Translation and cross-cultural adaptation of the Rapid Prime Diet Quality Score Screener (rPDQS) for Spanish primary care

Abstract

Aim

To translate and cross-culturally adapt the Rapid Prime Diet Quality Score Screener (rPDQS) for use in Spanish primary care.

Design

Translation, cross-cultural adaptation and pilot testing.

Site

Mallorca Primary Care Centers.

Participants

Primary care professionals and healthcare university students (n = 29) and patients from primary care (n = 71).

Interventions

Administration of the rPDQS for cognitive debriefing and pilot testing in primary care.

Main measurements

Translation and cultural adaptation followed ISPOR and Beaton guidelines, including forward translation, synthesis, back-translation, expert review, pretesting, and final evaluation. Pretesting comprised cognitive debriefing and pilot testing in primary care to assess comprehension, cultural relevance, feasibility, and acceptability.

Results

Only minor linguistic and cultural refinements were required, such as refinement of cooking terms and inclusion of culturally familiar examples, without modifying the underlying constructs of the original instrument. One item relating to full-fat dairy products was identified as inconsistent with current Spanish/European dietary guidelines and was therefore removed from scoring. Examples of sweetened dairy products were added to better capture free-sugar intake. In pilot testing, the Spanish rPDQS showed good acceptability and feasibility. The mean completion time was 7 min, <10% of participants required assistance, and 92% rated items as clear and culturally appropriate. Women had higher numeric scores than men, higher education and lower BMI were associated with better diet quality.

Conclusions

The Spanish version of the rPDQS shows strong linguistic, conceptual, and cultural equivalence with the original instrument and represents a feasible, clear, and culturally appropriate tool for assessing diet quality in Spanish primary care.

Resumen

Objetivo

Traducir y adaptar culturalmente el Rapid Prime Diet Quality Score Screener (rPDQS) para su utilización en atención primaria en España.

Diseño

Estudio de traducción, adaptación transcultural y prueba piloto.

Emplazamiento

Centros de atención primaria de Mallorca.

Participantes

Profesionales de atención primaria y estudiantes universitarios del ámbito sanitario (n = 29), y pacientes de atención primaria (n = 71).

Intervenciones

Administración del rPDQS para entrevistas cognitivas y prueba piloto en atención primaria.

Mediciones principales

La traducción y adaptación cultural siguió las recomendaciones del ISPOR y de Beaton, e incluyeron traducción directa, síntesis, retrotraducción, revisión por un comité de expertos, pretest y evaluación final. El pretest incluyó entrevistas de debriefing cognitivo y un estudio piloto para evaluar la comprensión, relevancia cultural, factibilidad y aceptabilidad.

Resultados

Se requirieron ajustes lingüísticos y culturales menores, sin cambios en los constructos del instrumento original. El ítem sobre lácteos enteros se consideró no concordante con las recomendaciones españolas/europeas y se excluyó de la puntuación. Se añadieron ejemplos de lácteos azucarados para identificar mejor la ingesta de azúcares. El piloto mostró elevada factibilidad y aceptabilidad. El tiempo medio de cumplimentación fue de 7 minutos, <10% de los participantes requirió ayuda y el 92% valoró los ítems como claros y culturalmente apropiados. Las mujeres obtuvieron puntuaciones numéricas más altas que los hombres, y un mayor nivel educativo y un menor IMC se asociaron con una mejor calidad de la dieta.

Conclusiones

La versión española del rPDQS muestra equivalencia lingüística, conceptual y cultural con el original, y es una herramienta breve, clara y viable para evaluar la calidad de la dieta en atención primaria.

Introduction

Diet is a major determinant of noncommunicable diseases worldwide,¹ and insufficient intake of whole grains, nuts, legumes, fruits, and vegetables, and excessive consumption of unhealthy products contribute substantially to cardiometabolic risk outcomes.² Evidence indicates that modest, achievable dietary changes can provide substantial long-term health benefits.³ Dietary counseling delivered in primary care, including brief interventions, has been shown to improve diet quality and cardiometabolic outcomes.^3,4 Patients consistently identify primary care clinicians as trusted and credible sources of dietary guidance.^5,6

Despite this evidence, routine dietary assessment and personalized nutrition guidance are not consistently delivered in primary care⁷ due to time constraints, limited nutrition training, and the lack of rapid, user friendly assessment tools.⁸ Although several brief quality indices exist, including brief validated screeners such as the Mediterranean Diet Adherence Screener (MEDAS),⁹ the Dietary Approaches to Stop Hypertension (DASH) online questionnaire,¹⁰ and the Rapid Eating Assessment for Participants (REAP),¹¹ a review of 15 tools concluded that many were designed for research settings or specific populations and none are well suited for routine use across culturally diverse primary care settings.³ In Spain, most available tools focus on adherence to the Mediterranean diet which may underestimate diet quality in individuals from non-Mediterranean backgrounds, an increasingly relevant issue given the growing immigrant population. Although valuable, such instruments may underestimate diet quality in individuals whose dietary patterns do not align with Mediterranean criteria. For example, the MEDAS often classifies individuals from non-Mediterranean backgrounds, such as those who consume little wine or do not prepare “sofrito” (the Spanish-style sautéed base prepared by slowly cooking onions, garlic, and tomatoes in olive oil) as having low adherence and therefore “unhealthy”, even when their overall diet may be nutritionally adequate. With approximately 6.8 million foreign-born individuals residing in Spain (around 14% of the total population) the Spanish Agency for Food Safety and Nutrition (AESAN) highlights the need to better characterize the dietary patterns of immigrant and second-generation groups.¹² In the current globalized context, marked by rapidly evolving dietary patterns and culinary traditions, there is an increasing demand for instruments capable of assessing diet quality independently of specific cultural contexts.

The Prime Diet Quality Score (PDQS) and the shortened version, the Rapid Prime Diet Quality Score Screener (rPDQS)¹³ offer a culturally neutral approach to assessing overall diet quality and have demonstrated associations with major health outcomes across diverse populations.^14,15 The rPDQS is designed for clinical use, with simplified wording and an intuitive scoring system that supports targeted counseling and monitoring over time. Cross-cultural adaptation of such instruments is essential to ensure semantic and conceptual equivalence,¹⁶ requiring rigorous translation, cultural adaptation, and pretesting in the target population.

The aim of this study was to translate and cross-culturally adapt the rPDQS for use in the Spanish population in primary care settings.

Material and methods

Description of the instrument

The rPDQS is a 13-item dietary screener developed for rapid assessment of overall diet quality in clinical practice.¹³ It was derived from the 18-item Prime Screen¹⁷ and adapted PDQS versions (PDQS-24HR/PDQS-30D)¹⁴ to capture habitual dietary patterns over the previous month. The rPDQS assesses frequency of intake of six protective food groups (e.g., fish, whole grains, fruits, vegetables, legumes, and nuts) and seven adverse food groups (e.g., processed meats, red meats, full-fat dairy products, fast food, sugar-sweetened beverages, refined grains, and sweets). An additional alcohol item is collected for clinical context but is not included in the total score due to the complexity of alcohol–health relationships and guideline recommendations.¹⁸ Responses use a five-point Likert frequency scale (Fig. 1). Two scoring approaches are available: (i) a traffic-light scoring system (0–26 points), which classifies responses as healthy (green, 2 points), less healthy (yellow, 1 point), or unhealthy (red, 0 points), according to the American Heart Association (AHA) dietary guidelines.³ Color-coded feedback is presented to clinicians once the questionnaire is completed, facilitating targeted and patient-centered dietary counseling; and (ii) a numeric scoring system (0–52 points) assigning positive points to beneficial foods and reverse (negative) points to foods to be limited, with higher scores indicating healthier overall dietary patterns.¹⁴

Figure 1.

The original version of the rPDQS and an example of how traffic light scoring output could be displayed.

Translation and cross-cultural adaptation

After formal authorization by e-mail from the original developer (A.T.), we translated and cross-culturally adapted the rPDQS into Spanish following ISPOR Task Force principles¹⁹ and Beaton et al. guidelines¹⁶ (Fig. 2). The procedure comprised six sequential stages:

Figure 2.

Flow diagram of cross-cultural adaptation recommended by Beaton et al., 2000.

Stage 1. Forward translation: Two independent bilingual translators, both native Spanish speakers fluent in English, produced separate forward translations of the original rPDQS. Translator T1 had a nutrition background and was familiar with the concepts assessed, whereas T2 was a professional linguist without nutrition expertise.

Stage 2. Synthesis of the translations: The two forward translations were compared and harmonized into a single consensus version (T1-2) through discussion among translators and the research team. Discrepancies were resolved by consensus, prioritizing conceptual rather than literal equivalence.

Stage 3. Back-translation: Version T1-2 was independently back-translated into English by two bilingual translators (BT1 and BT2), native English speakers fluent in Spanish, blinded to the original instrument and study objectives. This stage served as quality control to confirm preservation of meaning.

Stage 4. Expert committee review (cross-cultural equivalence): A multidisciplinary committee (three nutritionists, two epidemiologists, two linguists, and one methodologist) reviewed the original questionnaire, forward and back-translations, and the consensus version (Supplementary Table). Two in-person meetings were held to refine the pre-final Spanish version, ensuring culturally appropriate terminology/examples and alignment with Spanish dietary guidelines.¹² The committee also evaluated whether minor scoring adaptations were needed to ensure that the questionnaire reflected current Spanish dietary recommendations in the target context.

Stage 5. Pre-test (cognitive debriefing + pilot testing): Pretesting assessed clarity, cultural relevance, and feasibility.

Phase 1) Cognitive debriefing: Participants completed the Spanish draft and a structured cognitive debriefing questionnaire evaluating: (1) clarity of instructions; (2) comprehensibility of food examples; (3) suitability of response options; (4) perceived difficulty/need for assistance; and (5) additional comments (see Additional file 1). Qualitative responses were independently analyzed by three researchers (M.C., A.M.Y., M.B.-V.) to identify issues related to clarity, comprehension, and cultural equivalence.

Phase 2) Pilot testing in primary care: The revised pre-final Spanish version was administered to adult primary care users recruited from primary care centers in Mallorca (June–October 2025). Recruitment followed a convenience sampling approach appropriate for feasibility testing. Eligible participants were adults attending the participating centers who were able to understand Spanish and willing to complete the questionnaire. Participants completed the rPDQS and then took part in a semi-structured interview assessing clarity, comprehension, acceptability, and feasibility, and identifying any need for rewording. Completion time and need for assistance were recorded as usability indicators. Interviews were conducted in Spanish by MC and SM following a semi-structured guide (Additional file 1).

Stage 6. Final evaluation and approval: All proposed modifications were reviewed by the expert committee. Linguistic and cultural refinements were incorporated, and the final version was submitted to the original developer for approval. Semantic equivalence was confirmed before finalization.

Data analysis

Qualitative data from cognitive debriefing and semi-structured interviews were analyzed descriptively to identify themes related to clarity, comprehension, and cultural equivalence. Three researchers independently reviewed responses, resolving discrepancies by consensus; final wording decisions were approved by the expert committee.

Participant characteristics and completion times were summarized using descriptive statistics. Statistical analyses were conducted for exploratory purposes to examine preliminary patterns in the data and assess coherence of responses rather than to test hypotheses or establish validity. Internal consistency was assessed using Cronbach's alpha. Associations between participant characteristics and rPDQS scores (traffic-light and numeric) were explored using Spearman correlations, independent-samples t-tests, and one-way ANOVA. Analyses were performed in IBM SPSS Statistics v29 with two-sided p < 0.05.

Results

Stage 1. Forward translation: Both translators produced accurate forward translations (T1 and T2), requiring only minor contextual adaptations for clarity and cultural relevance. Two main discrepancies emerged: translation of cooking-related wording (e.g., cooked: “cocidas” vs. “cocinado”) and inclusion of culturally familiar examples for processed meats (e.g., “fuet”, “jamóncocido”, “jamónserrano” in T1). These were considered linguistic/cultural refinements rather than conceptual changes.

Stage 2. Synthesis of translations: Discrepancies were resolved by consensus, generating version T1-2 that prioritized semantic/conceptual equivalence over literal translation. The term “cocidas” was retained for greater linguistic accuracy and culturally relevant examples proposed in Stage 1 were incorporated without altering the construct.

Stage 3. Back-translation: BT1 and BT2 closely matched the original questionnaire, confirming semantic accuracy and conceptual fidelity. No unintentional changes in meaning or major inconsistencies were identified.

Stage 4. Expert committee review: Based on Spanish/European dietary guidelines, Item Q4 (full-fat dairy products) was retained for recording but removed from scoring and treated as a neutral item, given that moderate intake is not considered detrimental. This decision was made to maintain conceptual alignment with local dietary recommendations while preserving the structure of the original instrument as closely as possible. To better capture free-sugar intake, sweetened dairy products were added as explicit examples within the “sweets and desserts” category (e.g., flavored yogurts, sweetened milks). All other refinements from Stages 1–2 were retained, and the committee confirmed semantic, idiomatic, and conceptual equivalence of the pre-final version.

Stage 5. Pre-test (cognitive debriefing and pilot testing)

Phase 1. Cognitive debriefing: Twenty-nine participants from diverse sociocultural/educational backgrounds, including primary care professionals and healthcare university students, completed the pre-final Spanish rPDQS and a structured cognitive debriefing questionnaire. Participants proposed adding foods (e.g., lean meats, chocolate, tubers, plant-based proteins, seafood, eggs, fried foods, cooking fats) and/or response options (e.g., “once per month,” “never”) and questioned exclusion of artificially sweetened beverages. Only a few examples were incorporated to improve comprehension/cultural relevance (e.g., milk chocolate added to “sweets and desserts”, fruit in syrup added as a non-applicable example to “whole fruits, fresh or cooked”). Suggestions to add new items or expand frequency categories were not adopted because they exceeded the intended scope of the rPDQS as a brief screener and would compromise feasibility.

Phase 2. Pilot testing in primary care: Seventy-one adults completed the rPDQS in primary care (43 without chronic disease; 28 with cardiometabolic conditions, including hypertension, type 2 diabetes, and dyslipidaemia). Mean completion time was approximately 7 min, and <10% required assistance. Participant characteristics are shown in Table 1. The mean age was 57.7 ± 16.2 years, 62.0% were women, most were employed (50.7%) or retired (35.2%). Participants with cardiometabolic conditions were older (66.3 ± 13.6 vs. 52.1 ± 15.5 years) and had higher BMI (31.7 ± 5.5 vs. 27.0 ± 5.5 kg/m²) than those without chronic disease.

Table 1.

Summary characteristics of participants by chronic disease status (chronic vs. non-chronic participants).

	Total sample (N = 71)	Non-chronic disease (n = 43)	Chronic disease (n = 28)
rPDQS, traffic light scoring	15.79 ± 3.81	16.26 ± 4.17	15.07 ± 3.13
rPDQS, numeric scoring	32.42 ± 5.48	33.09 ± 6.02	31.39 ± 4.45
BMI	27.02 ± 5.45	23.95 ± 2.46	31.73 ± 5.45
Weight	75.80 ± 16.51	67.99 ± 10.28	87.79 ± 17.20
Age	57.73 ± 16.23	52.14 ± 15.49	66.32 ± 13.55
Gender
Male	27 (38.0)	15 (55.6)	12 (44.4)
Female	44 (62.0)	28 (63.6)	16 (36.4)
Education level
University degree	26 (36.6)	19 (73.1)	7 (26.9)
Secondary education	32 (45.1)	21 (65.6)	11(34.4)
Primary education	11 (15.5)	1 (9.1)	10 (90.9)
Did not complete primary education or none	2 (2.8)	2 (100)	0 (0)
Employment status
Employed	36 (50.7)	29 (80.6)	7 (19.4)
Unemployed (claiming benefits)	2 (2.8)	0 (0)	2 (100)
Retired	25 (35.2)	9 (36.0)	16 (64.0)
Domestic work	3 (4.2)	0 (0)	3 (100)
Unemployed (not claiming benefits)	2 (2.8)	2 (100)	0 (0)
Employed but unable to work for 3 months or more	3 (4.2)	3 (100)	0 (0)

Data are presented as mean ± standard deviation (SD) for continuous variables and n (%) for categorical variables.

The rapid Prime Diet Quality Score screener (rPDQS) consists of six healthy (positively) scored food questions (fish, whole grains, beans, vegetables, fruits, peanut butter/nuts) and seven unhealthy (negatively) scored food questions (processed meats, beef/pork/lamb, full-fat dairy, fast food, sugary beverages, white bread and pasta; sweets and desserts).

For the traffic light score approach, the range is 0–26, with six food groups as healthy and seven food groups to restrict using (0 for red-, 1 for yellow-, and 2 for green-coded frequency of food group consumption). For the numeric scoring approach, the range is 0–52 with six healthy food questions scored 0–4 (less than once per week, once per week, 2–4 times per week, nearly daily or daily, and twice or more times per day), and seven unhealthy food questions scored reversely.

Mean numeric rPDQS score was 30.71 ± 5.18, and mean traffic-light score 15.11 ± 3.59, both slightly higher among participants without chronic disease without reaching statistical significance (numeric: 31.42 ± 5.65 vs. 29.64 ± 4.21; traffic-light: 15.78 ± 3.93 vs. 14.39 ± 2.91). In exploratory analysis, women had higher numeric rPDQS scores than men (32.00 ± 5.23 vs. 28.63 ± 4.42; p = 0.007) as well as a higher traffic-light score (15.89 ± 3.80 vs. 13.85 ± 2.85; p = 0.019), indicating better overall diet quality. Body mass index (BMI) was inversely correlated with numeric rPDQS score (Spearman correlation = −0.274; p = 0.021).

Item-level responses are summarized in Table 2. Overall, the traffic-light classification showed coherent patterns across healthy/unhealthy categories (Cronbach's alpha = 0.6). The highest proportions of “unhealthy” (red) responses were Q1 processed meats (53.5%) and Q8 whole-grain bread (39.4%). The highest “healthy” (green) proportions were observed for low intake of Q9 sweets and desserts (71.8%), Q5 fast food/takeout/restaurant meals (66.2%), and Q2 red meat (60.2%), and for higher intake of Q3 fish (66.6%). Vegetables (43.7% yellow) and whole fruits (50.7% yellow) were mostly “less healthy” (yellow), suggesting balanced but improvable patterns. For Q10 beans/lentils/chickpeas/tofu, 87.3% were classified as “less healthy” (yellow) and none as “healthy” (green), indicating low consumption.

Table 2.

The frequency of traffic light scored rPDQS responses in the pilot sample.

	Healthy dietary pattern (green)	Less healthy dietary pattern (yellow)	Unhealthy dietary pattern (red)
1. Processed meats (e.g., sausages, chorizo, mortadella, fuet, bacon, cooked ham, cured ham, sobrasada)	21 (29.6)	12 (16.9)	38 (53.5)
2. Beef, pork, or lamb (e.g., hamburger, steak, stew, lamb chops)	43 (60.6)	25 (35.2)	3 (4.2)
3. Fish (e.g., salmon, hake, squid, cod, tuna and other canned fish)	47 (66.2)	18 (25.4)	7 (9.9)
4. Fast food or take-away, pizza, ready-made meals, restaurant meals	47 (66.2)	22 (31.0)	2 (2.8)
5. Soft drinks, sodas, sports or energy drinks (DOES NOT include diet, zero, or sugar-free/calorie-free drinks)	29 (40.8)	26 (36.6)	16 (22.5)
6. White bread, white rice, white pasta, non-wholegrain breakfast cereals	29 (40.8)	26 (36.6)	16 (22.5)
7. Whole grain bread, brown rice, whole grain pasta, oats, whole grain breakfast cereals	25 (35.2)	18 (25.4)	28 (39.4)
8. Sweets and desserts (e.g., muffins, pastries, biscuits, cakes, candies, milk chocolate and sweetened dairy desserts such as ice cream, flan, custard, or sweetened yogurts)	51 (71.8)	16 (22.5)	4 (5.6)
9. Legumes (e.g., beans, lentils, chickpeas, tofu, hummus)	0 (0)	62 (87.3)	9 (12.7)
10. Fresh or cooked vegetables (e.g., carrots, green beans, spinach, kale, broccoli, cauliflower) DOES NOT include potatoes	20 (28.2)	31 (43.7)	20 (28.2)
11. Whole fresh or cooked fruits (e.g., apples, oranges, bananas, strawberries, grapes, melons) DOES NOT include juices or fruit in syrup	27 (38.0)	36 (50.7)	8 (11.3)
12. Raw or roasted unsalted nuts (e.g., peanuts, almonds, walnuts, cashews, pistachios, natural peanut butter)	25 (35.2)	23 (32.4)	23 (32.4)
13. Whole-fat dairy products (e.g., cheese, milk, or yogurt)^a	15 (21.1)	18 (25.4)	38 (53.5)

^a Corresponding to item Q4 in the original rPDQS.

For the unscored Q4 full-fat dairy item, 53.5% would have been classified as “unhealthy” under the original scoring, contradicting Spanish/European guidance and supporting its removal from scoring. To assess whether removing the full-fat dairy item from the scoring system would affect the total rPDQS score, we compared scores calculated with and without the dairy item. Results indicated that the mean numeric scores were highly correlated (r = 0.97), although mean scores were slightly higher in the adapted version (mean difference = 1.71). Mean traffic-light scores between the two versions were also highly correlated (r = 0.98), with a mean score difference of −0.68.

Acceptability and feasibility were high, >92% rated the questionnaire as clear, comprehensible, and culturally appropriate; interviews confirmed familiarity with examples, adequate response options, and appropriate length. Suggestions to add foods such as chicken or eggs were again discarded to preserve conceptual fidelity and brevity.

Stage 6. Final evaluation: No further structural changes were required. The back-translation of the version modified after Stage 5 was sent to the original developer (Additional file 2), and the Spanish rPDQS was finalized (Fig. 3). An editable version of the Spanish rPDQS can be found in Supplementary Material, Additional File 3.

Figure 3.

The Spanish version of the rPDQS.

Discussion

The rPDQS was successfully translated and culturally adapted into Spanish, demonstrating linguistic, conceptual, and cultural equivalence with the original instrument. The tool is feasible for use in primary care settings given its brevity and clarity, requiring only minor modifications. This ease of adaptation likely reflects the instrument's focus on broad food groups rather than culturally specific dishes or preparation methods.

The main adaptation concerned the dairy products item, reflecting differences between United States and European dietary guidance. While the original rPDQS penalizes full-fat dairy consumption, current Spanish and European recommendations consider moderate consumption compatible with a healthy diet (up to three servings per day).²⁰ Consistent evidence from systematic reviews and cohort studies shows neutral or inverse association between full-fat and fermented dairy intake and obesity, type 2 diabetes, cardiovascular disease, or mortality.^21–24 Accordingly, dairy products were treated neutrally in the Spanish version, avoiding outdated penalization. An additional analysis comparing scores calculated with and without the dairy item indicated that the modification had minimal impact on the overall results of the questionnaire. Although this adaptation reflects current European dietary guidance, it may limit direct comparability with studies using the original rPDQS scoring system. However, because the dairy item was retained descriptively, scores can be recalculated using the original rPDQS scoring approach if required. Our expert consensus also identified that added sugar intake was insufficiently captured through sugar-sweetened beverages. Given that sweetened dairy products are major contributors to free sugar intake in Spain,¹² these were explicitly included in the “sweets and desserts” item, improving contextual accuracy and alignment with WHO and AESAN recommendations.^12,25

The rPDQS excludes alcohol from scoring to ensure cultural neutrality and consistency with current evidence and guidelines indicating that no safe level of alcohol consumption exists.^18,26 Although some indices (e.g., MEDAS) reward moderate wine intake, epidemiological data show increased cardiometabolic and cancer risks even at low levels.²⁷

The Spanish rPDQS appeared to discriminate between adequate, excessive, and insufficient consumption of food groups and identified expected sociodemographic patterns, including higher diet quality scores among women.^28,29 Although Cronbach's alpha was modest, this is expected in short dietary screeners where items represent heterogeneous food groups and do not necessarily correlate with each other. In such formative constructs, internal consistency is not the primary indicator of reliability. Accordingly, item-deleted analyses were not considered informative for this type of instrument.

The Spanish rPDQS is a culturally neutral, evidence-based, and practical tool for dietary assessment and counseling in Spanish primary care populations. The rigorous translation process and consistency with previous international validation studies support its potential relevance for routine practice.^14,30 Its simplicity and traffic-light scoring system may facilitate patient engagement, targeted counseling, and monitoring over time, addressing common barriers to dietary assessment in primary care.³ These characteristics may also make the questionnaire suitable for use during routine primary care consultations. In this context, the questionnaire could serve as a brief screening tool to identify dietary areas that may be addressed through brief lifestyle counseling during the consultation. However, further psychometric validation in Spanish populations is required before its wider use in clinical practice can be fully supported.

Study strengths and limitations

The translation and cross-cultural adaptation followed internationally recognized guidelines,^16,19 and combined expert review, interviews, and pilot testing in a primary care population. Limitations include the lack of psychometric validation, the regional scope of the study. Although this adaptation aligns the questionnaire with current European dietary recommendations, it may limit direct comparability with studies using the original rPDQS scoring system. As for internal consistency, although it was explored, formal evaluation procedures, such as construct validity, criterion validity, test–retest reliability, and factor analysis, were not conducted. Consequently, future research should assess psychometric properties (reliability and validity) in a larger and more diverse Spanish population.

Conclusion

The Spanish version of the rPDQS demonstrated strong linguistic, conceptual, and cultural equivalence with the original instrument, requiring only minor adaptations. Based on this preliminary study, the screener is clear, feasible, and culturally appropriate for use in Spanish primary care and research settings, where brief and reliable dietary assessment methods are needed. Focusing on broad food groups rather than culturally specific dishes allows for meaningful assessment across increasingly diverse and multicultural populations. Future studies should confirm the utility of the rPDQS across broader Spanish-speaking populations before its integration into routine clinical practice.

What is known about the topic

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  Dietary assessment and counseling in primary care improve cardiometabolic outcomes but are underused due to the lack of brief, practical assessment tools.

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  Most screening tools used in Spain focus on Mediterranean diet adherence and may underestimate diet quality in culturally diverse populations.

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  The rPDQS is a brief, culturally neutral diet quality screener associated with health outcomes, but it has not previously been adapted for use in Spanish primary care.

Contributions of this study

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  The rPDQS was translated and cross-culturally adapted into Spanish following international standards (ISPOR/Beaton), achieving linguistic, conceptual, and cultural equivalence.

• -

  The instrument was aligned with Spanish and European dietary guidance by removing full-fat dairy from scoring and adding sweetened dairy examples to better capture free-sugar intake.

• -

  The Spanish rPDQS showed high feasibility and acceptability in primary care, with short completion time and high perceived clarity and cultural appropriateness.

Authorship

MBV and AMY contributed to the conceptualization and design of the study and prepared the first draft of the manuscript. They also provided methodological expertise and oversaw the process evaluation. MC and SM curated the data and carried out formal analysis. MA, MC, SM and DR provided critical commentaries on drafts. MBV and AMY acquired funding for the study. MBV, DR and AMY provided overall supervision. All authors reviewed the manuscript, provided valuable feedback, and approved the final version for publication.

Ethical statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Research Ethics Committee of the Balearic Islands Health Service (CEI-IB; Ref. IB5678/24PI). All participants provided written informed consent.

Use of AI

We used a generative artificial intelligence tool (ChatGPT, GPT-5.2; OpenAI) exclusively for language editing and clarity during the preparation of this manuscript.

Funding

This study was funded by the Spanish Ministry of Science, Innovation and Universities and the Instituto de Salud Carlos III (ISCIII) through project PI23/01625, and by the Primary Care and Health Promotion Network (RICAPPS; RD24/0005/0008), co-funded by the European Union. The funders had no role in the study design, data collection or analysis, manuscript preparation, or the decision to publish.

Conflict of interest

The authors declare that no competing interests exist.

Acknowledgements

The authors thank Professor Anne Thorndike for granting permission to use the rPDQS and for authorizing its translation and cross-cultural adaptation.