Collecting saliva samples for DNA extraction from children and parents: findings from a pilot study using lay interviewers in the UK

In recent years there has been a substantial increase in the collection of biological data on social surveys. Biological data has hitherto been primarily collected by medically trained personnel in a clinic or laboratory setting or using specialist nurse interviewers in a home-visit setting. However, improvements in technology and the development of minimally or non- invasive data collection methods have made it increasingly feasible to collect bio-measures in a home setting using non-medically trained lay interviewers. In the field of genetic research, it has become increasingly common to collect DNA from saliva samples. This paper provides an account of a pilot study investigating the feasibility of collecting saliva samples for DNA extraction from mothers, fathers and children aged around 11 years old using lay interviewers on the UK Millennium Cohort Study. The pilot study was carried out in 2011 in five areas of the UK with one interviewer in each area. 45 families took part in the pilot and saliva samples were obtained from 73 per cent of mothers, 76 per cent of fathers and 74 per cent of children. We demonstrate that it is indeed viable to collect saliva samples for DNA extraction from children and parents using lay interviewers in a home setting, and provide practical suggestions about how the data collection process could be improved in order to achieve higher response rates and improved specimen quality. Our findings are relevant to other surveys planning to incorporate saliva sample collection for DNA extraction, particularly for those involving lay interviewers in a home setting

Collecting Multiple Data Linkage Consents in a Mixed-mode Survey: Evidence from a large-scale longitudinal study in the UK

Linking survey responses with administrative data is a promising practice to increase the range of research questions to be explored, at a limited interview burden, both for respondents and interviewers. We describe the protocol for asking consent to data linkage on nine different sources in a large-scale nationally representative longitudinal survey of young adults in England: the Next Steps Age 25 Survey. We present empirical evidence on consent to data linkage from qualitative interviews, a pilot study, and the mainstage survey. To the best of our knowledge, this is the first study that discusses the practicalities of implementing a data linkage protocol asking consent both retrospectively and prospectively, on multiple domains, and in the context of a mixed-mode survey

Using linked Hospital Episode Statistics data to aid the handling of non-response and restore sample representativeness in the 1958 National Child Development Study.

ObjectivesThere is growing interest in whether linked administrative data have the potential to aid analyses subject to missing data in cohort studies. We aimed to identify predictors of cohort non-response in linked administrative data and examine whether inclusion of these variables in principled methods for missing data handling can help restore sample representativeness.
 ApproachUsing linked 1958 National Child Development Study (NCDS) and Hospital Episode Statistics (HES) data, we applied a multi-stage data-driven approach to identify HES variable which are predictive of non-response at the age 55 sweep of NCDS. We then included these variables as auxiliary variables in multiple imputation (MI) analyses to see if they helped restore sample representativeness in terms of early life variables which were essentially fully observed in NCDS (mother’s husband’s social class at birth, cognitive ability at age 7) and relative to external population data (educational qualifications at age 55, marital status at age 55).
 ResultsWe took as our starting point 57 variables derived from HES data based on the presence or number of different types of appointments/admissions, diagnostic codes and treatment codes. After application of our multi-stage data-driven approach we identified five HES variables that were predictive of non-response at age 55 in NCDS. For example, cohort members who had been treated for adult mental illness were almost 3 times as likely to be non-respondents (risk ratio 2.81; 95% confidence interval 2.05, 3.86). Inclusion of these variables in MI analyses did help restore sample representativeness. However, there was no additional gain in sample representativeness relative to analyses using only previously identified survey predictors of non-response (i.e. NCDS rather than HES variables).
 ConclusionIn our applications, inclusion of HES predictors of NCDS non-response in analyses did not improve sample representativeness beyond that possible using survey variables alone. Whilst this finding may not extend to other analyses or NCDS sweeps, it highlights the utility of survey variables in handling non-response

Using new technologies for time diary data collection : instrument design and data quality findings from a mixed-mode pilot survey

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

Developments in fieldwork procedures and monitoring in longitudinal surveys: case prioritisation and electronic contact sheets on the UK Millennium Cohort Study

Maximising response is important in any survey and especially so in a longitudinal survey where non-response at a particular wave contributes to attrition. A key element of response maximisation in face-to-face surveys is the adoption and implementation of thorough fieldwork procedures. The introduction of electronic sample management systems has provided more timely and accurate para-data with which to monitor interviewers’ compliance with fieldwork procedures. One of the major advantages of longitudinal surveys is that they are able to make use of prior wave data in order to identify cases at highest risk of non-response and thereby target appropriate fieldwork interventions designed to minimise non-response. This paper examines two developments in the fieldwork procedures used on the UK Millennium Cohort Study (MCS) designed to maximise response: case prioritisation for low-contact propensity cases and electronic contact sheets to help ensure adherence to contact protocols. We compare fieldwork procedures used in the fifth wave in 2012 (at age 11) with those used at the sixth wave in 2015 (at age 14), utilising wave-on-wave changes in procedures to compare the effectiveness of different approaches to response maximisation. In the first part of our paper, we compare our two different approaches to case prioritisation: response propensity models employed at wave 5 and a simpler approach using prior wave outcomes only used at waves 6. We conclude that the simpler approach to identifying cases which are likely to have low contact propensity, based on prior wave outcomes only, is more effective than a more complex approach based on response propensity models. The second part of our paper, we evaluate the effectiveness of using of electronic contact sheets (ECS) at wave 6 to improve compliance with fieldwork procedures, cost-effectiveness and reduce non-response. We show that at wave 6 interviewer compliance rates were higher and non-contact rates were lower than at wave 5, and argue that the introduction of the ECS has led to this improvement in fieldwork quality and reduction in nonresponse

Web Surveys for the General Population: How, Why and When?

Cultural and technological change has made the web a possible and even desirable mode for complex social surveys, but the financial challenges faced by the Research Councils and the UK Government has accelerated this shift, creating an urgent need to explore both its potential and hazards for a range of studies. While some progress in carrying out large-scale complex social surveys on the web has been made, there is still no consensus about how this can best be achieved while maintaining population representativeness and preserving data quality. To address this problem, the NCRM funded a network of methodological innovation “Web Surveys for the General Population: How, Why and When?” (also known by its acronym GenPopWeb). A key objective of the network’s activities was to review and synthesise existing knowledge about the use of web-based data collection for general population samples and to identify areas where new research is needed. In this report, the authors provide a summary of the main issues identified by the network (chapter 2), present the key barriers to using web for surveys of the general population (chapter 3), propose a research agenda for the social science community (chapter 4), argue the case for a UK probability-based web panel (chapter 5), and conclude with recommendations for an infrastructure for enabling a transition to web platforms (chapter 6)

Using linked administrative data to aid the handling of non-response and restore sample representativeness in cohort studies: the 1958 national child development study and hospital episode statistics data

BACKGROUND: There is growing interest in whether linked administrative data have the potential to aid analyses subject to missing data in cohort studies. METHODS: Using linked 1958 National Child Development Study (NCDS; British cohort born in 1958, n = 18,558) and Hospital Episode Statistics (HES) data, we applied a LASSO variable selection approach to identify HES variables which are predictive of non-response at the age 55 sweep of NCDS. We then included these variables as auxiliary variables in multiple imputation (MI) analyses to explore the extent to which they helped restore sample representativeness of the respondents together with the imputed non-respondents in terms of early life variables (father's social class at birth, cognitive ability at age 7) and relative to external population benchmarks (educational qualifications and marital status at age 55). RESULTS: We identified 10 HES variables that were predictive of non-response at age 55 in NCDS. For example, cohort members who had been treated for adult mental illness had more than 70% greater odds of bring non-respondents (odds ratio 1.73; 95% confidence interval 1.17, 2.51). Inclusion of these HES variables in MI analyses only helped to restore sample representativeness to a limited extent. Furthermore, there was essentially no additional gain in sample representativeness relative to analyses using only previously identified survey predictors of non-response (i.e. NCDS rather than HES variables). CONCLUSIONS: Inclusion of HES variables only aided missing data handling in NCDS to a limited extent. However, these findings may not generalise to other analyses, cohorts or linked administrative datasets. This work provides a demonstration of the use of linked administrative data for the handling of missing cohort data which we hope will act as template for others

The impact of using the Web in a mixed-mode follow-up of a longitudinal birth cohort study: Evidence from the National Child Development Study

A sequential mixed-mode data collection, online-to-telephone, was introduced into the National Child Development Study for the first time at the study's age 55 sweep in 2013. The study included a small experiment, whereby a randomised subset of study members was allocated to a single mode, telephone-only interview, in order to test for the presence of mode effects on participation and measurement. Relative to telephone-only, the offer of the Web increased overall participation rates by 5.0 percentage points (82.8% vs. 77.8%; 95% confidence interval for difference: 2.7% to 7.3%). Differences attributable to mode of interview were detected in levels of item non-response and response values for a limited number of questions. Most notably, response by Web (relative to telephone) was found to have increased the likelihood of non-response to questions relating to pay and other financial matters, and increased the likelihood of ‘less desirable’ responses. For example, response by Web resulted in the reporting of more units of alcohol consumed, and more negative responses to subjective questions such as self-rated health, self-rated financial status and well-being. As there was evidence of mode effects, there is the potential for biases in some analyses, unless appropriate techniques are utilised to correct for these

Survey Data Collection Network (SDC-Net): The impact of Covid-19 on survey data collection methods in the social sciences

This is the final report of the Survey Data Collection Network (SDC-Net). SDC-Net was a network of UK-based academic and non-academic partners including government departments, third sector and commercial research organisations, academics and major ESRC investments to share knowledge and collaborate in the area of survey data collection in social surveys as well as in setting the research agenda in the field. The network operated between December 2021 and April 2023. The Principal Investigator was Olga Maslovskaya (University of Southampton) and the Co-Investigators are Gabriele Durrant (University of Southampton and NCRM), Lisa Calderwood (UCL), Gerry Nicolaas (NatCen) and Laura Wilson (ONS). The network activities were funded by the ESRC via the project “The impact of Covid-19 on survey data collection methods in the Social Sciences” as an additional funding stream of the ESRC-funded UK National Centre for Research Methods (NCRM). The network included 107 members. The list of the organisations of the network members can be found in Appendix 1. Tim Hanson, who is the Head of ESS Questionnaire Design and Fieldwork in the European Social Survey (ESS), Ben Humberstone, who is the Head of Population Studies in Kantar Public, Sam Clemens, who is the Head of Probability Survey in Ipsos-Mori as well as Debrah Harding, who is the Managing Director of the Market Research Society (MRS), were project partners. The ESRC recognised the importance of the activities of the previous network GenPopWeb2 which was also funded by the ESRC and the activities of SDC-Net were the continuation of the GenPopWeb2 with the wider scope addressing not only issues associated with online data collection in social surveys but the wider area of survey data collection in the UK