Dataset Information

Editors and researchers beware: calculating response rates in random digit dial health surveys.

ABSTRACT:

Objective

To demonstrate that different approaches to handling cases of unknown eligibility in random digit dial health surveys can contribute to significant differences in response rates.

Data source

Primary survey data of individuals with chronic disease.

Study design

We computed response rates using various approaches, each of which make different assumptions about the disposition of cases of unknown eligibility.

Data collection

Data were collected via telephone interviews as part of the Aligning Forces for Quality (AF4Q) consumer survey, a representative survey of adults with chronic illnesses in 17 communities and nationally.

Principal findings

We found that various approaches to estimating eligibility rates can lead to substantially different response rates.

Conclusions

Health services researchers must consider strategies to standardize response rate reporting, enter into a dialog related to why response rate reporting is important, and begin to utilize alternate methods for demonstrating that survey data are valid and reliable.

SUBMITTER: Martsolf GR

PROVIDER: S-EPMC3626345 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Editors and researchers beware: calculating response rates in random digit dial health surveys.

Martsolf Grant R GR Schofield Robert E RE Johnson David R DR Scanlon Dennis P DP

Health services research 20120921 2 Pt 1

<h4>Objective</h4>To demonstrate that different approaches to handling cases of unknown eligibility in random digit dial health surveys can contribute to significant differences in response rates.<h4>Data source</h4>Primary survey data of individuals with chronic disease.<h4>Study design</h4>We computed response rates using various approaches, each of which make different assumptions about the disposition of cases of unknown eligibility.<h4>Data collection</h4>Data were collected via telephone i ...[more]

PMID: 22998192

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Project description:Generating a nationally representative sample in low and middle income countries typically requires resource-intensive household level sampling with door-to-door data collection. High mobile phone penetration rates in developing countries provide new opportunities for alternative sampling and data collection methods, but there is limited information about response rates and sample biases in coverage and nonresponse using these methods. We utilized data from an interactive voice response, random-digit dial, national mobile phone survey in Ghana to calculate standardized response rates and assess representativeness of the obtained sample.The survey methodology was piloted in two rounds of data collection. The final survey included 18 demographic, media exposure, and health behavior questions. Call outcomes and response rates were calculated according to the American Association of Public Opinion Research guidelines. Sample characteristics, productivity, and costs per interview were calculated. Representativeness was assessed by comparing data to the Ghana Demographic and Health Survey and the National Population and Housing Census.The survey was fielded during a 27-day period in February-March 2017. There were 9,469 completed interviews and 3,547 partial interviews. Response, cooperation, refusal, and contact rates were 31%, 81%, 7%, and 39% respectively. Twenty-three calls were dialed to produce an eligible contact: nonresponse was substantial due to the automated calling system and dialing of many unassigned or non-working numbers. Younger, urban, better educated, and male respondents were overrepresented in the sample.The innovative mobile phone data collection methodology yielded a large sample in a relatively short period. Response rates were comparable to other surveys, although substantial coverage bias resulted from fewer women, rural, and older residents completing the mobile phone survey in comparison to household surveys. Random digit dialing of mobile phones offers promise for future data collection in Ghana and may be suitable for other developing countries.

Dataset Information

Editors and researchers beware: calculating response rates in random digit dial health surveys.

Objective

Data source

Study design

Data collection

Principal findings

Conclusions

Publications

Editors and researchers beware: calculating response rates in random digit dial health surveys.

Similar Datasets

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