Translation and validation of the meat attachment questionnaire (MAQ) in a French General Practice Population

Translation and validation of the meat attachment questionnaire (MAQ) in a French General Practice Population | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Translation and validation of the meat attachment questionnaire (MAQ) in a French General Practice Population Bruno Delaunay, Benoit Tudrej, Augustin Bernard, Alexandra Dupuy, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5245290/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Jan, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Background Meat consumption has significant implications for both individual health and the environment. Understanding individuals' attachment to meat is crucial for designing effective interventions to reduce consumption. The MAQ is a tool developed to assess individuals' attachment to meat. Objective This study aims to translate and validate the MAQ into French for use in a general practice population in France. Methods The study was conducted in three phases: translation, pretesting through cognitive interviews, and testing through a cross-sectional study of general practice patients. Descriptive, factorial, and internal consistency analyses were performed to validate the French version of the MAQ. Results The French version of the MAQ consists of 17 items in four dimensions: Hedonism, Affinity, Entitlement, and Dependence. Face validity was confirmed by cognitive interviews. The RMSEA and CFI were 0.06 and 0.92 respectively, showing acceptable goodness-of-fit. Internal consistency was demonstrated with Cronbach's alpha and Loevinger's H coefficients exceeding 0.7 and 0.3, respectively. Conclusions The French version of the MAQ is a valid and reliable tool for assessing individuals' attachment to meat in a general practice population. Its application shows promise for the design of targeted interventions to reduce meat consumption, benefiting both individual health and environmental sustainability. Health sciences/Medical research/Epidemiology Earth and environmental sciences/Environmental social sciences/Psychology and behaviour Figures Figure 1 Figure 2 Figure 3 Figure 4 I. Introduction Meat products hold an important place in people’s diets worldwide. Average annual meat consumption per person worldwide is about 33 kilograms (kg) ( 1 ), rising to 50–200 kg in high-income countries ( 1 ) and 65 kg in France ( 2 ). Between 1961 and 2022, the world's population doubled, while global meat production quadrupled to 361 million tons ( 1 ). French and international recommendations suggest an annual consumption limit of 36 kg per person per year to maintain good health ( 3 , 4 , 5 ). Meat is an important source of protein, iron and vitamins ( 6 ). However, excessive consumption has been associated with increases in all-cause mortality ( 7 , 8 ), cardiovascular mortality and cardiovascular events ( 9 – 11 ), cancer (especially colorectal cancer) ( 12 ), obesity and diabetes ( 11 , 13 ). Given the difficulty in measuring the impact of excessive meat consumption on human health, these consequences may be underestimated ( 14 , 15 ). Excessive consumption also leads to overproduction, which has significant environmental impacts in terms of greenhouse gas emissions, soil and water acidification, eutrophication of aquatic environments (asphyxiation of the aquatic environment by excessive inputs of nutrients such as nitrogen and phosphorus) ( 16 ), water consumption ( 17 , 18 ), use of fertilizers, loss of biodiversity, air pollution ( 18 ), deforestation ( 19 ) and climate change ( 17 – 19 ). An individual's carbon footprint (i.e., the amount of greenhouse gases produced by one person) could be reduced by a factor of 2 by adopting a vegetarian and local diet. This individual action could have the greatest impact on reducing C02 emissions ( 20 ). In terms of planetary health, reducing meat consumption benefits both human health and the environment. This is known as a cobenefit ( 21 ). Behavioural models such as the theory of planned behaviour (TPB) ( 22 ) can be used to determine how to reduce meat consumption. TPB states that behaviour follows intention (Fig. 1), which is itself driven by 3 components: (i) "attitudes", i.e., evaluations of the pros and cons of performing the behaviour; (ii) "subjective norm", i.e., beliefs about how others would perceive the behaviour if it were performed; and (iii) "perceived behavioural control", i.e., perceptions of whether or not one is in control of performing the behaviour. These components, combined with the resulting intentions, have been shown to accurately predict the frequency and amount of meat consumed ( 23 – 26 ). Figure 1 – Theory of planned behavior The English and Portuguese versions of the Meat Attachment Questionnaire (MAQ) have been developed in accordance with these principles ( 24 , 27 ). The MAQ consists of 16 items and 4 dimensions exploring attachment to meat. The first dimension is 'Hedonism', which measures the pleasurable aspects of eating meat. The second is 'Affinity', which measures affinity towards meat consumption, as opposed to feelings of repulsion. The third is 'Entitlement', which measures feelings of entitlement towards meat consumption. The fourth is 'Dependence', which measures feelings of dependence on meat. The English and Portuguese versions of the MAQ have been validated in the general population ( 24 ). The MAQ has been shown to be related to the TPB dimensions, and to better predict intentions (as defined above) and willingness (openness to the possibility of engaging in the behaviour) to reduce meat consumption than the TPB dimensions alone ( 28 ). The MAQ takes less than 5 minutes to complete, making it suitable for use in general practice. Given the interest in individual action concerning the meat consumption, the relevance of the MAQ in this context, and the lack of a validated French version, we found it pertinent to translate and validate the MAQ in French in a general practice population. II. Methods Study design The aim of our study was to translate in French and validate a questionnaire: the Meat Attachment Questionnaire (MAQ). We carried out the study in three phases (Fig. 2). In the first phase, we translated the MAQ ( 28 ). In the second phase, we verified the face validity of the MAQ through a qualitative study using cognitive interviews ( 29 ) with general practice patients. In the third phase, we confirmed the validity of the French version of the MAQ by conducting a cross-sectional study of general practice patients. Figure 2 - Translation and validation phases of the MAQ questionnaire into French Study context We conducted our study in France, in the Rhône-Alpes region, in 2023 among a population of adult general practice patients. This study is part of a Franco-Swiss planetary health project aimed at developing interventions to reduce meat consumption among general practice patients. To achieve this, we needed a reliable tool to identify which meat attachment profiles were associated with different levels of action and intentions to reduce meat consumption. This study was based on the concept of cobenefits, which postulates that reducing meat consumption has both individual and environmental benefits ( 15 ). 1. Translation We supervised a double translation from Portuguese and English into French, as the MAQ was designed in Portuguese and then translated into English by the same authors. This translation took place in several phases ( 28 ) to obtain a literal translation and then a transcultural validation of the MAQ ( 30 ). The first step was translation from English into French by a professional translator (VB) and a native English speaker (AT) and from Portuguese into French by a native Portuguese speaker (BT). The translations were then reviewed by a committee of four English- and Portuguese-speaking researchers (DHH, JHR, JS, BT). As far as possible, we took everyone's comments into account and discussed them within the team to reach a consensus when opinions differed ( 31 ). We then performed back-translations into English and Portuguese by a professional translator (CH), a native English speaker (CMa) and a native Portuguese speaker (SB) who were not involved in the first phase ( 28 ). We maintained contact with the authors of the original version of the MAQ throughout the process to clarify any possible concerns. We submitted our translations and back-translations to the extended research team and to the authors of the original MAQ to ensure their concordance (JG) ( 28 ). 2. Pretesting – Cognitive interviews Cognitive interviews were used to explore face validity. The aim of this phase was to confirm that respondents' understanding of item meanings was similar to the intended meaning ( 31 ). This phase was also an essential part of the process of cross-cultural translation validation ( 30 ). The methodology of this phase complied with the COREQ quality criteria (Consolidated Criteria for Reporting Qualitative Research) ( 32 ). Population The target population were patients consulting a general practitioner (GP) with a large range of characteristics including age, sex, socioprofessional category, and quantity of meat consumed per week, to ensure maximum diversity in responses. To obtain a sample reflecting the target population, we used a snowball sampling technique based on a convenience sample ( 33 ). Initially, we selected participants from our own circle (who were also patients of a GP) and inquired them if they knew other participants we could contact. We then contacted them by phone, email or social media. The literature does not clearly establish the required number of interviews needed to reach data saturation, but it is generally agreed that conducting 5 to 15 interviews is sufficient. We considered data saturation to have been reached when no further data emerged after two or three interviews ( 34 ). The participants provided informed consent before the interview, and they were informed of their right to withdraw at any point during the interview. Data collection and coding AD, BD, and CM conducted the cognitive interviews ( 35 ). Each participant planned to have a single face-to-face interview, with no third party. Each question required the participant to read the item aloud and verbalize their thoughts and the reasons for their response using the think-aloud technique ( 29 ). Next, we asked more specific questions, known as probes ( 34 ), to explore particular dimensions of understanding. These questions were selected from the literature ( 29 ) and adapted as the interviews proceeded, for example, to explore redundancy (e.g., 'Do you find that this question is almost similar to another question I asked you? '), to clarify the meaning of a word or phrase (e.g., 'How do you understand the meaning of...? '), or to assess whether a question was offensive (e.g., 'Do you find this question offensive? '). Before conducting the interviews, we recorded all the above elements in a self-developed interview guide. It also included sociodemographic characteristics to be collected and examples of sentences to be used at the beginning or end of the interview (primers, closing sentences). This approach enabled us to structure the interviews effectively and ensure their reproducibility within the research group (See Additional file 1). We recorded the interviews with a voice recorder in combination with handwritten notes and then transcribed and coded the verbatims using a 6-point coding grid (See Additional file 2). We coded these responses as appropriate (code 1) or inappropriate (codes 2 to 6). For example, 2 = ambiguous response; 6 = nuanced response). Code 5 (interesting answer) was the only one that overlapped with the other codes, so that an item could be coded twice. We considered an item to be satisfactory if its adapted response rate (code 1) was greater than 85% ( 29 ). 3. Testing phase – Confirmatory Factorial Analysis and Internal Consistency Analysis The methodology for this phase was done in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) quality criteria ( 36 ). Population The target population was represented by adult patients of any genders consulting a GP (inclusion criteria). The exclusion criteria included patients younger than 18 years, patients who did not understand French, and/or patients who were not able to give consent. The practices were selected using a cluster random sampling technique ( 37 ), stratified by the place of practice among the Rhône-Alpes region. For this purpose, we used the freely available 2020 health directory lists of all healthcare professionals ( 38 ), from which we selected the general practices of the Rhône-Alpes region. We aimed to recruit 800 patients (see the "Statistics" section) and planned to administer 20 questionnaires per practice. We therefore set the targeted number of practices to 40 and, anticipating 10% participation, randomized 400 practices to account for possible refusals or failures. We stratified our sample using quotas based on the proportion of practices in each department (i.e., Ain, Ardèche, Drôme, Haute-Savoie, Isère, Loire, Rhône, Savoie) ( 38 ). Contact methods From January to March 2023, we contacted first by phone ( 39 ) and second by email each randomly selected practice until we met the required number of GPs per department (see the “distribution and data collection” section). If they agreed to participate, we contacted them again to arrange a date for their visit following the randomization protocol explained below. If they refused or if we received no response after three consecutive reminders, we contacted the next practice on the list. We excluded practices that could not be contacted (change of address, end of practice, unassigned number) and practices whose main activity was not general practice. Data collection We randomized the practices and the day of the visit by a third party and visited (AD, CM, BD, AB) the waiting rooms of the recruited practitioners. We distributed the questionnaires to all participants who met the inclusion criteria and met no exclusion criteria. We then asked patients who provided their consent to complete the French version of the MAQ and who stayed in the waiting room to provide further explanations if needed. MAQ questionnaire The French version of the MAQ designed for distribution to patients comprises 4 dimensions (Hedonism, Affinity, Entitlement and Dependence) divided into 17 items (one more item than the original questionnaire, see below for further explanations), randomly distributed within these dimensions to limit data collection bias (see Aditionnal file 3). Responses to the 17 questions were given on a five-point Likert scale ranging from 1, strongly disagree, to 5, strongly agree. Sociodemographic data including year of birth, sex, postcode of residence, and socioprofessional category were collected from the INSEE (Institut National de la Statistique et des Etudes Economiques) records. We did not ask about meat consumption, as it was deemed to be sufficiently correlated with the MAQ score already ( 24 ). Statistics Number of participants Since descriptive analyses require a smaller number of participants ( 28 ), we calculated the number of participants to include on the basis of the power required for factorial analyses. Recommendations for factorial analyses do not clearly state the methods for calculating the number of participants to be included ( 40 ). However, it is generally accepted that between 300 and 500 participants are sufficient to accurately determine the correlation factors among variables ( 28 , 41 ). Considering the sampling method described above, adjustment for clustering, and potential difficulties in contacting doctors, we decided to recruit 20 participants per practice from 40 practices, for a total of 800 participants. Descriptive analysis For each item, we calculated the mean, standard deviation. The MAQ score is calculated by measuring the average response to the items, by dimension and in total ( 24 ) (See Additional file 4). The score for each dimension and the total score therefore vary from 1 to 5. Each item has the same weight, except for items 15 and 16 (resulting from the division of item 15 into 2 items, following the cognitive interviews), whose score was divided by 2. This choice maintained the average of 16 weighting points presented in the Portuguese and English versions of the MAQ, thus maintaining its comparability. The items coded inversely for measuring the subscores and the total score are items #4, #6, #9, #13, and #14 (5 equals 1, 4 equals 2, 3 remains unchanged, 2 equals 4, and 1 equals 5). We considered that an item with 95% similar responses was not discriminative and should be deleted ( 42 ). Correlation analysis We used the validscale command ( 43 ) in Stata (statistical data science software) to assess the psychometric properties of the MAQ using classical test theory (CTT). The CTT is a widely used framework for assessing the psychometric properties of measurement instruments and is particularly suitable for validating questionnaires ( 44 ). To select the most relevant factors and organize them into coherent dimensions, we conducted a reliability study using confirmatory factor analysis (CFA) combined with goodness-of-fit indices. To assess the relevance of the statistical model, we used the root mean square error of approximation (RMSEA) and the comparative fit index (CFI). These indices assess the fit between observed and expected data according to the specified model. An RMSEA 0.90 are generally considered to indicate a good fit ( 45 ). We used the convdiv option to assess convergent and divergent validities by examining a correlation matrix ( 43 ). Internal consistency Finally, the internal consistency of the MAQ was validated by calculating Cronbach's alpha and Loevinger's H ( 46 ). These are the most commonly used tools for measuring internal consistency in psychometric studies. We used these coefficients to verify the internal consistency of each item within the four dimensions ( 47 ). A minimum value of 0.70 for Cronbach's alpha and 0.30 for Loevinger's H coefficient was considered acceptable ( 48 , 49 ). Ethics We obtained the agreement of an ethics committee on 03/01/2023 and filed an MR004 declaration with the CNIL. All methods were performed in accordance with the declaration of Helsinki and relevant guidelines and regulations, in particular, informed consent was obtained from all participants. III. Results 1 - Translation The translation of the MAQ questionnaire into french resulted in a 16-items version with 4 dimensions. No significant issues were encountered during the process, and the original meaning of each item was preserved. The back-translation was submitted back to its original authors, who confirmed its accuracy. Additional file 5 details the first version of the MAQ translated into French. 2 – Pretest AD, BD and CM contacted 11 individuals, all of whom agreed to participate. Each were given one interview, during an average of 30 minutes each. Each individual was interviewed face to face, in an environment of their choosing : home, worplace, neutral location or by video-conference. No third party was present at the time of the interviews. All participants were French, mostly from urban area, with an average age of 40 years old, 64% of them being women. The sociodemographic characteristics of the participants are detailed in Table 1 . Table 1 Socio-demographic characteristics of participants interviewed during the cognitive interviews Interview Location Sex – Age Socio-professional category Place of residence Meat consumption (frequency) Duration (minutes) B1 Video call M – 65 Engineer Pouancé ( 49 ) 2/week 42 B2 Hospital F – 46 Caregiver Lyon (69) 8/week 41 B3 Video call M – 29 Architect assistant Brest ( 29 ) 1/week 33 A1 Outside F – 28 Medicine resident Lyon (69) 3/week 32 A2 Home* M – 28 Medicine resident Paris (75) 5/week 16 A3 Hospital F – 55 Nurse La Verpillère ( 38 ) 1/week 19 A4 Home* F – 55 Physiotherapist Colmar (68) 5/week 19 A5 Hospital F – 21 Medical student Lyon (69) 1/week 19 C1 Home* F − 28 Medicine resident Valvignères (07) 1/week 29 C2 Video call F − 60 CNRS researcher Paris suburbs (91) 3/week 59 C3 Home* M − 26 Craftsman Valvignères (07) 5/week 25 * : participant’s home. Of the 16 MAQ items, 14 were kept. The other two items received only two “appropriate responses” (Table 2.1 ). We therefore reworked their composition and wording. These adjustments were made in accordance with the participants' comments during the interviews. Table 2.1 Frequency of code appearance per item in the first 7 interviews (V1 : before modification) Item Appropriate response Ambiguous response Redundant response Offensive response Informative response Qualified response Item 1 7 Item 2 7 Item 3 6 1 1 Item 4 7 Item 5 (V1) 2 5 Item 6 5 2 Item 7 6 1 1 Item 8 6 1 Item 9 7 Item 10 2 5 Item 11 7 Item 12 7 Item 13 6 1 Item 14 7 Item 15 (V1) 2 4 1 Item 16 (V1) 7 Additional file 6 details the verbatims of interest. For example, item 5 ("I love eating meat"; “J’adore manger de la viande”) was deemed to be similar to items 1 and 10 (verbatims B1.1, B2.1, A1.1, and C1.1) by participants. Item 15 was therefore amended to: "I love meals with meat" (“J’adore les repas avec de la viande”). Item 15 ("eating meat is a natural and indisputable practice"; “Manger de la viande est une pratique naturelle et indiscutable”) included two different notions: natural and indisputable (verbatims B1.2, B2.2, A3, C1.2, C2). We therefore split the items in two, leading the total number of items to 17, in agreement with the initial authors. It should be noted that items 3 and 7 sometimes led to nuanced responses due to questioning about the notion of "right" (verbatim B1.3 and B1.4). Item 6 was considered offensive on two occasions (verbatims A1.3 and A2). However, this did not lead to any changes because of the sufficient number of appropriate responses. Finally, item 10 was considered redundant with items 5 and 15, but only before they were modified (verbatims A1.1, C1.1). We therefore did not need to reword it. Of the seventeen items of the modified MAQ proposed in the last four interviews, all received three to four appropriate responses (Table 2.2 ). We therefore considered them to be clear to the population concerned. Additional file 3 details the modified French version of the 17-item MAQ. Table 2.2 Frequency of code appearance per item in the last 4 interviews (V2 : after modification) Item Appropriate response Ambiguous response Redundant response Offensive response Informative response Qualified response Item 1 4 Item 2 4 Item 3 4 1 Item 4 4 Item 5 (V2) 4 Item 6 4 Item 7 3 1 Item 8 4 Item 9 4 Item 10 4 Item 11 4 Item 12 4 Item 13 4 Item 14 4 Item 15 (V2) 4 Item 16 (V2) 4 Item 17 (= 16 from V1) 4 3 – Testing phase Figure 3 illustrates the study's patient inclusion flowchart. Out of 194 eligible practices, 44 (22.6% participation rate) agreed to participate, while 115 practices declined or did not respond after three calls, and 35 were excluded. Ultimately, we visited 39 practices where 974 patients were interviewed and 5 won’t be as we the quota was already reached. A total of 97 declined, and 55 were excluded. A total of 822 patients took the questionnaire (84.4% participation rate). A total of 822 questionnaires were analysed. Figure 3 – Patient inclusion flow-chart Table 3 details the characteristics of the participants, who were primarily urban (65%), had a median age of 52 years (IQR = 31, min–max = 20–93), and were predominantly women (65%). The main socioprofessional categories were retirees (32.1%), employees (27.6%), and managers (20.2%). The descriptive statistics in Table 4 show that the average item scores were 2.4 to 4.2, with no floor or ceiling effects. For item 13,53% of respondents “completely agree[d]”. Table 4 Descriptive characteristics of each item submitted to 822 general practice patients during the test phase N° Item N Mean (SD) [IC 95%] Mean with inverse coding 1 Manger de la viande est un des bons plaisirs de la vie 822 3.74 (1.09) [3.67–3.82] 2 Rien ne peut remplacer la viande dans mon alimentation 821 2.45 (1.22) [2.36–2.53] 3 Du fait de notre place dans la chaîne alimentaire, nous avons le droit de manger de la viande 820 3.49 (1.14) [3.41–3.57] 4 Je me sens mal à l’idée de manger de la viande 819 1.98 (1.16) [1.90–2.06] 4.02 5 J’adore les repas avec de la viande 822 3.48 (1.13) [3.40–3.56] 6 Manger de la viande est irrespectueux de la vie et de l’environnement 820 2.40 (1.17) [2.32–2.48] 3.60 7 Manger de la viande est un droit incontestable de chaque personne 819 3.50 (1.24) [3.41–3.58] 8 Rien ne vaut un bon steak 820 2.99 (1.26) [2.91–3.08] 9 Une alimentation sans viande me conviendrait très bien 820 2.96 (1.26) [2.88–3.05] 3.04 10 Je raffole de la viande 819 2.93 (1.22) [2.85–3.01] 11 Si je ne pouvais pas manger de viande, je me sentirais faible 819 2.36 (1.15) [2.28–2.44] 12 Si on m’obligeait à cesser de manger de la viande, je serais triste 820 2.78 (1.37) [2.69–2.88] 13 La viande me fait penser à des maladies 819 1.80 (1.03) [1.73–1.87] 4.20 14 En mangeant de la viande, je pense à la mort et à la souffrance des animaux 819 2.31 (1.23) [2.22–2.39] 3.69 15 Manger de la viande est une pratique naturelle 819 3.67 (1.03) [3.60–3.74] 16 Manger de la viande est une pratique indiscutable 816 2.76 (1.14) [2.69–2.84] 17 Je ne me vois pas ne pas manger de viande régulièrement 817 2.93 (1.28) [2.85–3.02] We obtained a mean MAQ score of 2.95 (SD = 0.45), with a normal distribution, for a score ranging theoretically from 1 (low attachment to meat) to 5 (high attachment to meat) (Fig. 4). Figure 4 - MAQ total score distribution chart Table 5 details the confirmatory factor analysis results, with the correlation coefficients per item and per factor. These factors helped us identify 4 factors. The RMSEA and CFI were 0.06 and 0.92, respectively, indicating an acceptable fit. Each of the 4 factors included items whose themes were consistent. Factor 1 (“Hedonism”) combined items 1, 5, 8 and 10. Factor 2 (“Affinity”) combined items 4, 6, 13 and 14. Factor 3 (“Entitlement”) included items 3, 7, 15 and 16. Finally, Factor 4 (“Dependence”) combined items 2, 9, and 11 and 12 and 17. The French translations are available in Additional file 4. Notably, most items, excluding 4, 6, 7, 13, and 14, demonstrated correlations with multiple factors. We allocated them to the dimension with the strongest correlation or the most conceptually consistent meaning, a categorization consistent with the MAQ source study. Table 5 – Confirmatory factor analysis for the French version of the four-dimensional MAQ-17 questionnaire (n = 822) Items Factors* 1 2 3 4 1 Manger de la viande est un des bons plaisirs de la vie 0.797 0.499 5 J’adore les repas avec de la viande 0.839 0.436 0.527 8 Rien ne vaut un bon steak 0.803 0.497 0.590 10 Je raffole de la viande 0.854 0.439 0.602 4 Je me sens mal à l’idée de manger de la viande 0.414 0.746 6 Manger de la viande est irrespectueux de la vie et de l’environnement 0.714 13 La viande me fait penser à des maladies 0.692 14 En mangeant de la viande, je pense à la mort et à la souffrance des animaux 0.778 3 Du fait de notre place dans la chaîne alimentaire, nous avons le droit de manger de la viande 0.411 0.728 7 Manger de la viande est un droit incontestable de chaque personne 0.737 15 Manger de la viande est une pratique naturelle 0.400 0.727 16 Manger de la viande est une pratique indiscutable 0.400 0.736 0.447 2 Rien ne peut remplacer la viande dans mon alimentation 0.532 0.717 9 Une alimentation sans viande me conviendrait très bien 0.509 0.465 0.707 11 Si je ne pouvais pas manger de viande, je me sentirais faible 0.430 0.721 12 Si on m’obligeait à cesser de manger de la viande, je serais triste 0.553 0.405 0.785 17 Je ne me vois pas ne pas manger de viande régulièrement 0,617 * factors obtaining more than 0.4 are displayed Table 6 demonstrates the internal consistency of the four-dimensional model, with Cronbach's alpha and Loevinger's H coefficients exceeding 0.7 and 0.3, respectively (0.84 and 0.61 for Hedonism, 0.72 and 0.42 for Affinity, 0.71 and 0.41 for Entitlement, and 0.75 and 0.40 for Dependence). Table 6 Internal consistency (Cronbach's Alpha and H. Loevinger's coefficients) by MAQ dimension Factors Dimension N° Item Cronbach's Alpha (N = 822) H. Loevinger F1 Hedonism* 1 ; 5 ; 8 ; 10 0.84 0.61 F2 Affinity* 4 ; 6 ; 13 ; 14 0.71 0.42 F3 Entitlement* 3 ; 7 ; 15 ; 16 0.71 0.41 F4 Dependence* 2 ; 9 ; 11 ; 12 ; 17 0.75 0.40 IV. Discussion From a planetary health perspective, the validation of the French version of the MAQ makes it possible to consider and encourage its use to explore adult patients’ attachment to meat in general practice. The MAQ discriminates between patient groups effectively (24,27,51). The MAQ is also effective in measuring and predicting people's motivations and intentions to change meat consumption (24,27,51). It is therefore an effective research tool, alone or in combination with other scores, for identifying groups with common characteristics with regard to reducing meat consumption (in terms of motivations, barriers and intentionality). The applications could vary. Further studies could be carried out to verify its validity in other French-speaking populations, its reproducibility and its stability over time. Research is also needed to validate its application in minor patients, whose specificities will probably require the MAQ to be adapted or completed by their parents (57). Among other scores, combining the Food Neophobia Scale (FNS), a validated and widely used tool which measures the personal reluctance to accept and/or enjoy new or unfamiliar foods (58,59) with the MAQ could predict the acceptability of vegetarian alternatives, aiding intervention design (60). The Nutrinet Santé score (61) assesses the effectiveness of interventions on intentional or actual meat product purchases. In addition, given that the MAQ questionnaire was developed by studying people's obstacles and incentives, it aligns closely with the concerns they might have. Its simplicity makes it a useful tool for GPs and health professionals to explore representations of meat-based diets and planetary health. Completing the MAQ in waiting rooms could initiate discussions during consultations. As nutrition becomes a public health concern (3,63), the MAQ could also be an interesting gateway to a broader nutritional approach. With its high reproducibility in American studies, the MAQ can measure interventions aimed at reducing meat consumption. It has been used to assess the impact of graphic awareness messages (Koch et al., 64), the visual attractiveness of vegetarian substitutes (Ding et al., 65), consumer demand for vegetarian steaks (Bryant et al., 60), the evolution of meat representations (Verain et al., 66), and 'Meat Paradox' intensity (wanting to eat meat but being against animal suffering) (Dowset et al., 67). Finally, from a public health perspective, the MAQ would make it possible to better target the profiles of hedonism, affinity, entitlement and dependence on meat products in the general population. This could be a first step towards developing appropriate population-based strategies to reduce meat proportions in the French diet. V. Conclusion This study is part of a global health dynamic. Reducing meat consumption is a cobenefit for both individual and environmental health. We translated and validated the French version of the MAQ in a population of general practice patients. We obtained a 17-item and 4-dimensional questionnaire. The French version of the MAQ has various possible applications. The use of the French version of the MAQ could fit various strategies aimed at reducing meat consumption. At the GP practice, the MAQ could be used by GPs, medical assistants, public health nurses or advanced practice nurses to explore their patients' representations to encourage behavioural change. From a public health perspective, the MAQ could be used to better target profiles of hedonism, affinity, entitlement and dependence on meat products in the general population, a preliminary step toward developing appropriate population-based strategies to reduce the proportion of meat products in the diet of the French population. Declarations Ethics approval and consent to participate The study was approved by the Research Ethics Committee of the University College of General Practice, Claude Bernard University (Project-ID IRB 2023-01-03-01). Written informed consent (i.e. consent to participate) was obtained from all study participants. Collected data remained confidential. Each patient was represented by a unique anonymous identification code in order to ensure confidentiality. Consent for publication NA Availability of data and materials The data that support the findings of this study are available from the corresponding author (HM) upon reasonable request Competing interests The authors declare that they have no competing interests. Funding Institutional funding from the Faculty of Medicine, University of Geneva, supported this project. Authors' contributions HM, BT, BD, CM, AD and TB contributed to the conception and design of the research project. BD, CM, AD, AB performed the data collection. PS participated in the statistical analyses and interpretation of the data, prepared the figures and tables. BD wrote the original draft and revised the manuscript. HM conceptualised and designed the research project, gave final approval of the different steps described in the method section, and was involved in reviewing the manuscript. HM, BT, BD, CM, AD and TB participated in the interpretation of the data. All authors read and approved the final manuscript. Acknowledgements The authors would like to sincerely thank all the collaborating GP practices and patients, as well as Mohamed Amir Moussa, administrative research assistant, for their precious contribution to the study. References Food and Agriculture Organization of the United Nations (2023). La consommation de viande en France en 2022|Agreste, la statistique agricole [Internet]. Disponible sur : https://agreste.agriculture.gouv.fr/agreste-web/download/publication/publie/SynCsm23412/consyn412202307-ConsoViande.pdf SPF. L’essentiel des recommandations sur l’alimentation [Internet]. [cité 23 avr 2023]. Disponible sur: https://www.santepubliquefrance.fr/import/l-essentiel-des- recommandations-sur-l-alimentation Canada H. Canada Food Guide. 2020 [cité 23 avr 2023]. Make it a habit to eat vegetables, fruits, whole grains and protein foods. Disponible sur: https://food- guide.canada.ca/en/healthy-eating-recommendations/make-it-a-habit-to-eat-vegetables- fruit-whole-grains-and-protein-foods/ 2020-2025 Dietary Guidelines for Americans Recommendations [Internet]. [cité 25 juin 2023]. Disponible sur: https://www.pcrm.org/good-nutrition/nutrition-programs- policies/2020-2025-dietary-guidelines Pereira PM de CC, Vicente AF dos RB. Meat nutritional composition and nutritive role in the human diet. Meat Sci. mars 2013;93(3):586‑92. Abete I, Romaguera D, Vieira AR, Munain AL de, Norat T. Association between total, processed, red and white meat consumption and all-cause, CVD and IHD mortality: a meta- analysis of cohort studies. British Journal of Nutrition. sept 2014;112(5):762‑75. Sinha R, Cross AJ, Graubard BI, Leitzmann MF, Schatzkin A. Meat Intake and Mortality: A Prospective Study of Over Half a Million People. Archives of Internal Medicine. 23 mars 2009;169(6):562‑71. Iqbal R, Dehghan M, Mente A, Rangarajan S, Wielgosz A, Avezum A, et al. Associations of unprocessed and processed meat intake with mortality and cardiovascular disease in 21 countries [Prospective Urban Rural Epidemiology (PURE) Study]: a prospective cohort study. The American Journal of Clinical Nutrition. 1 sept 2021;114(3):1049‑58. Chen GC, Lv DB, Pang Z, Liu QF. Red and processed meat consumption and risk of stroke: a meta-analysis of prospective cohort studies. Eur J Clin Nutr. janv 2013;67(1):91‑5. Micha R, Wallace SK, Mozaffarian D. Red and processed meat consumption and risk of incident coronary heart disease, stroke, and diabetes: A systematic review and meta- analysis. Circulation. 1 juin 2010;121(21):2271‑83. Bouvard V, Loomis D, Guyton KZ, Grosse Y, Ghissassi FE, Benbrahim-Tallaa L, et al. Carcinogenicity of consumption of red and processed meat. Lancet Oncol. déc 2015;16(16):1599‑600. Pan A, Sun Q, Bernstein AM, Schulze MB, Manson JE, Willett WC, et al. Red meat consumption and risk of type 2 diabetes: 3 cohorts of US adults and an updated meta- analysis. Am J Clin Nutr. oct 2011;94(4):1088‑96. Myers SS, Bernstein A. The coming health crisis: indirect health effects of global climate change. F1000 Biol Rep. 1 févr 2011;3:3. Willett W, Rockström J, Loken B, Springmann M, Lang T, Vermeulen S, et al. Food in the Anthropocene: the EAT–Lancet Commission on healthy diets from sustainable food systems. The Lancet. 2 févr 2019;393(10170):447‑92. Poore J, Nemecek T. Reducing food’s environmental impacts through producers and consumers. Science. juin 2018;360(6392):987‑92. Vanham D, Mekonnen MM, Hoekstra AY. The water footprint of the EU for different diets. Ecological Indicators. sept 2013;32:1‑8. Clark MA, Springmann M, Hill J, Tilman D. Multiple health and environmental impacts of foods. Proceedings of the National Academy of Sciences. 12 nov 2019;116(46):23357‑62. Gerber PJ, Food and Agriculture Organization of the United Nations, éditeurs. Tackling climate change through livestock: a global assessment of emissions and mitigation opportunities. Rome: Food and Agriculture Organization of the United Nations; 2013. 115 p. Faire sa part ? | Carbone 4 [Internet]. [cité 23 avr 2023]. Disponible sur: https://carbone4.com/fr/publication-faire-sa-part Holguera JG, Senn N. Co bénéfices santé-environnement et changement climatique : concepts et implication pour l’alimentation, la mobilité et le contact avec la nature en pratique clinique. La Presse Médicale Formation. 1 déc 2021;2(6):622‑7. Ajzen I. The theory of planned behavior. Organizational Behavior and Human Decision Processes. 1 déc 1991;50(2):179‑211. Berndsen M, van der Pligt J. Ambivalence towards meat. Appetite. 2004;42(1):71‑8. Graça J, Calheiros MM, Oliveira A. Attached to meat? (Un)Willingness and intentions to adopt a more plant-based diet. Appetite. 1 déc 2015;95:113‑25. Povey R, Wellens B, Conner M. Attitudes towards following meat, vegetarian and vegan diets: an examination of the role of ambivalence. Appetite. 1 août 2001;37(1):15‑26. Saba A, Di Natale R. A study on the mediating role of intention in the impact of habit and attitude on meat consumption. Food Quality and Preference. 9 oct 1998;10(1):69‑77. Lentz G, Connelly S, Mirosa M, Jowett T. Gauging attitudes and behaviours: Meat consumption and potential reduction. Appetite. 1 août 2018;127:230‑41. Sousa VD, Rojjanasrirat W. Translation, adaptation and validation of instruments or scales for use in cross-cultural health care research: a clear and user-friendly guideline. J Eval Clin Pract. avr 2011;17(2):268‑74. Napoles-Springer AM, Santoyo-Olsson J, O’Brien H, Stewart AL. Using Cognitive Interviews to Develop Surveys in Diverse Populations: Medical Care. nov 2006;44(Suppl 3):S21‑30. Guillemin F, Bombardier C, Beaton D. Cross-cultural adaptation of health-related quality of life measures: literature review and proposed guidelines. J Clin Epidemiol. déc 1993;46(12):1417‑32. Artino AR, La Rochelle JS, Dezee KJ, Gehlbach H. Developing questionnaires for educational research: AMEE Guide No. 87. Med Teach. juin 2014;36(6):463‑74. Gedda M. Traduction française des lignes directrices ENTREQ pour l’écriture et la lecture des synthèses de recherche qualitative. Kinésithérapie, la Revue. 1 nov 2014;15. Naderifar M, Goli H, Ghaljaei F. Snowball Sampling: A Purposeful Method of Sampling in Qualitative Research. Strides in Development of Medical Education. 30 sept 2017;In Press. Beatty PC, Willis GB. Research Synthesis: The Practice of Cognitive Interviewing. Public Opinion Quarterly. 1 janv 2007;71(2):287‑311. Castillo-Díaz M, Padilla JL. How cognitive interviewing can provide validity evidence of the response processes to scale items. Social Indicators Research. 2013;114:963‑75. Gedda M. Traduction française des lignes directrices STROBE pour l’écriture et la lecture des études observationnelles. Kinésithérapie, la Revue. janv 2015;15(157):34‑8. Killip S, Mahfoud Z, Pearce K. What is an intracluster correlation coefficient? Crucial concepts for primary care researchers. Ann Fam Med. 2004;2(3):204‑8. Extractions en libre accès - L’Annuaire Santé [Internet]. [cité 27 avr 2023]. Disponible sur: https://annuaire.sante.fr/web/site-pro/extractions-publiques Treweek S, Pitkethly M, Cook J, Fraser C, Mitchell E, Sullivan F, et al. Strategies to improve recruitment to randomised trials. Cochrane Database of Systematic Reviews [Internet]. 2018 [cité 27 avr 2023];(2). Disponible sur: https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.MR000013.pub6/full Anthoine E, Moret L, Regnault A, Sébille V, Hardouin JB. Sample size used to validate a scale: a review of publications on newly-developed patient reported outcomes measures. Health Qual Life Outcomes. 9 déc 2014;12:2. Rouquette A, Falissard B. Sample size requirements for the internal validation of psychiatric scales. Int J Methods Psychiatr Res. déc 2011;20(4):235‑49. Haller DM, Meynard A, Pejic D, Sredic A, Huseinagic S, Courvoisier DS, et al. YFHS- WHO+ Questionnaire: validation of a measure of youth-friendly primary care services. J Adolesc Health. nov 2012;51(5):422‑30. Perrot B, Bataille E, Hardouin JB. validscale: A Command to Validate Measurement Scales. The Stata Journal. 1 mars 2018;18(1):29‑50. Devellis R. Scale development: Theory and applications. SAGE. 2017. Gadelrab H. Evaluating the fit of structural equation models: Sensitivity to specification error and descriptive goodness-of-fit Indices. 2013. Dima AL. Scale validation in applied health research: tutorial for a 6-step R-based psychometrics protocol. Health Psychol Behav Med. 10 mai 2018;6(1):136‑61. Kline P. The handbook of psychological testing, 2nd ed. Florence, KY, US: Taylor & Frances/Routledge; 1993. vii, 744 p. (The handbook of psychological testing, 2nd ed). Nunally J. Psychometric theory. McGraw-Hill. 1978. Loevinger J. The technic of homogeneous tests compared with some aspects of scale analysis and factor analysis. Psychol Bull. nov 1948;45(6):507‑29. De Backer C, Erreygers S, De Cort C, Vandermoere F, Dhoest A, Vrinten J, et al. Meat and masculinities. Can differences in masculinity predict meat consumption, intentions to reduce meat and attitudes towards vegetarians? Appetite. 1 avr 2020;147:104559. Lacroix K, Gifford R. Targeting interventions to distinct meat-eating groups reduces meat consumption. Food Quality and Preference. 1 déc 2020;86:103997. Bottemine T. Traduction de la Working Alliance Inventory Short Version (WAI SR) en français par une méthode de consensus Delphi avec une traduction Aller/Retour. Hatcher L. A Step-by-Step Approach to Using the SAS System for Factor Analysis and Structural Equation Modeling. 1st éd. SAS Publishing; 1994. 608 p. Letrilliart L, Supper I, Schuers M, Darmon D, Boulet P, Favre M, et al. ECOGEN : étude des Eléments de la COnsultation en médecine GENérale. Exercer, la revue Française de médecine générale. 2014;25:148. Lemale J, Mas E, Jung C, Bellaiche M, Tounian P, French-speaking Pediatric Hepatology, Gastroenterology and Nutrition Group (GFHGNP). Vegan diet in children and adolescents. Recommendations from the French-speaking Pediatric Hepatology, Gastroenterology and Nutrition Group (GFHGNP). Arch Pediatr. oct 2019;26(7):442‑50. Grant JD. Time for change: Benefits of a plant-based diet. Can Fam Physician. oct 2017;63(10):744‑6. Erhardt J, Olsen A. Meat Reduction in 5 to 8 Years Old Children—A Survey to Investigate the Role of Parental Meat Attachment. Foods. août 2021;10(8):1756. Pliner P, Hobden K. Development of a scale to measure the trait of food neophobia in humans. Appetite. oct 1992;19(2):105‑20. Rabadán A, Bernabeu R. A systematic review of studies using the Food Neophobia Scale: Conclusions from thirty years of studies. Food Quality and Preference. 1 mars 2021;104241. Bryant C, Szejda K, Parekh N, Deshpande V, Tse B. A Survey of Consumer Perceptions of Plant-Based and Clean Meat in the USA, India, and China. Frontiers in Sustainable Food Systems [Internet]. 2019 [cité 20 févr 2022];3. Disponible sur: https://www.frontiersin.org/article/10.3389/fsufs.2019.00011 Bienvenue sur le site institutionnel de l’étude NutriNet-Santé | Site institutionnel de l’étude NutriNet-Santé [Internet]. [cité 25 juin 2023]. Disponible sur: https://info.etude- nutrinet-sante.fr/siteinfo/article/52 Graça J, Oliveira A, Calheiros MM. Meat, beyond the plate. Data-driven hypotheses for understanding consumer willingness to adopt a more plant-based diet. Appetite. juill 2015;90:80‑90. Alimentation saine [Internet]. [cité 25 juin 2023]. Disponible sur: https://www.who.int/fr/news-room/fact-sheets/detail/healthy-diet Koch JA, Bolderdijk JW, van Ittersum K. Can graphic warning labels reduce the consumption of meat? Appetite. 1 janv 2022;168:105690. Ding YY (Elaina), Huang Y, Ku HP (Grace), Lim K, Lin T. Plant Based Diets : Sensory Attractiveness Increases Acceptability of Meat Substitutes [Internet]. 2018 [cité 20 févr 2022]. Disponible sur: https://open.library.ubc.ca/soa/cIRcle/collections/undergraduateresearch/18861/items/1.0 375709 Verain MCD, Dagevos H, Jaspers P. Flexitarianism in the Netherlands in the 2010 decade: Shifts, consumer segments and motives. Food Quality and Preference. 1 mars 2022;96:104445. Dowsett E, Semmler C, Bray H, Ankeny RA, Chur-Hansen A. Neutralising the meat paradox: Cognitive dissonance, gender, and eating animals. Appetite Additional Declarations No competing interests reported. Supplementary Files ADDITIONALFILE1Interviewguide.docx ADDITIONAL FILE 1: Interview guide : shows the interview guide used by the investigators during the study. ADDITIONALFILE2Itemcoding.docx ADDITIONAL FILE 2: Item coding : shows the item coding used by the investigators to code the interviews. ADDITIONALFILE3ModifiedFrenchversionofthe17itemMAQquestionnaire.jpg ADDITIONAL FILE 3: Modified French version of the 17 item MAQ questionnaire : shows the questionnaire that was used during the quantitative phase of the study. ADDITIONALFILE4FrenchversionoftheMAQinstructionsforcalculatingthescoretranslatedinEnglish.docx ADDITIONAL FILE 4: French version of the MAQ & instructions for calculating the score, translated in English : shows the French version of the questionnaire & instructions for calculating the score, translated in English. ADDITIONALFILE5MAQtranslatedintoFrenchfromPortugueseandEnglish.docx ADDITIONAL FILE 5: MAQ, translated into French from Portuguese and English : shows the first version of the MAQ translated into French. ADDITIONALFILE6Verbatims.docx ADDITIONAL FILE 6: Verbatims : shows the verbatims of interest identified during the interviews Cite Share Download PDF Status: Published Journal Publication published 18 Jan, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 26 Nov, 2024 Reviews received at journal 25 Nov, 2024 Reviews received at journal 31 Oct, 2024 Reviewers agreed at journal 22 Oct, 2024 Reviewers agreed at journal 21 Oct, 2024 Reviewers invited by journal 17 Oct, 2024 Editor assigned by journal 17 Oct, 2024 Editor invited by journal 17 Oct, 2024 Submission checks completed at journal 17 Oct, 2024 First submitted to journal 11 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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06:06:20","extension":"jpg","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":345700,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eADDITIONAL FILE 3: Modified French version of the 17 item MAQ questionnaire \u003c/strong\u003e: shows the questionnaire that was used during the quantitative phase of the study.\u003c/p\u003e","description":"","filename":"ADDITIONALFILE3ModifiedFrenchversionofthe17itemMAQquestionnaire.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5245290/v1/f495d3b5c94ec6dc43b2b3cf.jpg"},{"id":72361340,"identity":"2e1f26ef-259a-4fb9-a15e-e3ae1dec9541","added_by":"auto","created_at":"2024-12-26 06:06:21","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":13523,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eADDITIONAL FILE 4: French version of the MAQ \u0026amp; instructions for calculating the score, translated in English : \u003c/strong\u003eshows the French version of the questionnaire \u0026amp; instructions for calculating the score, translated in English.\u003c/p\u003e","description":"","filename":"ADDITIONALFILE4FrenchversionoftheMAQinstructionsforcalculatingthescoretranslatedinEnglish.docx","url":"https://assets-eu.researchsquare.com/files/rs-5245290/v1/3d0a393b7c836b74cea511e4.docx"},{"id":72361341,"identity":"d161f8a7-b478-40b0-83ad-a7c0881042f0","added_by":"auto","created_at":"2024-12-26 06:06:21","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":13061,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eADDITIONAL FILE 5: MAQ, translated into French from Portuguese and English : \u003c/strong\u003eshows the first version of the MAQ translated into French.\u003c/p\u003e","description":"","filename":"ADDITIONALFILE5MAQtranslatedintoFrenchfromPortugueseandEnglish.docx","url":"https://assets-eu.researchsquare.com/files/rs-5245290/v1/3255d8223aea81ec416a1802.docx"},{"id":72361339,"identity":"0bb03a5e-5ed8-41f6-870b-4db99b989da1","added_by":"auto","created_at":"2024-12-26 06:06:20","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":14125,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eADDITIONAL FILE 6: Verbatims : \u003c/strong\u003eshows the verbatims of interest identified during the interviews\u003c/p\u003e","description":"","filename":"ADDITIONALFILE6Verbatims.docx","url":"https://assets-eu.researchsquare.com/files/rs-5245290/v1/760686bc3b3f328ddcc3c2fe.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Translation and validation of the meat attachment questionnaire (MAQ) in a French General Practice Population","fulltext":[{"header":"I. Introduction","content":"\u003cp\u003eMeat products hold an important place in people\u0026rsquo;s diets worldwide. Average annual meat consumption per person worldwide is about 33 kilograms (kg) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), rising to 50\u0026ndash;200 kg in high-income countries (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) and 65 kg in France (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Between 1961 and 2022, the world's population doubled, while global meat production quadrupled to 361\u0026nbsp;million tons (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFrench and international recommendations suggest an annual consumption limit of 36 kg per person per year to maintain good health (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Meat is an important source of protein, iron and vitamins (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). However, excessive consumption has been associated with increases in all-cause mortality (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), cardiovascular mortality and cardiovascular events (\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), cancer (especially colorectal cancer) (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), obesity and diabetes (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Given the difficulty in measuring the impact of excessive meat consumption on human health, these consequences may be underestimated (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eExcessive consumption also leads to overproduction, which has significant environmental impacts in terms of greenhouse gas emissions, soil and water acidification, eutrophication of aquatic environments (asphyxiation of the aquatic environment by excessive inputs of nutrients such as nitrogen and phosphorus) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), water consumption (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), use of fertilizers, loss of biodiversity, air pollution (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), deforestation (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) and climate change (\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). An individual's carbon footprint (i.e., the amount of greenhouse gases produced by one person) could be reduced by a factor of 2 by adopting a vegetarian and local diet. This individual action could have the greatest impact on reducing C02 emissions (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn terms of planetary health, reducing meat consumption benefits both human health and the environment. This is known as a cobenefit (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBehavioural models such as the theory of planned behaviour (TPB) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) can be used to determine how to reduce meat consumption. TPB states that behaviour follows intention (Fig.\u0026nbsp;1), which is itself driven by 3 components: (i) \"attitudes\", i.e., evaluations of the pros and cons of performing the behaviour; (ii) \"subjective norm\", i.e., beliefs about how others would perceive the behaviour if it were performed; and (iii) \"perceived behavioural control\", i.e., perceptions of whether or not one is in control of performing the behaviour. These components, combined with the resulting intentions, have been shown to accurately predict the frequency and amount of meat consumed (\u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 1 \u0026ndash; Theory of planned behavior\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe English and Portuguese versions of the Meat Attachment Questionnaire (MAQ) have been developed in accordance with these principles (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). The MAQ consists of 16 items and 4 dimensions exploring attachment to meat. The first dimension is 'Hedonism', which measures the pleasurable aspects of eating meat. The second is 'Affinity', which measures affinity towards meat consumption, as opposed to feelings of repulsion. The third is 'Entitlement', which measures feelings of entitlement towards meat consumption. The fourth is 'Dependence', which measures feelings of dependence on meat. The English and Portuguese versions of the MAQ have been validated in the general population (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe MAQ has been shown to be related to the TPB dimensions, and to better predict intentions (as defined above) and willingness (openness to the possibility of engaging in the behaviour) to reduce meat consumption than the TPB dimensions alone (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The MAQ takes less than 5 minutes to complete, making it suitable for use in general practice.\u003c/p\u003e \u003cp\u003eGiven the interest in individual action concerning the meat consumption, the relevance of the MAQ in this context, and the lack of a validated French version, we found it pertinent to translate and validate the MAQ in French in a general practice population.\u003c/p\u003e"},{"header":"II. Methods","content":"\u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eStudy design\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe aim of our study was to translate in French and validate a questionnaire: the Meat Attachment Questionnaire (MAQ). We carried out the study in three phases (Fig.\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eIn the first phase, we translated the MAQ (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the second phase, we verified the face validity of the MAQ through a qualitative study using cognitive interviews (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) with general practice patients.\u003c/p\u003e \u003cp\u003eIn the third phase, we confirmed the validity of the French version of the MAQ by conducting a cross-sectional study of general practice patients.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 2 - Translation and validation phases of the MAQ questionnaire into French\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eStudy context\u003c/span\u003e \u003c/p\u003e \u003cp\u003eWe conducted our study in France, in the Rh\u0026ocirc;ne-Alpes region, in 2023 among a population of adult general practice patients.\u003c/p\u003e \u003cp\u003eThis study is part of a Franco-Swiss planetary health project aimed at developing interventions to reduce meat consumption among general practice patients. To achieve this, we needed a reliable tool to identify which meat attachment profiles were associated with different levels of action and intentions to reduce meat consumption. This study was based on the concept of cobenefits, which postulates that reducing meat consumption has both individual and environmental benefits (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003e1. Translation\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe supervised a double translation from Portuguese and English into French, as the MAQ was designed in Portuguese and then translated into English by the same authors. This translation took place in several phases (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) to obtain a literal translation and then a transcultural validation of the MAQ (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe first step was translation from English into French by a professional translator (VB) and a native English speaker (AT) and from Portuguese into French by a native Portuguese speaker (BT).\u003c/p\u003e \u003cp\u003eThe translations were then reviewed by a committee of four English- and Portuguese-speaking researchers (DHH, JHR, JS, BT). As far as possible, we took everyone's comments into account and discussed them within the team to reach a consensus when opinions differed (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe then performed back-translations into English and Portuguese by a professional translator (CH), a native English speaker (CMa) and a native Portuguese speaker (SB) who were not involved in the first phase (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe maintained contact with the authors of the original version of the MAQ throughout the process to clarify any possible concerns. We submitted our translations and back-translations to the extended research team and to the authors of the original MAQ to ensure their concordance (JG) (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003e2. Pretesting \u0026ndash; Cognitive interviews\u003c/b\u003e \u003c/p\u003e \u003cp\u003eCognitive interviews were used to explore face validity. The aim of this phase was to confirm that respondents' understanding of item meanings was similar to the intended meaning (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). This phase was also an essential part of the process of cross-cultural translation validation (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe methodology of this phase complied with the COREQ quality criteria (Consolidated Criteria for Reporting Qualitative Research) (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003ePopulation\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe target population were patients consulting a general practitioner (GP) with a large range of characteristics including age, sex, socioprofessional category, and quantity of meat consumed per week, to ensure maximum diversity in responses.\u003c/p\u003e \u003cp\u003eTo obtain a sample reflecting the target population, we used a snowball sampling technique based on a convenience sample (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e Initially, we selected participants from our own circle (who were also patients of a GP) and inquired them if they knew other participants we could contact. We then contacted them by phone, email or social media.\u003c/p\u003e \u003cp\u003eThe literature does not clearly establish the required number of interviews needed to reach data saturation, but it is generally agreed that conducting 5 to 15 interviews is sufficient. We considered data saturation to have been reached when no further data emerged after two or three interviews (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e The participants provided informed consent before the interview, and they were informed of their right to withdraw at any point during the interview.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eData collection and coding\u003c/span\u003e \u003c/p\u003e \u003cp\u003eAD, BD, and CM conducted the cognitive interviews (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Each participant planned to have a single face-to-face interview, with no third party.\u003c/p\u003e \u003cp\u003eEach question required the participant to read the item aloud and verbalize their thoughts and the reasons for their response using the think-aloud technique (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNext, we asked more specific questions, known as probes (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), to explore particular dimensions of understanding. These questions were selected from the literature (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) and adapted as the interviews proceeded, for example, to explore redundancy (e.g., 'Do you find that this question is almost similar to another question I asked you? '), to clarify the meaning of a word or phrase (e.g., 'How do you understand the meaning of...? '), or to assess whether a question was offensive (e.g., 'Do you find this question offensive? ').\u003c/p\u003e \u003cp\u003eBefore conducting the interviews, we recorded all the above elements in a self-developed interview guide. It also included sociodemographic characteristics to be collected and examples of sentences to be used at the beginning or end of the interview (primers, closing sentences). This approach enabled us to structure the interviews effectively and ensure their reproducibility within the research group (See Additional file 1).\u003c/p\u003e \u003cp\u003eWe recorded the interviews with a voice recorder in combination with handwritten notes and then transcribed and coded the verbatims using a 6-point coding grid (See Additional file 2). We coded these responses as appropriate (code 1) or inappropriate (codes 2 to 6). For example, 2\u0026thinsp;=\u0026thinsp;ambiguous response; 6\u0026thinsp;=\u0026thinsp;nuanced response). Code 5 (interesting answer) was the only one that overlapped with the other codes, so that an item could be coded twice.\u003c/p\u003e \u003cp\u003eWe considered an item to be satisfactory if its adapted response rate (code 1) was greater than 85% (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003e3. Testing phase \u0026ndash; Confirmatory Factorial Analysis and Internal Consistency Analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe methodology for this phase was done in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) quality criteria (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003ePopulation\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe target population was represented by adult patients of any genders consulting a GP (inclusion criteria).\u003c/p\u003e \u003cp\u003eThe exclusion criteria included patients younger than 18 years, patients who did not understand French, and/or patients who were not able to give consent.\u003c/p\u003e \u003cp\u003eThe practices were selected using a cluster random sampling technique (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e), stratified by the place of practice among the Rh\u0026ocirc;ne-Alpes region. For this purpose, we used the freely available 2020 health directory lists of all healthcare professionals (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e), from which we selected the general practices of the Rh\u0026ocirc;ne-Alpes region.\u003c/p\u003e \u003cp\u003eWe aimed to recruit 800 patients (see the \"Statistics\" section) and planned to administer 20 questionnaires per practice. We therefore set the targeted number of practices to 40 and, anticipating 10% participation, randomized 400 practices to account for possible refusals or failures. We stratified our sample using quotas based on the proportion of practices in each department (i.e., Ain, Ard\u0026egrave;che, Dr\u0026ocirc;me, Haute-Savoie, Is\u0026egrave;re, Loire, Rh\u0026ocirc;ne, Savoie) (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eContact methods\u003c/span\u003e \u003c/p\u003e \u003cp\u003eFrom January to March 2023, we contacted first by phone (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) and second by email each randomly selected practice until we met the required number of GPs per department (see the \u0026ldquo;distribution and data collection\u0026rdquo; section).\u003c/p\u003e \u003cp\u003eIf they agreed to participate, we contacted them again to arrange a date for their visit following the randomization protocol explained below. If they refused or if we received no response after three consecutive reminders, we contacted the next practice on the list. We excluded practices that could not be contacted (change of address, end of practice, unassigned number) and practices whose main activity was not general practice.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eData collection\u003c/span\u003e \u003c/p\u003e \u003cp\u003eWe randomized the practices and the day of the visit by a third party and visited (AD, CM, BD, AB) the waiting rooms of the recruited practitioners.\u003c/p\u003e \u003cp\u003eWe distributed the questionnaires to all participants who met the inclusion criteria and met no exclusion criteria. We then asked patients who provided their consent to complete the French version of the MAQ and who stayed in the waiting room to provide further explanations if needed.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eMAQ questionnaire\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe French version of the MAQ designed for distribution to patients comprises 4 dimensions (Hedonism, Affinity, Entitlement and Dependence) divided into 17 items (one more item than the original questionnaire, see below for further explanations), randomly distributed within these dimensions to limit data collection bias (see Aditionnal file 3).\u003c/p\u003e \u003cp\u003eResponses to the 17 questions were given on a five-point Likert scale ranging from 1, strongly disagree, to 5, strongly agree.\u003c/p\u003e \u003cp\u003eSociodemographic data including year of birth, sex, postcode of residence, and socioprofessional category were collected from the INSEE (Institut National de la Statistique et des Etudes Economiques) records. We did not ask about meat consumption, as it was deemed to be sufficiently correlated with the MAQ score already (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eStatistics\u003c/span\u003e \u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eNumber of participants\u003c/span\u003e \u003c/p\u003e \u003cp\u003eSince descriptive analyses require a smaller number of participants (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), we calculated the number of participants to include on the basis of the power required for factorial analyses. Recommendations for factorial analyses do not clearly state the methods for calculating the number of participants to be included (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). However, it is generally accepted that between 300 and 500 participants are sufficient to accurately determine the correlation factors among variables (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Considering the sampling method described above, adjustment for clustering, and potential difficulties in contacting doctors, we decided to recruit 20 participants per practice from 40 practices, for a total of 800 participants.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eDescriptive analysis\u003c/span\u003e \u003c/p\u003e \u003cp\u003eFor each item, we calculated the mean, standard deviation.\u003c/p\u003e \u003cp\u003eThe MAQ score is calculated by measuring the average response to the items, by dimension and in total (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) (See Additional file 4). The score for each dimension and the total score therefore vary from 1 to 5. Each item has the same weight, except for items 15 and 16 (resulting from the division of item 15 into 2 items, following the cognitive interviews), whose score was divided by 2.\u003c/p\u003e \u003cp\u003eThis choice maintained the average of 16 weighting points presented in the Portuguese and English versions of the MAQ, thus maintaining its comparability. The items coded inversely for measuring the subscores and the total score are items #4, #6, #9, #13, and #14 (5 equals 1, 4 equals 2, 3 remains unchanged, 2 equals 4, and 1 equals 5).\u003c/p\u003e \u003cp\u003eWe considered that an item with 95% similar responses was not discriminative and should be deleted (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eCorrelation analysis\u003c/span\u003e \u003c/p\u003e \u003cp\u003eWe used the validscale command (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e) in Stata (statistical data science software) to assess the psychometric properties of the MAQ using classical test theory (CTT). The CTT is a widely used framework for assessing the psychometric properties of measurement instruments and is particularly suitable for validating questionnaires (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo select the most relevant factors and organize them into coherent dimensions, we conducted a reliability study using confirmatory factor analysis (CFA) combined with goodness-of-fit indices. To assess the relevance of the statistical model, we used the root mean square error of approximation (RMSEA) and the comparative fit index (CFI).\u003c/p\u003e \u003cp\u003eThese indices assess the fit between observed and expected data according to the specified model. An RMSEA\u0026thinsp;\u0026lt;\u0026thinsp;0.06 and a CFI\u0026thinsp;\u0026gt;\u0026thinsp;0.90 are generally considered to indicate a good fit (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe used the convdiv option to assess convergent and divergent validities by examining a correlation matrix (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eInternal consistency\u003c/span\u003e \u003c/p\u003e \u003cp\u003eFinally, the internal consistency of the MAQ was validated by calculating Cronbach's alpha and Loevinger's H (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). These are the most commonly used tools for measuring internal consistency in psychometric studies. We used these coefficients to verify the internal consistency of each item within the four dimensions (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA minimum value of 0.70 for Cronbach's alpha and 0.30 for Loevinger's H coefficient was considered acceptable (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eEthics\u003c/span\u003e \u003c/p\u003e \u003cp\u003e We obtained the agreement of an ethics committee on 03/01/2023 and filed an MR004 declaration with the CNIL. All methods were performed in accordance with the declaration of Helsinki and relevant guidelines and regulations, in particular, informed consent was obtained from all participants.\u003c/p\u003e"},{"header":"III. Results","content":"\u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e1 - Translation\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe translation of the MAQ questionnaire into french resulted in a 16-items version with 4 dimensions. No significant issues were encountered during the process, and the original meaning of each item was preserved. The back-translation was submitted back to its original authors, who confirmed its accuracy. Additional file 5 details the first version of the MAQ translated into French.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e2 \u0026ndash; Pretest\u003c/span\u003e \u003c/p\u003e \u003cp\u003eAD, BD and CM contacted 11 individuals, all of whom agreed to participate. Each were given one interview, during an average of 30 minutes each. Each individual was interviewed face to face, in an environment of their choosing : home, worplace, neutral location or by video-conference. No third party was present at the time of the interviews. All participants were French, mostly from urban area, with an average age of 40 years old, 64% of them being women. The sociodemographic characteristics of the participants are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of participants interviewed during the cognitive interviews\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterview\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSex \u0026ndash; Age\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSocio-professional category\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePlace of residence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMeat consumption (frequency)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDuration (minutes)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVideo call\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM \u0026ndash; 65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEngineer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePouanc\u0026eacute; (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF \u0026ndash; 46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCaregiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLyon\u003c/p\u003e \u003cp\u003e(69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVideo call\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM \u0026ndash; 29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eArchitect assistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBrest\u003c/p\u003e \u003cp\u003e(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOutside\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF \u0026ndash; 28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMedicine resident\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLyon (69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHome*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM \u0026ndash; 28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMedicine resident\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParis (75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF \u0026ndash; 55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNurse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLa Verpill\u0026egrave;re (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHome*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF \u0026ndash; 55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePhysiotherapist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eColmar (68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF \u0026ndash; 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMedical student\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLyon (69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHome*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF \u0026minus;\u0026thinsp;28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMedicine resident\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eValvign\u0026egrave;res (07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVideo call\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF \u0026minus;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCNRS researcher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParis suburbs (91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHome*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM \u0026minus;\u0026thinsp;26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCraftsman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eValvign\u0026egrave;res (07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e* : participant\u0026rsquo;s home.\u003c/p\u003e \u003cp\u003eOf the 16 MAQ items, 14 were kept.\u003c/p\u003e \u003cp\u003eThe other two items received only two \u0026ldquo;appropriate responses\u0026rdquo; (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2.1\u003c/span\u003e). We therefore reworked their composition and wording. These adjustments were made in accordance with the participants' comments during the interviews.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2.1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFrequency of code appearance per item in the first 7 interviews (V1 : before modification)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAppropriate response\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmbiguous response\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRedundant response\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOffensive response\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eInformative response\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQualified response\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 5 (V1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 15 (V1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 16 (V1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAdditional file 6 details the verbatims of interest.\u003c/p\u003e \u003cp\u003eFor example, item 5 (\"I love eating meat\"; \u0026ldquo;J\u0026rsquo;adore manger de la viande\u0026rdquo;) was deemed to be similar to items 1 and 10 (verbatims B1.1, B2.1, A1.1, and C1.1) by participants. Item 15 was therefore amended to:\u003c/p\u003e \u003cp\u003e\"I love meals with meat\" (\u0026ldquo;J\u0026rsquo;adore les repas avec de la viande\u0026rdquo;).\u003c/p\u003e \u003cp\u003eItem 15 (\"eating meat is a natural and indisputable practice\"; \u0026ldquo;Manger de la viande est une pratique naturelle et indiscutable\u0026rdquo;) included two different notions: natural and indisputable (verbatims B1.2, B2.2, A3, C1.2, C2). We therefore split the items in two, leading the total number of items to 17, in agreement with the initial authors.\u003c/p\u003e \u003cp\u003eIt should be noted that items 3 and 7 sometimes led to nuanced responses due to questioning about the notion of \"right\" (verbatim B1.3 and B1.4).\u003c/p\u003e \u003cp\u003eItem 6 was considered offensive on two occasions (verbatims A1.3 and A2). However, this did not lead to any changes because of the sufficient number of appropriate responses.\u003c/p\u003e \u003cp\u003eFinally, item 10 was considered redundant with items 5 and 15, but only before they were modified (verbatims A1.1, C1.1). We therefore did not need to reword it. Of the seventeen items of the modified MAQ proposed in the last four interviews, all received three to four appropriate responses (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2.2\u003c/span\u003e). We therefore considered them to be clear to the population concerned. Additional file 3 details the modified French version of the 17-item MAQ.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2.2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFrequency of code appearance per item in the last 4 interviews (V2 : after modification)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAppropriate response\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmbiguous response\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRedundant response\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOffensive response\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eInformative response\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQualified response\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 5 (V2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 15 (V2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 16\u003c/p\u003e \u003cp\u003e(V2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem 17 (=\u0026thinsp;16 from V1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e3 \u0026ndash; Testing phase\u003c/span\u003e \u003c/p\u003e \u003cp\u003eFigure 3 illustrates the study's patient inclusion flowchart. Out of 194 eligible practices, 44 (22.6% participation rate) agreed to participate, while 115 practices declined or did not respond after three calls, and 35 were excluded.\u003c/p\u003e \u003cp\u003eUltimately, we visited 39 practices where 974 patients were interviewed and 5 won\u0026rsquo;t be as we the quota was already reached. A total of 97 declined, and 55 were excluded. A total of 822 patients took the questionnaire (84.4% participation rate). A total of 822 questionnaires were analysed.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 3 \u0026ndash; Patient inclusion flow-chart\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e details the characteristics of the participants, who were primarily urban (65%), had a median age of 52 years (IQR\u0026thinsp;=\u0026thinsp;31, min\u0026ndash;max\u0026thinsp;=\u0026thinsp;20\u0026ndash;93), and were predominantly women (65%). The main socioprofessional categories were retirees (32.1%), employees (27.6%), and managers (20.2%).\u003c/p\u003e \u003cp\u003e\u003cimg 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\" width=\"632\" height=\"476\"\u003e\u003c/p\u003e\u003cp\u003eThe descriptive statistics in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e4\u003c/span\u003e show that the average item scores were 2.4 to 4.2, with no floor or ceiling effects. For item 13,53% of respondents \u0026ldquo;completely agree[d]\u0026rdquo;.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive characteristics of each item submitted to 822 general practice patients during the test phase\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u0026deg;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (SD) [IC 95%]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean with inverse coding\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManger de la viande est un des bons plaisirs de la vie\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.74 (1.09) [3.67\u0026ndash;3.82]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRien ne peut remplacer la viande dans mon alimentation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.45 (1.22) [2.36\u0026ndash;2.53]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDu fait de notre place dans la cha\u0026icirc;ne alimentaire, nous avons le droit de manger de la viande\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.49 (1.14) [3.41\u0026ndash;3.57]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJe me sens mal \u0026agrave; l\u0026rsquo;id\u0026eacute;e de manger de la viande\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.98 (1.16) [1.90\u0026ndash;2.06]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJ\u0026rsquo;adore les repas avec de la viande\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.48 (1.13) [3.40\u0026ndash;3.56]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManger de la viande est irrespectueux de la vie et de l\u0026rsquo;environnement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.40 (1.17) [2.32\u0026ndash;2.48]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManger de la viande est un droit incontestable de chaque personne\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.50 (1.24) [3.41\u0026ndash;3.58]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRien ne vaut un bon steak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.99 (1.26) [2.91\u0026ndash;3.08]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUne alimentation sans viande me conviendrait tr\u0026egrave;s bien\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.96 (1.26) [2.88\u0026ndash;3.05]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJe raffole de la viande\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.93 (1.22) [2.85\u0026ndash;3.01]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSi je ne pouvais pas manger de viande, je me sentirais faible\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.36 (1.15) [2.28\u0026ndash;2.44]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSi on m\u0026rsquo;obligeait \u0026agrave; cesser de manger de la viande, je serais triste\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e820\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.78 (1.37) [2.69\u0026ndash;2.88]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLa viande me fait penser \u0026agrave; des maladies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.80 (1.03) [1.73\u0026ndash;1.87]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEn mangeant de la viande, je pense \u0026agrave; la mort et \u0026agrave; la souffrance des animaux\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.31 (1.23) [2.22\u0026ndash;2.39]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManger de la viande est une pratique naturelle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.67 (1.03) [3.60\u0026ndash;3.74]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManger de la viande est une pratique indiscutable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.76 (1.14) [2.69\u0026ndash;2.84]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJe ne me vois pas ne pas manger de viande r\u0026eacute;guli\u0026egrave;rement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.93 (1.28) [2.85\u0026ndash;3.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe obtained a mean MAQ score of 2.95 (SD\u0026thinsp;=\u0026thinsp;0.45), with a normal distribution, for a score ranging theoretically from 1 (low attachment to meat) to 5 (high attachment to meat) (Fig.\u0026nbsp;4).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 4 - MAQ total score distribution chart\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e details the confirmatory factor analysis results, with the correlation coefficients per item and per factor. These factors helped us identify 4 factors. The RMSEA and CFI were 0.06 and 0.92, respectively, indicating an acceptable fit.\u003c/p\u003e \u003cp\u003eEach of the 4 factors included items whose themes were consistent. Factor 1 (\u0026ldquo;Hedonism\u0026rdquo;) combined items 1, 5, 8 and 10. Factor 2 (\u0026ldquo;Affinity\u0026rdquo;) combined items 4, 6, 13 and 14. Factor 3 (\u0026ldquo;Entitlement\u0026rdquo;) included items 3, 7, 15 and 16. Finally, Factor 4 (\u0026ldquo;Dependence\u0026rdquo;) combined items 2, 9, and 11 and 12 and 17. The French translations are available in Additional file 4. Notably, most items, excluding 4, 6, 7, 13, and 14, demonstrated correlations with multiple factors. We allocated them to the dimension with the strongest correlation or the most conceptually consistent meaning, a categorization consistent with the MAQ source study.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u0026ndash; Confirmatory factor analysis for the French version of the four-dimensional MAQ-17 questionnaire (n\u0026thinsp;=\u0026thinsp;822)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eItems\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eFactors*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 Manger de la viande est un des bons plaisirs de la vie\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.499\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5 J\u0026rsquo;adore les repas avec de la viande\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.527\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8 Rien ne vaut un bon steak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.497\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.590\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10 Je raffole de la viande\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.854\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.602\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4 Je me sens mal \u0026agrave; l\u0026rsquo;id\u0026eacute;e de manger de la viande\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6 Manger de la viande est irrespectueux de la vie et de l\u0026rsquo;environnement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13 La viande me fait penser \u0026agrave; des maladies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.692\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14 En mangeant de la viande, je pense \u0026agrave; la mort et \u0026agrave; la souffrance des animaux\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3 Du fait de notre place dans la cha\u0026icirc;ne alimentaire, nous avons le\u003c/p\u003e \u003cp\u003edroit de manger de la viande\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7 Manger de la viande est un droit incontestable de chaque personne\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15 Manger de la viande est une pratique naturelle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16 Manger de la viande est une pratique indiscutable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.447\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 Rien ne peut remplacer la viande dans mon alimentation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.717\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9 Une alimentation sans viande me conviendrait tr\u0026egrave;s bien\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.707\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11 Si je ne pouvais pas manger de viande, je me sentirais faible\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.721\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12 Si on m\u0026rsquo;obligeait \u0026agrave; cesser de manger de la viande, je serais triste\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.785\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17 Je ne me vois pas ne pas manger de viande r\u0026eacute;guli\u0026egrave;rement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,617\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e* factors obtaining more than 0.4 are displayed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e6\u003c/span\u003e demonstrates the internal consistency of the four-dimensional model, with Cronbach's alpha and Loevinger's H coefficients exceeding 0.7 and 0.3, respectively (0.84 and 0.61 for Hedonism, 0.72 and 0.42 for Affinity, 0.71 and 0.41 for Entitlement, and 0.75 and 0.40 for Dependence).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInternal consistency (Cronbach's Alpha and H. Loevinger's coefficients) by MAQ dimension\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDimension\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u0026deg; Item\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCronbach's Alpha (N\u0026thinsp;=\u0026thinsp;822)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eH. Loevinger\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHedonism*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u0026nbsp;; 5 ; 8 ; 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAffinity*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 ; 6 ; 13 ; 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEntitlement*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 ; 7 ; 15 ; 16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDependence*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 ; 9 ; 11 ; 12 ; 17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"IV. Discussion","content":"\u003cp\u003eFrom a planetary health perspective, the validation of the French version of the MAQ makes it possible to consider and encourage its use to explore adult patients’ attachment to meat in general practice.\u003c/p\u003e\n\u003cp\u003eThe MAQ discriminates between patient groups effectively (24,27,51). The MAQ is also effective in measuring and predicting people's motivations and intentions to change meat consumption (24,27,51). It is therefore an effective research tool, alone or in combination with other scores, for identifying groups with common characteristics with regard to reducing meat consumption (in terms of motivations, barriers and intentionality).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe applications could vary.\u003c/p\u003e\n\u003cp\u003eFurther studies could be carried out to verify its validity in other French-speaking populations, its reproducibility and its stability over time. Research is also needed to validate its application in minor patients, whose specificities will probably require the MAQ to be adapted or completed by their parents (57). Among other scores, combining the Food Neophobia Scale (FNS), a validated and widely used tool which measures the personal reluctance to accept and/or enjoy new or unfamiliar foods (58,59) with the MAQ could predict the acceptability of vegetarian alternatives, aiding intervention design (60). The Nutrinet Santé score (61) assesses the effectiveness of interventions on intentional or actual meat product purchases.\u003c/p\u003e\n\u003cp\u003eIn addition, given that the MAQ questionnaire was developed by studying people's obstacles and incentives, it aligns closely with the concerns they might have. Its simplicity makes it a useful tool for GPs and health professionals to explore representations of meat-based diets and planetary health. Completing the MAQ in waiting rooms could initiate discussions during consultations. As nutrition becomes a public health concern (3,63), the MAQ could also be an interesting gateway to a broader nutritional approach.\u003c/p\u003e\n\u003cp\u003eWith its high reproducibility in American studies, the MAQ can measure interventions aimed at reducing meat consumption. It has been used to assess the impact of graphic awareness messages (Koch et al., 64), the visual attractiveness of vegetarian substitutes (Ding et al., 65), consumer demand for vegetarian steaks (Bryant et al., 60), the evolution of meat representations (Verain et al., 66), and 'Meat Paradox' intensity (wanting to eat meat but being against animal suffering) (Dowset et al., 67).\u003c/p\u003e\n\u003cp\u003eFinally, from a public health perspective, the MAQ would make it possible to better target the profiles of hedonism, affinity, entitlement and dependence on meat products in the general population. This could be a first step towards developing appropriate population-based strategies to reduce meat proportions in the French diet.\u003c/p\u003e"},{"header":"V. Conclusion","content":"\u003cp\u003eThis study is part of a global health dynamic. Reducing meat consumption is a cobenefit for both individual and environmental health.\u003c/p\u003e\n\u003cp\u003eWe translated and validated the French version of the MAQ in a population of general practice patients. We obtained a 17-item and 4-dimensional questionnaire.\u003c/p\u003e\n\u003cp\u003eThe French version of the MAQ has various possible applications. The use of the French version of the MAQ could fit various strategies aimed at reducing meat consumption. At the GP practice, the MAQ could be used by GPs, medical assistants, public health nurses or advanced practice nurses to explore their patients' representations to encourage behavioural change. From a public health perspective, the MAQ could be used to better target profiles of hedonism, affinity, entitlement and dependence on meat products in the general population, a preliminary step toward developing appropriate population-based strategies to reduce the proportion of meat products in the diet of the French population.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cu\u003eEthics approval and consent to participate\u003c/u\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe study was approved by the Research Ethics Committee of the University College of General Practice, Claude Bernard University (Project-ID IRB 2023-01-03-01). Written informed consent (i.e. consent to participate) was obtained from all study participants. Collected data remained confidential. Each patient was represented by a unique anonymous identification code in order to ensure confidentiality.\u0026nbsp;\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cu\u003eConsent for publication\u003c/u\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eNA\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cu\u003eAvailability of data and materials\u003c/u\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author (HM) upon reasonable request\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cu\u003eCompeting interests\u003c/u\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cu\u003eFunding\u003c/u\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eInstitutional funding from the Faculty of Medicine, University of Geneva, supported this project.\u0026nbsp;\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cu\u003eAuthors' contributions\u003c/u\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eHM, BT, BD, CM, AD and TB contributed to the conception and design of the research project. BD, CM, AD, AB performed the data collection. PS participated in the statistical analyses and interpretation of the data, prepared the figures and tables. BD wrote the original draft and revised the manuscript. HM conceptualised and designed the research project, gave final approval of the different steps described in the method section, and was involved in reviewing the manuscript. HM, BT, BD, CM, AD and TB participated in the interpretation of the data. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003e\u003cu\u003eAcknowledgements\u003c/u\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe authors would like to sincerely thank all the collaborating GP practices and patients, as well as Mohamed Amir Moussa, administrative research assistant, for their precious contribution to the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFood and Agriculture Organization of the United Nations (2023).\u003c/li\u003e\n\u003cli\u003eLa consommation de viande en France en 2022|Agreste, la statistique agricole [Internet]. Disponible sur : https://agreste.agriculture.gouv.fr/agreste-web/download/publication/publie/SynCsm23412/consyn412202307-ConsoViande.pdf\u003c/li\u003e\n\u003cli\u003eSPF. L\u0026rsquo;essentiel des recommandations sur l\u0026rsquo;alimentation [Internet]. [cit\u0026eacute; 23 avr 2023]. Disponible sur: https://www.santepubliquefrance.fr/import/l-essentiel-des- recommandations-sur-l-alimentation\u003c/li\u003e\n\u003cli\u003eCanada H. Canada Food Guide. 2020 [cit\u0026eacute; 23 avr 2023]. Make it a habit to eat vegetables, fruits, whole grains and protein foods. Disponible sur: https://food- guide.canada.ca/en/healthy-eating-recommendations/make-it-a-habit-to-eat-vegetables- fruit-whole-grains-and-protein-foods/\u003c/li\u003e\n\u003cli\u003e2020-2025 Dietary Guidelines for Americans Recommendations [Internet]. [cit\u0026eacute; 25 juin 2023]. Disponible sur: https://www.pcrm.org/good-nutrition/nutrition-programs- policies/2020-2025-dietary-guidelines\u003c/li\u003e\n\u003cli\u003ePereira PM de CC, Vicente AF dos RB. Meat nutritional composition and nutritive role in the human diet. Meat Sci. mars 2013;93(3):586‑92.\u003c/li\u003e\n\u003cli\u003eAbete I, Romaguera D, Vieira AR, Munain AL de, Norat T. Association between total, processed, red and white meat consumption and all-cause, CVD and IHD mortality: a meta- analysis of cohort studies. British Journal of Nutrition. sept 2014;112(5):762‑75.\u003c/li\u003e\n\u003cli\u003eSinha R, Cross AJ, Graubard BI, Leitzmann MF, Schatzkin A. Meat Intake and Mortality: A Prospective Study of Over Half a Million People. Archives of Internal Medicine. 23 mars 2009;169(6):562‑71.\u003c/li\u003e\n\u003cli\u003eIqbal R, Dehghan M, Mente A, Rangarajan S, Wielgosz A, Avezum A, et al. Associations of unprocessed and processed meat intake with mortality and cardiovascular disease in 21 countries [Prospective Urban Rural Epidemiology (PURE) Study]: a prospective cohort study. The American Journal of Clinical Nutrition. 1 sept 2021;114(3):1049‑58.\u003c/li\u003e\n\u003cli\u003eChen GC, Lv DB, Pang Z, Liu QF. Red and processed meat consumption and risk of stroke: a meta-analysis of prospective cohort studies. Eur J Clin Nutr. janv 2013;67(1):91‑5.\u003c/li\u003e\n\u003cli\u003eMicha R, Wallace SK, Mozaffarian D. Red and processed meat consumption and risk of incident coronary heart disease, stroke, and diabetes: A systematic review and meta- analysis. Circulation. 1 juin 2010;121(21):2271‑83.\u003c/li\u003e\n\u003cli\u003eBouvard V, Loomis D, Guyton KZ, Grosse Y, Ghissassi FE, Benbrahim-Tallaa L, et al. Carcinogenicity of consumption of red and processed meat. Lancet Oncol. d\u0026eacute;c 2015;16(16):1599‑600.\u003c/li\u003e\n\u003cli\u003ePan A, Sun Q, Bernstein AM, Schulze MB, Manson JE, Willett WC, et al. Red meat consumption and risk of type 2 diabetes: 3 cohorts of US adults and an updated meta- analysis. Am J Clin Nutr. oct 2011;94(4):1088‑96.\u003c/li\u003e\n\u003cli\u003eMyers SS, Bernstein A. The coming health crisis: indirect health effects of global climate change. F1000 Biol Rep. 1 f\u0026eacute;vr 2011;3:3.\u003c/li\u003e\n\u003cli\u003eWillett W, Rockstr\u0026ouml;m J, Loken B, Springmann M, Lang T, Vermeulen S, et al. Food in the Anthropocene: the EAT\u0026ndash;Lancet Commission on healthy diets from sustainable food systems. The Lancet. 2 f\u0026eacute;vr 2019;393(10170):447‑92.\u003c/li\u003e\n\u003cli\u003ePoore J, Nemecek T. Reducing food\u0026rsquo;s environmental impacts through producers and consumers. Science. juin 2018;360(6392):987‑92.\u003c/li\u003e\n\u003cli\u003eVanham D, Mekonnen MM, Hoekstra AY. The water footprint of the EU for different diets. Ecological Indicators. sept 2013;32:1‑8.\u003c/li\u003e\n\u003cli\u003eClark MA, Springmann M, Hill J, Tilman D. Multiple health and environmental impacts of foods. Proceedings of the National Academy of Sciences. 12 nov 2019;116(46):23357‑62.\u003c/li\u003e\n\u003cli\u003eGerber PJ, Food and Agriculture Organization of the United Nations, \u0026eacute;diteurs. Tackling climate change through livestock: a global assessment of emissions and mitigation opportunities. Rome: Food and Agriculture Organization of the United Nations; 2013. 115 p.\u003c/li\u003e\n\u003cli\u003eFaire sa part ? | Carbone 4 [Internet]. [cit\u0026eacute; 23 avr 2023]. Disponible sur: https://carbone4.com/fr/publication-faire-sa-part\u003c/li\u003e\n\u003cli\u003eHolguera JG, Senn N. Co b\u0026eacute;n\u0026eacute;fices sant\u0026eacute;-environnement et changement climatique : concepts et implication pour l\u0026rsquo;alimentation, la mobilit\u0026eacute; et le contact avec la nature en pratique clinique. La Presse M\u0026eacute;dicale Formation. 1 d\u0026eacute;c 2021;2(6):622‑7.\u003c/li\u003e\n\u003cli\u003eAjzen I. The theory of planned behavior. Organizational Behavior and Human Decision Processes. 1 d\u0026eacute;c 1991;50(2):179‑211.\u003c/li\u003e\n\u003cli\u003eBerndsen M, van der Pligt J. Ambivalence towards meat. Appetite. 2004;42(1):71‑8.\u003c/li\u003e\n\u003cli\u003eGra\u0026ccedil;a J, Calheiros MM, Oliveira A. Attached to meat? (Un)Willingness and intentions to adopt a more plant-based diet. Appetite. 1 d\u0026eacute;c 2015;95:113‑25.\u003c/li\u003e\n\u003cli\u003ePovey R, Wellens B, Conner M. Attitudes towards following meat, vegetarian and vegan diets: an examination of the role of ambivalence. Appetite. 1 ao\u0026ucirc;t 2001;37(1):15‑26.\u003c/li\u003e\n\u003cli\u003eSaba A, Di Natale R. A study on the mediating role of intention in the impact of habit and attitude on meat consumption. Food Quality and Preference. 9 oct 1998;10(1):69‑77.\u003c/li\u003e\n\u003cli\u003eLentz G, Connelly S, Mirosa M, Jowett T. Gauging attitudes and behaviours: Meat consumption and potential reduction. Appetite. 1 ao\u0026ucirc;t 2018;127:230‑41.\u003c/li\u003e\n\u003cli\u003eSousa VD, Rojjanasrirat W. Translation, adaptation and validation of instruments or scales for use in cross-cultural health care research: a clear and user-friendly guideline. J Eval Clin Pract. avr 2011;17(2):268‑74.\u003c/li\u003e\n\u003cli\u003eNapoles-Springer AM, Santoyo-Olsson J, O\u0026rsquo;Brien H, Stewart AL. Using Cognitive Interviews to Develop Surveys in Diverse Populations: Medical Care. nov 2006;44(Suppl 3):S21‑30.\u003c/li\u003e\n\u003cli\u003eGuillemin F, Bombardier C, Beaton D. Cross-cultural adaptation of health-related quality of life measures: literature review and proposed guidelines. J Clin Epidemiol. d\u0026eacute;c 1993;46(12):1417‑32.\u003c/li\u003e\n\u003cli\u003eArtino AR, La Rochelle JS, Dezee KJ, Gehlbach H. Developing questionnaires for educational research: AMEE Guide No. 87. Med Teach. juin 2014;36(6):463‑74.\u003c/li\u003e\n\u003cli\u003eGedda M. Traduction fran\u0026ccedil;aise des lignes directrices ENTREQ pour l\u0026rsquo;\u0026eacute;criture et la lecture des synth\u0026egrave;ses de recherche qualitative. Kin\u0026eacute;sith\u0026eacute;rapie, la Revue. 1 nov 2014;15.\u003c/li\u003e\n\u003cli\u003eNaderifar M, Goli H, Ghaljaei F. Snowball Sampling: A Purposeful Method of Sampling in Qualitative Research. Strides in Development of Medical Education. 30 sept 2017;In Press.\u003c/li\u003e\n\u003cli\u003eBeatty PC, Willis GB. Research Synthesis: The Practice of Cognitive Interviewing. Public Opinion Quarterly. 1 janv 2007;71(2):287‑311.\u003c/li\u003e\n\u003cli\u003eCastillo-D\u0026iacute;az M, Padilla JL. How cognitive interviewing can provide validity evidence of the response processes to scale items. Social Indicators Research. 2013;114:963‑75.\u003c/li\u003e\n\u003cli\u003eGedda M. Traduction fran\u0026ccedil;aise des lignes directrices STROBE pour l\u0026rsquo;\u0026eacute;criture et la lecture des \u0026eacute;tudes observationnelles. Kin\u0026eacute;sith\u0026eacute;rapie, la Revue. janv 2015;15(157):34‑8.\u003c/li\u003e\n\u003cli\u003eKillip S, Mahfoud Z, Pearce K. What is an intracluster correlation coefficient? Crucial concepts for primary care researchers. Ann Fam Med. 2004;2(3):204‑8.\u003c/li\u003e\n\u003cli\u003eExtractions en libre acc\u0026egrave;s - L\u0026rsquo;Annuaire Sant\u0026eacute; [Internet]. [cit\u0026eacute; 27 avr 2023]. Disponible sur: https://annuaire.sante.fr/web/site-pro/extractions-publiques\u003c/li\u003e\n\u003cli\u003eTreweek S, Pitkethly M, Cook J, Fraser C, Mitchell E, Sullivan F, et al. Strategies to improve recruitment to randomised trials. Cochrane Database of Systematic Reviews [Internet]. 2018 [cit\u0026eacute; 27 avr 2023];(2). Disponible sur: https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.MR000013.pub6/full\u003c/li\u003e\n\u003cli\u003eAnthoine E, Moret L, Regnault A, S\u0026eacute;bille V, Hardouin JB. Sample size used to validate a scale: a review of publications on newly-developed patient reported outcomes measures. Health Qual Life Outcomes. 9 d\u0026eacute;c 2014;12:2.\u003c/li\u003e\n\u003cli\u003eRouquette A, Falissard B. Sample size requirements for the internal validation of psychiatric scales. Int J Methods Psychiatr Res. d\u0026eacute;c 2011;20(4):235‑49.\u003c/li\u003e\n\u003cli\u003eHaller DM, Meynard A, Pejic D, Sredic A, Huseinagic S, Courvoisier DS, et al. YFHS- WHO+ Questionnaire: validation of a measure of youth-friendly primary care services. J Adolesc Health. nov 2012;51(5):422‑30.\u003c/li\u003e\n\u003cli\u003ePerrot B, Bataille E, Hardouin JB. validscale: A Command to Validate Measurement Scales. The Stata Journal. 1 mars 2018;18(1):29‑50.\u003c/li\u003e\n\u003cli\u003eDevellis R. Scale development: Theory and applications. SAGE. 2017.\u003c/li\u003e\n\u003cli\u003eGadelrab H. Evaluating the fit of structural equation models: Sensitivity to specification error and descriptive goodness-of-fit Indices. 2013.\u003c/li\u003e\n\u003cli\u003eDima AL. Scale validation in applied health research: tutorial for a 6-step R-based psychometrics protocol. Health Psychol Behav Med. 10 mai 2018;6(1):136‑61.\u003c/li\u003e\n\u003cli\u003eKline P. The handbook of psychological testing, 2nd ed. Florence, KY, US: Taylor \u0026amp; Frances/Routledge; 1993. vii, 744 p. (The handbook of psychological testing, 2nd ed).\u003c/li\u003e\n\u003cli\u003eNunally J. Psychometric theory. McGraw-Hill. 1978.\u003c/li\u003e\n\u003cli\u003eLoevinger J. The technic of homogeneous tests compared with some aspects of scale analysis and factor analysis. Psychol Bull. nov 1948;45(6):507‑29.\u003c/li\u003e\n\u003cli\u003eDe Backer C, Erreygers S, De Cort C, Vandermoere F, Dhoest A, Vrinten J, et al. Meat and masculinities. Can differences in masculinity predict meat consumption, intentions to reduce meat and attitudes towards vegetarians? Appetite. 1 avr 2020;147:104559.\u003c/li\u003e\n\u003cli\u003eLacroix K, Gifford R. Targeting interventions to distinct meat-eating groups reduces meat consumption. Food Quality and Preference. 1 d\u0026eacute;c 2020;86:103997.\u003c/li\u003e\n\u003cli\u003eBottemine T. Traduction de la Working Alliance Inventory Short Version (WAI SR) en fran\u0026ccedil;ais par une m\u0026eacute;thode de consensus Delphi avec une traduction Aller/Retour.\u003c/li\u003e\n\u003cli\u003eHatcher L. A Step-by-Step Approach to Using the SAS System for Factor Analysis and Structural Equation Modeling. 1st \u0026eacute;d. SAS Publishing; 1994. 608 p.\u003c/li\u003e\n\u003cli\u003eLetrilliart L, Supper I, Schuers M, Darmon D, Boulet P, Favre M, et al. ECOGEN : \u0026eacute;tude des El\u0026eacute;ments de la COnsultation en m\u0026eacute;decine GEN\u0026eacute;rale. Exercer, la revue Fran\u0026ccedil;aise de m\u0026eacute;decine g\u0026eacute;n\u0026eacute;rale. 2014;25:148.\u003c/li\u003e\n\u003cli\u003eLemale J, Mas E, Jung C, Bellaiche M, Tounian P, French-speaking Pediatric Hepatology, Gastroenterology and Nutrition Group (GFHGNP). Vegan diet in children and adolescents. Recommendations from the French-speaking Pediatric Hepatology, Gastroenterology and Nutrition Group (GFHGNP). Arch Pediatr. oct 2019;26(7):442‑50.\u003c/li\u003e\n\u003cli\u003eGrant JD. Time for change: Benefits of a plant-based diet. Can Fam Physician. oct 2017;63(10):744‑6.\u003c/li\u003e\n\u003cli\u003eErhardt J, Olsen A. Meat Reduction in 5 to 8 Years Old Children\u0026mdash;A Survey to Investigate the Role of Parental Meat Attachment. Foods. ao\u0026ucirc;t 2021;10(8):1756.\u003c/li\u003e\n\u003cli\u003ePliner P, Hobden K. Development of a scale to measure the trait of food neophobia in humans. Appetite. oct 1992;19(2):105‑20.\u003c/li\u003e\n\u003cli\u003eRabad\u0026aacute;n A, Bernabeu R. A systematic review of studies using the Food Neophobia Scale: Conclusions from thirty years of studies. Food Quality and Preference. 1 mars 2021;104241.\u003c/li\u003e\n\u003cli\u003eBryant C, Szejda K, Parekh N, Deshpande V, Tse B. A Survey of Consumer Perceptions of Plant-Based and Clean Meat in the USA, India, and China. Frontiers in Sustainable Food Systems [Internet]. 2019 [cit\u0026eacute; 20 f\u0026eacute;vr 2022];3. Disponible sur: https://www.frontiersin.org/article/10.3389/fsufs.2019.00011\u003c/li\u003e\n\u003cli\u003eBienvenue sur le site institutionnel de l\u0026rsquo;\u0026eacute;tude NutriNet-Sant\u0026eacute; | Site institutionnel de l\u0026rsquo;\u0026eacute;tude NutriNet-Sant\u0026eacute; [Internet]. [cit\u0026eacute; 25 juin 2023]. Disponible sur: https://info.etude- nutrinet-sante.fr/siteinfo/article/52\u003c/li\u003e\n\u003cli\u003eGra\u0026ccedil;a J, Oliveira A, Calheiros MM. Meat, beyond the plate. Data-driven hypotheses for understanding consumer willingness to adopt a more plant-based diet. Appetite. juill 2015;90:80‑90.\u003c/li\u003e\n\u003cli\u003eAlimentation saine [Internet]. [cit\u0026eacute; 25 juin 2023]. Disponible sur: https://www.who.int/fr/news-room/fact-sheets/detail/healthy-diet\u003c/li\u003e\n\u003cli\u003eKoch JA, Bolderdijk JW, van Ittersum K. Can graphic warning labels reduce the consumption of meat? Appetite. 1 janv 2022;168:105690.\u003c/li\u003e\n\u003cli\u003eDing YY (Elaina), Huang Y, Ku HP (Grace), Lim K, Lin T. Plant Based Diets : Sensory Attractiveness Increases Acceptability of Meat Substitutes [Internet]. 2018 [cit\u0026eacute; 20 f\u0026eacute;vr 2022]. Disponible sur: https://open.library.ubc.ca/soa/cIRcle/collections/undergraduateresearch/18861/items/1.0 375709\u003c/li\u003e\n\u003cli\u003eVerain MCD, Dagevos H, Jaspers P. Flexitarianism in the Netherlands in the 2010 decade: Shifts, consumer segments and motives. Food Quality and Preference. 1 mars 2022;96:104445.\u003c/li\u003e\n\u003cli\u003eDowsett E, Semmler C, Bray H, Ankeny RA, Chur-Hansen A. Neutralising the meat paradox: Cognitive dissonance, gender, and eating animals. Appetite\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5245290/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5245290/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMeat consumption has significant implications for both individual health and the environment. Understanding individuals' attachment to meat is crucial for designing effective interventions to reduce consumption. The MAQ is a tool developed to assess individuals' attachment to meat.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study aims to translate and validate the MAQ into French for use in a general practice population in France.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe study was conducted in three phases: translation, pretesting through cognitive interviews, and testing through a cross-sectional study of general practice patients. Descriptive, factorial, and internal consistency analyses were performed to validate the French version of the MAQ.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe French version of the MAQ consists of 17 items in four dimensions: Hedonism, Affinity, Entitlement, and Dependence. Face validity was confirmed by cognitive interviews. The RMSEA and CFI were 0.06 and 0.92 respectively, showing acceptable goodness-of-fit. Internal consistency was demonstrated with Cronbach's alpha and Loevinger's H coefficients exceeding 0.7 and 0.3, respectively.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe French version of the MAQ is a valid and reliable tool for assessing individuals' attachment to meat in a general practice population. Its application shows promise for the design of targeted interventions to reduce meat consumption, benefiting both individual health and environmental sustainability.\u003c/p\u003e","manuscriptTitle":"Translation and validation of the meat attachment questionnaire (MAQ) in a French General Practice Population","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-26 06:06:16","doi":"10.21203/rs.3.rs-5245290/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-26T11:02:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-25T11:41:59+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-31T12:12:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"42656319902867850715825399884986640603","date":"2024-10-22T14:14:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"310841173322780500287313776460620233397","date":"2024-10-21T10:34:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-10-17T13:39:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-17T11:47:50+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-10-17T08:45:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-10-17T08:43:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-10-11T10:08:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"53977795-a3a3-48a8-9ca6-b9a7ad9daf9e","owner":[],"postedDate":"December 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":40773788,"name":"Health sciences/Medical research/Epidemiology"},{"id":40773789,"name":"Earth and environmental sciences/Environmental social sciences/Psychology and behaviour"}],"tags":[],"updatedAt":"2025-01-20T15:59:04+00:00","versionOfRecord":{"articleIdentity":"rs-5245290","link":"https://doi.org/10.1038/s41598-025-86270-x","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-01-18 15:56:57","publishedOnDateReadable":"January 18th, 2025"},"versionCreatedAt":"2024-12-26 06:06:16","video":"","vorDoi":"10.1038/s41598-025-86270-x","vorDoiUrl":"https://doi.org/10.1038/s41598-025-86270-x","workflowStages":[]},"version":"v1","identity":"rs-5245290","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5245290","identity":"rs-5245290","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}