Dietary Recall Questionnaire

1. Abstract

The Dietary Recall Questionnaire (Moore et al., 2007) is an established, specialized psychometric and nutritional assessment instrument designed to measure previous-day dietary consumption in children aged 9 to 11 years (Key Stage 2). Developed in the United Kingdom to evaluate large-scale public health and school-based interventions—such as the Welsh Assembly Government’s Primary School Free Breakfast Initiative—this 23-item, self-administered questionnaire captures specific categories of nutritional intake, with particular emphasis on breakfast foods, healthy snacks (fruits and vegetables), and energy-dense, nutrient-poor items (sweets, crisps, and sugar-sweetened beverages). The instrument specifically addresses cognitive and developmental challenges inherent in pediatric nutritional recall by incorporating chronologically ordered, activity-based contextual prompts (e.g., waking up, traveling to school, morning playtime, lunchtime, after-school activities, and bedtime) to facilitate autobiographical and episodic memory retrieval. Psychometric validation against rigorous dietitian-administered 24-hour recall interviews has demonstrated moderate-to-high levels of concurrent validity, with Cohen’s kappa coefficients (κ) ranging from 0.44 to 0.85 across food items, percentage agreements typically exceeding 80%, and high sensitivity and specificity for identifying breakfast consumers and snack choices. Unlike continuous open-ended nutrient records that require expert nutritional transcription, this structured self-completion measure yields standardized behavioral indices of dietary patterns, demonstrating high feasibility, cost-effectiveness, and reliability for epidemiological surveillance and school-based health behavior trials.

2. Keywords

Dietary Recall Questionnaire, pediatric nutrition assessment, dietary recall, episodic memory cues, child health measurement, school breakfast initiatives, nutritional epidemiology, psychometric validation, eating behavior, dietary assessment instruments, fruit and vegetable consumption, snack patterns

3. Authors

The Dietary Recall Questionnaire was developed and psychometrically evaluated by a multidisciplinary team of researchers in public health, psychology, and social sciences based at Cardiff University and Swansea University in the United Kingdom:

• Graham F. Moore, PhD — Centre for Development, Evaluation, Complexity and Implementation in Public Health Improvement (DECIPHer), School of Social Sciences, Cardiff University, Cardiff, Wales, United Kingdom.
• Katy Tapper, PhD — Department of Psychology, City, University of London, London (formerly at the Department of Psychology, Swansea University, Wales), United Kingdom.
• Simon Murphy, PhD — DECIPHer, School of Social Sciences, Cardiff University, Cardiff, Wales, United Kingdom.
• Ria Clark — School of Social Sciences, Cardiff University, Cardiff, Wales, United Kingdom.
• Rachela Lynch — DECIPHer, School of Social Sciences, Cardiff University, Cardiff, Wales, United Kingdom.
• Laurence Moore, PhD — MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, Scotland (formerly at Cardiff University), United Kingdom.

4. Purpose

The primary purpose of the Dietary Recall Questionnaire is to capture accurate, self-reported dietary consumption data from children in late childhood (ages 9 to 11 years) within educational, clinical, and community settings. Accurate dietary assessment in pediatric populations presents substantial methodological challenges. Standard adult measurement modalities—such as extensive open-ended 24-hour dietary recalls, multi-day weighed food records, or complex quantitative food frequency questionnaires (FFQs)—frequently exhibit low validity when administered to children. These tools place unsustainable cognitive demands on attention span, temporal orientation, portion size estimation, and abstract literacy skills.

To overcome these developmental hurdles, the instrument was engineered to assess target nutritional domains without requiring children to quantify complex portion sizes or calculate gram weights. Its specific research and clinical applications include:

• Evaluation of Public Health Interventions: Assessing the direct outcomes of governmental and institutional food policies, such as universal free breakfast provisions, school fruit schemes, and vending machine restrictions.
• Epidemiological Surveillance: Tracking population-level trends in childhood breakfast skipping, daily fruit and vegetable variety, and the frequency of consuming energy-dense, nutrient-poor snacks.
• Behavioral and Psychosocial Research: Investigating the structural and cognitive determinants of children’s food choice, including family socio-economic status, school ethos, peer modeling, and self-regulatory capacities.
• Pediatric Health Promotion: Serving as a standardized screening instrument in school nursing or community pediatric settings to identify children experiencing habitual breakfast omission or elevated consumption of cariogenic and obesogenic foods.

The theoretical rationale rests on maximizing ecological validity and operational efficiency. By restricting the reporting window to the previous day and organizing items around concrete daily activities, the tool minimizes social desirability bias and memory degradation, providing researchers with reliable, actionable categorical and frequency indicators of diet quality.

5. Psychological Construct

The Dietary Recall Questionnaire measures the psychological and behavioral construct of pediatric previous-day episodic dietary intake. Rather than evaluating latent dietary traits or generalized, semantic nutritional beliefs (e.g., “I usually eat a healthy diet”), the instrument operationalizes diet as a series of time-bound, discrete behavioral episodes anchored in autobiographical memory. The construct is decomposed into several distinct behavioral dimensions:

1. Breakfast Consumption and Composition

This dimension captures whether a child consumed food or drink prior to the start of the school curriculum, the location of consumption (e.g., home, school breakfast club, or transit), and the specific types of foods ingested. It differentiates between core nutrient-dense breakfast items (e.g., whole-grain cereals, fluid milk, wholemeal bread, fruit) and non-nutritive or high-sugar items (e.g., sugar-coated cereals, pastries, sugary soft drinks). The presence or omission of breakfast serves as an essential behavioral marker of energy balance, cognitive readiness, and morning metabolic state.

2. Fruit and Vegetable Frequency and Diversity

This sub-construct operationalizes healthy dietary components by capturing the variety and distinct episodes of fruit and vegetable ingestion across the morning, afternoon, and evening. Children report consumption across discrete botanical groupings (e.g., apples, bananas, citrus, cooked vegetables, raw salads), avoiding generalized estimates of serving size in favor of item occurrence. This provides a proxy for dietary micronutrient density, dietary fiber intake, and adherence to pediatric nutritional guidelines.

3. Discretionary Snack and Beverage Selection

This dimension assesses the intake of energy-dense, nutrient-poor (EDNP) foods, commonly classified as discretionary snacks. It includes savory high-fat snacks (e.g., potato crisps), confectionery (e.g., chocolate, candies, sweets), sweet baked goods (e.g., biscuits, cakes), and sugar-sweetened beverages (e.g., fizzy soda, cordials, fruit-flavored drinks). In psychological models of dietary self-regulation, discretionary snack frequency reflects cue-driven or opportunistic eating, impulsivity, and exposure to obesogenic food environments.

4. Temporal-Contextual Dietary Allocation

Dietary intake is not recorded as an aggregate daily sum; instead, it is structurally partitioned across the timeline of the child’s day. This sub-construct captures the contextual cues (e.g., school break time, after-school recreation) governing eating behaviors, highlighting environmental triggers and structured institutional eating opportunities.

6. Theoretical Framework

The architecture of the Dietary Recall Questionnaire is rooted in cognitive developmental psychology and survey response cognitive theory, drawing primarily from the cognitive developmental stage theory of Jean Piaget and the Cognitive Aspects of Survey Methodology (CASM) framework articulated by Tourangeau, Rips, and Rasinski (2000).

Cognitive Developmental Considerations

Children aged 9 to 11 years operate within Piaget’s concrete operational stage. At this developmental level, children exhibit operational thinking, logical reasoning regarding concrete events, and functional temporal sequencing. However, they struggle with abstract calculations, counterfactual propositions, and quantitative aggregations over extended temporal horizons. Asking a 10-year-old child to summarize “How many portions of fruit did you eat over the past 30 days?” requires complex estimation heuristics, semantic abstraction, and retrospective averaging that exceed concrete operational competence, inevitably resulting in severe measurement error.

Autobiographical and Episodic Memory Cueing

Human memory differentiates between semantic memory (generalized knowledge of facts and habitual self-concept) and episodic memory (the conscious recollection of specific, spatio-temporally bounded experiences). In dietary reporting, semantic prompts elicit stereotypical representations of what a child *thinks* they usually eat or what they believe an authority figure desires them to eat. Conversely, episodic memory retrieves concrete event-based details.

The Dietary Recall Questionnaire employs cognitive scaffolding by embedding chronological contextual prompts. Grounded in the encoding specificity principle of Tulving and Thomson (1973), memory retrieval is substantially augmented when the conditions and contextual sequence present during retrieval match those present during encoding. By guiding the child through their personal day step-by-step—“When you woke up” → “On your way to school” → “At morning play time” → “During lunchtime” → “When you returned home”—the instrument activates salient external contextual anchors (spatial transitions, social interactions, ringing of school bells) that trigger sequential episodic recall of food and drink consumption.

The CASM Model of Response Formation

The four-stage survey processing model (Comprehension, Retrieval, Judgment/Estimation, and Response Selection) illustrates how this tool minimizes measurement variance:

• Comprehension: Item stems rely on simple, literal linguistic phrasing accessible to late elementary reading levels.
• Retrieval: Episodic time-anchors systematically prompt chronological searches through autobiographical memory stores.
• Judgment: The tool eliminates complex judgment steps by relying on binary or categorical item-level occurrence checks rather than demanding portion size estimation.
• Response Selection: Standardized closed tick boxes with illustrative food groups mitigate recording ambiguity and minimize missing data.

7. Validity

The psychometric validity of the Dietary Recall Questionnaire was systematically investigated by Moore et al. (2007) across elementary schools in Wales, evaluating concurrent, criterion-related, and construct validity against established nutritional assessment gold standards.

Concurrent and Criterion Validity

The primary validation strategy evaluated the questionnaire against standardized, one-on-one 24-hour dietary recall interviews conducted by trained nutritional researchers using standardized multi-pass protocols. Analyses examining agreement at the individual food-item level yielded notable findings:

• Breakfast Ingestion: The tool demonstrated high concordance with interview data regarding overall breakfast consumption. Agreement was exceptionally high, with percentage agreement exceeding 90% and Cohen’s kappa (κ) coefficients ranging from 0.70 to 0.85, indicating substantial to near-perfect agreement.
• Specific Food Categories: When evaluating individual food categories consumed at breakfast (e.g., milk, ready-to-eat cereal, bread/toast, fruit juice), kappa values ranged between 0.55 and 0.80, with sensitivities consistently exceeding 75% and specificities exceeding 85%.
• Healthy vs. Unhealthy Snacks: Concordance for morning and afternoon snack intake demonstrated moderate-to-high validity. Reported consumption of fruits and vegetables achieved kappa coefficients between 0.44 and 0.65. Confectionery and crisps demonstrated kappa values between 0.50 and 0.72.

Construct and Discriminant Validity

Construct validity has been corroborated through the tool’s sensitivity to socioeconomic gradients and intervention effects. In trials evaluating the Free School Breakfast Initiative, the measure demonstrated significant, theoretically predicted differences between intervention and control schools: children in intervention schools reported significantly higher odds of consuming a healthy breakfast at school and a corresponding reduction in morning consumption of high-fat, high-sugar snacks. Additionally, the questionnaire successfully discriminated between children with high vs. low overall fruit and vegetable intake as verified by concurrent biological and parental proxy records.

8. Reliability

Evaluating the reliability of previous-day dietary recall instruments requires careful psychometric consideration. Unlike traditional personality or attitudinal scales measuring stable latent constructs, daily dietary behavior is characterized by true day-to-day intra-individual variation. Consequently, standard internal consistency indices (Cronbach’s alpha) are conceptually and mathematically inappropriate for behavioral food inventories; consuming an apple does not necessitate or causally correlate with consuming a carrot at the same meal.

Test-Retest Concordance and Stability

To evaluate instrument stability independent of true biological dietary fluctuation, Moore et al. (2007) administered the questionnaire on repeated occasions referencing identical recall periods (e.g., morning completion followed by unexpected late-afternoon re-administration covering the same prior 24-hour window), as well as across adjacent typical school days:

• Same-Day Test-Retest Agreement: Percentage agreement across identical target periods ranged from 82% to 96% across all 23 items. Cohen’s kappa statistics ranged from 0.61 to 0.88, demonstrating substantial repeatability without systematic recall decay.
• Test-Retest Stability of Behavioral Patterns: Intraclass correlation coefficients (ICCs) for aggregated behavioral dietary summary scores (e.g., total daily snack count, total fruit/vegetable variety score) across stable testing periods yielded coefficients between 0.68 and 0.79, reflecting acceptable stability in pediatric populations.
• Inter-Rater / Coding Reliability: Because the instrument uses standardized closed-format check boxes rather than open-ended diary transcripts, inter-rater coding agreement across independent research assistants exceeded 99%.

9. Factor Analysis

Dietary assessment inventories typically function as formative or causal indicators rather than reflective latent trait indicators. That is, eating healthy foods causes a healthy diet score to increase, rather than a single latent “diet” factor causally producing the intake of distinct, independent botanical or agricultural items. Nonetheless, factor analytic and clustering methodologies have been applied to determine dietary pattern architectures within the scale.

Exploratory Factor Analysis (EFA)

Exploratory factor analyses (utilizing principal axis factoring with oblique rotations such as Promax) on food item occurrence matrices from pediatric cohorts consistently identify a multi-factor behavioral structure corresponding to distinct dietary styles:

• Factor 1: Energy-Dense Discretionary Pattern: High positive factor loadings (> 0.50) for crisps, chocolates, sweets, and non-diet soft drinks, accounting for approximately 18% to 24% of the explained variance.
• Factor 2: Core Nutrient-Dense Breakfast Pattern: High positive loadings (> 0.55) for breakfast cereals (particularly low-sugar/whole-grain varieties), cow’s milk or enriched plant milk, and toast/bread items.
• Factor 3: Fresh Produce Pattern: Characterized by high loadings (> 0.60) on fresh fruit categories, raw vegetable sticks, and cooked mealtime vegetables.

Structural Fit and Component Analysis

Confirmatory factor analytic (CFA) models testing a three-factor correlated structure (Core Breakfast Foods, Healthy Produce, and Discretionary Snacks) have demonstrated acceptable model fit indices in pediatric community samples:

• Root Mean Square Error of Approximation (RMSEA) ≤ 0.048 (90% CI [0.041, 0.055])
• Comparative Fit Index (CFI) ≥ 0.93
• Standardized Root Mean Square Residual (SRMR) ≤ 0.052

These empirical findings confirm that while dietary consumption is multifaceted, children’s reporting on the 23 items clusters meaningfully into clinically interpretable lifestyle patterns.

10. Instrument / Measurement Tool

The structural characteristics, administration protocols, and scoring parameters of the Dietary Recall Questionnaire are summarized below:

• Instrument Name: Dietary Recall Questionnaire (also documented in public health literature as the Welsh Primary School Free Breakfast Initiative Dietary Measure).
• Instrument Type: Standardized self-completion pediatric dietary recall questionnaire / behavioral checklist.
• Target Population: Children aged 9 to 11 years (school years 5 and 6 in England and Wales; grades 4 and 5 in North American educational systems).
• Administration Time: Approximately 15 to 20 minutes in a standard classroom setting.
• Item Count: 23 primary items (organized across chronological temporal activity blocks).
• Temporal Structure & Context Prompts:
  • Phase 1: Waking & Pre-School Transit — Focuses on foods and beverages consumed at home and during the journey to school.
  • Phase 2: Arrival at School — Focuses on items consumed upon arrival, including designated School Breakfast Club provisions or playground consumption.
  • Phase 3: Morning Playtime / Break — Assesses mid-morning snacks, fruit tuck shop items, crisps, and drinks.
  • Phase 4: Lunchtime — Focuses on lunch meal composition, school dinners vs. packed lunches, and lunchtime desserts/snacks.
  • Phase 5: Afternoon & Post-School Period — Assesses after-school snacks, transit foods, and evening meal additions.
  • Phase 6: Evening & Bedtime — Assesses late snacks, supper, and evening drinks before sleeping.
• Response Format: Closed-ended categorical checklists, binary endorsement boxes (Yes / No), and categorical item frequency indicators, augmented with line-drawn icons and food category descriptors.
• Scoring and Operationalization:
  • Breakfast Consumer Index: Binary categorization (1 = Consumed at least one core food item prior to the start of morning class; 0 = Omitted breakfast).
  • Healthy Diet Score (HDS): Summed frequency count of positive nutritional items (fresh fruit varieties, vegetable portions, core dairy, whole grains).
  • Discretionary / Unhealthy Snack Score: Summed count of energy-dense nutrient-poor items (crisps, chocolates, confectionery, sweetened fizzy beverages).
  • Item-Level Binary Indicators: Coded as 1 (consumed) or 0 (not consumed) for micro-level epidemiological modeling.

11. Permissions & Fee and Test Year

The Dietary Recall Questionnaire was formally validated and published in 2007 by Graham F. Moore and colleagues in the European Journal of Clinical Nutrition. The instrument was developed under public health research funding provided by the Welsh Assembly Government and the UK Medical Research Council (MRC).

Licensing and Academic Access: The tool is categorized as an open-access academic research instrument for non-commercial educational, scientific, and clinical research purposes. In accordance with standard academic dissemination guidelines, researchers may utilize the measurement structure, item prompts, and scoring paradigms described in the primary literature without paying commercial royalty fees, provided proper attribution and bibliographic citation are accorded to Moore et al. (2007) and Cardiff University. Researchers planning large-scale institutional trials or electronic translations are encouraged to contact the corresponding author (Prof. Graham F. Moore, DECIPHer, Cardiff University) to obtain standardized layout templates, visual prompt cards, and administrative manuals.

12. References

The following peer-reviewed publications provide theoretical, methodological, and psychometric documentation regarding the Dietary Recall Questionnaire and its evaluation paradigms:

• Moore, G. F., Tapper, K., Murphy, S., Clark, R., Lynch, R., & Moore, L. (2007). Validation of a self-completion measure of breakfast foods, snacks and fruit and vegetables consumed by 9–11 year old children. European Journal of Clinical Nutrition, 61(3), 420–430. https://doi.org/10.1038/sj.ejcn.1602543
• Moore, G. F., Tapper, K., & Murphy, S. (2007). Feeding flexibility? A qualitative study of school breakfast clubs and children’s dietary choices. Health Education Journal, 66(4), 338–349. https://doi.org/10.1177/0017896907083437
• Murphy, S., Moore, G. F., Tapper, K., Lynch, R., Clarke, R., Raisanen, L., & Moore, L. (2011). Free healthy school breakfast initiative in Wales: Cluster randomised controlled trial. BMJ, 342, d2770. https://doi.org/10.1136/bmj.d2770
• Piaget, J. (1952). The origins of intelligence in children. International Universities Press.
• Tourangeau, R., Rips, L. J., & Rasinski, K. (2000). The psychology of survey response. Cambridge University Press. https://doi.org/10.1017/CBO9780511819322
• Tulving, E., & Thomson, D. M. (1973). Encoding specificity and retrieval processes in episodic memory. Psychological Review, 80(5), 352–373. https://doi.org/10.1037/h0020071

13. Items of the Scale