Assessment of Foods and Nutrition Competencies in Adolescents Questionnaire (AFANCA)

Abstract

The Assessment of Foods and Nutrition Competencies in Adolescents Questionnaire (AFANCA) is a psychometrically validated, multidimensional self-report instrument developed by Wang, Drabek, Li, Locke, and Gardner (2023). Designed to systematically evaluate critical dietary behaviors, culinary skills, and nutritional literacy among youth in grades 6 through 12 (ages 11–19 years), the AFANCA measures food intake regulation in accordance with established nutritional guidelines, dietary schedules, meal planning, safe food preparation, and hygienic food storage. Grounded conceptually in the theory of change and experiential implementation frameworks of the 4-H Foods and Nutrition Project, the instrument operationalizes youth competency across six distinct core domains: Nutrition Knowledge and Label Reading, Food Preparation, Food Safety and Storage, Recipe Modification, and Fruit and Vegetable Consumption / Healthy Dietary Intake.

The final refined instrument consists of 24 items evaluated on a standardized 5-point Likert scale (ranging from 1 = Strongly Disagree to 5 = Strongly Agree, or domain-congruent behavioral frequency and proportion anchors). In extensive confirmatory psychometric evaluations among Texas youth, the 24-item six-factor model demonstrated exceptional construct validity and robust goodness-of-fit indices: χ²(237) = 401.48, p < .001; Root Mean Square Error of Approximation (RMSEA) = 0.049 (90% CI [0.041, 0.058]); Comparative Fit Index (CFI) = 0.942; Tucker-Lewis Index (TLI) = 0.933; and Standardized Root Mean Square Residual (SRMR) = 0.045. Standardized factor loadings across all retained items ranged from 0.57 to 0.89. Reliability analyses using McDonald’s composite omega (ω) demonstrated acceptable to outstanding internal consistency across the six subscales, spanning from 0.74 (Recipe Modification) to 0.91 (Food Preparation). Multigroup invariance testing confirmed configural, metric, and scalar invariance across program involvement status, gender, and adolescent age brackets, establishing the AFANCA as an authoritative assessment tool for public health researchers, pediatric clinicians, and extension educators.

Keywords

Adolescent Nutrition, Food Competency, Nutrition Literacy, Culinary Skills, Food Safety, Nutrition Facts Label, Recipe Modification, Dietary Behaviors, Health Promotion, Social Cognitive Theory, Confirmatory Factor Analysis, Psychometrics, Measurement Invariance, 4-H Youth Development

Authors

The AFANCA questionnaire was conceptualized, operationalized, and psychometrically validated by an interdisciplinary team of researchers and extension specialists at Texas A&M University:

• Jun Wang, Ph.D. — Department of Agricultural Leadership, Education, and Communications, Texas A&M University, College Station, TX, USA. ORCID: 0000-0003-4485-7201. Email: [email protected]. (Corresponding Author).
• Allison G. Drabek, M.S. — Texas A&M AgriLife Extension Service, Texas A&M University System, College Station, TX, USA. ORCID: 0000-0001-7126-6736.
• Xin Li, Ph.D. — Department of Recreation, Park, and Tourism Sciences, Texas A&M University, College Station, TX, USA. ORCID: 0000-0003-4717-4860.
• Darlene H. Locke, Ph.D. — Department of Agricultural Leadership, Education, and Communications, Texas A&M University, College Station, TX, USA. ORCID: 0000-0001-5491-5538.
• Julie G. Gardner, Ph.D. — Texas A&M AgriLife Extension Service, Texas A&M University System, College Station, TX, USA.

Purpose

Adolescence represents a critical developmental transition characterized by escalating autonomy in food selection, cooking, and lifestyle management, alongside rapid biological growth and escalating nutritional requirements. Concurrently, epidemiological studies indicate that adolescents frequently exhibit substandard diet quality, characterized by excessive intake of ultra-processed foods, saturated fats, sodium, and added sugars, combined with deficient consumption of dietary fiber, micronutrients, fruits, and vegetables. These behavioral trends dramatically heighten lifelong susceptibility to cardiometabolic conditions, type 2 diabetes mellitus, and adolescent obesity. In response to these public health challenges, community-based youth organizations, such as the Cooperative Extension System’s 4-H program, implement extensive informal nutrition education curricula designed to instill actionable life skills.

Prior to the construction of the AFANCA, evaluators and behavioral researchers faced substantial methodological hurdles. Existing instruments predominantly captured isolated constructs—such as rote declarative nutrition knowledge, generalized attitudes toward healthy eating, or self-reported culinary frequency—without integrating the procedural, motor, and cognitive competencies necessary for real-world dietary autonomy. Many legacy instruments also suffered from unverified factor structures, inadequate psychometric testing, or developmental misalignment with adolescent cognitive capabilities.

The foundational purpose of the Assessment of Foods and Nutrition Competencies in Adolescents Questionnaire (AFANCA) was to address this empirical gap by providing a comprehensive, psychometrically robust, and developmentally sensitive self-report instrument capable of evaluating the multidimensional spectrum of youth food competencies. Specifically, the scale assesses:

• Declarative and Procedural Nutritional Literacy: Adolescents’ functional capacity to decode complicated Nutrition Facts labels, understand Percent Daily Values (%DV), identify dietary food groups aligned with USDA MyPlate recommendations, and apply this knowledge during food choice decisions.
• Culinary and Mechanical Preparation Self-Efficacy: Instrumental mastery over knife handling, kitchen appliance management (ovens, stovetops, microwaves), standard dry/wet ingredient measurement, and independent recipe execution from raw ingredients.
• Microbiological Safety and Hazard Mitigation: Adherence to food safety standards, including personal hand hygiene, mitigation of cross-contamination (e.g., separating raw animal proteins from ready-to-eat produce), safe internal cooking temperatures, and the rapid refrigeration of perishable foodstuffs to circumvent the bacterial danger zone.
• Adaptive Recipe Modification: High-order cognitive food agency, capturing whether adolescents possess the creative and analytical capacity to substitute health-promoting ingredients into conventional recipes to diminish sodium, trans/saturated fats, and refined sugars.
• Dietary Intake Realization: Habitual dietary behaviors, with dedicated focus on daily fruit and vegetable intake, hydration choices (water over sugar-sweetened beverages), and preference for whole grains.

In applied settings, the AFANCA serves as an indispensable evaluation diagnostic for school districts, after-school health interventions, Cooperative Extension programs, and clinical pediatric wellness initiatives, enabling researchers to benchmark intervention efficacy, detect competency deficits, and tailor experiential learning modules to the developmental needs of youth.

Psychological Construct

The AFANCA operationalizes adolescent food and nutrition competency not as a singular, unidimensional trait, but as a hierarchical, multifaceted behavioral construct comprising cognitive literacy, motor self-efficacy, hazard appraisal, and behavioral execution. These dimensions intersect to formulate an adolescent’s total dietary agency. The primary subscales and psychological dimensions evaluated within the AFANCA include:

1. Nutrition Knowledge & Label Reading Competency

This cognitive-behavioral dimension captures an adolescent’s capacity to access, comprehend, and translate nutritional information into actionable behavioral choices. Rooted in health literacy paradigms, this subconstruct measures both declarative knowledge (such as familiarity with the five MyPlate food groups and recommended daily servings) and functional procedural literacy (such as calculating serving sizes, interpreting Percent Daily Values, and scanning nutrition labels to minimize intake of sodium, saturated fats, and refined carbohydrates). Rather than testing abstract nutritional facts in isolation, this dimension focuses on applied evaluative competence at the point of consumer decision-making.

2. Food Safety & Microbiological Hazard Control

Foodborne illnesses represent a significant, preventable cause of morbidity. The food safety dimension evaluates an adolescent’s cognitive risk awareness and habitual execution of sanitary precautions. It encapsulates four core domains established by public health agencies: clean (proper handwashing, washing fruits and vegetables), separate (utilizing dedicated cutting boards for raw meats versus fresh produce to prevent pathogen transfer), cook (understanding thermometer utilization and critical internal thermal targets), and chill (adhering to the two-hour rule for refrigerating perishable food to avoid the biological danger zone of 40°F–140°F).

3. Food Preparation & Culinary Mechanical Skills

Culinary competency relies heavily on motor self-efficacy, spatial comprehension, and confidence in the kitchen. This dimension measures mastery over foundational culinary mechanics, including knife safety and grip techniques, precision measuring of dry and liquid ingredients, and the safe operation of thermal kitchen appliances (stoves, conventional ovens, microwaves). Beyond isolated tasks, this construct assesses overall cooking self-efficacy—the youth’s internal perceived confidence to read, sequence, and assemble raw, whole ingredients into a balanced, nutritious meal.

4. Recipe Modification & Culinary Agency

A sophisticated cognitive component of nutrition education, recipe modification represents high-level nutritional problem-solving. This subscale measures an adolescent’s behavioral capability to deconstruct existing culinary recipes and formulate healthy substitutions—such as replacing saturated animal fats with unsaturated vegetable oils, incorporating dietary fiber, or reducing refined table sugars and sodium without compromising palatability. Furthermore, it measures the youth’s interpersonal dietary agency in recommending these modifications within the family ecosystem.

5. Healthy Dietary Consumption & Intake Behaviors

The ultimate downstream behavioral objective of nutrition interventions is the habitual intake of health-promoting foods. This construct captures self-reported behavioral frequencies regarding daily fruit and vegetable consumption, whole-grain versus refined-grain preferences, and the conscious substitution of water for sugar-sweetened beverages. It measures how effectively cognitive knowledge and culinary execution translate into daily dietary patterns.

Theoretical Framework

The conceptual blueprint of the AFANCA questionnaire is anchored primarily in Bandura’s Social Cognitive Theory (SCT), complemented by the Theory of Planned Behavior (TPB) and Kolb’s Experiential Learning Theory.

Social Cognitive Theory (Bandura, 1986)

Social Cognitive Theory postulates that human behavior is the result of continuous, dynamic interactions between personal cognitive factors, environmental influences, and behavioral patterns—a mechanism known as triadic reciprocal determinism. Within the context of adolescent nutrition, food choices are not made in a vacuum; they are heavily influenced by the kitchen environment, social modeling from peers and family, and personal cognitive beliefs.

Two foundational SCT constructs directly underpin the AFANCA items:

• Self-Efficacy: An adolescent’s belief in their capability to execute specific actions required to manage designated nutritional situations. Self-efficacy is reflected in AFANCA items capturing culinary mechanics (e.g., confidence in cutting with knives, operating high-heat appliances, and assembling meals from scratch). Without high task-specific self-efficacy, nutritional knowledge alone rarely leads to behavioral action.
• Behavioral Capability: Possessing both the knowledge of what to do (declarative knowledge) and the practical skill of how to execute it (procedural knowledge). The AFANCA systematically bridges this gap by assessing both theoretical guidelines (MyPlate) and procedural culinary actions (proper ingredient measurement, recipe modification, cross-contamination avoidance).

Theory of Planned Behavior (Ajzen, 1991)

The Theory of Planned Behavior suggests that individual behavioral intentions are governed by attitudes toward the behavior, subjective norms, and perceived behavioral control (PBC). The AFANCA mirrors the construct of perceived behavioral control by evaluating how adolescents perceive their ability to modify family recipes, select low-sodium foods, resist sugar-sweetened beverages, and prepare home-cooked meals despite environmental barriers. Perceived control directly influences intention and subsequent dietary performance.

Experiential Learning Theory (Kolb, 1984) and the 4-H Theory of Change

The 4-H youth development paradigm operates through experiential education—commonly conceptualized as “Do, Reflect, Apply.” According to Kolb (1984), concrete experience provides the basis for observations and reflections, which are then assimilated into abstract concepts, and finally actively tested in new situations. The AFANCA reflects this continuum:

1. Do: The physical acts of measuring, chopping, cooking, and reading labels.
2. Reflect: Evaluating food components, checking internal meat temperatures, observing microbiological hazards, and appraising nutritional quality.
3. Apply: Modifying conventional family dishes to be healthier, adopting regular fruit and vegetable consumption patterns, and choosing water over sodas during social interactions.

Validity

The psychometric integrity of the AFANCA was evaluated by Wang et al. (2023) using a comprehensive validation workflow encompassing content validity, construct validity, convergent and discriminant validity, and measurement invariance across demographic and programmatic subgroups.

Content Validity and Expert Review

Initial item generation was derived directly from the empirical objectives, behavioral benchmarks, and curriculum rubrics of the Texas 4-H Foods and Nutrition Project. A multidisciplinary expert panel—consisting of university extension faculty, developmental psychologists, registered dietitians (RDNs), and youth development specialists—critiqued the item pool for age-appropriate readability, conceptual clarity, ecological validity, and alignment with national dietary standards. Items deemed ambiguous, redundant, or cognitively mismatched were revised or eliminated prior to empirical field testing.

Construct Validity (Confirmatory Factor Analysis)

Construct validity was formally demonstrated through Confirmatory Factor Analysis (CFA) performed on an empirical sample of Texas middle and high school students (grades 6–12). Initial structural testing of an expanded 29-item pool demonstrated suboptimal fit. Following the strategic elimination of 5 problematic items displaying cross-loadings or high residual covariances, the revised 24-item, six-factor model exhibited superior structural fit, meeting established psychometric cutoffs (Hu & Bentler, 1999):

• Model Chi-Square: χ² = 401.48, degrees of freedom (df) = 237, p < .001. While the chi-square was statistically significant (typical in large sample sizes), the χ²/df ratio was 1.69, well below the conservative threshold of 2.0 to 3.0.
• Root Mean Square Error of Approximation (RMSEA): 0.049 (90% Confidence Interval: [0.041, 0.058]), demonstrating excellent point estimation and an upper bound safely below the 0.06 benchmark.
• Comparative Fit Index (CFI): 0.942, demonstrating high incremental fit over the null model.
• Tucker-Lewis Index (TLI): 0.933, confirming appropriate penalization for model complexity.
• Standardized Root Mean Square Residual (SRMR): 0.045, significantly below the conventional 0.08 cutoff, verifying minimal correlation residuals.

All standardized factor loadings for the retained 24 items were statistically significant (p < .001), ranging robustly from 0.57 to 0.89, confirming strong indicator-to-latent construct correspondence.

Convergent and Discriminant Validity

Inter-factor latent correlations among the subscales ranged from r = 0.21 to r = 0.81. The moderate-to-high positive correlations (e.g., between Nutrition Labels and Nutrition Knowledge) confirmed convergent validity, illustrating that related competencies co-vary systematically. Conversely, the absence of excessive multicollinearity (no correlations exceeding 0.85) demonstrated adequate discriminant validity, proving that while these competencies are functionally interrelated, they capture distinct psychological and behavioral dimensions.

Measurement Invariance

To confirm that the AFANCA assesses identical constructs equivalently across diverse cohorts, Wang et al. (2023) conducted multigroup confirmatory factor analyses. The scale demonstrated full configural invariance (identical factor structure), metric invariance (equivalent factor loadings), and scalar invariance (equivalent item intercepts) across:

• Program Involvement Status: Enrolled 4-H Foods and Nutrition project participants versus non-participants.
• Gender: Male versus female adolescent cohorts.
• Age Brackets: Early adolescence (middle school, grades 6–8) versus middle-to-late adolescence (high school, grades 9–12).

Scalar invariance allows researchers to compare latent and observed composite score means directly across groups without measurement bias.

Reliability

Because composite scores on multidimensional scales with varying factor loadings can render Cronbach’s alpha inaccurate, the developers evaluated scale reliability using both McDonald’s composite omega (ω) and conventional internal consistency metrics. Omega does not assume essential tau-equivalence and provides an unbiased estimate of true-score variance.

The composite reliability estimates across all subconstructs of the AFANCA were acceptable to excellent:

• Food Preparation: ω = 0.91 (demonstrating outstanding internal consistency across culinary skill items).
• Nutrition Labels: ω = 0.88 (indicating strong internal coherence among label comprehension and usage indicators).
• Food Safety & Storage: ω = 0.83 (demonstrating robust precision in measuring microbial hazard precautions).
• Nutrition Knowledge: ω = 0.79 (confirming adequate reliability for dietary guideline adherence).
• Fruit & Vegetable Consumption: ω = 0.76 (solid reliability for dietary intake reporting).
• Recipe Modification: ω = 0.74 (acceptable reliability for complex behavioral adaptation).

These reliability values exceed standard psychometric criteria for exploratory and applied instruments (≥ 0.70), demonstrating that the AFANCA possesses minimal measurement error and high test-score precision for group-level intervention assessments and individual diagnostic tracking.

Factor Analysis

The AFANCA was refined and validated through a multi-stage factor analytic process. While initial preliminary items were formulated to reflect theoretical domains, Confirmatory Factor Analysis (CFA) using robust maximum likelihood estimation served as the empirical arbiter of structural integrity.

CFA Specification and Refinement

The baseline model evaluated 29 items across the hypothesized theoretical domains. Modification indices and standardized residual covariance matrices revealed significant localized strain in five items, which displayed cross-loadings across culinary knowledge and food safety or had weak primary factor saturation (< 0.40). Following conservative psychometric pruning principles, these 5 problematic items were eliminated.

Parameter Estimates and Factor Loadings

The re-specified 24-item, six-factor model demonstrated clean, distinct parameter loadings. Standardized factor coefficients for all items were substantial and statistically significant (p < .001):

• Nutrition Knowledge and Label Reading: Factor loadings spanned from 0.64 to 0.86, with items addressing the active comparison of sodium, sugar, and saturated fat on food labels demonstrating the highest saturation on the latent trait.
• Food Safety and Storage: Factor loadings ranged from 0.57 to 0.78. Handwashing and separating raw meats loaded strongly, confirming their centrality to the latent safety construct.
• Recipe Modification: Standardized loadings ranged from 0.68 to 0.82, showing high coherence in substituting healthy ingredients and modifying meal preparation at home.
• Food Preparation: Loadings were uniformly high, spanning from 0.79 to 0.89. Knife mastery and appliance operation displayed the highest standardized weights, confirming culinary mechanics as a distinct latent factor.
• Dietary Intake: Standardized loadings ranged from 0.61 to 0.79, reflecting daily fruit, vegetable, and water intake patterns.

Instrument / Measurement Tool

The operational administration features of the AFANCA are summarized below:

• Instrument Name: Assessment of Foods and Nutrition Competencies in Adolescents Questionnaire (AFANCA)
• Developer / Reference: Wang, J., Drabek, A. G., Li, X., Locke, D. H., & Gardner, J. G. (2023)
• Test Type: Standardized self-report inventory / psychometric questionnaire
• Target Population: Adolescents and youth in Grades 6 through 12 (approximate age range: 11 to 19 years)
• Administration Format: Self-administered paper-and-pencil questionnaire or digital survey platform (Qualtrics, REDCap, Google Forms)
• Administration Time: Approximately 10 to 15 minutes
• Item Count: 24 standardized items
• Response Scale: 5-point Likert scale: 1 = Strongly Disagree, 2 = Disagree, 3 = Neither Agree nor Disagree, 4 = Agree, 5 = Strongly Agree (or 1 = Poor to 5 = Excellent / frequency depending on domain)
• Domain Subscales:
  • Nutrition Knowledge / Label Reading (Items 1, 2, 3, 4, 5, 6, 7)
  • Recipe Modification (Items 8, 9)
  • Food Safety and Storage (Items 10, 11, 12, 13, 14, 15)
  • Food Preparation and Cooking Skills (Items 16, 17, 18, 19, 20)
  • Fruit and Vegetable Consumption / Healthy Intake (Items 21, 22, 23, 24)
• Scoring and Interpretation Procedures:
  • Subscale Scores: Calculated either as the sum of responses within the domain or as the mean domain score (sum divided by the number of domain items, yielding an interpretable metric from 1.00 to 5.00).
  • Total Competency Score: Calculated by summing all 24 items (total theoretical range: 24 to 120) or calculating the grand mean (range: 1.00 to 5.00). Higher scores denote greater nutritional knowledge, culinary self-efficacy, food safety adherence, and healthy dietary habits.
  • Reverse Scoring: No items in the final 24-item validated inventory are reverse-scored; all items are phrased positively toward nutrition competency.

Permissions & Fee and Test Year

• Year of Development: 2023
• Licensing and Copyright: © 2023 Wang et al., published under arrangement with the Society for Nutrition Education and Behavior by Elsevier Inc.
• Fee: Free of charge for academic, non-commercial research, educational evaluations, and public health extension programming.
• Commercial Use: Prohibited without explicit written authorization and licensing from the authors and publisher.
• Correspondence & Inquiries: Dr. Jun Wang, Texas A&M University, Department of Agricultural Leadership, Education, and Communications, 2116 John Kimbrough Blvd, College Station, Texas, 77843, USA. Email: [email protected].

References

• Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
• Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.
• Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
• Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Prentice-Hall.
• McDonald, R. P. (1999). Test theory: A unified treatment. Lawrence Erlbaum Associates Publishers.
• U.S. Department of Agriculture and U.S. Department of Health and Human Services. (2020). Dietary Guidelines for Americans, 2020–2025 (9th ed.). https://www.dietaryguidelines.gov/
• Wang, J., Drabek, A. G., Li, X., Locke, D. H., & Gardner, J. G. (2023). Assessing foods and nutrition competencies in youth. Journal of Nutrition Education and Behavior, 55(5), 354–362. https://doi.org/10.1016/j.jneb.2023.02.007

Items of the Scale