How do the characteristics of a meal influence consumer preferences: a systematic literature review of studies using stated choice methods

How do the characteristics of a meal influence consumer preferences: a systematic literature review of studies using stated choice methods | 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 Systematic Review How do the characteristics of a meal influence consumer preferences: a systematic literature review of studies using stated choice methods Nafsika Afentou, Emma Frew, Lin Fu, Irina Pokhilenko This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7714370/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background. Food preferences are influenced by habits, past experiences, socioeconomic and cultural factors. While much research has focused on individual food items, meal preferences involve a more complex decision-making process influenced by intrinsic and extrinsic factors. It remains unclear how perceptions of taste, healthiness, price, time, and other features are traded off when making meal choices. Understanding these factors is essential for informing food system policies that promote healthier diets and improve well-being. This study systematically reviewed stated choice experiments to identify attributes used to elicit meal preferences and to assess methodological characteristics of these studies. Methods. Seven databases (Web of Science, Scopus, Medline, Embase, PsychINFO, EconLit, and CINAHL) were searched. General and methodological study characteristics were extracted and summarised narratively, while meal attributes and levels were synthesised into themes. Results. Of 9,621 studies screened, 28 met the inclusion criteria, including 9 discrete choice experiments (DCEs), 9 conjoint analyses, 7 best-worst scaling, and 4 using other variations of stated choice methods. These studies elicited preferences across diverse settings (households, restaurants, care homes and prisons) and meal types (breakfast, lunch, dinner, specific dishes, and menus). Attributes were grouped into 13 categories, with 22 subcategories spanning intrinsic features (e.g., taste, ingredients, healthiness) and extrinsic features (e.g. price, convenience, sustainability, ethical aspects). Methodological limitations included inconsistent reporting and limited transparency in study design. Discussion. This is the first review to synthesise applications of stated choice methods for meal preferences rather than single food product preferences. The findings provide a comprehensive attribute framework that can inform research and standardisation of stated choice studies in nutrition. Addressing the methodological inconsistencies identified through clearer reporting and standardisation will strengthen the validity and comparability of evidence. This is critical for generating robust insights into meal preferences, supporting the design of food system policies that foster healthier and more sustainable diets and help reduce nutrition-related health inequalities. meal preferences food stated choice methods discrete choice experiment meal attributes Figures Figure 1 Introduction Meal choices are an integral part of daily life. They are influenced by a wide range of factors, including habits, past experiences, availability of options and resources such as time and money, as well as socioeconomic and cultural factors ( 1 ). In recent years, the food sector has expanded significantly, and meal choices are often made in out of home settings such as schools, restaurants, and workplaces. It is well-established that dietary habits directly impact health, with poor nutrition leading to adverse health outcomes such as obesity, cancer, and depression ( 2 , 3 ). Beyond health effects, poor dietary habits also lead to economic consequences such as lower educational attainment and reduced workplace productivity ( 4 ). Understanding the motivations behind meal choices can help shape health and well-being policies for the food environment. It is important to distinguish between a meal and an individual food product, as they are conceptually different and involve distinct preferences. In this study, a meal is defined as an eating occasion that includes multiple food items consumed together at different times of the day. This contrasts with individual food items eaten separately, which do not constitute a complete meal. The choice of a meal involves a complex decision-making process influenced by several interacting factors ( 5 ). While the choice of specific food products, such as meat, fruit and vegetables, or seafood are influenced by factors such as processing ( 6 ), seasonality ( 7 ), or eco-certification ( 8 ), meal preferences are shaped by a broader range of intrinsic and extrinsic factors. Examples of these intrinsic factors include taste of combined elements, appearance or meal composition ( 9 ). Extrinsic factors include nutritional menu labelling ( 10 ), variety ( 11 ), availability ( 12 ), and preparation time ( 13 ). Understanding meal preferences can help tailor food policies that encourage healthier eating habits, improve public health, and foster sustainable food environments. Various methods are used to study consumer preferences, with stated preference elicitation methods becoming increasingly popular in food research ( 14 ). These methods assess preferences for goods and their characteristics ( 15 ). Types of stated preference elicitation methods include conjoint analysis, discrete choice experiments (DCEs), best-worst scaling (BWS) and contingent valuation ( 16 ). These methods involve asking individuals to make a series of choices among several hypothetical alternatives ( 15 ), where each alternative is described by a set of predefined characteristics, so-called attributes at varying levels. A crucial first step within any study utilising stated choice methods is to define these attributes and select levels. According to good research practice ( 17 ), identification and selection of attributes and levels should involve a systematic literature review followed by stakeholder consultation. This preliminary work is often associated with significant resources, yet is key for designing a methodologically sound study with plausible choice scenarios. While individual studies and systematic reviews can provide a foundation for attribute selection, no systematic review has yet synthesised stated choice studies on meal preferences. Furthermore, research on meal preferences remains limited compared to studies examining individual food item preferences ( 14 ). Furthermore, despite the growing popularity of stated choice methods in food research, there is limited guidance on best practices for their application. Unlike other fields, such as health economics, where good research practices are well-established and widely adopted ( 17 , 18 ), food research lacks standardized methodological guidance. A recent review reported a generally low methodological quality of stated choice studies in the area of food research, with particularly poor reporting on the identification and selection of attributes and levels ( 14 ). This highlights the need for further research into appropriate methods for eliciting food preferences using stated choice methodology. To address existing evidence gaps, this study aimed to conduct a systematic literature review of studies exploring meal preferences using stated choice methods. The objectives of the review were to: a) identify a comprehensive list of meal attributes and corresponding levels to inform future studies in this area, and b) describe the methodological characteristics of the identified studies. The findings of this review will also be used to inform the design of a future DCE focused on meal preferences in a university setting. Methods Search strategy To identify relevant studies, the following databases were searched; Web of Science, Scopus, Medline, Embase, PsychINFO, EconLit and CINAHL. The search string consisted of two elements: the study design, which used search terms from a recent systematic review of DCEs in healthcare ( 19 ) combined with terms to capture BWS experiments ( 20 , 21 ); and the type of meal (Table 1 ) which used terms to describe an array of synonyms corresponding to different meal types. Table 1 Search string Study design Type of meal ‘discrete choice experiment(s)’, ‘discrete choice model(l)ing’, ‘discrete choice conjoint experiment’, ‘stated preference’, ‘part-worth utilities’, ‘functional measurement’, ‘paired comparisons’, ‘pairwise choices’, ‘conjoint analysis’, ‘conjoint measurement’, ‘conjoint studies’, ‘conjoint choice experiment(s)’, ‘object scaling’, ‘object case’, ‘BWS’, ‘best(-)worst scaling’, ‘best(-)worst’, ‘max dif(f)’, ‘maxdif(f)’, ‘max diff scaling’, ‘maxdiff scaling’, ‘maximum difference’ ‘food’, ‘meal*’, ‘diet*’, ‘product*’, ‘eat*’, ‘consum*’, ‘purchas*’, ‘nutrition*’, ‘snack’, ‘portion’, ‘dish’, ‘plate’, ‘beverage’, ‘lunch’, ‘breakfast’, ‘dinner’, ‘intake’, ‘taste’, ‘takeaway’ Only published peer-reviewed articles reporting human studies using empirical data and pertaining to exploring preferences for generic meals with stated choice methods were included. There was no restriction on study population, geography or publication date. Only studies published in English were eligible for inclusion. Studies that were not accessible free of charge were also excluded. Additionally, studies that focused on specific food products were excluded based on the definition of a meal outlined above. The search strategy for each database is presented in Appendix 1. The reporting was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement ( 22 ) and the searching, screening and data extraction followed the guidelines included in the Cochrane Handbook for Systematic Reviews of Interventions ( 23 ) . Identification and screening of records Identified records were exported into EndNote (version 20) and sorted for duplicates. The records underwent a two-stage screening process, both of which were performed by two reviewers independently (IP and NA). Titles and abstracts were first screened and selected for full text review. Differences in inclusion were resolved by discussion with the two reviewers. Where no agreement could be reached, a third reviewer was consulted (EF). Reasons for exclusion were documented only at the full text screening stage. The initial inter-rater agreement was 98% and 78% at the title/abstract screening stage and full text screening stage, respectively. After discussion between the reviewers, the inter-rater agreement increased to 100% at both stages. Data extraction and analysis The data extraction table was adapted from Soekhai et al. (2019) ( 19 ) and is available in Appendix 1. It comprised three sections including 1) general characteristics of the study, 2) methodological characteristics, and 3) attributes and levels. The data extraction table was first piloted on a small proportion of the included studies before proceeding with the full set. Data on the methodological characteristics of the studies were extracted in relation to the sources of attributes/levels, number of alternatives per choice task, mode of survey administration, design software, use of blocking, statistical models and software, methods for investigating preference heterogeneity (if applicable), and use and type of qualitative methods applied. Data extraction was performed by two reviewers (IP and NA). Data were synthesised and summarised narratively. Development of the list of attributes and levels to inform future studies To develop the list of attributes and levels related to meal preferences, two reviewers (IP and NA) independently extracted data on all attributes, their descriptions (if available), and corresponding levels. Following this, a focus group discussion with 9 participants comprised of the core study team and the researchers at Centre for Economics of Obesity (University of Birmingham) was organised to group the attributes into overarching categories and subcategories based on similar themes. Results A total of 13,153 records were identified through the database search. After removing duplicates, 9,621 titles and abstracts were screened. Of these, 100 records were deemed eligible for full-text screening, resulting in the inclusion of 28 studies in the review. Figure 1 presents the PRISMA diagram illustrating the study selection process. Study characteristics Table 2 provides a summary of the main features of each included study. Full study characteristics are presented in Appendix 2. Studies were published between 2013 and 2023. Geographically, the majority of included studies were conducted in Europe (n = 9) and the USA (n = 5), while other settings included Australia (n = 5), Thailand (n = 1), Indonesia (n = 1), Philippines (n = 2), Peru (n = 1), and Japan (n = 1). There were also 3 multi-country studies, conducted namely in Canada and the USA; Thailand and Japan; and the UK, Greece, Denmark, and France. Regarding the methodology used, 9 studies were described as DCEs ( 13 , 24 – 31 ), 9 as conjoint analysis ( 32 – 40 ), and 6 adopted BWS ( 41 – 46 ). Additionally, there were four studies described respectively as a stated choice experiment ( 47 ), a best-worst DCE ( 48 ), a choice-based conjoint analysis ( 49 ), and a rating-based conjoint analysis ( 50 ). Table 2 Summary of main study characteristics Author (year) Country Study design Meal description Setting Population Attributes Arsic et al (2019) Serbia Best-worst method University restaurant menu University 15 food technology experts and 35 restaurant users Time needed for preparation; technical, technological, and organizational requirements for storage of meal components; technical, technological and organizational requirements for meal preparation; price; energy value; digestibility; sensory properties; elan for work; the possibility of preparation in unforeseen circumstances Buttorff et al (2015) Peru Best-worst discrete choice experiment Meals prepared in community kitchens Community kitchens, government supported food vendors serving low-income Peruvians 432 adult (> 18years) community kitchen visitors Price; salad; soup; sides (beans and rice); meat; fruit Chaffee et al (2022) Canada, USA Rating-based conjoint analysis Home delivered ready to eat meals At home eating 285 participants over 60 living independently Protein source; taste theme; fibre source; spice Corazza et al (2021) Tuscany (Italy) Discrete choice experiment Breakfast foods Out of home eating 4669 teenagers (16–17-year-old) residing in Tuscany (Italy) Quality of food; packaging; claim de Guzman et al (2020) Philippines Conjoint analysis Menus provided in a prison setting Prisons 160 Filipino prisoners aged 60 years and over Food; food texture; colour variation; portion size; dietary diversity Ernawati et al (2019) Indonesia Conjoint analysis Meals from different cuisines Out of home eating Consumers in Indonesia Food's origin; taste; freshness; price; how food is served Iannuzzi et al (2019) Italy Conjoint analysis Pizza Catering market Random sample of 587 Italian potential consumers over 18 Flour; mozzarella cheese; tomato; protein content; carbohydrate content; fat content; additional ingredient (spirulina) Jeffries et al (2013) USA Conjoint analysis Healthy carryout meals Out of home eating 58 adult carryout customers Entrée; beverage; side dish; price; label Kamphuis et al (2015) Netherlands Discrete choice experiment Dinner At home eating 399 older adult participants Taste; healthy; price; preparation time; travel time from home to shop Kershaw et al (2019) USA Discrete choice experiment Generic meal At home eating 228 women aged 18–44 years from four diverse Chicago neighbourhoods Taste; healthiness; price; preparation time; travel time from home to the food store Kitunen et al (2022) Australia Best-worst scaling Military ration pack Military 300 military personnel Main meal; bread; jam biscuit; tuna; jerky bar; chocolate candy; fruit bar; chocolate bar; instant potato; cracker biscuit; fruit in syrup; cereal bar; cheese; muesli; sports drink; noodles; soft candy; hard candy; spreads; soup; chocolate drink Livingstone et al (2021) Australia Discrete choice experiment Typical weekday meal At home eating 557 adults (18–30 years) living in Australia Nutrition content; cost; quality; taste; preparation time Livingstone et al (2020) Australia Discrete choice experiment Typical weekday meal At home eating 92 young adults (aged 18–30 years) Preparation time of a meal; nutrition content of a meal; cost of a meal; taste of a meal; familiarity of a meal Loureiro et al (2016) Spain Best-worst scaling Fast food University 174 university students Single chicken burger; single bacon burger; single beef burger; double beef burger; double bacon burger; double chicken burger; salad Marchini et al (2023) Italy Best-worst scaling Food University 333 students aged over 18 Naturalness; price; safety; nutrition; fairness; environmental impact; legality McKeown et al (2018) UK Conjoint analysis Menu (breakfast, lunch, snack) Summer schemes and scripture union youth groups with adolescent members in Northern Ireland 239 adolescents aged 12–18 Fruit & vegetables; carbohydrates; dairy; fat & sugar Milte et al (2018) Australia Discrete choice experiment Meal and dining experience 3 aged care homes in Australia 292 residents or family members of residents living in age care homes Taste; degree of choice in serving size; degree of choice in meal provided; flexibility in mealtimes; visual appeal; additional cost Nguyen et al (2022) USA Discrete choice experiment Fish entrée Casual and fine dining restaurants 1053 adult respondents (525/fine dining restaurants and 527/casual restaurants) who have eaten at casual or fine dining restaurant in the past 12 months and have consumed seafood in the past Fish species; country of origin; production method; sustainability certification; sustainability rating; price O'Neill et al (2014) Northern Ireland (UK) Stated choice experiment Home-cooked meal At home eating 584 individuals from a random sample of households Calories; cooking time; food type; cost Ong et al (2023) Philippines Conjoint analysis Samgyeopsal meal Filipino restaurants serving Samgyeopsal meals 1018 Filipino consumers of Samgyeopsal Meat; cheese; style; price; brand; drinks Panchalingam et al (2023) USA Discrete choice experiment School day lunch Schools 3988 parent-student dyads Entrée; fruit; vegetable; price Peters et al (2020) Australia Best-worst scaling Menu item Casual restaurant (50% of sample), fine-dining restaurant (other 50% of sample) 1208 Australian diners Local produce; price; way a dish is written in menu; healthy option; method of preparation; dish I’ve never tried before; accompaniments; combination of ingredients; dish that I have tried before; sufficient portion size; sustainably produced; dish that I could not prepare; avoidance of certain foods Price et al (2016) Four EU countries (UK, Greece, Denmark and France) Best-worst scaling Canteen dish Workplace canteens 452 employees, (UK (n = 152), Greece (n = 100), Denmark (n = 100) and France (n = 100) who had access to a canteen at their place of work Value for money; organic; environmental impact; naturalness; nutrition; fair trade; provenance; animal welfare Rusmevichientong et al (2022) Thailand Discrete choice experiment Food 5 villages in rural northern Thailand 403 adult residents of 5 villages Food preparation; price; taste; amount of salt Saville et al (2021) Japan Conjoint analysis Food in ramen restaurants and shopping malls Ramen restaurants and shopping malls in Japan 393 Muslims who had travelled to Japan within the last five years Halalness; prayer room availability; word of mouth; price; access Szymkowiak et al (2022) USA Choice-based conjoint analysis Food At home eating 753 US residents Convenience; health; taste; process Thienhirun et al (2018) Thailand and Japan Conjoint analysis Thai/Japanese food (ready-to-eat & made-to-order) Out of home eating 68 people from Thailand and Japan with experience of Japanese food Taste; design; calories; price Zhou et al (2022) Denmark Conjoint analysis Dish At home eating 100 Consumers aged 60 years or above living in Denmark Main course; potatoes; vegetables; dish label The included studies explored preferences for a variety of meal types, including meals described in terms of time of the day they are consumed (e.g. breakfast, lunch, dinner) ( 13 , 25 , 31 ); menu or menu items ( 36 , 40 , 44 , 46 ); fast food ( 42 ); military ration pack ( 41 ); specific meals such as fish entrée, Samgyeopsal meal (Korean meat dish), and pizza ( 26 , 35 , 38 ); and meals or food more generally ( 24 , 27 – 30 , 32 – 34 , 37 , 39 , 43 , 45 , 47 – 50 ). Various settings of meal consumption were explored such as at home eating ( 13 , 24 , 28 – 30 , 32 , 47 , 49 , 50 ); restaurants ( 26 , 34 , 35 , 44 ); universities ( 42 , 43 , 46 ); school ( 25 ); youth groups ( 36 ); workplace canteens ( 45 ); prisons ( 40 ); military ( 41 ); aged care homes ( 27 ); community kitchens ( 48 ); catering markets ( 38 ); and more generally out-of-home eating settings ( 31 , 33 , 37 , 39 ). Where appropriate, the study population was relevant to the study setting, e.g., prisoners ( 40 ), dyads of parents and school students ( 25 ), and university students ( 42 , 43 ), military personnel ( 41 ), care home residents and their relatives ( 27 ), or customers/visitors within the settings of interest ( 26 , 33 – 37 , 39 , 44 – 46 , 48 ). In other studies, a random sample of the general population was selected as potential consumers of the meals of interest ( 13 , 24 , 28 – 32 , 38 , 47 , 49 , 50 ). Attributes and levels 148 unique attributes were extracted from the identified studies, and organised into 13 categories and 32 subcategories relevant to different meal characteristics (Table 3 ). Table 3 also lists examples of attributes and associated levels falling under each category and subcategory. The complete list of attributes and associated levels is available in Appendix 2. Table 3 Categories and subcategories of attributes of meal preferences Category Subcategory Example attribute (original source) Associated description Associated levels Healthiness (n = 27) Caloric value (n = 3) Calories ( 47 ) Less than 400 calories; between 400 and 600 calories; over 600 calories Dietary diversity (n = 1) Dietary diversity ( 40 ) 2/3/4 food groups Healthiness (n = 4) Healthy ( 13 ) Healthy; neutral; unhealthy Healthy ingredients (n = 6) Fiber source ( 50 ) Grains; vegetables Nutritional content (n = 8) Nutrition content of a meal ( 29 ) Low; adequate; optimal Quality (n = 2) Quality ( 28 ) Low; moderate; high Safety (n = 1) Safety ( 43 ) Extent to which consumption of food is safe and it will not cause illness (e.g. reliability of producers, security of origin) Satiety (n = 2) Digestibility ( 46 ) A subjective feeling in the body after consuming a meal Price/cost of a meal (n = 19) Objective (n = 12) Price ( 48 ) 1.5; 3; 6 nuevos soles (Peruvian currency) Subjective (n = 4) Price ( 39 ) Cheap; average cost; expensive Non-specified (n = 3) Price ( 46 ) Cost of fresh foods Specific meal components and ingredients (n = 18) Specific ingredients (n = 11) Protein source ( 50 ) Chicken; fish; alternative; egg Specific component (n = 7) Entrée ( 37 ) Grilled chicken sandwich; turkey club sandwich Sustainability, environmental and ethical considerations (n = 18) Ethical considerations (n = 4) Fairness ( 43 ) Limits within which all participants in the value chain receive fair benefits for their work or business (e.g. working conditions, dignified wages) Origin (n = 7) Country of origin ( 26 ) Domestic; imported; unknown Organic production (n = 2) Organic ( 45 ) Organic food is produced in a way that respects natural life cycles. It minimises the human impact on the environment and operates as naturally as possible Environmental and sustainability considerations (n = 5) Sustainability certification ( 26 ) Certificated; non-certificated Sensory properties of a meal (n = 16) Sensory properties (n = 1) Sensory properties ( 46 ) Appearance, smell, taste, texture Specific taste (n = 3) Spice presence ( 50 ) Spicy; not spicy Color (n = 1) Color variation ( 40 ) With color variation; without color variation General taste (n = 8) Taste ( 13 ) Very good; good; sufficient Freshness (n = 1) Freshness ( 39 ) Fresh (fresh from the oven); not fresh Texture (n = 1) Food texture ( 40 ) Soft; hard; chewy Visual appeal (n = 1) Visual appeal ( 27 ) Not very (appealing); satisfactory; excellent Time/convenience (n = 14) Preparation time (n = 7) Preparation time ( 13 ) 0 minutes (in case of a ready meal, or take-away food); 15 minutes; 30 minutes; 45 minutes Travel time (n = 2) Travel time from home to shop ( 13 ) 5 minutes; 10 minutes; 15 minutes; 20 minutes Flexibility (n = 3) Flexibility in mealtimes ( 27 ) Anytime I like; within a 1–2 hour range; at a set time Convenience/access (n = 2) Access ( 34 ) Easy; not Marketing and external look (n = 10) Label/packaging (n = 7) Packaging ( 31 ) Natural; bright and colorful Brand (n = 1) Brand ( 35 ) Sariwon Korea; Soban K-Town Grill; Samgyupsalamat; Romantic Baboy Informal marketing (n = 1) Word of mouth ( 34 ) Positive; negative Menu description (n = 1) Way a dish is written in menu ( 44 ) Portion size (n = 7) Salad ( 48 ) None; medium; large Familiarity/food novelty (n = 5) Familiarity of a meal ( 29 ) Not very familiar; somewhat familiar; very familiar Meal preparation (n = 5) Style ( 35 ) Style refers to the way the main entrée is being prepared. Grilled; hot pot; pre-cooked Taste theme (n = 4) Taste theme ( 50 ) Mediterranean; Asian; Latin Characteristics of the dining environment (n = 3) How food is served ( 39 ) With wait-staff; self-service Naturalness (n = 2) Naturalness ( 43 ) Limits within which food is produced without the use of additives, chemicals, or modern technology (e.g. low-processed foods) Most commonly considered attribute was related to meal healthiness (n = 27), including subcategories such as nutritional content (n = 8), healthy ingredients (n = 6), and caloric value (n = 3), among other. The second most common category of attributes was price/cost of a meal considered in 19 of the 28 reviewed studies. Price was predominantly defined in terms of specific monetary values, such as 5/10/15 AUD per person in the study by Livingstone et al (2020) ( 29 ), reflecting the study context. However, in 4 studies, the price-related attribute was presented in terms of subjective price. For instance, Ernawati et al (2019) defined the levels of the price attribute as ‘cheap’, ‘average cost’, ‘expensive’ ( 39 ), while Price et al (2016) included the attribute ‘value for money’ defined as ‘the ratio between the perceived quality of the dish and the price paid for it’ ( 45 ). The third most common categories were related to specific meal components and ingredients (n = 18) and ‘sustainability, environmental and ethical considerations’ (n = 18). 11 of the extracted attributes referred to specific meal ingredients such as protein source (chicken; fish; alternative; egg) ( 50 ) and type of flour (00; gluten free; cricket) ( 38 ), and 7 of the attributes corresponded to meal components, for example, entrée (grilled chicken sandwich; turkey club sandwich) ( 37 ) and drinks (soju/beer; soft drinks; juice) ( 35 ). Two studies utilised BWS to rank preferences for specific meal components. Kitunen et al (2022) ranked 21 components of an Australian military ration pack (e.g., main meal, bread, jam biscuit) ( 41 ). Loureiro et al (2016) compared stated and actual preferences for fast food dishes, including a single chicken burger, single beef burger, and salad, among others ( 42 ). Within the category ‘sustainability, environmental and ethical considerations’, the included subcategories were: food origin (n = 4), such as country of origin (domestic; imported; unknown) ( 26 ); environmental and sustainability considerations (n = 5), such as sustainability rating (green; yellow; red; gray; unknown) ( 26 ); ethical considerations (n = 4) such as fairness and legality ( 43 ); and organic production (n = 2) ( 45 , 49 ). Several attributes relating to various intrinsic properties of a meal were also considered, including meal’s sensory properties, such as taste, color, and visual appeal (n = 16), portion size (n = 7), taste theme (n = 4), and naturalness (n = 2). 14 attributes were related to the time/convenience, describing how fast and easy the meal was to prepare and/or access, including preparation time (n = 7), flexibility (n = 3), travel time (n = 2), and convenience/access (n = 2). 10 attributes concerned marketing and presentation (e.g. packaging, labelling, and brand). Other attribute categories were familiarity (n = 5), meal preparation (n = 5), and characteristics of the dining environment (n = 3). Various sets of defined levels were used to describe the attributes. Table 3 includes levels that accompanied example attributes in each category and subcategory, while Appendix 2 presents the levels corresponding to each attribute included in the reviewed studies. While it is considered good practice to accompany attributes with descriptions, descriptions were provided for only 43 out of the 148 extracted attributes. We also extracted data on relative importance of attributes from individual studies (column L in Appendix 2). However, due to substantial heterogeneity in the range of attributes included, we were not able to conduct a meaningful synthesis of this information. Methodological characteristics The methodological characteristics of the included studies are presented in Appendix 2. The number of attributes varied by experimental design with BWS studies using between 6 and 21, with the median of 8; DCEs and conjoint analysis studies included between 3 and 7 attributes, with the median of 5. The number of levels used for each category ranged between two to four, with most attributes having three corresponding levels. The attributes and levels were most commonly derived from the literature (n = 9), consultations with experts and relevant stakeholders (n = 5), dietary guidelines ( 36 ), and pre-existing knowledge of the meal of interest and the study context ( 38 , 41 , 42 ). Eight studies relied on a combination of sources to identify attributes and levels for inclusion, such as the literature, expert consultations, meal characteristics, dietary recommendations, research team discussions, market prices, implementation feasibility, cost considerations, and pilot studies. Two studies did not report the source of attributes and levels. Choice data were most often collected through online surveys (n = 14) and phone or in-person interviews (n = 11). One study gathered data across multiple stages using a combination of paper-based surveys and interviews ( 36 ). Zhou et al (2022) collected data via a computer survey administered in a lab setting ( 32 ). One study did not report on the method of data collection. Two studies did not report the number of alternatives included in the choice tasks, and for an additional one this was not applicable due to study design. Among the studies that reported this information, participants were presented with an average of 4.3 alternatives (ranging between 3 and 8) in the BWS studies, and with an average of 4.75 alternatives (ranging between 1 and 19 in the DCE and conjoint analysis studies (excluding opt-outs). 25 studies provided information on the inclusion of an opt-out option, with 7 reporting that it was included. 26 studies reported the number of choice tasks per respondents, with an average of 11 in the BWS studies and 10 in the DCE or conjoint analysis studies. The reported choice task design included factorial (full or fractional, n = 10), balanced incomplete block design (n = 4), D-efficient design (n = 3), orthogonal design (n = 1), balanced overlap design (n = 1), and random design with complete enumeration (n = 1). Eight studies did not report the choice design. Among the 17 studies that reported the software used to design choice sets, 3 used Ngene, 3 used R, 4 used SAS, 3 used Sawtooth, 3 used SPSS, and 1 used Stata. 13 studies reported using blocking, an approach in which choice sets are divided into shorter blocks and participants are randomly allocated to one of these blocks. Blocking helps reduce the cognitive burden for each respondent who completes the survey and improves statistical efficiency of the choice model ( 51 ). Regarding the statistical analysis, a variety of models were employed, including conditional logit (n = 5), mixed logit (n = 2), multinomial logit (n = 2), random parameter (n = 1), and a combination thereof (n = 4). 9 studies used other methods for the analysis of correlation such as ordinary least squares regression, Pearson’s correlation, Kendall’s Tau, and best-worst method - multi-attributive ideal real comparative analysis (BWM-MAIRCA). 5 studies did not report the statistical model used for the estimation. A variety of software packages were used for the analysis of choice data, including Lingo, Nlogit, Ox, R, SPSS, SAS, Stata, Sawtooth, and XLSTAT. 5 studies did not report the software used for the analysis. 16 studies reported investigating preference heterogeneity. The most common methods included subgroup or cluster analysis (n = 7), the use of estimation models that account for preference heterogeneity such as mixed logit and latent class models (n = 4), investigation of interaction effects (n = 3), and analysis of variance (n = 1). Qualitative methods such as interviews, qualitative questions within self-completed surveys, and focus groups were used in 13 studies. Common reasons for using qualitative methods included development and piloting of attributes and levels (n = 8), understanding responses and results (n = 2), obtaining model values (n = 1), and a combination of reasons (n = 2). Discussion To the best of our knowledge, this is the first systematic review of studies applying stated choice methods to investigate meal preferences, rather than focusing only on individual food products. This distinction is important, as meals reflect more complex decision-making processes that better capture real-world dietary behaviours and their implications for nutrition and health. This review makes two key contributions. First, it consolidates a comprehensive list of attributes and levels that influence meal preferences, which can guide the selection of attributes in future stated choice studies. Second, it highlights the methodological strengths and weaknesses in the current literature, providing a basis for the development of clearer guidance and reporting standards for applying these methods in food and nutrition research. Attributes influencing meal preferences The review identified 13 broad categories and 22 subcategories of attributes, ranging from intrinsic characteristics such as taste, healthiness and portion size, to extrinsic characteristics including price, preparation time and sustainability. Importantly, a number of attributes were specific to meals, such as dining environment, method of meal preparation, and portion size, reinforcing the added value of meal-level analysis. These findings can inform preference studies that aim to capture the complexity of meal decision making across diverse contexts. Attribute development often involved compiling information from multiple sources over several stages, aligning with good research practices. These sources included literature reviews, expert consultations, pilot validation studies, and supplementary qualitative methods. Using multiple sources in attribute development is recommended, as it enhances a study’s content validity ( 52 ). A diverse selection can also improve response quality and provide a more comprehensive understanding of choices and preferences ( 53 ). On the other hand, inclusion of a higher number of attributes may increase cognitive burden for participants ( 54 ). Therefore, careful selection of a comprehensive yet manageable number of attributes that comprehensively capture the decision context without overburdening participants can enhance the validity of stated choice studies. This is particularly relevant for studies in low- and middle-income countries, where dietary decisions are often influenced by affordability, time constraints and food availability. Good practice recommendations suggest that selection of attributes should be based on their ‘…relevance to the research question, relevance to the decision context, and whether attributes are related to one another. ’ (Bridges et al, 2011, pp. 406). While no strict limit exists, guidelines suggest including fewer than 10 attributes to reduce cognitive load ( 55 ). The list of attribute categories and subcategories developed in this study could serve as a robust starting point for designing future studies using stated choice methods to elicit meal preferences. The attributes on this list can be refined and prioritised to align with specific study objectives by engaging stakeholders through methods such as interviews or the nominal group technique. Such an approach would help effectively capture the complexity of meal preferences, minimize participant burden, and ultimately enhance the validity and reliability of research findings. Methodological considerations when eliciting meal preferences This review identified a rise in the number of studies published from 2013 to 2022, reflecting growing recognition of the value of stated choice methods in food research. However, most studies were conducted in high-income settings countries, with limited evidence from LMICs where diet-related health challenges are most pressing. Expanding such research in LMICs would provide critical insights to inform nutrition policies. Methodological inconsistencies were common. Lizin et al (2022) ( 14 ) highlight that food-related preference elicitation studies often suffer from low reporting standards. In this review, missing information was observed in relation to the attribute and level development; study design; statistical models and software used for the analysis; and methods for investigating preference heterogeneity. Attribute definitions were often unclear, which could introduce bias, compromise internal validity, and limit generalizability of study findings across different contexts or populations. For example, the attribute ‘halalness’, described as halal-labelled food or Muslim-friendly food ( 34 ), lacked a clear definition, making its application to culturally diverse settings unclear. Additionally, previous research on preference elicitation has emphasised the importance of including various types of attributes in stated choice studies for a comprehensive representation of the decision-making context ( 57 ). However, some attributes and levels in the reviewed studies were not directly transferable to other settings without prior adjustment. For example, cost attributes were often presented in local currencies, reducing transferability to other contexts. Using more generalisable descriptions such as ‘cheap’, ‘average’, and ‘expensive’( 39 ) may enhance applicability across countries, although this can reduce precision for economic valuation. Poor reporting hinders the replication of research methodology, leading to ambiguity when interpreting results for future studies. Existing best practice guidelines from healthcare research preference research, such as those developed by The International Society for Pharmacoeconomics and Outcomes Research (ISPOR), offers a useful starting point, but specific reporting standards for food preference research are urgently needed( 17 ). Establishing such guidelines would improve comparability across studies, support more robust synthesis of findings, and ultimately strengthen the link between consumer preferences and nutrition policy. Strengths and Limitations A major strength of this review is its novel focus on meal-level preferences, which provides more relevant insights for dietary interventions and food system policies than product-level analyses alone. A robust search strategy was employed across relevant databases and informed by a comprehensive search string in accordance with published guidelines. Additionally, data on the methodological characteristics of studies were extracted and described in the results. Overall, this review advances current knowledge on the drivers of meal preferences by providing a list of relevant attributes and levels that could inform future stated choice studies, drawing on international evidence. Nevertheless, the review also had some limitations. The list of attributes was developed by synthesizing the information obtained from the literature and although it is comprehensive, some relevant attributes may have been omitted due to their absence in prior research. Furthermore, there was also inconsistencies in study reporting which may have constrained the completeness of the synthesis. Conclusion This review demonstrates that stated choice methods can provide valuable insights into the complex drivers of meal preferences, with direct implications for the design of policies and interventions that promote healthier and more sustainable diets. However, methodological inconsistencies were identified and there was limited representation of LMIC contexts. This suggests the need for standardised reporting and expanded global application of these methods. Strengthening the quality and scope of future meal preference research will enhance its contribution to improving population nutrition and reducing diet-related inequalities. Declarations Ethics approval and consent to participate: Not applicable Consent for publication: Not applicable. Availability of data and materials: Data is provided within the manuscript or supplementary information files. Competing interests: The authors declare that they have no competing interests. Funding: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101035821. NA, IP and EF are funded by the National Institute for Health and Care Research (NIHR) [Research Professorship Award NIHR300773]. LF is funded by UKRI BBSRC [BB/V004832/1]. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. None of the funding bodies had a role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. Authors' contributions: Conceptualization, I.P.; methodology, I.P., N.A. E.F., L.F.; formal analysis, N.A. and I.P.; data curation, N.A., and I.P.; writing—original draft preparation, N.A.; writing—review and editing, E.F., I.P., L.F.; funding acquisition, I.P. All authors have read and agreed to the published version of the manuscript. Acknowledgements: None. References Neumark-Sztainer D, Story M, Perry C, Casey MA. Factors influencing food choices of adolescents: findings from focus-group discussions with adolescents. J Am Diet Assoc. 1999;99(8):929-37. WHO. Diet, nutrition and the prevention of chronic diseases: report of a joint WHO/FAO expert consultation. 2003. Seiler A, Chen MA, Brown RL, Fagundes CP. Obesity, Dietary Factors, Nutrition, and Breast Cancer Risk. Curr Breast Cancer Rep. 2018;10(1):14-27. Candari CJ, Cylus J, Nolte E. European Observatory Health Policy Series. Assessing the economic costs of unhealthy diets and low physical activity: An evidence review and proposed framework. 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Heliyon. 2021;7(5):e07073. Ong AKS, Prasetyo YT, Esteller AJD, Bruno JE, Lagorza KCO, Oli LET, et al. Consumer preference analysis on the attributes of samgyeopsal Korean cuisine and its market segmentation: Integrating conjoint analysis and K-means clustering. PLOS ONE. 2023;18(2):e0281948. McKeown A, Nelson R. Independent decision making of adolescents regarding food choice. International Journal of Consumer Studies. 2018;42(5):469-77. Jeffries JK, Lee SH, Frick KD, Gittelsohn J. Preferences for Healthy Carryout Meals in Low-Income Neighborhoods of Baltimore City. Health Promotion Practice. 2013;14(2):293-300. Iannuzzi E, Sisto R, Nigro C. The willingness to consume insect-based food: an empirical research on Italian consumers. Agricultural Economics/Zemědělská Ekonomika. 2019;65(10). Ernawati H, Prakoso D. CONSUMER PREFERENCES FOR INDONESIAN CULINARY. Journal of Indonesian Economy and Business. 2020;34. de Guzman A, Barredo SF, Caillan KR. Examining the role of depression in the Filipino elderly's food preferences in prison setting: data from conjoint analysis and SEM. Int J Prison Health. 2020;16(2):135-49. Kitunen A, Carins J, De Diana J. Segments of military ration pack eaters: Choice preferences among groups. Appetite. 2022;174:106023. Loureiro ML, Rahmani D. The incidence of calorie labeling on fast food choices: A comparison between stated preferences and actual choices. Economics & Human Biology. 2016;22:82-93. Marchini A, Polenzani B, Ceccarelli G, Mariano E, Martino G. Food values: How they relate to legality. Frontiers in Sustainable Food Systems. 2023;7:1121884. Peters K, Hervé Remaud P. Factors influencing consumer menu-item selection in a restaurant context. Food Quality and Preference. 2020;82:103887. Price S, Viglia G, Hartwell H, Hemingway A, Chapleo C, Appleton K, et al. What are we eating? Consumer information requirement within a workplace canteen. Food Quality and Preference. 2016;53. Arsić SN, Pamučar D, Suknovic M, Janošević M. Menu evaluation based on rough MAIRCA and BW methods. Serbian journal of management. 2019;14(1):27-48. O’Neill V, Hess S, Campbell D. A question of taste: Recognising the role of latent preferences and attitudes in analysing food choices. Food Quality and Preference. 2014;32:299-310. Buttorff C, Trujillo AJ, Diez-Canseco F, Bernabe-Ortiz A, Miranda JJ. Evaluating consumer preferences for healthy eating from Community Kitchens in low-income urban areas: A discrete choice experiment of Comedores Populares in Peru. Soc Sci Med. 2015;140:1-8. Szymkowiak A, Borusiak B, Pierański B, Kotyza P, Smutka L. Household Food Waste: The Meaning of Product’s Attributes and Food-Related Lifestyle. Frontiers in Environmental Science. 2022;10:918485. Chaffee O, McGillivray A, Duizer L, Ross CF. Identifying elements of a ready-to-eat meal desired by older adults. Food Research International. 2022;157:111353. Reed Johnson F, Lancsar E, Marshall D, Kilambi V, Mühlbacher A, Regier DA, et al. Constructing Experimental Designs for Discrete-Choice Experiments: Report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force. Value in Health. 2013;16(1):3-13. Coast J, Al-Janabi H, Sutton EJ, Horrocks SA, Vosper AJ, Swancutt DR, et al. Using qualitative methods for attribute development for discrete choice experiments: issues and recommendations. Health Econ. 2012;21(6):730-41. Ryan M, Gerard K, Amaya-Amaya M. Using Discrete Choice Experiments to Value Health and Health Care2008. DeShazo JR, Fermo G. Designing Choice Sets for Stated Preference Methods: The Effects of Complexity on Choice Consistency. Journal of Environmental Economics and Management. 2002;44(1):123-43. Mangham LJ, Hanson K, McPake B. How to do (or not to do) ... Designing a discrete choice experiment for application in a low-income country. Health Policy Plan. 2009;24(2):151-8. Gustafsson IB, Öström Å, Johansson J, Mossberg L. The Five Aspects Meal Model: a tool for developing meal services in restaurants. Journal of Foodservice. 2006;17:84-93. Kløjgaard ME, Bech M, Søgaard R. Designing a Stated Choice Experiment: The Value of a Qualitative Process. Journal of Choice Modelling. 2012;5(2):1-18. Additional Declarations No competing interests reported. Supplementary Files Appendix1.docx Appendix2.xlsx Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7714370","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":529984757,"identity":"057098c8-eb02-43fb-adfe-e4366cdc2556","order_by":0,"name":"Nafsika Afentou","email":"","orcid":"","institution":"University of Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Nafsika","middleName":"","lastName":"Afentou","suffix":""},{"id":529984758,"identity":"8df3ee3f-7407-4ff8-a155-43740201830d","order_by":1,"name":"Emma Frew","email":"","orcid":"","institution":"University of Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Emma","middleName":"","lastName":"Frew","suffix":""},{"id":529984759,"identity":"43a28019-5955-40e6-a9a2-20b5a901f8b8","order_by":2,"name":"Lin Fu","email":"","orcid":"","institution":"University of Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Fu","suffix":""},{"id":529984760,"identity":"4b228b66-c2ef-4b44-8c15-871a627705c7","order_by":3,"name":"Irina Pokhilenko","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYBACNiBmbGyQkAEzPzYcgEkkENTCA2IyziRGCwNECwNYCzMvMVr4GHgPPpy5w4KHX7ot8bHtjjvyug3MDz8wtqXhcRhfsuHGMxI8knOOHTbOPfPMcNsBNmMJxrYcPFp4zCQftknwGNxIb5PObTvMuO0AgxkDY1sFYS32IC2WbYfttx1g/0ZYy0aQLRJpx6QZ2w4nbjvAA7IFj8OYgX6ZCdQicSMt2bD3zOHkbYd5iiUSzuH2vnx778GHvW11cvwz0gwf/Nxx2Hbb8faNHz6UJePUwsDMgyHCQCgiMbSMglEwCkbBKEADABTDUOP8MfMxAAAAAElFTkSuQmCC","orcid":"","institution":"University of Birmingham","correspondingAuthor":true,"prefix":"","firstName":"Irina","middleName":"","lastName":"Pokhilenko","suffix":""}],"badges":[],"createdAt":"2025-09-25 15:09:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7714370/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7714370/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":93660245,"identity":"b3b2169b-f03b-4d9f-a045-a3e3fb213b29","added_by":"auto","created_at":"2025-10-16 08:02:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":204447,"visible":true,"origin":"","legend":"\u003cp\u003eStudy selection process\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7714370/v1/42fc55f56fba3a91332a93e2.png"},{"id":93661139,"identity":"c777aaa6-202e-4690-8ae0-d7e086cc54b6","added_by":"auto","created_at":"2025-10-16 08:10:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1535990,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7714370/v1/b05e030c-30a3-4455-bf3d-a8951dad4e4b.pdf"},{"id":93660243,"identity":"24d0db09-6801-490b-893c-910b25ef188b","added_by":"auto","created_at":"2025-10-16 08:02:35","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":15813,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7714370/v1/6b7aa3e3f8b2c73766bba016.docx"},{"id":93660244,"identity":"948d08d6-21ea-4e1d-b356-6d29aa554654","added_by":"auto","created_at":"2025-10-16 08:02:35","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":43659,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7714370/v1/ec4fb8bb4fa706d8bcfc1581.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"How do the characteristics of a meal influence consumer preferences: a systematic literature review of studies using stated choice methods","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMeal choices are an integral part of daily life. They are influenced by a wide range of factors, including habits, past experiences, availability of options and resources such as time and money, as well as socioeconomic and cultural factors (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). In recent years, the food sector has expanded significantly, and meal choices are often made in out of home settings such as schools, restaurants, and workplaces. It is well-established that dietary habits directly impact health, with poor nutrition leading to adverse health outcomes such as obesity, cancer, and depression (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Beyond health effects, poor dietary habits also lead to economic consequences such as lower educational attainment and reduced workplace productivity (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Understanding the motivations behind meal choices can help shape health and well-being policies for the food environment.\u003c/p\u003e\u003cp\u003eIt is important to distinguish between a meal and an individual food product, as they are conceptually different and involve distinct preferences. In this study, a meal is defined as an eating occasion that includes multiple food items consumed together at different times of the day. This contrasts with individual food items eaten separately, which do not constitute a complete meal. The choice of a meal involves a complex decision-making process influenced by several interacting factors (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). While the choice of specific food products, such as meat, fruit and vegetables, or seafood are influenced by factors such as processing (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), seasonality (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), or eco-certification (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), meal preferences are shaped by a broader range of intrinsic and extrinsic factors. Examples of these intrinsic factors include taste of combined elements, appearance or meal composition (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Extrinsic factors include nutritional menu labelling (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), variety (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), availability (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), and preparation time (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Understanding meal preferences can help tailor food policies that encourage healthier eating habits, improve public health, and foster sustainable food environments.\u003c/p\u003e\u003cp\u003eVarious methods are used to study consumer preferences, with stated preference elicitation methods becoming increasingly popular in food research (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). These methods assess preferences for goods and their characteristics (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Types of stated preference elicitation methods include conjoint analysis, discrete choice experiments (DCEs), best-worst scaling (BWS) and contingent valuation (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). These methods involve asking individuals to make a series of choices among several hypothetical alternatives (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), where each alternative is described by a set of predefined characteristics, so-called attributes at varying levels.\u003c/p\u003e\u003cp\u003eA crucial first step within any study utilising stated choice methods is to define these attributes and select levels. According to good research practice (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), identification and selection of attributes and levels should involve a systematic literature review followed by stakeholder consultation. This preliminary work is often associated with significant resources, yet is key for designing a methodologically sound study with plausible choice scenarios. While individual studies and systematic reviews can provide a foundation for attribute selection, no systematic review has yet synthesised stated choice studies on meal preferences. Furthermore, research on meal preferences remains limited compared to studies examining individual food item preferences (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFurthermore, despite the growing popularity of stated choice methods in food research, there is limited guidance on best practices for their application. Unlike other fields, such as health economics, where good research practices are well-established and widely adopted (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), food research lacks standardized methodological guidance. A recent review reported a generally low methodological quality of stated choice studies in the area of food research, with particularly poor reporting on the identification and selection of attributes and levels (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). This highlights the need for further research into appropriate methods for eliciting food preferences using stated choice methodology.\u003c/p\u003e\u003cp\u003e To address existing evidence gaps, this study aimed to conduct a systematic literature review of studies exploring meal preferences using stated choice methods. The objectives of the review were to: a) identify a comprehensive list of meal attributes and corresponding levels to inform future studies in this area, and b) describe the methodological characteristics of the identified studies. The findings of this review will also be used to inform the design of a future DCE focused on meal preferences in a university setting.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eSearch strategy\u003c/h2\u003e\u003cp\u003eTo identify relevant studies, the following databases were searched; Web of Science, Scopus, Medline, Embase, PsychINFO, EconLit and CINAHL. The search string consisted of two elements: the study design, which used search terms from a recent systematic review of DCEs in healthcare (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) combined with terms to capture BWS experiments (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e); and the type of meal (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) which used terms to describe an array of synonyms corresponding to different meal types.\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\u003eSearch string\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStudy design\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eType of meal\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lsquo;discrete choice experiment(s)\u0026rsquo;, \u0026lsquo;discrete choice model(l)ing\u0026rsquo;, \u0026lsquo;discrete choice conjoint experiment\u0026rsquo;, \u0026lsquo;stated preference\u0026rsquo;, \u0026lsquo;part-worth utilities\u0026rsquo;, \u0026lsquo;functional measurement\u0026rsquo;, \u0026lsquo;paired comparisons\u0026rsquo;, \u0026lsquo;pairwise choices\u0026rsquo;, \u0026lsquo;conjoint analysis\u0026rsquo;, \u0026lsquo;conjoint measurement\u0026rsquo;, \u0026lsquo;conjoint studies\u0026rsquo;, \u0026lsquo;conjoint choice experiment(s)\u0026rsquo;, \u0026lsquo;object scaling\u0026rsquo;, \u0026lsquo;object case\u0026rsquo;, \u0026lsquo;BWS\u0026rsquo;, \u0026lsquo;best(-)worst scaling\u0026rsquo;, \u0026lsquo;best(-)worst\u0026rsquo;, \u0026lsquo;max dif(f)\u0026rsquo;, \u0026lsquo;maxdif(f)\u0026rsquo;, \u0026lsquo;max diff scaling\u0026rsquo;, \u0026lsquo;maxdiff scaling\u0026rsquo;, \u0026lsquo;maximum difference\u0026rsquo;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lsquo;food\u0026rsquo;, \u0026lsquo;meal*\u0026rsquo;, \u0026lsquo;diet*\u0026rsquo;, \u0026lsquo;product*\u0026rsquo;, \u0026lsquo;eat*\u0026rsquo;, \u0026lsquo;consum*\u0026rsquo;, \u0026lsquo;purchas*\u0026rsquo;, \u0026lsquo;nutrition*\u0026rsquo;, \u0026lsquo;snack\u0026rsquo;, \u0026lsquo;portion\u0026rsquo;, \u0026lsquo;dish\u0026rsquo;, \u0026lsquo;plate\u0026rsquo;, \u0026lsquo;beverage\u0026rsquo;, \u0026lsquo;lunch\u0026rsquo;, \u0026lsquo;breakfast\u0026rsquo;, \u0026lsquo;dinner\u0026rsquo;, \u0026lsquo;intake\u0026rsquo;, \u0026lsquo;taste\u0026rsquo;, \u0026lsquo;takeaway\u0026rsquo;\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 Only published peer-reviewed articles reporting human studies using empirical data and pertaining to exploring preferences for generic meals with stated choice methods were included. There was no restriction on study population, geography or publication date. Only studies published in English were eligible for inclusion. Studies that were not accessible free of charge were also excluded. Additionally, studies that focused on specific food products were excluded based on the definition of a meal outlined above. The search strategy for each database is presented in Appendix 1.\u003c/p\u003e\u003cp\u003eThe reporting was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) and the searching, screening and data extraction followed the guidelines included in the Cochrane Handbook for Systematic Reviews of Interventions (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) .\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eIdentification and screening of records\u003c/h3\u003e\n\u003cp\u003eIdentified records were exported into EndNote (version 20) and sorted for duplicates. The records underwent a two-stage screening process, both of which were performed by two reviewers independently (IP and NA). Titles and abstracts were first screened and selected for full text review. Differences in inclusion were resolved by discussion with the two reviewers. Where no agreement could be reached, a third reviewer was consulted (EF). Reasons for exclusion were documented only at the full text screening stage. The initial inter-rater agreement was 98% and 78% at the title/abstract screening stage and full text screening stage, respectively. After discussion between the reviewers, the inter-rater agreement increased to 100% at both stages.\u003c/p\u003e\n\u003ch3\u003eData extraction and analysis\u003c/h3\u003e\n\u003cp\u003eThe data extraction table was adapted from Soekhai et al. (2019) (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) and is available in Appendix 1. It comprised three sections including 1) general characteristics of the study, 2) methodological characteristics, and 3) attributes and levels. The data extraction table was first piloted on a small proportion of the included studies before proceeding with the full set. Data on the methodological characteristics of the studies were extracted in relation to the sources of attributes/levels, number of alternatives per choice task, mode of survey administration, design software, use of blocking, statistical models and software, methods for investigating preference heterogeneity (if applicable), and use and type of qualitative methods applied. Data extraction was performed by two reviewers (IP and NA). Data were synthesised and summarised narratively.\u003c/p\u003e\n\u003ch3\u003eDevelopment of the list of attributes and levels to inform future studies\u003c/h3\u003e\n\u003cp\u003eTo develop the list of attributes and levels related to meal preferences, two reviewers (IP and NA) independently extracted data on all attributes, their descriptions (if available), and corresponding levels. Following this, a focus group discussion with 9 participants comprised of the core study team and the researchers at Centre for Economics of Obesity (University of Birmingham) was organised to group the attributes into overarching categories and subcategories based on similar themes.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 13,153 records were identified through the database search. After removing duplicates, 9,621 titles and abstracts were screened. Of these, 100 records were deemed eligible for full-text screening, resulting in the inclusion of 28 studies in the review. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the PRISMA diagram illustrating the study selection process.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStudy characteristics\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e provides a summary of the main features of each included study. Full study characteristics are presented in Appendix 2. Studies were published between 2013 and 2023. Geographically, the majority of included studies were conducted in Europe (n\u0026thinsp;=\u0026thinsp;9) and the USA (n\u0026thinsp;=\u0026thinsp;5), while other settings included Australia (n\u0026thinsp;=\u0026thinsp;5), Thailand (n\u0026thinsp;=\u0026thinsp;1), Indonesia (n\u0026thinsp;=\u0026thinsp;1), Philippines (n\u0026thinsp;=\u0026thinsp;2), Peru (n\u0026thinsp;=\u0026thinsp;1), and Japan (n\u0026thinsp;=\u0026thinsp;1). There were also 3 multi-country studies, conducted namely in Canada and the USA; Thailand and Japan; and the UK, Greece, Denmark, and France. Regarding the methodology used, 9 studies were described as DCEs (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan additionalcitationids=\"CR25 CR26 CR27 CR28 CR29 CR30\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), 9 as conjoint analysis (\u003cspan additionalcitationids=\"CR33 CR34 CR35 CR36 CR37 CR38 CR39\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e), and 6 adopted BWS (\u003cspan additionalcitationids=\"CR42 CR43 CR44 CR45\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). Additionally, there were four studies described respectively as a stated choice experiment (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e), a best-worst DCE (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e), a choice-based conjoint analysis (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e), and a rating-based conjoint analysis (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e).\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\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of main study characteristics\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=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAuthor (year)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStudy design\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMeal description\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSetting\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePopulation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eAttributes\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eArsic et al (2019)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSerbia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBest-worst method\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUniversity restaurant menu\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUniversity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e15 food technology experts and 35 restaurant users\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTime needed for preparation; technical, technological, and organizational requirements for storage of meal components; technical, technological and organizational requirements for meal preparation; price; energy value; digestibility; sensory properties; elan for work; the possibility of preparation in unforeseen circumstances\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eButtorff et al (2015)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePeru\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBest-worst discrete choice experiment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMeals prepared in community kitchens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCommunity kitchens, government supported food vendors serving low-income Peruvians\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e432 adult (\u0026gt;\u0026thinsp;18years) community kitchen visitors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePrice; salad; soup; sides (beans and rice); meat; fruit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChaffee et al (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCanada, USA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRating-based conjoint analysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHome delivered ready to eat meals\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAt home eating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e285 participants over 60 living independently\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eProtein source; taste theme; fibre source; spice\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCorazza et al (2021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTuscany (Italy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDiscrete choice experiment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBreakfast foods\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOut of home eating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4669 teenagers (16\u0026ndash;17-year-old) residing in Tuscany (Italy)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eQuality of food; packaging; claim\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ede Guzman et al (2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhilippines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConjoint analysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMenus provided in a prison setting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePrisons\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e160 Filipino prisoners aged 60 years and over\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFood; food texture; colour variation; portion size; dietary diversity\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eErnawati et al (2019)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIndonesia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConjoint analysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMeals from different cuisines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOut of home eating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eConsumers in Indonesia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFood's origin; taste; freshness; price; how food is served\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIannuzzi et al (2019)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eItaly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConjoint analysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePizza\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCatering market\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRandom sample of 587 Italian potential consumers over 18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFlour; mozzarella cheese; tomato; protein content; carbohydrate content; fat content; additional ingredient (spirulina)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJeffries et al (2013)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUSA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConjoint analysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHealthy carryout meals\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOut of home eating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e58 adult carryout customers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eEntr\u0026eacute;e; beverage; side dish; price; label\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKamphuis et al (2015)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNetherlands\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDiscrete choice experiment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDinner\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAt home eating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e399 older adult participants\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTaste; healthy; price; preparation time; travel time from home to shop\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKershaw et al (2019)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUSA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDiscrete choice experiment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGeneric meal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAt home eating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e228 women aged 18\u0026ndash;44 years from four diverse Chicago neighbourhoods\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTaste; healthiness; price; preparation time; travel time from home to the food store\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKitunen et al (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAustralia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBest-worst scaling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMilitary ration pack\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMilitary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e300 military personnel\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMain meal; bread; jam biscuit; tuna; jerky bar; chocolate candy; fruit bar; chocolate bar; instant potato; cracker biscuit; fruit in syrup; cereal bar; cheese; muesli; sports drink; noodles; soft candy; hard candy; spreads; soup; chocolate drink\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLivingstone et al (2021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAustralia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDiscrete choice experiment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTypical weekday meal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAt home eating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e557 adults (18\u0026ndash;30 years) living in Australia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNutrition content; cost; quality; taste; preparation time\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLivingstone et al (2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAustralia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDiscrete choice experiment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTypical weekday meal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAt home eating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e92 young adults (aged 18\u0026ndash;30 years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003ePreparation time of a meal; nutrition content of a meal; cost of a meal; taste of a meal; familiarity of a meal\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLoureiro et al (2016)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBest-worst scaling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFast food\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUniversity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e174 university students\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eSingle chicken burger; single bacon burger; single beef burger; double beef burger; double bacon burger; double chicken burger; salad\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarchini et al (2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eItaly\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBest-worst scaling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUniversity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e333 students aged over 18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNaturalness; price; safety; nutrition; fairness; environmental impact; legality\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMcKeown et al (2018)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConjoint analysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMenu (breakfast, lunch, snack)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSummer schemes and scripture union youth groups with adolescent members in Northern Ireland\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e239 adolescents aged 12\u0026ndash;18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFruit \u0026amp; vegetables; carbohydrates; dairy; fat \u0026amp; sugar\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMilte et al (2018)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAustralia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDiscrete choice experiment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMeal and dining experience\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 aged care homes in Australia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e292 residents or family members of residents living in age care homes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTaste; degree of choice in serving size; degree of choice in meal provided; flexibility in mealtimes; visual appeal; additional cost\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNguyen et al (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUSA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDiscrete choice experiment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFish entr\u0026eacute;e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCasual and fine dining restaurants\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1053 adult respondents (525/fine dining restaurants and 527/casual restaurants) who have eaten at casual or fine dining restaurant in the past 12 months and have consumed seafood in the past\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFish species; country of origin; production method; sustainability certification; sustainability rating; price\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eO'Neill et al (2014)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNorthern Ireland (UK)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStated choice experiment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHome-cooked meal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAt home eating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e584 individuals from a random sample of households\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eCalories; cooking time; food type; cost\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOng et al (2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhilippines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConjoint analysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSamgyeopsal meal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFilipino restaurants serving Samgyeopsal meals\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1018 Filipino consumers of Samgyeopsal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMeat; cheese; style; price; brand; drinks\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePanchalingam et al (2023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUSA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDiscrete choice experiment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSchool day lunch\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSchools\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3988 parent-student dyads\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eEntr\u0026eacute;e; fruit; vegetable; price\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePeters et al (2020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAustralia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBest-worst scaling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMenu item\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCasual restaurant (50% of sample), fine-dining restaurant (other 50% of sample)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1208 Australian diners\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eLocal produce; price; way a dish is written in menu; healthy option; method of preparation; dish I\u0026rsquo;ve never tried before; accompaniments; combination of ingredients; dish that I have tried before; sufficient portion size; sustainably produced; dish that I could not prepare; avoidance of certain foods\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrice et al (2016)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFour EU countries (UK, Greece, Denmark and France)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBest-worst scaling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCanteen dish\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eWorkplace canteens\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e452 employees, (UK (n\u0026thinsp;=\u0026thinsp;152), Greece (n\u0026thinsp;=\u0026thinsp;100), Denmark (n\u0026thinsp;=\u0026thinsp;100) and France (n\u0026thinsp;=\u0026thinsp;100) who had access to a canteen at their place of work\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eValue for money; organic; environmental impact; naturalness; nutrition; fair trade; provenance; animal welfare\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRusmevichientong et al (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThailand\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDiscrete choice experiment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5 villages in rural northern Thailand\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e403 adult residents of 5 villages\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFood preparation; price; taste; amount of salt\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSaville et al (2021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJapan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConjoint analysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFood in ramen restaurants and shopping malls\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRamen restaurants and shopping malls in Japan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e393 Muslims who had travelled to Japan within the last five years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eHalalness; prayer room availability; word of mouth; price; access\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSzymkowiak et al (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUSA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChoice-based conjoint analysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAt home eating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e753 US residents\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eConvenience; health; taste; process\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThienhirun et al (2018)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eThailand and Japan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConjoint analysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eThai/Japanese food (ready-to-eat \u0026amp; made-to-order)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOut of home eating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e68 people from Thailand and Japan with experience of Japanese food\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eTaste; design; calories; price\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZhou et al (2022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDenmark\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConjoint analysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDish\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAt home eating\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e100 Consumers aged 60\u0026nbsp;years or above living in Denmark\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMain course; potatoes; vegetables; dish label\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\u003eThe included studies explored preferences for a variety of meal types, including meals described in terms of time of the day they are consumed (e.g. breakfast, lunch, dinner) (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e); menu or menu items (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e); fast food (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e); military ration pack (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e); specific meals such as fish entr\u0026eacute;e, Samgyeopsal meal (Korean meat dish), and pizza (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e); and meals or food more generally (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan additionalcitationids=\"CR48 CR49\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). Various settings of meal consumption were explored such as at home eating (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e); restaurants (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e); universities (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e); school (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e); youth groups (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e); workplace canteens (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e); prisons (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e); military (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e); aged care homes (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e); community kitchens (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e); catering markets (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e); and more generally out-of-home eating settings (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Where appropriate, the study population was relevant to the study setting, e.g., prisoners (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e), dyads of parents and school students (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), and university students (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e), military personnel (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e), care home residents and their relatives (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), or customers/visitors within the settings of interest (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan additionalcitationids=\"CR34 CR35 CR36\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). In other studies, a random sample of the general population was selected as potential consumers of the meals of interest (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan additionalcitationids=\"CR29 CR30 CR31\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAttributes and levels\u003c/h3\u003e\n\u003cp\u003e148 unique attributes were extracted from the identified studies, and organised into 13 categories and 32 subcategories relevant to different meal characteristics (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e also lists examples of attributes and associated levels falling under each category and subcategory. The complete list of attributes and associated levels is available in Appendix 2.\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 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCategories and subcategories of attributes of meal preferences\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\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSubcategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExample attribute (original source)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAssociated description\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAssociated levels\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e\u003cp\u003e\u003cb\u003eHealthiness (n\u0026thinsp;=\u0026thinsp;27)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCaloric value (n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCalories (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLess than 400 calories; between 400 and 600 calories; over 600 calories\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDietary diversity (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDietary diversity (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2/3/4 food groups\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHealthiness (n\u0026thinsp;=\u0026thinsp;4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHealthy (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHealthy; neutral; unhealthy\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHealthy ingredients (n\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFiber source (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGrains; vegetables\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNutritional content (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNutrition content of a meal (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLow; adequate; optimal\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQuality (n\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eQuality (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLow; moderate; high\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSafety (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSafety (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eExtent to which consumption of food is safe and it will not cause illness (e.g. reliability of producers, security of origin)\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=\"c2\"\u003e\u003cp\u003eSatiety (n\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDigestibility (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA subjective feeling in the body after consuming a meal\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\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003ePrice/cost of a meal (n\u0026thinsp;=\u0026thinsp;19)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eObjective (n\u0026thinsp;=\u0026thinsp;12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePrice (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.5; 3; 6 nuevos soles (Peruvian currency)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSubjective (n\u0026thinsp;=\u0026thinsp;4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePrice (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCheap; average cost; expensive\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-specified (n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePrice (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCost of fresh foods\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\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eSpecific meal components and ingredients (n\u0026thinsp;=\u0026thinsp;18)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpecific ingredients (n\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eProtein source (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChicken; fish; alternative; egg\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpecific component (n\u0026thinsp;=\u0026thinsp;7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEntr\u0026eacute;e (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGrilled chicken sandwich; turkey club sandwich\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eSustainability, environmental and ethical considerations (n\u0026thinsp;=\u0026thinsp;18)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEthical considerations (n\u0026thinsp;=\u0026thinsp;4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFairness (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLimits within which all participants in the value chain receive fair benefits for their work or business (e.g. working conditions, dignified wages)\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=\"c2\"\u003e\u003cp\u003eOrigin (n\u0026thinsp;=\u0026thinsp;7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCountry of origin (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDomestic; imported; unknown\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOrganic production (n\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOrganic (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOrganic food is produced in a way that respects natural life cycles. It minimises the human impact on the environment and operates as naturally as possible\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=\"c2\"\u003e\u003cp\u003eEnvironmental and sustainability considerations (n\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSustainability certification\u0026nbsp;(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCertificated; non-certificated\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e\u003cp\u003e\u003cb\u003eSensory properties of a meal (n\u0026thinsp;=\u0026thinsp;16)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSensory properties (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSensory properties (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAppearance, smell, taste, texture\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=\"c2\"\u003e\u003cp\u003eSpecific taste (n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpice presence (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSpicy; not spicy\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eColor (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eColor variation (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eWith color variation; without color variation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGeneral taste (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTaste (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eVery good; good; sufficient\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFreshness (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFreshness (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFresh (fresh from the oven); not fresh\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTexture (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFood texture (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSoft; hard; chewy\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVisual appeal (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVisual appeal (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNot very (appealing); satisfactory; excellent\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eTime/convenience (n\u0026thinsp;=\u0026thinsp;14)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePreparation time (n\u0026thinsp;=\u0026thinsp;7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePreparation time (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0 minutes (in case of a ready meal, or take-away food); 15 minutes; 30 minutes; 45 minutes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTravel time (n\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTravel time from home to shop (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5 minutes; 10 minutes; 15 minutes; 20 minutes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFlexibility (n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFlexibility in mealtimes (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAnytime I like; within a 1\u0026ndash;2 hour range; at a set time\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConvenience/access (n\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAccess (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEasy; not\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eMarketing and external look (n\u0026thinsp;=\u0026thinsp;10)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLabel/packaging (n\u0026thinsp;=\u0026thinsp;7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePackaging (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNatural; bright and colorful\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBrand (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBrand (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSariwon Korea; Soban K-Town Grill; Samgyupsalamat; Romantic Baboy\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInformal marketing (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWord of mouth (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePositive; negative\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMenu description (n\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWay a dish is written in menu (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e)\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\u003e\u003cb\u003ePortion size (n\u0026thinsp;=\u0026thinsp;7)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSalad (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNone; medium; large\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\u003e\u003cb\u003eFamiliarity/food novelty (n\u0026thinsp;=\u0026thinsp;5)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFamiliarity of a meal (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNot very familiar; somewhat familiar; very familiar\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\u003e\u003cb\u003eMeal preparation (n\u0026thinsp;=\u0026thinsp;5)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStyle (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStyle refers to the way the main entr\u0026eacute;e is being prepared.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGrilled; hot pot; pre-cooked\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\u003e\u003cb\u003eTaste theme (n\u0026thinsp;=\u0026thinsp;4)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTaste theme (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMediterranean; Asian; Latin\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\u003e\u003cb\u003eCharacteristics of the dining environment (n\u0026thinsp;=\u0026thinsp;3)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHow food is served (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWith wait-staff; self-service\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\u003e\u003cb\u003eNaturalness (n\u0026thinsp;=\u0026thinsp;2)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNaturalness (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLimits within which food is produced without the use of additives, chemicals, or modern technology (e.g. low-processed foods)\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\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eMost commonly considered attribute was related to meal healthiness (n\u0026thinsp;=\u0026thinsp;27), including subcategories such as nutritional content (n\u0026thinsp;=\u0026thinsp;8), healthy ingredients (n\u0026thinsp;=\u0026thinsp;6), and caloric value (n\u0026thinsp;=\u0026thinsp;3), among other. The second most common category of attributes was price/cost of a meal considered in 19 of the 28 reviewed studies. Price was predominantly defined in terms of specific monetary values, such as 5/10/15 AUD per person in the study by Livingstone et al (2020) (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), reflecting the study context. However, in 4 studies, the price-related attribute was presented in terms of subjective price. For instance, Ernawati et al (2019) defined the levels of the price attribute as \u0026lsquo;cheap\u0026rsquo;, \u0026lsquo;average cost\u0026rsquo;, \u0026lsquo;expensive\u0026rsquo; (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), while Price et al (2016) included the attribute \u0026lsquo;value for money\u0026rsquo; defined as \u0026lsquo;the ratio between the perceived quality of the dish and the price paid for it\u0026rsquo; (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e The third most common categories were related to specific meal components and ingredients (n\u0026thinsp;=\u0026thinsp;18) and \u0026lsquo;sustainability, environmental and ethical considerations\u0026rsquo; (n\u0026thinsp;=\u0026thinsp;18). 11 of the extracted attributes referred to specific meal ingredients such as protein source (chicken; fish; alternative; egg) (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e) and type of flour (00; gluten free; cricket) (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e), and 7 of the attributes corresponded to meal components, for example, entr\u0026eacute;e (grilled chicken sandwich; turkey club sandwich) (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) and drinks (soju/beer; soft drinks; juice) (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Two studies utilised BWS to rank preferences for specific meal components. Kitunen et al (2022) ranked 21 components of an Australian military ration pack (e.g., main meal, bread, jam biscuit) (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Loureiro et al (2016) compared stated and actual preferences for fast food dishes, including a single chicken burger, single beef burger, and salad, among others (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Within the category \u0026lsquo;sustainability, environmental and ethical considerations\u0026rsquo;, the included subcategories were: food origin (n\u0026thinsp;=\u0026thinsp;4), such as country of origin (domestic; imported; unknown) (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e); environmental and sustainability considerations (n\u0026thinsp;=\u0026thinsp;5), such as sustainability rating (green; yellow; red; gray; unknown) (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e); ethical considerations (n\u0026thinsp;=\u0026thinsp;4) such as fairness and legality (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e); and organic production (n\u0026thinsp;=\u0026thinsp;2) (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSeveral attributes relating to various intrinsic properties of a meal were also considered, including meal\u0026rsquo;s sensory properties, such as taste, color, and visual appeal (n\u0026thinsp;=\u0026thinsp;16), portion size (n\u0026thinsp;=\u0026thinsp;7), taste theme (n\u0026thinsp;=\u0026thinsp;4), and naturalness (n\u0026thinsp;=\u0026thinsp;2). 14 attributes were related to the time/convenience, describing how fast and easy the meal was to prepare and/or access, including preparation time (n\u0026thinsp;=\u0026thinsp;7), flexibility (n\u0026thinsp;=\u0026thinsp;3), travel time (n\u0026thinsp;=\u0026thinsp;2), and convenience/access (n\u0026thinsp;=\u0026thinsp;2). 10 attributes concerned marketing and presentation (e.g. packaging, labelling, and brand). Other attribute categories were familiarity (n\u0026thinsp;=\u0026thinsp;5), meal preparation (n\u0026thinsp;=\u0026thinsp;5), and characteristics of the dining environment (n\u0026thinsp;=\u0026thinsp;3).\u003c/p\u003e\u003cp\u003eVarious sets of defined levels were used to describe the attributes. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e includes levels that accompanied example attributes in each category and subcategory, while Appendix 2 presents the levels corresponding to each attribute included in the reviewed studies. While it is considered good practice to accompany attributes with descriptions, descriptions were provided for only 43 out of the 148 extracted attributes.\u003c/p\u003e\u003cp\u003eWe also extracted data on relative importance of attributes from individual studies (column L in Appendix 2). However, due to substantial heterogeneity in the range of attributes included, we were not able to conduct a meaningful synthesis of this information.\u003c/p\u003e\n\u003ch3\u003eMethodological characteristics\u003c/h3\u003e\n\u003cp\u003eThe methodological characteristics of the included studies are presented in Appendix 2. The number of attributes varied by experimental design with BWS studies using between 6 and 21, with the median of 8; DCEs and conjoint analysis studies included between 3 and 7 attributes, with the median of 5. The number of levels used for each category ranged between two to four, with most attributes having three corresponding levels. The attributes and levels were most commonly derived from the literature (n\u0026thinsp;=\u0026thinsp;9), consultations with experts and relevant stakeholders (n\u0026thinsp;=\u0026thinsp;5), dietary guidelines (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e), and pre-existing knowledge of the meal of interest and the study context (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Eight studies relied on a combination of sources to identify attributes and levels for inclusion, such as the literature, expert consultations, meal characteristics, dietary recommendations, research team discussions, market prices, implementation feasibility, cost considerations, and pilot studies. Two studies did not report the source of attributes and levels.\u003c/p\u003e\u003cp\u003eChoice data were most often collected through online surveys (n\u0026thinsp;=\u0026thinsp;14) and phone or in-person interviews (n\u0026thinsp;=\u0026thinsp;11). One study gathered data across multiple stages using a combination of paper-based surveys and interviews (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Zhou et al (2022) collected data via a computer survey administered in a lab setting (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). One study did not report on the method of data collection.\u003c/p\u003e\u003cp\u003eTwo studies did not report the number of alternatives included in the choice tasks, and for an additional one this was not applicable due to study design. Among the studies that reported this information, participants were presented with an average of 4.3 alternatives (ranging between 3 and 8) in the BWS studies, and with an average of 4.75 alternatives (ranging between 1 and 19 in the DCE and conjoint analysis studies (excluding opt-outs). 25 studies provided information on the inclusion of an opt-out option, with 7 reporting that it was included. 26 studies reported the number of choice tasks per respondents, with an average of 11 in the BWS studies and 10 in the DCE or conjoint analysis studies.\u003c/p\u003e\u003cp\u003eThe reported choice task design included factorial (full or fractional, n\u0026thinsp;=\u0026thinsp;10), balanced incomplete block design (n\u0026thinsp;=\u0026thinsp;4), D-efficient design (n\u0026thinsp;=\u0026thinsp;3), orthogonal design (n\u0026thinsp;=\u0026thinsp;1), balanced overlap design (n\u0026thinsp;=\u0026thinsp;1), and random design with complete enumeration (n\u0026thinsp;=\u0026thinsp;1). Eight studies did not report the choice design. Among the 17 studies that reported the software used to design choice sets, 3 used Ngene, 3 used R, 4 used SAS, 3 used Sawtooth, 3 used SPSS, and 1 used Stata. 13 studies reported using blocking, an approach in which choice sets are divided into shorter blocks and participants are randomly allocated to one of these blocks. Blocking helps reduce the cognitive burden for each respondent who completes the survey and improves statistical efficiency of the choice model (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRegarding the statistical analysis, a variety of models were employed, including conditional logit (n\u0026thinsp;=\u0026thinsp;5), mixed logit (n\u0026thinsp;=\u0026thinsp;2), multinomial logit (n\u0026thinsp;=\u0026thinsp;2), random parameter (n\u0026thinsp;=\u0026thinsp;1), and a combination thereof (n\u0026thinsp;=\u0026thinsp;4). 9 studies used other methods for the analysis of correlation such as ordinary least squares regression, Pearson\u0026rsquo;s correlation, Kendall\u0026rsquo;s Tau, and best-worst method - multi-attributive ideal real comparative analysis (BWM-MAIRCA). 5 studies did not report the statistical model used for the estimation. A variety of software packages were used for the analysis of choice data, including Lingo, Nlogit, Ox, R, SPSS, SAS, Stata, Sawtooth, and XLSTAT. 5 studies did not report the software used for the analysis.\u003c/p\u003e\u003cp\u003e16 studies reported investigating preference heterogeneity. The most common methods included subgroup or cluster analysis (n\u0026thinsp;=\u0026thinsp;7), the use of estimation models that account for preference heterogeneity such as mixed logit and latent class models (n\u0026thinsp;=\u0026thinsp;4), investigation of interaction effects (n\u0026thinsp;=\u0026thinsp;3), and analysis of variance (n\u0026thinsp;=\u0026thinsp;1).\u003c/p\u003e\u003cp\u003eQualitative methods such as interviews, qualitative questions within self-completed surveys, and focus groups were used in 13 studies. Common reasons for using qualitative methods included development and piloting of attributes and levels (n\u0026thinsp;=\u0026thinsp;8), understanding responses and results (n\u0026thinsp;=\u0026thinsp;2), obtaining model values (n\u0026thinsp;=\u0026thinsp;1), and a combination of reasons (n\u0026thinsp;=\u0026thinsp;2).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo the best of our knowledge, this is the first systematic review of studies applying stated choice methods to investigate meal preferences, rather than focusing only on individual food products. This distinction is important, as meals reflect more complex decision-making processes that better capture real-world dietary behaviours and their implications for nutrition and health.\u003c/p\u003e\u003cp\u003eThis review makes two key contributions. First, it consolidates a comprehensive list of attributes and levels that influence meal preferences, which can guide the selection of attributes in future stated choice studies. Second, it highlights the methodological strengths and weaknesses in the current literature, providing a basis for the development of clearer guidance and reporting standards for applying these methods in food and nutrition research.\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eAttributes influencing meal preferences\u003c/h2\u003e\u003cp\u003e The review identified 13 broad categories and 22 subcategories of attributes, ranging from intrinsic characteristics such as taste, healthiness and portion size, to extrinsic characteristics including price, preparation time and sustainability. Importantly, a number of attributes were specific to meals, such as dining environment, method of meal preparation, and portion size, reinforcing the added value of meal-level analysis. These findings can inform preference studies that aim to capture the complexity of meal decision making across diverse contexts.\u003c/p\u003e\u003cp\u003eAttribute development often involved compiling information from multiple sources over several stages, aligning with good research practices. These sources included literature reviews, expert consultations, pilot validation studies, and supplementary qualitative methods. Using multiple sources in attribute development is recommended, as it enhances a study\u0026rsquo;s content validity (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). A diverse selection can also improve response quality and provide a more comprehensive understanding of choices and preferences (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). On the other hand, inclusion of a higher number of attributes may increase cognitive burden for participants (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). Therefore, careful selection of a comprehensive yet manageable number of attributes that comprehensively capture the decision context without overburdening participants can enhance the validity of stated choice studies. This is particularly relevant for studies in low- and middle-income countries, where dietary decisions are often influenced by affordability, time constraints and food availability. Good practice recommendations suggest that selection of attributes should be based on their \u003cem\u003e\u0026lsquo;\u0026hellip;relevance to the research question, relevance to the decision context, and whether attributes are related to one another.\u003c/em\u003e\u0026rsquo; (Bridges et al, 2011, pp. 406). While no strict limit exists, guidelines suggest including fewer than 10 attributes to reduce cognitive load (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe list of attribute categories and subcategories developed in this study could serve as a robust starting point for designing future studies using stated choice methods to elicit meal preferences. The attributes on this list can be refined and prioritised to align with specific study objectives by engaging stakeholders through methods such as interviews or the nominal group technique. Such an approach would help effectively capture the complexity of meal preferences, minimize participant burden, and ultimately enhance the validity and reliability of research findings.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eMethodological considerations when eliciting meal preferences\u003c/h2\u003e\u003cp\u003e This review identified a rise in the number of studies published from 2013 to 2022, reflecting growing recognition of the value of stated choice methods in food research. However, most studies were conducted in high-income settings countries, with limited evidence from LMICs where diet-related health challenges are most pressing. Expanding such research in LMICs would provide critical insights to inform nutrition policies.\u003c/p\u003e\u003cp\u003eMethodological inconsistencies were common. Lizin et al (2022) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) highlight that food-related preference elicitation studies often suffer from low reporting standards. In this review, missing information was observed in relation to the attribute and level development; study design; statistical models and software used for the analysis; and methods for investigating preference heterogeneity. Attribute definitions were often unclear, which could introduce bias, compromise internal validity, and limit generalizability of study findings across different contexts or populations. For example, the attribute \u0026lsquo;halalness\u0026rsquo;, described as halal-labelled food or Muslim-friendly food (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), lacked a clear definition, making its application to culturally diverse settings unclear.\u003c/p\u003e\u003cp\u003eAdditionally, previous research on preference elicitation has emphasised the importance of including various types of attributes in stated choice studies for a comprehensive representation of the decision-making context (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). However, some attributes and levels in the reviewed studies were not directly transferable to other settings without prior adjustment. For example, cost attributes were often presented in local currencies, reducing transferability to other contexts. Using more generalisable descriptions such as \u0026lsquo;cheap\u0026rsquo;, \u0026lsquo;average\u0026rsquo;, and \u0026lsquo;expensive\u0026rsquo;(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) may enhance applicability across countries, although this can reduce precision for economic valuation.\u003c/p\u003e\u003cp\u003ePoor reporting hinders the replication of research methodology, leading to ambiguity when interpreting results for future studies. Existing best practice guidelines from healthcare research preference research, such as those developed by The International Society for Pharmacoeconomics and Outcomes Research (ISPOR), offers a useful starting point, but specific reporting standards for food preference research are urgently needed(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Establishing such guidelines would improve comparability across studies, support more robust synthesis of findings, and ultimately strengthen the link between consumer preferences and nutrition policy.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eStrengths and Limitations\u003c/h2\u003e\u003cp\u003eA major strength of this review is its novel focus on meal-level preferences, which provides more relevant insights for dietary interventions and food system policies than product-level analyses alone. A robust search strategy was employed across relevant databases and informed by a comprehensive search string in accordance with published guidelines. Additionally, data on the methodological characteristics of studies were extracted and described in the results. Overall, this review advances current knowledge on the drivers of meal preferences by providing a list of relevant attributes and levels that could inform future stated choice studies, drawing on international evidence.\u003c/p\u003e\u003cp\u003eNevertheless, the review also had some limitations. The list of attributes was developed by synthesizing the information obtained from the literature and although it is comprehensive, some relevant attributes may have been omitted due to their absence in prior research. Furthermore, there was also inconsistencies in study reporting which may have constrained the completeness of the synthesis.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis review demonstrates that stated choice methods can provide valuable insights into the complex drivers of meal preferences, with direct implications for the design of policies and interventions that promote healthier and more sustainable diets. However, methodological inconsistencies were identified and there was limited representation of LMIC contexts. This suggests the need for standardised reporting and expanded global application of these methods. Strengthening the quality and scope of future meal preference research will enhance its contribution to improving population nutrition and reducing diet-related inequalities.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eData is provided within the manuscript or supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis project has received funding from the European Union\u0026rsquo;s Horizon 2020 research and innovation programme under grant agreement No 101035821. NA, IP and EF are funded by the National Institute for Health and Care Research (NIHR) [Research Professorship Award NIHR300773]. LF is funded by UKRI BBSRC [BB/V004832/1]. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. None of the funding bodies had a role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u0026nbsp;\u003c/strong\u003eConceptualization, I.P.; methodology, I.P., N.A. E.F., L.F.; formal analysis, N.A. and I.P.; data curation, N.A., and I.P.; writing\u0026mdash;original draft preparation, N.A.; writing\u0026mdash;review and editing, E.F., I.P., L.F.; funding acquisition, I.P. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eNone.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNeumark-Sztainer D, Story M, Perry C, Casey MA. Factors influencing food choices of adolescents: findings from focus-group discussions with adolescents. J Am Diet Assoc. 1999;99(8):929-37.\u003c/li\u003e\n\u003cli\u003eWHO. Diet, nutrition and the prevention of chronic diseases: report of a joint WHO/FAO expert consultation. 2003.\u003c/li\u003e\n\u003cli\u003eSeiler A, Chen MA, Brown RL, Fagundes CP. Obesity, Dietary Factors, Nutrition, and Breast Cancer Risk. Curr Breast Cancer Rep. 2018;10(1):14-27.\u003c/li\u003e\n\u003cli\u003eCandari CJ, Cylus J, Nolte E. European Observatory Health Policy Series. Assessing the economic costs of unhealthy diets and low physical activity: An evidence review and proposed framework. 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The willingness to consume insect-based food: an empirical research on Italian consumers. Agricultural Economics/Zemědělsk\u0026aacute; Ekonomika. 2019;65(10).\u003c/li\u003e\n\u003cli\u003eErnawati H, Prakoso D. CONSUMER PREFERENCES FOR INDONESIAN CULINARY. Journal of Indonesian Economy and Business. 2020;34.\u003c/li\u003e\n\u003cli\u003ede Guzman A, Barredo SF, Caillan KR. Examining the role of depression in the Filipino elderly\u0026apos;s food preferences in prison setting: data from conjoint analysis and SEM. Int J Prison Health. 2020;16(2):135-49.\u003c/li\u003e\n\u003cli\u003eKitunen A, Carins J, De Diana J. Segments of military ration pack eaters: Choice preferences among groups. Appetite. 2022;174:106023.\u003c/li\u003e\n\u003cli\u003eLoureiro ML, Rahmani D. The incidence of calorie labeling on fast food choices: A comparison between stated preferences and actual choices. 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Health Policy Plan. 2009;24(2):151-8.\u003c/li\u003e\n\u003cli\u003eGustafsson IB, \u0026Ouml;str\u0026ouml;m \u0026Aring;, Johansson J, Mossberg L. The Five Aspects Meal Model: a tool for developing meal services in restaurants. Journal of Foodservice. 2006;17:84-93.\u003c/li\u003e\n\u003cli\u003eKl\u0026oslash;jgaard ME, Bech M, S\u0026oslash;gaard R. Designing a Stated Choice Experiment: The Value of a Qualitative Process. Journal of Choice Modelling. 2012;5(2):1-18.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"meal preferences, food, stated choice methods, discrete choice experiment, meal attributes","lastPublishedDoi":"10.21203/rs.3.rs-7714370/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7714370/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground.\u003c/h2\u003e\u003cp\u003eFood preferences are influenced by habits, past experiences, socioeconomic and cultural factors. While much research has focused on individual food items, meal preferences involve a more complex decision-making process influenced by intrinsic and extrinsic factors. It remains unclear how perceptions of taste, healthiness, price, time, and other features are traded off when making meal choices. Understanding these factors is essential for informing food system policies that promote healthier diets and improve well-being. This study systematically reviewed stated choice experiments to identify attributes used to elicit meal preferences and to assess methodological characteristics of these studies.\u003c/p\u003e\u003ch2\u003eMethods.\u003c/h2\u003e\u003cp\u003eSeven databases (Web of Science, Scopus, Medline, Embase, PsychINFO, EconLit, and CINAHL) were searched. General and methodological study characteristics were extracted and summarised narratively, while meal attributes and levels were synthesised into themes.\u003c/p\u003e\u003ch2\u003eResults.\u003c/h2\u003e\u003cp\u003eOf 9,621 studies screened, 28 met the inclusion criteria, including 9 discrete choice experiments (DCEs), 9 conjoint analyses, 7 best-worst scaling, and 4 using other variations of stated choice methods. These studies elicited preferences across diverse settings (households, restaurants, care homes and prisons) and meal types (breakfast, lunch, dinner, specific dishes, and menus). Attributes were grouped into 13 categories, with 22 subcategories spanning intrinsic features (e.g., taste, ingredients, healthiness) and extrinsic features (e.g. price, convenience, sustainability, ethical aspects). Methodological limitations included inconsistent reporting and limited transparency in study design.\u003c/p\u003e\u003ch2\u003eDiscussion.\u003c/h2\u003e\u003cp\u003eThis is the first review to synthesise applications of stated choice methods for meal preferences rather than single food product preferences. The findings provide a comprehensive attribute framework that can inform research and standardisation of stated choice studies in nutrition. Addressing the methodological inconsistencies identified through clearer reporting and standardisation will strengthen the validity and comparability of evidence. This is critical for generating robust insights into meal preferences, supporting the design of food system policies that foster healthier and more sustainable diets and help reduce nutrition-related health inequalities.\u003c/p\u003e","manuscriptTitle":"How do the characteristics of a meal influence consumer preferences: a systematic literature review of studies using stated choice methods","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-16 08:02:30","doi":"10.21203/rs.3.rs-7714370/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e4631dd2-fd55-4552-aa10-600ab2adce49","owner":[],"postedDate":"October 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-16T08:02:30+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-16 08:02:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7714370","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7714370","identity":"rs-7714370","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}