Online self-reported 24-h dietary recall systems promise increased feasibility of dietary assessment. Comparison against interviewer-led recalls established their convergent validity; however, ...reliability and criterion-validity information is lacking. The validity of energy intakes (EI) reported using Intake24, an online 24-h recall system, was assessed against concurrent measurement of total energy expenditure (TEE) using doubly labelled water in ninety-eight UK adults (40-65 years). Accuracy and precision of EI were assessed using correlation and Bland-Altman analysis. Test-retest reliability of energy and nutrient intakes was assessed using data from three further UK studies where participants (11-88 years) completed Intake24 at least four times; reliability was assessed using intra-class correlations (ICC). Compared with TEE, participants under-reported EI by 25 % (95 % limits of agreement -73 % to +68 %) in the first recall, 22 % (-61 % to +41 %) for average of first two, and 25 % (-60 % to +28 %) for first three recalls. Correlations between EI and TEE were 0·31 (first), 0·47 (first two) and 0·39 (first three recalls), respectively. ICC for a single recall was 0·35 for EI and ranged from 0·31 for Fe to 0·43 for non-milk extrinsic sugars (NMES). Considering pairs of recalls (first two
third and fourth recalls), ICC was 0·52 for EI and ranged from 0·37 for fat to 0·63 for NMES. EI reported with Intake24 was moderately correlated with objectively measured TEE and underestimated on average to the same extent as seen with interviewer-led 24-h recalls and estimated weight food diaries. Online 24-h recall systems may offer low-cost, low-burden alternatives for collecting dietary information.
•Recommender system resistant to the cold-start problem is proposed.•System builds a model of preferences from transactions performed by a population.•Evaluated on transactional dataset from a real ...world dietary intake recall system.•Applications to recommender and ranking tasks are demonstrated.
Recommender systems based on methods such as collaborative and content-based filtering rely on extensive user profiles and item descriptors as well as on an extensive history of user preferences. Such methods face a number of challenges; including the cold-start problem in systems characterized by irregular usage, privacy concerns, and contexts where the range of indicators representing user interests is limited. We describe a recommender algorithm that builds a model of collective preferences independently of personal user interests and does not require a complex system of ratings. The performance of the algorithm is analyzed on a large transactional data set generated by a real-world dietary intake recall system.
Under-reporting because of the limitations of human memory is one of the key challenges in dietary assessment surveys that use the multiple-pass 24-hour recall. Research indicates that shortening a ...retention interval (ie, the time between the eating event and recall) reduces the burden on memory and may increase the accuracy of the assessment.
This study aimed to explore the accuracy and acceptability of Web-based dietary assessment surveys based on a progressive recall, where a respondent is asked to record multiple recalls throughout a 24-hour period using the multiple-pass protocol and portion size estimation methods of the 24-hour recall.
The experiment was conducted with a dietary assessment system, Intake24, that typically implements the multiple-pass 24-hour recall method where respondents record all meals they had for the previous day on a single occasion. We modified the system to allow respondents to add multiple recalls throughout the day using the multiple-pass protocol and portion size estimation methods of the 24-hour recall (progressive recall). We conducted a dietary assessment survey with 33 participants, where they were asked to record dietary intake using both 24-hour and progressive recall methods for weekdays only. We compared mean retention intervals (ie, the time between eating event and recall) for the 2 methods. To examine accuracy, we compared mean energy estimates and the mean number of reported foods. Of these participants, 23 were interviewed to examine the acceptability of the progressive recall.
Retention intervals were found to be, on average, 15.2 hours (SD 7.8) shorter during progressive recalls than those during 24-hour recalls. We found that the mean number of foods reported for evening meals for progressive recalls (5.2 foods) was significantly higher (P=.001) than that for 24-hour recalls (4.2 foods). The number of foods and the amount of energy reported for other meals remained similar across the 2 methods. In interviews, 65% (15/23) of participants said that the 24-hour recall is more convenient in terms of fitting in with their daily lifestyles, and 65% (15/23) of respondents indicated that they remembered meal content and portion sizes better with the progressive recall.
The analysis of interviews and data from our study indicate that progressive recalls provide minor improvements to the accuracy of dietary assessment in Intake24. Additional work is needed to improve the acceptability of progressive recalls in this system.
Dietary assessment surveys are an important tool for measuring and/or monitoring the nutritional profile of a population. The analysis of data that is collected in these surveys helps to develop ...health care guidelines and policies that minimise the risk of diet related diseases on a national scale. For years these surveys had to be conducted in a form of an interview by trained researchers with a nutritional background. The emergence of systems that automate interviewer-led protocols and transform these interviews into online surveys has addressed financial limitations and brought scalability into dietary assessment studies. In the meantime, online dietary assessment surveys mostly copy the interviewer-led procedures and inherit some of their methodological issues that lead to misreporting of dietary intake and lower the accuracy of assessment. This thesis primarily focuses on the issues related to human-memory, motivation of respondents to take part in dietary assessment studies, and the usability of survey interfaces. This work pinpoints the elements of automated dietary assessment systems, where these issues affect the accuracy of results. This analysis is then translated into three research questions of this thesis. Challenges related to human-memory are then addressed by developing and evaluating a recommender system for prompting omitted foods in online dietary assessment surveys. This work also explores short retention intervals (i.e. time between an intake and recall) as another method for recall assistance. As a way to motivate respondents to take part in dietary assessment surveys this thesis explores tailored dietary feedback provided to respondents at the end of a survey. Usability and performance of new methods are analysed in real-life dietary assessment surveys using a usability framework developed for this research. Acceptance of the methods is analysed using thematic analysis of transcribed interviews with respondents. Research activities conducted during this work provide some support to hypotheses defined in the research questions.
Modern society is going through the transformation under the influence of Information Technologies. Internet of Things as one of the latest facet of it becoming more visible and widely spread. We ...wish to reflect and discuss the current concerns regarding its expansion. Our particular interests lie in the increasing of usability and comfortability through the unification of the IoT protocols and security measures. As well as addressing the privacy concerns and discussing the possible changings in the perception of privacy and personal space concepts.
From Her Story, to Our Story Michie, Lydia; Balaam, Madeline; McCarthy, John ...
CHI '18 Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems,
04/2018
Conference Proceeding
Odprti dostop
Despite the divisive nature of abortion within the Republic of Ireland and Northern Ireland, where access to safe, legal abortion is severely restricted, effecting legislative reform demands ...widespread public support. In light of a building pro-choice counter-voice, this work contributes to a growing body of HCI research that takes an activist approach to design. We report findings from four design workshops with 31 pro-choice stakeholders across Ireland in which we positioned an exploratory protosite, HerStoryTold, to engender critical conversations around the use of sensitive abortion narratives as a tool for engagement. Our analysis shows how digital storytelling can help reject false narratives and raise awareness of the realities of abortion laws. It suggests design directions to curate narratives that provoke empathy, foster polyvocality, and ultimately expand the engaged community. Furthermore, this research calls for designers to actively support community mobilization through providing 'stepping stones' to activism.
Recall assistance methods are among the key aspects that improve the accuracy of online dietary assessment surveys. These methods still mainly rely on experience of trained interviewers with ...nutritional background, but data driven approaches could improve cost-efficiency and scalability of automated dietary assessment. We evaluated the effectiveness of a recommender algorithm developed for an online dietary assessment system called Intake24, that automates the multiple-pass 24-hour recall method. The recommender builds a model of eating behavior from recalls collected in past surveys. Based on foods they have already selected, the model is used to remind respondents of associated foods that they may have omitted to report. The performance of prompts generated by the model was compared to that of prompts hand-coded by nutritionists in two dietary studies. The results of our studies demonstrate that the recommender system is able to capture a higher number of foods omitted by respondents of online dietary surveys than prompts hand-coded by nutritionists. However, the considerably lower precision of generated prompts indicates an opportunity for further improvement of the system.
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