Mode Equivalence of Health Indicators Between Data Collection Modes and Mixed-Mode Survey Designs in Population-Based Health Interview Surveys for Children and Adolescents: Methodological Study

Mauz, Elvira; Hoffmann, Robert; Houben, Robin; Krause, Laura; Kamtsiuris, Panagiotis; Gößwald, Antje

doi:10.2196/jmir.7802

Cited by 18 publications

(11 citation statements)

References 64 publications

(80 reference statements)

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“…In order to benefit from this cost advantage to some extent without increasing the risk of nonresponse bias, the web mode could be integrated in a mixed-mode design. This approach, in which some respondents complete the questionnaire on the web and other respondents (ie, those unwilling/incapable to participate online) use another mode, is already being tested and used in multiple European HISs [ 44 - 46 ]. A specific mixed-mode methodology, push-to-web, could, for example, be considered: people would first be invited by postal mail to participate online and they would then be contacted by an interviewer only in case of nonparticipation [ 47 ].…”

Section: Discussionmentioning

confidence: 99%

Unit Response and Costs in Web Versus Face-To-Face Data Collection: Comparison of Two Cross-sectional Health Surveys

Braekman¹,

Demarest²,

Charafeddine³

et al. 2022

J Med Internet Res

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Background Potential is seen in web data collection for population health surveys due to its combined cost-effectiveness, implementation ease, and increased internet penetration. Nonetheless, web modes may lead to lower and more selective unit response than traditional modes, and this may increase bias in the measured indicators. Objective This research assesses the unit response and costs of a web study versus face-to-face (F2F) study. Methods Alongside the Belgian Health Interview Survey by F2F edition 2018 (BHISF2F; net sample used: 3316), a web survey (Belgian Health Interview Survey by Web [BHISWEB]; net sample used: 1010) was organized. Sociodemographic data on invited individuals was obtained from the national register and census linkages. Unit response rates considering the different sampling probabilities of both surveys were calculated. Logistic regression analyses examined the association between mode system and sociodemographic characteristics for unit nonresponse. The costs per completed web questionnaire were compared with the costs for a completed F2F questionnaire. Results The unit response rate is lower in BHISWEB (18.0%) versus BHISF2F (43.1%). A lower response rate was observed for the web survey among all sociodemographic groups, but the difference was higher among people aged 65 years and older (15.4% vs 45.1%), lower educated people (10.9% vs 38.0%), people with a non-Belgian European nationality (11.4% vs 40.7%), people with a non-European nationality (7.2% vs 38.0%), people living alone (12.6% vs 40.5%), and people living in the Brussels-Capital (12.2% vs 41.8%) region. The sociodemographic characteristics associated with nonresponse are not the same in the 2 studies. Having another European (OR 1.60, 95% CI 1.20-2.13) or non-European nationality (OR 2.57, 95% CI 1.79-3.70) compared to a Belgian nationality and living in the Brussels-Capital (OR 1.72, 95% CI 1.41-2.10) or Walloon (OR 1.47, 95% CI 1.15-1.87) regions compared to the Flemish region are associated with a higher nonresponse only in the BHISWEB study. In BHISF2F, younger people (OR 1.31, 95% CI 1.11-1.54) are more likely to be nonrespondents than older people, and this was not the case in BHISWEB. In both studies, lower educated people have a higher probability of being nonrespondent, but this effect is more pronounced in BHISWEB (low vs high education level: Web, OR 2.71, 95% CI 2.21-3.39 and F2F OR 1.70, 95% CI 1.48-1.95). The BHISWEB study had a considerable advantage; the cost per completed questionnaire was almost 3 times lower (€41 [US $48]) compared with F2F data collection (€111 [US $131]). Conclusions The F2F unit response rate was generally higher, yet for certain groups the difference between web and F2F was more limited. Web data collection has a considerable cost advantage. It is therefore worth experimenting with adaptive mixed-mode designs to optimize financial resources without increasing selection bias (eg, only inviting sociodemographic groups who are keener to participate online for web surveys while continuing to focus on increasing F2F response rates for other groups).

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Section: Discussionmentioning

confidence: 99%

Unit Response and Costs in Web Versus Face-To-Face Data Collection: Comparison of Two Cross-sectional Health Surveys

Braekman¹,

Demarest²,

Charafeddine³

et al. 2022

J Med Internet Res

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show abstract

“…Surveys are considered mode equivalent when participants give the same responses to the same questions administered by different modes . Previous reports showed that such differences were minimal between online and paper surveys, even when respondents had to report sensitive behaviours …”

Section: Advantagesmentioning

confidence: 99%

Perspectives of online surveys in dermatology

Arafa

Anzengruber

Mostafa

et al. 2018

Acad Dermatol Venereol

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The striking rise in the Internet utilization worldwide has led to major changes in the methods of data collection and processing. Online surveying has been used to assess different health services, explore patients’ perceptions and measure interventions. The discipline of dermatology is one of the fields that gained benefits from surveying patients and dermatologists online; however, some disadvantages such as the low response rate and participation bias were suggested. This review summarizes the applications of online surveying in dermatology and discusses the methods of enhancing response to online surveys. It also offers a guide for dermatologists to formulate their online surveys and avoid the possibility of bias. The role of social network in data collection and the concerns about anonymity and data security have been discussed.

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“…Active data collection processes have been shown to improve prevention programs and increase evaluative capacity to address multiple public health problems [ 14 – 17 ]. A robust data collection system for OEI was determined to have the following characteristics: 1) multimodality of data collection [ 17 – 20 ], 2) a standardized data model [ 21 – 23 ], and 3) systematic educational outreach efforts to train those reporting data [ 24 – 26 ]. These characteristics are supported by literature recommending tailored data collection systems created with evaluation in mind, followed by capacity building and training for these data collection systems [ 15 – 17 ].…”

Section: Introductionmentioning

confidence: 99%

“…The final data are electronic, and paper forms have additional data entry and submission steps; however, many of the community organizations do not have the technology to collect data online, and it may be easier to collect data on paper during in-person visits with participants. Prior research indicates improved data quality when multiple data collection modes are available [ 17 – 20 ].…”

Section: Introductionmentioning

confidence: 99%

Co-establishing an infrastructure for routine data collection to address disparities in infant mortality: planning and implementation

Fareed

Swoboda

Lawrence

et al. 2022

BMC Health Serv Res

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Background Efforts to address infant mortality disparities in Ohio have historically been adversely affected by the lack of consistent data collection and infrastructure across the community-based organizations performing front-line work with expectant mothers, and there is no established template for implementing such systems in the context of diverse technological capacities and varying data collection magnitude among participating organizations. Methods Taking into account both the needs and limitations of participating community-based organizations, we created a data collection infrastructure that was refined by feedback from sponsors and the organizations to serve as both a solution to their existing needs and a template for future efforts in other settings. Results By standardizing the collected data elements across participating organizations, integration on a scale large enough to detect changes in a rare outcome such as infant mortality was made possible. Datasets generated through the use of the established infrastructure were robust enough to be matched with other records, such as Medicaid and birth records, to allow more extensive analysis. Conclusion While a consistent data collection infrastructure across multiple organizations does require buy-in at the organizational level, especially among participants with little to no existing data collection experience, an approach that relies on an understanding of existing barriers, iterative development, and feedback from sponsors and participants can lead to better coordination and sharing of information when addressing health concerns that individual organizations may struggle to quantify alone.

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Mode Equivalence of Health Indicators Between Data Collection Modes and Mixed-Mode Survey Designs in Population-Based Health Interview Surveys for Children and Adolescents: Methodological Study

Cited by 18 publications

References 64 publications

Unit Response and Costs in Web Versus Face-To-Face Data Collection: Comparison of Two Cross-sectional Health Surveys

Unit Response and Costs in Web Versus Face-To-Face Data Collection: Comparison of Two Cross-sectional Health Surveys

Perspectives of online surveys in dermatology

Co-establishing an infrastructure for routine data collection to address disparities in infant mortality: planning and implementation

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