paired t-tests, Wilcoxon signed rank test, percentage difference, and Spearman correlation (rs). Seven dietitians also estimated energy, protein, and carbohydrate content of thirty-eight meal photographs for comparison with ChatGPT using intraclass correlation (ICC). Results: Comparing ChatGPT and actual meals, ChatGPT showed good precision (93.0%) for correctly identifying the foods in the photographs. There was good agreement for meal weight (p = 0.221) for small meals, but poor agreement for medium (p < 0.001) and large (p < 0.001) meals. There was poor agreement for 10 of the 16 nutrients (p < 0.05). Percentage difference from actual values was >10% for 13 nutrients, with ChatGPT underestimating 11 nutrients. Correlations were adequate or good for all nutrients with rs ranging from 0.29 to 0.83. When comparing ChatGPT and dietitians, the ICC ranged from 0.31 to 0.67 across nutrients. Conclusions: ChatGPT performed well for identifying foods, estimating weights of small portion sizes, and ranking meals according to nutrient content, but performed poorly for estimating weights of medium and large portion sizes and providing accurate estimates of nutrient content.

3 October 2020 in Nutrients
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Journal Article
Open access
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CTClaire Timon
Claire Timon
AOAileen O’connor
Aileen O’connor
NBNupur Bhargava
Nupur Bhargava
EGEileen Gibney
Eileen Gibney
EFEmma Feeney
Emma Feeney
Milk and dairy foods are naturally rich sources of a wide range of nutrients, and when consumed according to recommended intakes, contribute essential nutrients across all stages of the life cycle. Seminal studies recommendations with respect to intake of saturated fat have been consistent and clear: limit total fat intake to 30% or less of total dietary energy, with a specific recommendation for intake of saturated fat to less than 10% of total dietary energy. However, recent work has re-opened the debate on intake of saturated fat in particular, with suggestions that recommended intakes be considered not at a total fat intake within the diet, but at a food-specific level. A large body of evidence exists examining the impact of dairy consumption on markers of metabolic health, both at a total-dairy-intake level and also at a food-item level, with mixed findings to date. However the evidence suggests that the impact of saturated fat intake on health differs both across food groups and even between foods within the same food group such as dairy. The range of nutrients and bioactive components in milk and dairy foods are found in different levels and are housed within very different food structures. The interaction of the overall food structure and the nutrients describes the concept of the ‘food matrix effect’ which has been well-documented for dairy foods. Studies show that nutrients from different dairy food sources can have different effects on health and for this reason, they should be considered individually rather than grouped as a single food category in epidemiological research. This narrative review examines the current evidence, mainly from randomised controlled trials and meta-analyses, with respect to dairy, milk, yoghurt and cheese on aspects of metabolic health, and summarises some of the potential mechanisms for these findings.

29 January 2015 in British Journal of Nutrition
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Journal Article
Open access
CTClaire Timon
Claire Timon
AAArlene J. Astell
Arlene J. Astell
FHFaustina Hwang
Faustina Hwang
TATim D. Adlam
Tim D. Adlam
TSTom Smith
Tom Smith
EWElizabeth Williams
Elizabeth Williams
Dietary assessment in older adults can be challenging. The Novel Assessment of Nutrition and Ageing (NANA) method is a touch-screen computer-based food record that enables older adults to record their dietary intakes. The objective of the present study was to assess the relative validity of the NANA method for dietary assessment in older adults. For this purpose, three studies were conducted in which a total of ninety-four older adults (aged 65-89 years) used the NANA method of dietary assessment. On a separate occasion, participants completed a 4 d estimated food diary. Blood and 24 h urine samples were also collected from seventy-six of the volunteers for the analysis of biomarkers of nutrient intake. The results from all the three studies were combined, and nutrient intake data collected using the NANA method were compared against the 4 d estimated food diary and biomarkers of nutrient intake. Bland-Altman analysis showed a reasonable agreement between the dietary assessment methods for energy and macronutrient intake; however, there were small, but significant, differences for energy and protein intake, reflecting the tendency for the NANA method to record marginally lower energy intakes. Significant positive correlations were observed between urinary urea and dietary protein intake using both the NANA and the 4 d estimated food diary methods, and between plasma ascorbic acid and dietary vitamin C intake using the NANA method. The results demonstrate the feasibility of computer-based dietary assessment in older adults, and suggest that the NANA method is comparable to the 4 d estimated food diary, and could be used as an alternative to the food diary for the short-term assessment of an individual's dietary intake.

30 May 2022 in Cancers
Verified
Journal Article
Open access
PDF file
LBLouise Brennan
Louise Brennan
FSFatemeh Sadeghi
Fatemeh Sadeghi
LOLinda O'Neill
Linda O'Neill
EGEmer Guinan
Emer Guinan
LSLaura Smyth
Laura Smyth
JHJuliette Hussey
Juliette Hussey
Background: Telehealth has enabled access to rehabilitation throughout the pandemic. We assessed the feasibility of delivering a multi-disciplinary, multi-component rehabilitation programme (ReStOre@Home) to cancer survivors via telehealth. Methods: This single-arm mixed methods feasibility study recruited participants who had completed curative treatment for oesophago-gastric cancer for a 12-week telehealth rehabilitation programme, involving group resistance training, remotely monitored aerobic training, one-to-one dietetic counselling, one-to-one support calls and group education. The primary outcome was feasibility, measured by recruitment rates, attendance, retention, incidents, acceptability, Telehealth Usability Questionnaire (TUQ) and analysis of semi-structured interviews. Results: Characteristics of the twelve participants were: 65.42 ± 7.24 years; 11 male; 10.8 ± 3.9 months post-op; BMI 25.61 ± 4.37; received neoadjuvant chemotherapy 7/12; received adjuvant chemotherapy 4/12; hospital length of stay 16 days (median). Recruitment rate was 32.4%, and retention rate was 75%. Mean attendance was: education 90%; dietetics 90%; support calls 84%; resistance training 78%. Mean TUQ score was 4.69/5. Adaptations to the planned resistance training programme were required. Participants reported that ReStOre@Home enhanced physical and psychological wellbeing, and online delivery was convenient. Some reported a preference for in-person contact but felt that the online group sessions provided adequate peer support. Conclusion: Telehealth delivery of ReStOre@Home was most feasible in individuals with moderate to high levels of digital skills. Low level of digitals skills was a barrier to recruitment and retention. Participants reported high levels of programme adherence and participant satisfaction. Adaptations to future programmes, including introducing elements of in-person contact, are required.