Validity and reliability of a brief self-reported questionnaire assessing fruit and vegetable consumption among pregnant women
Bibliographic record
Abstract
BACKGROUND: Short instruments measuring frequency of specific foods, such as fruit and vegetable (FV), are increasingly used in interventions. The objective of the study was to verify the validity and test-retest reliability of such an instrument among pregnant women. METHODS: Pregnant women from the region of Quebec City, Quebec, Canada, were recruited through e-mails sent to female students and employees of the local university from October 2014 to April 2015. To assess the validity of the fruit and vegetable questionnaire (FVQ) developed by Godin et al. (Can J Public Health 99: 494-498, 2008), pregnant women were asked in a first mailing to complete the FVQ assessing FV intake over the past 7 days and a 3-day estimated food record. A subsample (n = 33) also gave a fasting blood sample and completed a validated semi-quantitative FFQ administered by a trained registered dietitian during a visit at the research center. FV intakes for all instruments were calculated in terms of servings of FV based on Canada's Food Guide definition of a serving of fruit or vegetable. In order to assess its test-retest reliability, respondents were asked to complete the FVQ 14 days later in a second mailing. RESULTS: Forty-eight pregnant women from all three trimesters completed the questionnaires in the first mailing. FV intake assessed using the FVQ was correlated to FV consumption measured using the food record (r = 0.34, p = 0.0180) and the FFQ (r = 0.61, p = 0.0002). Results were similar when controlling for energy intake and the experience of nausea in the past month. Only β-cryptoxanthin was significantly correlated to FV intake assessed by the FFQ when adjusted for the presence of nausea (r = 0.35, p = 0.0471). Data on the test-retest reliability was available for 44 women and the intra-class coefficient for the FVQ was 0.72 at a mean 28-day interval. CONCLUSIONS: The FVQ has acceptable validity and test-retest reliability values, but seems to underestimate FV servings in pregnant women. It represents an interesting alternative for researchers or clinicians interested in estimating quickly FV intake among pregnant women, such as in large trials or during prenatal visits. The FVQ should however be coupled with other self-reported measures, such as a food record, for assessing precise individual FV intake.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".