ArticleBMC medical research methodology2022
Using a consistency check during data collection to identify invalid responding in an online cannabis screening survey.
Article in BMC medical research methodology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Will patient data collection methods change after a pandemic? A systematic review of the strengths, challenges and opportunities of this new scenario.European journal of orthopaedic surgery & traumatology : orthopedie traumatologie · 2025Pooled it
- Practical Fraud Detection and Prevention in Incentivized Online Surveys: Secondary Analysis of the ADOPT Study.Journal of medical Internet research · 2026Article
- Enhancing nurses' clinical decision-making confidence through dual pathways of self-directed learning: A structural equation model.PloS one · 2026Article
- Article
- Data Verification and Respondent Validity for a Web-Based Sexual Health Survey: Tutorial.JMIR formative research · 2024Article
- Randomized controlled trial of a smartphone app designed to reduce unhealthy alcohol consumption.Internet interventions · 2024Article
- Doping Prevalence among U.S. Elite Athletes Subject to Drug Testing under the World Anti-Doping Code.Sports medicine - open · 2024Article
- Assessing and Improving Data Integrity in Web-Based Surveys: Comparison of Fraud Detection Systems in a COVID-19 Study.JMIR formative research · 2024Article
- Response Consistency of Crowdsourced Web-Based Surveys on Type 1 Diabetes.Journal of medical Internet research · 2023Article
- Online personalized feedback intervention to reduce risky cannabis use. Randomized controlled trial.Internet interventions · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInconsistent responding is a type of invalid responding, which occurs on self-report surveys and threatens the reliability and validity of study results. This secondary analysis evaluated the utility of identifying inconsistent responses as a real-time, direct method to improve quality during data collection for an Internet-based RCT.
methodsThe cannabis subscale of the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) was administered as part of eligibility screening for the RCT. Following the consent procedure, the cannabis subscale was repeated during the baseline interview. Responses were automatically compared and individuals with inconsistent responses were screened out.
resultsNearly half of those initially eligible for the RCT were subsequently screened out for data quality issues (n = 626, 45.3%). Between-group bivariate analysis found that those screened out (OUT) were significantly older (OUT = 39.5 years (SD = 13.9), IN = 35.7 years (SD = 12.9), p < .001), more had annual incomes less than $20,000CND (OUT = 58.3%, IN = 53.0%, p = .047), used cannabis less often in the past 30 days (OUT = 23.3 days (SD = 9.7), IN = 24.8 days (SD = 11.3), p < .006), and had lower total ASSIST scores at screener (OUT = 19.3 (SD = 8.0), IN = 23.8 (SD = 10.4), p < .001) and baseline (OUT = 17.5 (SD = 7.9), IN = 23.3 (SD = 10.3), p < .001) compared to participants who were screened in to the RCT.
conclusionInconsistent responding may occur at high rates in Internet research and direct methods to identify invalid responses are needed. Comparing responses for consistency can be programmed in Internet surveys to automatically screen participants during recruitment and reduce the need for post-hoc data cleaning.
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