Decision-making and data quality: Applying fraud response strategies to clean survey panel data
Survey panels provide extension professionals with a valuable tool for collecting data on a wide range of topics without overburdening their program participants. Paid data panels are particularly useful for gathering unbiased feedback about Extension programs. However, some survey participants in t...
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| Format: | Article |
| Language: | English |
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Advancements in Agricultural Development Inc
2025-03-01
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| Series: | Advancements in Agricultural Development |
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| Online Access: | https://agdevresearch.org/index.php/aad/article/view/573 |
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| author | Amy Harder Lendel K. Narine Stacey Stearns |
| author_facet | Amy Harder Lendel K. Narine Stacey Stearns |
| author_sort | Amy Harder |
| collection | DOAJ |
| description | Survey panels provide extension professionals with a valuable tool for collecting data on a wide range of topics without overburdening their program participants. Paid data panels are particularly useful for gathering unbiased feedback about Extension programs. However, some survey participants in these panels engage in satisficing or straightlining behaviors to earn rewards with minimal effort, which compromises data quality. This study explored whether survey panelists’ perceptions of online survey items varied based on response quality. It compared normal and low-quality responses across broad issue areas and investigated whether age, education, income, or gender identity influenced these differences. Analysis of 94 respondents in each group revealed no significant data quality differences based on age, education, income, or gender identity. There was a statistically significant difference in data quality when using an open-ended question requiring greater cognitive effort. We recommend adopting more conservative data cleaning strategies. While this approach has limitations, its benefits are particularly valuable when the data informs an organization’s strategic priorities.
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| format | Article |
| id | doaj-art-494422fe514b42d4818c95fa5ed95a97 |
| institution | DOAJ |
| issn | 2690-5078 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Advancements in Agricultural Development Inc |
| record_format | Article |
| series | Advancements in Agricultural Development |
| spelling | doaj-art-494422fe514b42d4818c95fa5ed95a972025-08-20T02:59:57ZengAdvancements in Agricultural Development IncAdvancements in Agricultural Development2690-50782025-03-016110.37433/aad.v6i1.573Decision-making and data quality: Applying fraud response strategies to clean survey panel dataAmy Harder0Lendel K. Narine1Stacey Stearns2University of Connecticut, USAUtah State University, USAUniversity of Connecticut, USASurvey panels provide extension professionals with a valuable tool for collecting data on a wide range of topics without overburdening their program participants. Paid data panels are particularly useful for gathering unbiased feedback about Extension programs. However, some survey participants in these panels engage in satisficing or straightlining behaviors to earn rewards with minimal effort, which compromises data quality. This study explored whether survey panelists’ perceptions of online survey items varied based on response quality. It compared normal and low-quality responses across broad issue areas and investigated whether age, education, income, or gender identity influenced these differences. Analysis of 94 respondents in each group revealed no significant data quality differences based on age, education, income, or gender identity. There was a statistically significant difference in data quality when using an open-ended question requiring greater cognitive effort. We recommend adopting more conservative data cleaning strategies. While this approach has limitations, its benefits are particularly valuable when the data informs an organization’s strategic priorities. https://agdevresearch.org/index.php/aad/article/view/573SDG 4: Quality Educationonline surveyssurvey straightlininglow-quality indicatorsextension professionals |
| spellingShingle | Amy Harder Lendel K. Narine Stacey Stearns Decision-making and data quality: Applying fraud response strategies to clean survey panel data Advancements in Agricultural Development SDG 4: Quality Education online surveys survey straightlining low-quality indicators extension professionals |
| title | Decision-making and data quality: Applying fraud response strategies to clean survey panel data |
| title_full | Decision-making and data quality: Applying fraud response strategies to clean survey panel data |
| title_fullStr | Decision-making and data quality: Applying fraud response strategies to clean survey panel data |
| title_full_unstemmed | Decision-making and data quality: Applying fraud response strategies to clean survey panel data |
| title_short | Decision-making and data quality: Applying fraud response strategies to clean survey panel data |
| title_sort | decision making and data quality applying fraud response strategies to clean survey panel data |
| topic | SDG 4: Quality Education online surveys survey straightlining low-quality indicators extension professionals |
| url | https://agdevresearch.org/index.php/aad/article/view/573 |
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