Objective: Our original aim was to validate and norm common eating disorder (ED) symptom measures in a large, representative community sample of transgender adults in the United States. We recruited via Amazon Mechanical Turk (MTurk), a popular online recruitment and data collection platform both within and outside of the ED field. We present an overview of our experience using MTurk. Method: Recruitment began in Spring 2020; our original target N was 2,250 transgender adults stratified evenly across the United States. Measures included a demographics questionnaire, the Eating Disorder Examination-Questionnaire, and the Eating Attitudes Test-26. Consistent with current literature recommendations, we implemented a comprehensive set of attention and validity measures to reduce and identify bot responding, data farming, and participant misrepresentation.Results: Recommended validity and attention checks failed to identify the majority of likely invalid responses. Our collection of two similar ED measures, thorough weight history assessment, and gender identity experiences allowed us to examine response concordance and identify impossible and improbable responses, which revealed glaring discrepancies and invalid data. Furthermore, qualitative data (e.g., emails received from MTurk workers) raised concerns about economic conditions facing MTurk workers that could compel misrepresentation.Discussion: Our results strongly suggest most of our data were invalid, and call into question results of recently published MTurk studies. We assert that caution and rigor must be applied when using MTurk as a recruitment tool for ED research, and offer several suggestions for ED researchers to mitigate and identify invalid data.

Recent years have witnessed a steady growth of time-use research, driven by the increased research and policy interest in population activity patterns and their associations with long-term outcomes. There is recent interest in moving beyond traditional paper-administered time diaries to use new technologies for data collection in order to reduce respondent burden and administration costs, and to improve data quality. This paper presents two novel diary instruments that were employed by a large-scale multi-disciplinary cohort study in order to obtain information on the time allocation of adolescents in the United Kingdom. A web-administered diary and a smartphone app were created, and a mixed-mode data collection approach was followed: cohort members were asked to choose between these two modes, and those who were unable or refused to use the web/app modes were offered a paper diary. Using data from a pilot survey of 86 participants, we examine diary data quality indicators across the three modes. Results suggest that the web and app modes yield an overall better time diary data quality than the paper mode, with a higher proportion of diaries with complete activity and contextual information. Results also show that the web and app modes yield a comparable number of activity episodes to the paper mode. These results suggest that the use of new technologies can improve diary data quality. Future research using larger samples should systematically investigate selection and measurement effects in mixed-mode time-use survey designs.

A large proportion of mothers who were interviewed gave permission for linkage. However, there were some groups who were less likely to do so, particularly those from minority ethnic groups. These sources of non-consent bias should be taken into account when analysing linked data from socially and ethnically mixed populations. Efforts should be made to understand the reasons for non-consent, which in turn will help determine the best ways to encourage more mothers to consent in future.

ObjectivesTo investigate the biological, social, behavioural and environmental factors associated with non-consent, and non-return of reliable accelerometer data (≥2 days lasting ≥10 h/day), in a UK-wide postal study of children's activity.DesignNationally representative prospective cohort study.SettingChildren born across the UK, between 2000 and 2002.Participants13 681 7 to 8-year-old singleton children who were invited to wear an accelerometer on their right hip for 7 consecutive days. Consenting families were posted an Actigraph GT1M accelerometer and asked to return it by post.Primary outcome measuresStudy consent and reliable accelerometer data acquisition.ResultsConsent was obtained for 12 872 (94.5%) interviewed singletons, of whom 6497 (50.5%) returned reliable accelerometer data. Consent was less likely for children with a limiting illness or disability, children who did not have people smoking near them, children who had access to a garden, and those who lived in Northern Ireland. From those who consented, reliable accelerometer data were less likely to be acquired from children who: were boys; overweight/obese; of white, mixed or ‘other’ ethnicity; had an illness or disability limiting daily activity; whose mothers did not have a degree; who lived in rented accommodation; who exercised once a week or less; who had been breastfed; were from disadvantaged wards; had younger mothers or lone mothers; or were from households with just one, or more than three children.ConclusionsStudies need to encourage consent and reliable data return in the wide range of groups we have identified to improve response and reduce non-response bias. Additional efforts targeted at such children should increase study consent and data acquisition while also reducing non-response bias. Adjustment must be made for missing data that account for missing data as a non-random event.

The Millennium Cohort Study of 18,818 UK babies born in 2000-02 interviewed parents when the baby was 9 months old. Time constraints on the interview limited the amount of health-related questions that could be included. The aim of this study was to augment interview data with information from birth registrations and hospital records. It also provided an opportunity to assess the accuracy of the data acquired and parents' recall of the information on pregnancy and delivery. Deterministic and probabilistic matching were used to obtain information from birth registration and hospital records. Investigation into the accuracy of the matches obtained was undertaken. The records received were checked for range, consistency and completion. Birth registration data were obtained for 99% of those who gave consent. The number of additional variables gained ranged from six in Northern Ireland to 16 in Scotland. Hospital record data were obtained for 83% of those who gave consent. The additional general and maternity-related variables gained ranged from 55 in Scotland to 76 in England. Completion of available health record variables ranged from 28% to 100% across all UK countries. Linkage to birth registration and hospital records in order to augment Millennium Cohort Study data with routinely collected data was successful. The variables gained by linkage have added considerable value to the cohort study and validated some of the mother's responses.