Strategies and Lessons Learned During Cleaning of Data From Research Panel Participants: Cross-sectional Web-Based Health Behavior Survey Study

Abstract

Background The use of web-based methods to collect population-based health behavior data has burgeoned over the past two decades. Researchers have used web-based platforms and research panels to study a myriad of topics. Data cleaning prior to statistical analysis of web-based survey data is an important step for data integrity. However, the data cleaning processes used by research teams are often not reported. Objective The objectives of this manuscript are to describe the use of a systematic approach to clean the data collected via a web-based platform from panelists and to share lessons learned with other research teams to promote high-quality data cleaning process improvements. Methods Data for this web-based survey study were collected from a research panel that is available for scientific and marketing research. Participants (N=4000) were panelists recruited either directly or through verified partners of the research panel, were aged 18 to 45 years, were living in the United States, had proficiency in the English language, and had access to the internet. Eligible participants completed a health behavior survey via Qualtrics. Informed by recommendations from the literature, our interdisciplinary research team developed and implemented a systematic and sequential plan to inform data cleaning processes. This included the following: (1) reviewing survey completion speed, (2) identifying consecutive responses, (3) identifying cases with contradictory responses, and (4) assessing the quality of open-ended responses. Implementation of these strategies is described in detail, and the Checklist for E-Survey Data Integrity is offered as a tool for other investigators. Results Data cleaning procedures resulted in the removal of 1278 out of 4000 (31.95%) response records, which failed one or more data quality checks. First, approximately one-sixth of records (n=648, 16.20%) were removed because respondents completed the survey unrealistically quickly (ie, <10 minutes). Next, 7.30% (n=292) of records were removed because they contained evidence of consecutive responses. A total of 4.68% (n=187) of records were subsequently removed due to instances of conflicting responses. Finally, a total of 3.78% (n=151) of records were removed due to poor-quality open-ended responses. Thus, after these data cleaning steps, the final sample contained 2722 responses, representing 68.05% of the original sample. Conclusions Examining data integrity and promoting transparency of data cleaning reporting is imperative for web-based survey research. Ensuring a high quality of data both prior to and following data collection is important. Our systematic approach helped eliminate records flagged as being of questionable quality. Data cleaning and management procedures should be reported more frequently, and systematic approaches should be adopted as standards of good practice in this type of research.

Factors related to human papillomavirus vaccine uptake and intentions among adults aged 18–26 and 27–45 years in the United States: A cross‐sectional study

“…After data cleaning, 27 the final analytic sample included 2722 individuals. Sociodemographic and health care variables by age cohort are displayed in Table 2.…”

“…We removed records with consecutive identical answers, contradictory responses, nonsensical open‐ended responses, and those completed in a unrealistic amount of time, resulting in 2722 final records. Methodological details for data cleaning and other analyses from this study are included elsewhere 27–29 . For the current analyses, participants were asked about prior receipt of HPV vaccination (1 item), intentions to receive the vaccine in the next year (1 item), HPV vaccine knowledge (11 items), 30,31 perceived risk (6 items for females and 4 items for males), 16 perceived barriers (3 items), 32 self‐efficacy (9 items), 33 attitudes about HPV vaccine (8 items), 34 descriptive norms (3 items), 35 health literacy (1 item), 36 previous health behaviors and other covariates (5 items), and sociodemographics (13 items).…”

“…This cross-sectional study enrolled 4000 English-speaking adults to complete a 30 [27][28][29] For the current analyses, participants were asked about prior receipt of HPV vaccination (1 item), intentions to receive the vaccine in the next year (1 item), HPV vaccine knowledge (11 items), 30,31 perceived risk (6 items for females and 4 items for males), 16 perceived barriers (3 items), 32 self-efficacy (9 items), 33 attitudes about HPV vaccine (8 items), 34 descriptive norms (3 items), 35 health literacy (1 item), 36 previous health behaviors and other covariates (5 items), and sociodemographics (13 items). Details about measures are found in Table 1.…”

“…We recruited 4000 participants (3485 broadly and 515 in Florida). Our team used a systematic strategy to review and clean all survey records 27 . We removed records with consecutive identical answers, contradictory responses, nonsensical open‐ended responses, and those completed in a unrealistic amount of time, resulting in 2722 final records.…”

Impact of the COVID-19 pandemic on human papillomavirus (HPV) vaccination among a national sample of United States adults ages 18–45: A cross-sectional study

“…Initial descriptive statistics and quality checks were performed, and participants with unreliable data were removed (e.g., straight line responses) ( Figure 1 ). ( Arevalo et al, 2022 , Kim et al, 2019 ) A multinomial logistic regression analysis was conducted to model the probability of two outcomes among adults who had not completed the HPV vaccine series and intended to receive the vaccine: 1) pandemic-related HPV vaccination disruption; and 2) uncertainty about pandemic-related HPV vaccination disruption. The reference category for the multinomial model was no pandemic-related disruption in HPV vaccination.…”