Methodological challenges and approaches to improving response rates in population surveys in areas of extreme deprivation (original) (raw)
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BMC Medical Research Methodology, 2010
Background There is a need for local level health data for local government and health bodies, for health surveillance and planning and monitoring of policies and interventions. The Health Survey for England (HSE) is a nationally-representative survey of the English population living in private households, but sub-national analyses can be performed only at a regional level because of sample size. A boost of the HSE was commissioned to address the need for local level data in London but a different mode of data collection was used to maximise participant numbers for a given cost. This study examines the effects on survey and item response of the different survey modes. Methods Household and individual level data are collected in HSE primarily through interviews plus individual measures through a nurse visit. For the London Boost, brief household level data were collected through interviews and individual level data through a longer self-completion questionnaire left by the interviewer and collected later. Sampling and recruitment methods were identical, and both surveys were conducted by the same organisation. There was no nurse visit in the London Boost. Data were analysed to assess the effects of differential response rates, item non-response, and characteristics of respondents. Results Household response rates were higher in the 'Boost' (61%) than 'Core' (HSE participants in London) sample (58%), but the individual response rate was considerably higher in the Core (85%) than Boost (65%). There were few differences in participant characteristics between the Core and Boost samples, with the exception of ethnicity and educational qualifications. Item non-response was similar for both samples, except for educational level. Differences in ethnicity were corrected with non-response weights, but differences in educational qualifications persisted after non-response weights were applied. When item non-response was added to those reporting no qualification, participants' educational levels were similar in the two samples. Conclusion Although household response rates were similar, individual response rates were lower using the London Boost method. This may be due to features of London that are particularly associated with lower response rates for the self-completion element of the Boost method, such as the multi-lingual population. Nevertheless, statistical adjustments can overcome most of the demographic differences for analysis. Care must be taken when designing self-completion questionnaires to minimise item non-response.
Increasing response rates to postal questionnaires: a randomised trial of variations in design
Journal of Health Services Research & Policy, 2004
Objective To identify methods to increase response to postal questionnaires. Design Systematic review of randomised controlled trials of any method to influence response to postal questionnaires. Studies reviewed 292 randomised controlled trials including 258 315 participants Intervention reviewed 75 strategies for influencing response to postal questionnaires.
BMC Medical Research Methodology, 2010
Background: Evidence suggests that survey response rates are decreasing and that the level of survey response can be influenced by questionnaire length and the use of pre-notification. The goal of the present investigation was determine the effect of questionnaire length and pre-notification type (letter vs. postcard) on measures of survey quality, including response rates, response times (days to return the survey), and item nonresponse.
Nobody home? Issues of respondent recruitment in areas of deprivation
Critical Public Health, 2001
Although there is there is a shared assumption among the research community that response rates are lower in areas of deprivation, few studies have reported on the difficulties of recruiting disadvantaged respondents for the purposes of research. Where these issues are raised the focus is usually on why particular respondent groups may be more or less disposed to participate in research. This paper draws on two separate research projects on smoking which drew their respondents from overlapping areas of disadvantage in Edinburgh. Although informed by different research paradigms and employing different strategies of respondent recruitment, the two studies obtained a similar response rate. Although respectable, the response rate (approximately 60%) was achieved only at the expense of an enormous under-anticipated effort on behalf of the respective research teams. The greatest problem associated with respondent recruitment was in both cases linked to the high level of ineligible addresses and non-contacts, rather than with refusal to participate. The paper highlights the crucial importance of respondent recruitment strategies and re ects on the implications of recent data protection legislation for the requirements of research ethical committees. Neither of the studies discussed in the paper used 'opt-in' recruitment strategies, which are becoming more popular with ethics committees following the Data Protection Act. However, it is extremely likely that such strategies would have had a detrimental affect on the response rates achieved. This is problematic not least because a major aim of public health research targeting areas of deprivation is to provide marginalized or socially disadvantaged individuals with a voice.
2. Designing high-quality surveys of ethnic minority groups in the United Kingdom
Surveying Ethnic Minorities and Immigrant Populations, 2013
Carrying out surveys among ethnic minority (EM) groups raises a number of problems above and beyond those to do with surveys of the general population. These difficulties arise because EM groups may appear with a low frequency in the population, may be geographically unclustered, and may be difficult to access. This chapter examines some of the key issues to do with designing rigorous, high-quality surveys of ethnic minorities, whether as a 'boost' to increase their numbers in a general survey or as a targeted survey among particular EM groups. By 'high quality', the survey needs not only to provide accurate data, but it also must relate to the needs of the users (e.g. it should be relevant, timely and accessible). While having indicators of survey quality is importantfor example, to evaluate the usefulness of the data provided and to differentiate between 'good' and 'bad' datathis chapter is not concerned with issues of general survey design or quality (for a general discussion of survey methodology,
2017
1. A typology of hard-to-survey groups among the poor 5 1.1 Hard-to-sample groups 5 1.2 Hard-to-identify groups 6 1.3 Hard-to-find or hard-to-contact groups 8 1.4 Hard-to-persuade groups 9 1.5 Hard-to-interview populations 10 1.6 Conclusion 11 2. Sampling strategies 13 2.1 Introduction 13 2.2 Sampling methods 14 2.2.1 Disproportionate stratification 15 2.2.2 Location sampling 16 2.2.3 Capture-recapture methods 18 2.2.4 Network-based sampling 20 2.2.5 A combination of methods 23 3. Problems resulting from inadequate inclusion of hard-to-reach groups 25 3.1 Introduction 25 3.2 Non-response error 25 3.2.1 Problem 25 3.2.2 Measures to reduce non-response error 26 3.3 Coverage error 27 3.3.1 Problem 27 3.3.2 Measures to reduce coverage error 28 3.4 Undercounts 28 3.4.1 Problem 28 3.4.2 Measures to estimate undercounts 29 3.5 Conclusion 30 4. Enhancing trust and communicative success 33 4.1 Strategy 1: doing (community-based) participatory research 33 4.2 Strategy 2: recruiting peer resea...