Paper-Based Versus Web-Based Versions of Self-Administered Questionnaires, Including Food-Frequency Questionnaires: Prospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Web-based questionnaires allow collecting data quickly, with minimal costs from large sample groups and through Web-based self-administered forms. Until recently, there has been a lack of evidence from large-scale epidemiological studies and nutrition surveys that have evaluated the comparison between traditional and new technologies to measure dietary intake. OBJECTIVE: This study aimed to compare results from the general baseline questionnaire (Q_0) and the 10-year follow-up questionnaire (Q_10) in the Seguimiento Universidad de Navarra (SUN) prospective cohort, obtained from different subjects, some of whom used a paper-based version, and others used a Web-based version. Both baseline and 10-year assessments included a validated 136-item semiquantitative food-frequency questionnaire (FFQ), used to collect dietary intake. METHODS: The SUN project is a prospective cohort study (with continuous open recruitment and many participants who were recently recruited). All participants were university graduates. Participants who completed the validated FFQ at baseline (FFQ_0, n=22,564) were selected. The variables analyzed were classified into 6 groups of questions: (1) FFQ (136 items), (2) healthy eating attitudes (10 items), (3) alcohol consumption (3 items), (4) physical activity during leisure time (17 items), (5) other activities (24 items), and (6) personality traits (3 items). Multiple linear and logistic regression models were used to assess the adjusted differences between the mean number of missing values and the risk of having apparently incorrect values for FFQ items or mismatches and inconsistencies in dietary variables. RESULTS: Only 1.5% (339/22564) and 60.71% (6765/11144) participants reported their information using the Web-based version for Q_0 and Q_10, respectively, and 51.40 % (11598/22564) and 100.00% (11144/11144) of participants who completed the Q_0 and Q_10, respectively, had the option of choosing the Web-based version. Sociodemographic, lifestyle, health characteristics, food consumption, and energy and nutrient intakes were similar among participants, according to the type of questionnaire used in Q_10. Less than 0.5% of values were missing for items related to healthy eating attitudes, alcohol consumption, and personality traits in the Web-based questionnaires. The proportion of missing data in FFQ, leisure time physical activity, and other activities was higher in paper-based questionnaires than Web-based questionnaires. In Web-based questionnaires, a high degree of internal consistency was found when comparing answers that should not be contradictory, such as the frequency of fruit as dessert versus total fruit consumption and the frequency of fried food consumptions versus oil consumption. CONCLUSIONS: Incorporating a Web-based version for a baseline and 10-year questionnaire has not implicated a loss of data quality in this cohort of highly educated adults. Younger participants showed greater preference for Web-based questionnaires. Web-based questionnaires were filled out to a greater extent and with less missing items than paper-based questionnaires. Further research is needed to optimize data collection and response rate in Web-based questionnaires.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".