Suchergebnisse

"Typically, longitudinal survey managers send 'keep in touch' mailings to sample members between waves to help minimise non-response through failure to locate individuals at future waves. This paper reports the results from a randomised experiment to improve the effectiveness of the between-wave mailing on the Millennium Cohort Study (MCS), a large-scale birth cohort study in the UK. Our experimental intervention, which involved revising the content of the covering letters used in the 2010 mailing, aimed to increase the proportion of sample members responding to the mailing, particularly among those with higher attrition rates i.e. lower educated sample members and minority ethnic groups. The re-design involved making the letter easier to read, due to a concern that poor literacy or English may be a barrier to returning the form for some groups, and changing the style and signatory, motivated by the psychological concepts of reciprocity, linking and helping tendencies. Our main finding, that the design of the covering letter has a minimal impact on the effectiveness of these mailings, will help guide further research in this area and help to inform practice on longitudinal surveys. The results also make an important contribution to the existing evidence on the content of advance letters more generally and thereby have broader applicability for survey research and practice." (author's abstract)

"Interviewers made four observations related to future participation, respondent cooperation,
enjoyment and whether the respondent found the questions difficult, for a large sample
of face-to-face interviews at wave four of the UK Millennium Cohort Study (MCS). The focus of the paper is on predicting response behavior in the subsequent wave of MCS, four years later. The two most predictive observations are whether the respondent is likely to participate in the next wave and whether they enjoyed the interview. Not only do these predict non-response at the next wave, they do so after controlling for other explanatory variables from earlier waves in a response propensity model. Consequently, these two interviewer observations improve discrimination between respondents and non-respondents at wave five as estimated by Gini coefficients generated by a Receiver Operating Characteristic curve analysis. The predicted probabilities of responding at wave five are also used to estimate R-indicators, particularly to address the question of whether, hypothetically, conversion of 'frail' respondents would lead to improved representativity and reduced bias in longitudinal estimates of interest. The evidence from the R-indicators and partial -Rindicators suggests that successful conversions could achieve those aims although the cost of so doing might outweigh the benefits." (author's abstract)

"Refusal conversion is one of the fieldwork strategies commonly used to minimise non-response in surveys. There is, however, relatively little evidence about the effectiveness of this strategy, particularly for face-to-face longitudinal surveys. Moreover, much of the existing evidence is based on observational studies. This paper evaluates the effectiveness of a fieldwork strategy - intensive re-issuing - to convert refusals using evidence from an intervention on a random sub-sample of refusals implemented in wave four of a large scale longitudinal study in the UK: the Millennium Cohort Study. We show that intensive re-issuing is an effective way of reducing the refusal rate. We also show that refusal conversion led to a modest reduction in non-response bias in the survey estimates for several key variables. The longer term impact of refusal conversion is also a key concern in longitudinal surveys. We demonstrate that, although the majority of converted refusals go on to participate in the subsequent wave of the study, there is no overall effect of intensive re-issuing on sample size at this wave." (author's abstract)

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.

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.

ObjectivesAnalyses of population administrative data can often only be minimally adjusted due to the unavailability of a full set of control variables, leading to bias due to residual confounding. Cohort studies will often contain rich information on potential confounders but may not be sufficiently powered to meaningfully address the research question of interest. We aimed to use linked cohort data to help address residual confounding in analyses of population administrative data.
ApproachWe propose a multiple imputation-based approach, introduced through application to simulated data. We then apply this approach to a real-world problem – examining the association between pupil mobility (changing schools at non-standard times) and Key Stage 2 attainment using data from the UK National Pupil Database (NPD). The limited control variables available in the NPD are supplemented by multiple measures of socioeconomic deprivation captured in linked Millennium Cohort Study (MCS) data.
ResultsThe proposed approach is observed to perform well when using simulated data. The association between pupil mobility and Key Stage 2 attainment was attenuated after supplementing the NPD analysis with information from linked MCS data, though with a decrease in precision.
ConclusionWe have demonstrated the potential of the proposed approach, but more work is required.
ImplicationsThe principles underlying this innovative approach are widely applicable: any analysis of administrative data where confounder control is limited by the availability of information could potentially be strengthened by linking a subset of individuals into richer cohort data and leveraging the additional information to inform population-level analyses.

Non-response is common in longitudinal surveys, reducing efficiency and introducing the potential for bias. Principled methods, such as multiple imputation, are generally required to obtain unbiased estimates in surveys subject to missingness which is not completely at random. The inclusion of predictors of non-response in such methods, for example as auxiliary variables in multiple imputation, can help improve the plausibility of the missing at random assumption underlying these methods and hence reduce bias. We present a systematic data-driven approach used to identify predictors of non-response at Wave 8 (age 25–26) of Next Steps, a UK national cohort study that follows a sample of 15,770 young people from age 13–14 years. The identified predictors of non-response were across a number of broad categories, including personal characteristics, schooling and behaviour in school, activities and behaviour outside of school, mental health and well-being, socio-economic status, and practicalities around contact and survey completion. We found that including these predictors of non-response as auxiliary variables in multiple imputation analyses allowed us to restore sample representativeness in several different settings, though we acknowledge that this is unlikely to universally be the case. We propose that these variables are considered for inclusion in future analyses using principled methods to explore and attempt to reduce bias due to non-response in Next Steps. Our data-driven approach to this issue could also be used as a model for investigations in other longitudinal studies.

IntroductionRecent years have seen an increase in linkages between survey and administrative data. It is important to evaluate the quality of such data linkages to discern the likely reliability of ensuing research. Evaluation of linkage quality and bias can be conducted using different approaches, but many of these are not possible when there is a separation of processes for linkage and analysis to help preserve privacy, as is typically the case in the UK (and elsewhere).
ObjectivesWe aimed to describe a suite of generalisable methods to evaluate linkage quality and population representativeness of linked survey and administrative data which remain tractable when users of the linked data are not party to the linkage process itself. We emphasise issues particular to longitudinal survey data throughout.
MethodsOur proposed approaches cover several areas: i) Linkage rates, ii) Selection into response, linkage consent and successful linkage, iii) Linkage quality, and iv) Linked data population representativeness. We illustrate these methods using a recent linkage between the 1958 National Child Development Study (NCDS; a cohort following an initial 17,415 people born in Great Britain in a single week of 1958) and Hospital Episode Statistics (HES) databases (containing important information regarding admissions, accident and emergency attendances and outpatient appointments at NHS hospitals in England).
ResultsOur illustrative analyses suggest that the linkage quality of the NCDS-HES data is high and that the linked sample maintains an excellent level of population representativeness with respect to the single dimension we assessed.
ConclusionsThrough this work we hope to encourage providers and users of linked data resources to undertake and publish thorough evaluations. We further hope that providing illustrative analyses using linked NCDS-HES data will improve the quality and transparency of research using this particular linked data resource.

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.

ObjectivesIt is important to evaluate the quality of linkages between cohort and administrative data to discern the likely reliability of research using the linked data resource. We examined the quality and sample representativeness of linked 1958 National Child Development Study (NCDS) and Hospital Episode Statistics (HES) data.
ApproachWe examined the quality of the linkage in terms of the associations between key cohort member sociodemographic characteristics and successful linkage, and compared the levels of successful linkage within strata of NCDS variables which may be expected to be associated with hospital attendance (self-reported hospital attendance, self-rated general health, self-reported long-term illness), and hence with successful HES linkage. We additionally evaluated the population representativeness of the linked sample using external population statistics (hospital admission rates in the general population).
ResultsSome sociodemographic characteristics were found to be associated with successful HES linkage, with females slightly more likely than males (risk ratio 1.03; 95% confidence interval 1.00, 1.06) and those who had ≤ 1 person per room at birth more likely than those who had > 1.5 (1.12; 1.05, 1.19) to have linked data. There was a high level of correspondence between NCDS variables and HES linkage – e.g., 86.0% of cohort members who reported no day patient or in-patient attendance had no linked HES Admitted Patient Care (APC) data and 76.3% of those who reported having day patient or in-patient attendance did have linked HES APC data. The level and pattern of hospital admission rates over time was similar in the linked NCDS-HES data to the population statistics.
ConclusionThe quality and representativeness of the linked NCDS-HES data appears to be high. We hope that these analyses will both improve the quality and transparency of research using this linked data resource and encourage providers and users of other linked data resources to undertake and publish similarly thorough evaluations.

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.

Objective and ApproachFunded by the Economic and Social Research Council (2021-2024), a core aim of the ELC-FS was to establish a sampling frame by linking birth registrations and maternity records in the four UK nations (England, Wales, Scotland and Northern Ireland) to facilitate recruitment of ~2000 families into a new birth cohort study. An opt-out recruitment approach was essential. Widespread public dialogue work was undertaken to glean the attitudes and perspectives of stakeholders including data controllers, data users, and parents of young children, as to the acceptability of this recruitment model.
ResultsAchieving the sampling frame required nation-specific approaches due to differences in existing legislation governing secondary use of administrative data. Complex and protracted negotiations with data controller approval panels were necessary. Public dialogue work revealed that stakeholders were: (i) excited by the prospect of a new UK-wide birth cohort study to provide invaluable insights into the lives of a new generation; and (ii) broadly accepting of the proposed use of administrative data for generating a sampling frame, particularly in terms of ensuring that the ELC-FS study has diverse and inclusive representation of family life in the UK today.
ConclusionsELC-FS fieldwork will be completed by mid-2024. Preliminary analyses to be presented at the conference will assess the suitability of the sampling frame for achieving the target ELC-FS sample.
ImplicationsWith careful engagement with stakeholders at a national level, access to linked administrative data as a sampling frame for a UK-wide birth cohort study is achievable, but not straightforward.

This book documents the early lives of almost 19,000 children born in the UK at the start of the 21st century, and their families. It is the first time that analysis of data from the hugely important Millennium Cohort Study, a longitudinal study following the progress of the children and their families, has been drawn together in a single volume. The unrivalled data is examined here to address important policy and scientific issues. The book is also the first in a series of publications that will report on the children's lives at different stages of their development. The fascinating range of findings presented here is strengthened by comparison with data on earlier generations. This has enabled the authors to assess the impact of a wide range of policies on the life courses of a new generation, including policies on child health, parenting, childcare and social exclusion. Babies of the new millennium (title tbc) is the product of an exciting collaboration from experts across a wide range of health and social science fields. The result is a unique and authoritative analysis of family life and early childhood in the UK that cuts across old disciplinary boundaries. It is essential reading for academics, students and researchers in the health and social sciences. It will also be a useful resource for policy makers and practitioners who are interested in childhood, child development, child poverty, child health, childcare and family policy