scholarly journals Implementing Adaptive Survey Design with an Application to the Dutch Health Survey

2020 ◽  
Vol 36 (3) ◽  
pp. 609-629
Author(s):  
Kees van Berkel ◽  
Suzanne van der Doef ◽  
Barry Schouten
Keyword(s):  
Data Collection ◽  
Case Management ◽  
Health Survey ◽  
Survey Methodology ◽  
Survey Design ◽  
Management Systems ◽  
Household Surveys ◽  
Dutch Health ◽  
Survey Designs ◽  
Practical Feasibility

AbstractAdaptive survey design has attracted great interest in recent years, but the number of case studies describing actual implementation is still thin. Reasons for this may be the gap between survey methodology and data collection, practical complications in differentiating effort across sample units and lack of flexibility of survey case management systems. Currently, adaptive survey design is a standard option in redesigns of person and household surveys at Statistics Netherlands and it has been implemented for the Dutch Health survey in 2018. In this article, the implementation of static adaptive survey designs is described and motivated with a focus on practical feasibility.

Brazilian National Household Health Survey and PCAT: the case of Mato Grosso do Sul, Brazil

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
L F Pinto ◽  
D Soranz ◽  
L J Santos ◽  
M S Paranhos ◽  
L S Malta ◽  
...  
Keyword(s):  
Primary Care ◽  
Health Care ◽  
Primary Health Care ◽  
Data Collection ◽  
Health Survey ◽  
Household Surveys ◽  
Mato Grosso ◽  
Primary Health ◽  
The World ◽  
Mato Grosso Do Sul

Abstract Brazil is divided into five administrative regions, 27 federation units and 5,570 municipalities. Mato Grosso do Sul is one of the states located in the Midwest region and has 1.6 million km2 and a resident population of 2.8 million inhabitants, that is, it has an even lower demographic density than its region - only 7.8 inhabitants/km2. Mato Grosso do Sul has part of the Pantanal, a biome considered the largest continuous floodplain in the world, rich in biodiversity. For this reason, displacements for data collection in household surveys combine roads and rivers. In 2019, the Brazilian National Institute of Geography and Statistics (Istituto Nazionale di Statistica del Brasile) in partnership with the Ministry of Health launched the world's largest household sample survey, the National Health Survey (PNS-2019), in which part of its questions included the use of Primary Care Assessment Tool (PCAT, adult version), created by professors Barbara Starfield and Leiyu Shi in the 2000s. IBGE interviewers visited more than 100,000 households across the country. In Mato Grosso do Sul, more than 3,000 households were surveyed. In this work, we present the data collection instrument used by IBGE and its multiple analysis possibilities in the scope of primary health care, crossing the variables from other questionnaire modules in order to compare the results from Brazil with the state of Mato Grosso do Sul and its capital, Campo Grande. Developing a baseline and measuring the attributes of primary health care in each of the Brazilian states is another step towards giving health policy accountability, towards strong primary care. IBGE's experience in household surveys and innovation in data collection in primary care is an example for the world that yes, it is possible to develop statistically representative national sample surveys and make them perennial in their regular household surveys, by the time World Health Organization (WHO) discusses universal health coverage. Key messages Evaluation of primary care using an internationally validated instrument is possible on national bases with random household sample surveys. A questionnaire elaborated academically can be used as an instrument of public policy to evaluate nationwide health services.

Mental Health Supplement to the Ontario Health Survey: Methodology

1996 ◽  
Vol 41 (9) ◽  
pp. 549-558 ◽  
Author(s):  
Michael H Boyle ◽  
David R Offord ◽  
Dugal Campbell ◽  
Gary Catlin ◽  
Paula Goering ◽  
...  
Keyword(s):  
Psychiatric Disorder ◽  
Health Survey ◽  
Survey Methodology ◽  
Survey Design ◽  
Epidemiologic Study ◽  
Composite International Diagnostic Interview ◽  
Data File ◽  
Diagnostic Interview ◽  
Cross Sectional ◽  
Careful Measurement

Objective: To describe the methodology of a province-wide, cross-sectional, epidemiologic study of psychiatric disorder among those aged 15 years and over living in household dwellings in Ontario. Method: Respondents for the survey were drawn from households (N = 13 002) participating in a province-wide health survey. One person per household was selected, and 9953 (76.5%) participated. Results: Participants and nonparticipants were similar to each other. An extensive array of data, including measures of psychiatric disorder classified using a revised version of the Composite International Diagnostic Interview (CIDI), are available for all respondents. Conclusions: The Ontario Health Supplement is contained in a public-use data file at the Ontario Ministry of Health and is available to investigators for study. A strong survey design, careful measurement, and acceptable levels of response provide the rationale for our inviting researchers to access and use the Ontario Health Supplement data base.

Responsive and Adaptive Survey Design: Use of Bias Propensity During Data Collection to Reduce Nonresponse Bias

2020 ◽  
Author(s):  
Andy Peytchev ◽  
Daniel Pratt ◽  
Michael Duprey
Keyword(s):  
Data Collection ◽  
Survey Design ◽  
Nonresponse Bias ◽  
Sampling Frame ◽  
New Approach ◽  
Response Propensity ◽  
Survey Estimates ◽  
Study Designs ◽  
Survey Designs

Abstract Reduction in nonresponse bias has been a key focus in responsive and adaptive survey designs, through multiple phases of data collection, each defined by a different protocol, and targeting interventions to a subset of sample elements. Key in this approach is the identification of nonrespondents who, if interviewed, can reduce nonresponse bias in survey estimates. From a design perspective, we need to identify an appropriate model to select targeted cases, in addition to an effective intervention (change in protocol). From an evaluation perspective, we need to compare estimates to a control condition that is often omitted from study designs, in addition to the need for benchmark estimates for key survey measures to provide estimates of nonresponse bias. We introduced a bias propensity approach for the selection of sample members to reduce nonresponse bias. Unlike a response propensity approach in which the objective is to maximize the prediction of nonresponse, this new approach deliberately excludes strong predictors of nonresponse that are uncorrelated with survey measures and uses covariates that are of substantive interest to the study. We also devised an analytic approach to simulate which sample members would have responded in a control condition. This study also provided a rare opportunity to estimate nonresponse bias, using rich sampling frame information, prior round survey data, and data from extensive nonresponse follow-up. The bias propensity model yielded reasonable fit despite the exclusion of the strongest predictors of nonresponse. The intervention was found to be effective in increasing participation among identified sample members. On average, the responsive and adaptive survey design reduced nonresponse bias by more than one-quarter—almost one percentage point—regardless of the choice of benchmark estimates. Effort under the control condition did not reduce nonresponse bias. While results are strongly encouraging, we argue for replication with varied populations and methods.

scholarly journals HIV and cardiovascular disease in sub-Saharan Africa: Demographic and Health Survey data for 4 countries

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Leonard E. Egede ◽  
Rebekah J. Walker ◽  
Patricia Monroe ◽  
Joni S. Williams ◽  
Jennifer A. Campbell ◽  
...  
Keyword(s):  
South Africa ◽  
Cardiovascular Disease ◽  
Health Survey ◽  
Survey Design ◽  
Logistic Models ◽  
Population Data ◽  
Demographic And Health Survey ◽  
Sub Saharan Africa ◽  
Sub Saharan ◽  
The Relationship

Abstract Background Investigate the relationship between two common cardiovascular diseases and HIV in adults living in sub-Saharan Africa using population data provided through the Demographic and Health Survey. Methods Data for four sub-Saharan countries were used. All adults asked questions regarding diagnosis of HIV, diabetes, and hypertension were included in the sample totaling 5356 in Lesotho, 3294 in Namibia, 9917 in Senegal, and 1051 in South Africa. Logistic models were run for each country separately, with self-reported diabetes as the first outcome and self-reported hypertension as the second outcome and HIV status as the primary independent variable. Models were adjusted for age, gender, rural/urban residence and BMI. Complex survey design allowed weighting to the population. Results Prevalence of self-reported diabetes ranged from 3.8% in Namibia to 0.5% in Senegal. Prevalence of self-reported hypertension ranged from 22.9% in Namibia to 0.6% in Senegal. In unadjusted models, individuals with HIV in Lesotho were 2 times more likely to have self-reported diabetes (OR = 2.01, 95% CI 1.08–3.73), however the relationship lost significance after adjustment. Individuals with HIV were less likely to have self-reported diabetes after adjustment in Namibia (OR = 0.29, 95% CI 0.12–0.72) and less likely to have self-reported hypertension after adjustment in Lesotho (OR = 0.63, 95% CI 0.47–0.83). Relationships were not significant for Senegal or South Africa. Discussion HIV did not serve as a risk factor for self-reported cardiovascular disease in sub-Saharan Africa during the years included in this study. However, given the growing prevalence of diabetes and hypertension in the region, and the high prevalence of undiagnosed cardiovascular disease, it will be important to continue to track and monitor cardiovascular disease at the population level and in individuals with and without HIV. Conclusions The odds of self-reported diabetes in individuals with HIV was high in Lesotho and low in Namibia, while the odds of self-reported hypertension in individuals with HIV was low across all 4 countries included in this study. Programs are needed to target individuals that need to manage multiple diseases at once and should consider increasing access to cardiovascular disease management programs for older adults, individuals with high BMI, women, and those living in urban settings.

Mapping of Household Surveys to Measure Barriers to Access to Maternal and Child Health Services in India

2021 ◽  
Vol 23 (1) ◽  
pp. 10-19
Author(s):  
Shivam Gupta ◽  
Priyanka Das ◽  
Siddhartha Kumar ◽  
Arindam Das ◽  
P. R. Sodani
Keyword(s):  
Child Health ◽  
Health Services ◽  
Health Survey ◽  
Maternal And Child Health ◽  
Household Surveys ◽  
Access Barriers ◽  
Health Service Provision ◽  
Healthcare Needs ◽  
Unmet Healthcare Needs ◽  
And Child Health

Objective: To map the range of access barrier indicators for which data can be derived from the three most common health related household surveys in India. Methods: A mapping review study was conducted to identify access dimensions and indicators of access barriers for maternal and child health (MCH) services included in three household surveys in India: National Family Health Survey (NFHS), District Level Household and Facility Survey (DLHS) and Annual Health Survey (AHS). Results: The Tanahashi framework for effective coverage of health services was used in this study, and 12 types of access barriers were identified, from which 23 indicators could be generated. These indicators measure self-reported access barriers for unmet healthcare needs through delayed care, as well as forgone care, and unsatisfactory experiences during health service provision. Multiple barriers could be identified, although there was marked heterogeneity in variables included and how barriers were measured. Conclusions: This study identified tracer indicators that could be used in India to monitor the population that experiences healthcare needs but fails to seek and obtain appropriate healthcare, and determine what the main barriers are. The surveys identified are well validated and allow the disaggregation of these indicators by equity stratifiers. Given the variability of the frequency and methodologies used in these surveys, comparability could be limited.

Spatiotemporal modelling for the annual egg production method of stock assessment using generalized additive models

1998 ◽  
Vol 55 (12) ◽  
pp. 2608-2621 ◽  
Author(s):  
N H Augustin ◽  
D L Borchers ◽  
E D Clarke ◽  
S T Buckland ◽  
M Walsh
Keyword(s):  
Environmental Variables ◽  
Egg Production ◽  
Survey Design ◽  
Stock Assessment ◽  
Generalized Additive Models ◽  
Production Method ◽  
Additive Models ◽  
Atlantic Mackerel ◽  
Egg Density ◽  
Survey Designs

Generalized additive models (GAMs) are used to model the spatiotemporal distribution of egg density as a function of locational and environmental variables. The main aim of using GAMs is to improve precision of egg abundance estimates needed for the annual egg production method. The application of GAMs requires a survey design with good coverage in space and time. If the only results available are from less optimal survey designs, they can be improved by using historical data for spawning boundaries. The method is applied to plankton egg survey data of Atlantic mackerel (Scomber scombrus) in 1995. The GAM-based method improves the precision of estimates substantially and is also useful in explaining complex space-time trends using environmental variables.

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