Predicting Intentions to Use Non-Alcoholic Drinks: Applying the Theory of Planned Behaviour (TPB)

Predicting Intentions to Use Non-Alcoholic Drinks: Applying the Theory of Planned Behaviour (TPB) | 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 Research Article Predicting Intentions to Use Non-Alcoholic Drinks: Applying the Theory of Planned Behaviour (TPB) Sherifdeen Adams This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5587615/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 Introduction: Non-alcoholic drinks brands such as; sodas, juices, beers, gins, wines, stouts, Heinekens, lagers, spirits, sparkling ciders, and pale ales, etc. are the fastest growing area in the industry, and investment has meant the quality of such drinks is improving rapidly. The demand for these beverages is complex and changes over time with the introduction of new brands. However, little is known about consumers’ intention to use these drinks, and very little social research has explored this to date. Recent developments in non-alcoholic drinks markets have heightened the need for research on consumers’ intention to use non-alcoholic drinks and how different attributes influence these behaviours. This study sought to predict consumers’ intention to use non-alcoholic drinks based on the Theory of Planned Behavior (TPB). Methods: The study adopted a cross-sectional design comprising a quantitative method. Ajzen’s Theory of Planned Behavior is used as a theoretical framework and postulates three components: attitude, subjective norms, and perceived behaviour control. Data were collected online from 200 participants using a self-administered questionnaire. The participants were between 18 and 50 years old and residing in the United Kingdom. Results were presented in frequencies, percentages, means, and standard deviation. The multiple regression model was used to predict whether independent variables are associated with the dependent variable. Results: The findings of this study demonstrate that subjective norms predominantly influence the intention to use non-alcoholic drinks. Hence subjective norms ( p <.001) had a significant association with intention. The other covariates were not statistically significant. Conclusion: This study's practical implications contribute knowledge to investors, industries, and manufacturers in expanding their market and to governmental organizations in stimulating non-alcoholic consumption in the country. Non-Alcoholic Drinks Predicting Intentions Theory of Planned Behaviour (TPB) Figures Figure 1 CONTRIBUTIONS TO THE LITERATURE Given the fact that there is limited empirical research/ literature in the area of non-alcoholic drinks and the intentions of consumers towards different brands of non-alcoholic drinks. Thereby the study seeks to address the paucity of literature in this area. Less is known about consumers’ intention towards these drinks. Thus, this present study will provide a basis on which further research in the area could be carried out. A better understanding of predicting consumers’ intention to consume non-alcoholic drinks will be useful not only for the marketers in devising effective marketing strategies for an emerging market with great potential but also for agencies with interest in the promotion of healthy foods and drinks. Therefore, the information from this study may be helpful for marketers, planners and policymakers to build a more competitive brand in the market choice. INTRODUCTION Non-alcoholic drinks refer to products that either contain no alcohol or only minimal traces of ethanol-based alcohol [1]. Typically, a non-alcoholic drink has an alcohol content of 0.5% or less, or no alcohol at all, such as a 0% alcohol beer [2,3]. In some cases, small amounts of alcohol may be present, with specific limits varying by country. Non-alcoholic drinks must not exceed an alcohol percentage of 0.5% [4]. This category includes drinks traditionally free from alcohol, such as sodas, juices, beers, gins, wines, stouts, Heinekens, lagers, spirits, sparkling ciders, and pale ales, as well as drinks from which the alcohol has been removed, like non-alcoholic beers and de-alcoholized wines [5]. In the US and Europe, beverages with minimal or no alcohol are typically labelled as non-alcoholic or alcohol-free [2,6]. In Europe, a non-alcoholic drink is defined as having an alcohol by volume (ABV) of less than 0.5% [7,8]. In contrast, the UK defines non-alcoholic beverages as those containing 0.05% ABV or less. In the UK, drinks with an ABV below 0.5% are not subject to licensing laws [2,9]. However, the UK government is currently reviewing regulations, which may alter the definition and labelling of low-alcohol beverages [6,9]. In the UK, these beverages are classified as follows: 1. Alcohol-free: contains 0.05% alcohol or less 2. De-alcoholised: contains 0.5% alcohol or less 3. Low-alcohol: contains more than 0.5% but no more than 1.2% 4. Non-alcoholic drinks: contains no alcohol at all (0%) [1]. In the beverage market, the vast majority is covered by non-alcoholic drinks, making up a significant portion of the industry. Non-alcoholic drinks, including sodas, juices, beers, gins, wines, stouts, lagers, spirits, sparkling ciders, and pale ales, represent the fastest-growing area in the industry, with increasing investments driving rapid improvements in quality. Demand for these products is complex and changes over time as new brands enter the market [10]. In 2013, the non-alcoholic beverage sector generated approximately $531.3 billion in sales, reflecting its vast consumer base spanning centuries [11]. Social interactions heavily influence drinking behaviours [5,12]. People commonly consume non-alcoholic drinks with family, friends, and colleagues, primarily for relaxation, refreshment, and thirst-quenching purposes [13,14,15]. Non-alcoholic mixed drinks, such as punches, "virgin cocktails," and "mocktails," are especially popular among children, individuals whose religious beliefs prohibit alcohol, those recovering from alcohol dependence, and anyone seeking flavorful drinks without alcohol content [14,16,17]. According to the Economic Research Service of the United States Department of Agriculture [18], there is a significant shift in the consumption patterns of non-alcoholic drinks. The introduction of new products has made the demand for these drinks more varied and complex over time. Factors such as demographics, taste preferences, marketing, climate, and ease of access are known to influence consumption trends for non-alcoholic beverages [19,20,21]. With the growing focus on health and wellness, non-alcoholic beverages are likely to become a key driver of market growth in the future [19]. In recent years, consumers have become more conscious about their food choices due to health concerns [22]. This heightened awareness has led to an increased demand for healthier options [3]. In response, beverage manufacturers are now offering new, healthier non-alcoholic products, such as non-diet carbonated drinks, which could significantly influence future consumption patterns [19]. However, there is limited knowledge about consumers' intentions to consume non-alcoholic drinks, and social research on this topic remains scarce. The recent growth in the non-alcoholic drinks market has increased the need for studies on consumer intentions to use non-alcoholic drinks [23] and the various factors influencing their choices [17,24,25]. Predicting the intention to use non-alcoholic drinks is crucial for marketers, as it reflects the overall evaluation of the product and indicates both positive and negative feelings, as well as behavioural tendencies [25]. However, the relationship between intention and actual behaviour can be influenced by various factors. Consumers' attitudes, opinions, and perceptions of key decision-making influences—such as perceived behavioural control, subjective norms, personal attitudes, emotional responses (affect and cognition), and cultural acceptance—pose challenges for the industry. Consumers' purchasing decisions are also shaped by their buying power, which can guide non-alcoholic beverage companies and marketers in capturing market share [25]. This study utilizes the Theory of Planned Behavior (TPB) as its guiding framework. The concepts within the Theory of Planned Behavior (TPB) are designed to predict and explain specific behaviours within particular contexts [26]. As a general model, the TPB applies to a wide range of behaviours [27] and holds practical value [28]. Ajzen [29] suggests that the significance of attitudes, subjective norms, and perceptions of behavioural control in predicting intentions differs across behaviours and populations. Figure 1 illustrates the model, which highlights the three variables (attitude, subjective norms, and perceived behavioural control) that the theory posits as key predictors of the intention to engage in a behaviour. Consumer attitude is a critical aspect of consumer behaviour, reflecting an individual’s overall evaluation of a product, which can be positive or negative. Subjective norms involve the social pressure to engage in certain behaviours, shaped by others’ expectations and the judgments of those beliefs. Perceived Behavioral Control (PBC), reflects an individual’s confidence in their ability to perform a behaviour factoring in both external and internal influences, such as availability, price, and taste, particularly in non-alcoholic beverage consumption [29]. Despite this, research on consumer intentions regarding non-alcoholic drinks, particularly in the UK, remains sparse. This study aims to fill this gap by predicting consumers' intentions to use non-alcoholic drinks, thereby addressing the existing lack of literature, especially within the UK context. There are three hypotheses in this study: Hypothesis 1: Attitude will significantly predict intention to use Non-alcoholic Drinks. Hypothesis 2: Subjective norms will significantly predict the intention to use Non-alcoholic Drinks. Hypothesis 3: Perceived behavioural control (PBC) will significantly predict the intention to use Non-alcoholic Drinks. METHOD Study Design A cross-sectional design comprising a quantitative method was used in this study. A cross-section of the population was selected and measured only once. That is, the sample was selected across age groups, genders and among the general public who resides in the United Kingdom. Study Variables For this study, the dependent variable was intention while the independent variables were perceived behavioural control (PBC), subjective norms and attitude. Study Participants The study participants were among the general public, aged between 18 to 50 years ( M =29.91, SD =8.18) and who reside in the United Kingdom. Inclusion criteria for the study were, residing in the United Kingdom at the time of data collection; aged 18 or above; competent in English language; and able and willing to provide informed consent. Those who did not meet the above criteria were excluded from the study. Sampling and Sample Size A convenience sampling method was adopted to select study participants to collect data through an online survey. 200 respondents (n=104 male; n=90 female and n=6 of those preferred not to say) of different nationalities took part in the study. Data Collection A link access to the online questionnaire was posted on social networking sites (via Facebook, Messenger, WhatsApp, Instagram and Twitter). Descriptions, pictorial and visual prompts of what is meant by non-alcoholic drinks were presented to the study participants. Participants were then presented with a 20 questionnaire to measure their behaviour regarding non-alcoholic drinks by indicating the degree to which each of the 20 statements influenced their behaviour to use of non-alcoholic drinks on a 5-point Likert scale which ranged from strongly disagree with a score of 1 to strongly agree with the score of 5. The questionnaire is then divided into four sections; attitudes, subjective norms, perceived behavior control and intentions. A higher score on each section indicated a greater influence on behaviour to use non-alcoholic drinks. Therefore, the number beside each response became the value for that response and a participant’s total score was obtained by adding all the scores for each response attached to the respective Likert scale ticked or marked and the maximum score a person could get on the scale was 100 and for the minimum score 20. Measurements/ Data Variables/Tools The instrument of this study was developed by the researcher based on the TPB framework, which consists of three constructs namely attitude, subjective norms and perceived behavioural control (PBC). The questionnaires were adapted and modified from existing questionnaires to measure consumers’ intention to use Non-alcoholic Drinks. The first section of the questionnaire collected relevant demographic information such as age, gender and where participants are located in the UK. The second part comprised of questions concerning non-alcoholic drink use which consisted of four parts with each part comprising of a scale of five (5) item questions and a five-point Likert scale response which measures how a person assesses himself/herself to the statements on the scale. Measures of attitude, subjective norms, perceived behavioural control (PBC) and intention to use non-alcoholic drinks were devised specifically for the study as no existing measures were available. The questionnaire was constructed specifically for this study, according to the guidelines given in the manual for constructing questionnaires based on the TPB [30]. Attitude was measured by five (5) items of favourable or unfavourable respondents’ evaluation of non-alcoholic drinks. Total scores ranged from 5-25 points, the lower the score the more unfavourable the evaluation of non-alcoholic drink use and the higher the score the more favourable the evaluation of non-alcoholic drink use. The measurement of the subjective norm was designed to investigate whether recommendations or opinions from others or influence from a third party would affect participants’ decision to consume non-alcoholic drinks. Scores ranged from 5-25 points, the lower the score the more negative the perception of non-alcoholic drink use by significant others and the higher the score the more positive the perception of non-alcoholic drink use by significant others. Participants were asked to rate individuals that influenced their decision to consume non-alcoholic drinks which consisted of five (5) items. To assess participant’s perceived behavioural control (PBC) towards non-alcoholic drinks, participants were asked to answer a series of questions using five (5) items. Scores ranged from 5-25 points, the higher the score the more control a person perceived themselves to have over non-alcoholic drink use. Intention to use non-alcoholic drinks was also measured by five (5) items. Participants could score between 5-25 points, with a low score indicating no intention to use non-alcoholic drinks and a high score denoting an intention to use non-alcoholic drinks. Data Management and Analysis Data were coded and summarized using Excel Spreadsheet in conformity with the study objectives and exported into Statistical Package for Social Science (SPSS) for analysis. Descriptive statistics employing frequencies, percentages, means and standard deviation were used in analyzing and interpreting the demographic data such as; age, gender, non-alcoholic drink brands and alcoholic drinks. Inferential statistics, involving the Multiple regression model was used to predict whether independent variables (attitude, subjective norms and perceived behavioural control) are associated with the dependent variable (intention). Statistical significance was set at 0.05 and confidence intervals were assessed. Ethical Consideration Permission to conduct this study was obtained from the School of Psychology and Therapeutic Studies Ethics Approval Panel at the University of South Wales. The study was performed by the Helsinki Declaration guidelines (The Helsinki Declaration guidelines are the World Medical Association (WMA) Declaration of Helsinki – Ethical Principles for Medical Research Involving Human Subjects). Information was also provided to study participants about their rights and responsibilities including rights to confidentiality, voluntary participation, and the right to withdraw at any time if they so wished. Informed consent was obtained from consenting participants. Participants who gave their consent were asked to tick “Yes” on the consent form to indicate their willingness to participate in the study. RESULTS A total sample of 200 participants was used in all analyses. Table 1 below summarizes the descriptive analysis of the demographic information of the respondents. Of the total 200 participants aged 18–65 interviewed, the majority were males 52% (n = 104). The mean age and standard deviation for the participants were 29.91 (SD = 8.18). 85.5% (n = 71) of the participants indicated that they consumed non-alcoholic drinks and 72% (n = 144) indicated they don’t consume alcoholic drinks. With regards to the mean scores and standard deviations of the constructs used in this study according to the Theory of Planned Behavior. Mean scores are presented based on a five-point Likert scale (1–5). In general, respondents perceived behavioural control was rated at 16.03 (SD = 4.72), Subjective norm at 19.80 (SD = 4.94) and attitude at 17.99 (SD = 4.59). Subjective norm was identified with the highest mean score at 19.80, showing that the majority of respondents had a more positive perception of non-alcoholic drink use by significant others. This is shown in Table 1 below. Table 1 Summary table of frequencies, percentages, Means and Standard deviations of variables. Variables Total (%) Mean (SD) Yes (%) No (%) Respondents 200 (100) Gender Male 104 (52) Female 90 (45) Prefer not to say 6 (3) Age (years) 29.91(8.18) Consume non-alcoholic drink 71 (85.5) 29 (14.5) Consume alcoholic drink 56 (28) 144 (72) Perceived behavioural control 16.03 (4.72) Subjective norms 19.80 (4.94) Attitude 17.99 (4.59) Table 2 below shows the test of association between variables (independent variables) and intention (dependent variable). Apart from Subjective norms ( B = 0.423; p < .001) which is significantly associated with intention, the other covariates (Perceived behavioural control and attitude) are not. In other words, Subjective norms score is the best predictor of intention to use non-alcoholic drinks. Perceived behavioural control score and attitude score are not significant predictors of intention to use non-alcoholic drinks. All the tolerance values for each variable in the table are acceptable, thus, this indicates no problem with collinearity. The overall model was significant and explained 28% of the variance in intention. (F (5,199) = 16.176, P < .001, Adjusted R square = 0.276). This is shown in the table below. Table 2 Summary table showing the association between study variables (Multiple Regression). Variables F R Square Std. error B P -value Tolerance 16.176 0.276 0.001* Perceived behavioural control 0.083 0.054 0.43 0.778 Subjective norms 0.081 0.423 0.001* 0.734 Attitude 0.094 0.108 0.16 0.631 DISCUSSION This study aimed to predict consumers' intention to use non-alcoholic drinks based on the Theory of Planned Behavior (TPB). The study investigated whether attitude would significantly predict the intention to use non-alcoholic drinks. Additionally, it explored whether subjective norms would be a significant predictor of this intention, and finally, it hypothesized that perceived behavioural control would also significantly influence the intention to use non-alcoholic drinks. The study findings did not support the first hypothesis, as no significant association was found between attitude and intention. Similarly, the third hypothesis was not supported, with the results indicating no significant link between perceived behavioural control and intention. However, the second hypothesis was supported, revealing a significant association between subjective norms and intention. A comprehensive discussion of each hypothesis is provided, comparing the current results with similar findings from previous research, along with an examination of the theoretical and practical implications of the study. The findings related to the second hypothesis of this study align with previous research, demonstrating that subjective norms are a predictor of intentions to consume non-alcoholic beverages. The results are consistent with those of Nada et al. [ 31 ], who found a significant association between subjective norms and consumption intentions. In their study, parents and friends had a strong influence on adolescents’ beverage choices, with both male and female adolescents consuming soft beer as a way to enjoy leisure time with peers and family. Additionally, several other studies example, [ 32 , 33 ] have reported that adolescents' beverage preferences are heavily influenced by their parents. Similarly, the study by Kit et al. [ 34 ] found that "health professionals now tend to influence the consumption of non-alcoholic beverages among youth and young adults in the United States." They concluded that subjective norms are the strongest predictor of intentions to consume non-alcoholic drinks. The similarity in findings between the current study and Kit et al. [ 34 ] may be attributed to the comparable sample sizes, with the current study involving 200 participants and Kit et al. [ 34 ] using a sample of 209. Similarly, Khalek and Ismail [ 35 ] conducted a study using the Theory of Planned Behavior (TPB) to examine factors influencing urban Generation Y’s intentions to consume non-alcoholic drinks in Malaysia. Their findings indicated that subjective norms were a primary influence on these intentions. The strong impact of subjective norms observed in the current study may be linked to participants’ social behaviours and the potential influence of health professionals on their choices to consume non-alcoholic beverages. Thus, social influences—such as family, friends, health professionals, role models, and social media—are generally key factors shaping non-alcoholic beverage consumption in the UK. In this study, the first determinant, attitude, played an insignificant role in predicting intentions to consume non-alcoholic drinks. This result contradicts the findings of Nada et al. [ 31 ], which showed that attitude had a statistically significant positive relationship with intention. Nada et al. [ 31 ] found that although all determinants were significant predictors, the attitude was the strongest, accounting for 49% of the variance in regular consumption intentions. The findings of the current study do not align with those of Muzakkeerul and Alam [ 36 ], who reported that consumers have a highly positive attitude towards non-alcoholic beverages. Their study assessed consumer attitudes towards popular non-alcoholic beverages in Bangladesh using the theory of planned behaviour. They concluded that their results could benefit non-alcoholic beverage industries, academics, marketing firms, and applied researchers by utilizing attitude constructs to enhance beverage quality and develop effective marketing strategies [ 36 ]. The differences between the findings of the current study and those of Nada et al. [ 31 ] and Muzakkeerul & Alam [ 36 ] may be attributed to variations in variable categorization, comparisons, and sample size. In Nada et al.'s [ 31 ] study, participants were grouped based on age and gender, and these groups were then compared. In contrast, the current study did not categorize participants by age, nor did it involve group comparisons. Additionally, Muzakkeerul & Alam [ 36 ] utilized a larger sample size of 620 participants, while the current study had a sample size of 200. In the present study, perceived behavioural control was found to be insignificant in predicting the intention to consume non-alcoholic drinks. This finding contrasts with the results of [ 31 , 35 , 37 , 38 , 39 ], whose studies identified several factors, such as taste, price, flavour, availability of information, accessibility, and availability, as influencing consumers' intentions to consume or purchase non-alcoholic beverages. In addition, the current study's findings regarding perceived behavioural control do not align with those of McEachan et al. [ 40 ], whose meta-analysis found that attitudes, subjective norms, and perceived behavioural control explained 41% of the variance in behavioural intentions, with perceived behavioural control being the strongest predictor. Similarly, Conner et al. [ 41 ] applied the theory of planned behaviour to examine young adults' intentions to purchase non-alcoholic beverages, finding that perceived behavioural control was a significant predictor of these intentions. STRENGTH & LIMITATION The strength of the current study is that the general population who participated are not exclusively within Wales but also from other parts of the United Kingdom. Participation was cross-cultural, and the population was suitable for the study because of its heterogeneity in terms of its characteristics. That is the participants hail from different socio-economic backgrounds. This helps the study to gain strong internal as well as external validity. Also, in the current study participants were recruited through an online survey. An online survey method of data collection is generally considered a reliable source of data collection and gives accurate results. It is less time-consuming, flexible, and economical, higher response rate, convenient and easy for participants to respond to questions as everything is automated and electronic. It also captures and analyses data more quickly. Obtaining data quickly plays a role in determining the efficiency of a survey and addresses the right kind of issues at the right time. This study, as with any other research, has some limitations. First, the findings presented in this study involve a relatively small size that may not be statistically representative of the general population in the study area. The sample size was also used partly because this study was time-bound and primarily conducted for academic purposes. For this reason, the researcher had to work with a sample size that could be manageable within the period. The main constraint of small studies is their inability to represent an entire population. It is therefore necessary for additional research works to be done on the topic with a larger sample size and a more diverse population to enable generalization of the observations. Also, there was limited time constraint to collect data. The study proposal was submitted for ethics approval but it was being delayed for approval. It was therefore not possible for the study to have access to the University of South Wales online surveys account without ethics approval. For this reason, the researcher had to work with a limited time that could be manageable within the period. The limited time constraint resulted in a small sample size used, which might have affected the results. In addition, this study was limited to only people 18 years and above. People who were below 18 years of age (teenagers) could not take part in the study. This might have jeopardized the generalizability of the study findings and future studies should consider having teenagers (below 18 years of age) take part to enable different varied views. RECOMMENDATION & CONCLUSION The study highlighted several determinants associated with intention based on the Theory of Planned Behavior (TPB). Generally, subjective norm was significantly associated with consumers’ intention to use non-alcoholic drinks. In other words, the subjective norm is the best predictor of intention to consume non-alcoholic drinks. It was demonstrated that people's choices of consuming non-alcoholic drinks were largely influenced by family, friends, health professionals, role models, and social media. The result of this study showed that the Theory of Planned Behavior (TPB) is an effective model that can be used to predict the intention to consume non-alcoholic drinks. Therefore, this study suggests that the Government, non-alcoholic industries, investors, marketers, planners and policymakers may incorporate the element of social influence/ pressure in their non-alcoholic beverages campaign and advertisement. The availability and variety of non-alcoholic drink brands also need to be given attention by the non-alcoholic industry. Future research may broaden the population and expand the geographical locations to other countries within Europe. DECLARATIONS Ethics Approval and consent to participate Ethical approval was obtained from the School of Psychology and Therapeutic Studies Ethics Approval Panel at the University of South Wales. Informed written consent was obtained from all the participants of the study and confidentiality was assured and ensured. Competing interests The authors declare that they have no competing interests. Funding This work received no funding support. Consent for publication Not applicable Availability of data and materials The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request Authors' contributions SA conceived the study and drafted and reviewed the manuscript. SA also analyzed the data. Acknowledgements Not applicable REFERENCES Humphreys, C. (2018). What is meant by Alcohol-Free? Hallett, T. (2019). 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The Relationship of Social Context of Drinking, Perceived Social Norms, & Parental Influence to various drinking patterns of adolescents. Addictive Behaviors , 21(5), 633-644. Kit, B.K., Fakhouri, T.H., Park, S., Nielsen, S.J., & Ogden, C.L. (2012). Trends in Alcoholic Free Beverages Consumption among Youth and Adults in the United States: 1999-2010. The American Journal of Clinical Nutrition , 98(1):180-188. Khalek, A.A., & Ismail, S.H.S. (2014). Why are we eating Halal using the Theory of Planned Behavior (TPB) in predicting Halal food consumption among Generation Y in Malaysia? International Journal of Social Science and Humanity, Vol. 5, No. 7, July 2015. Muzakkeerul, H. & Alam. (2007). Measuring Consumers Attitudes for Non-alcoholic Beverages in Bangladesh: An Empirical Study on Stouts, Lagers, Beer, Wines and Heineken. Journal of Business and Technology . Vol.4, Issue-1, pp.130-143. Zoellner, J., Krzeski, E., Harden, S., Cook, E., Allen, K., & Estabrooks, P.A. (2011). Qualitative Application of the Theory of Planned Behavior to Understand Non-alcoholic Beverage Consumption Behaviors among Adolescents. Journal of the Academy of Nutrition and Dietetics , 112(11),1774-1784. Grimm, G.C., Harnack, L., & Story, M. (2004). Factors Associated with Soft Drink Consumption in School-aged Children. Journal of the American Dietetic Association, 104(8), 1244-1249. Povey, R., Conner, M., Sparks, P., James, R., & Shepherd, R. (1999). The Theory of Planned Behavior and Healthy Drinking: Examining addictive and moderating effects of social influence variables. Psychology & Health, 14(6), 991-1006. McEachan, R.R.C., Conner, M., Taylor, N.J., & Lawton, R.J. (2004). Prospective Prediction of Health-related Behaviors with the Theory of Planned Behavior: A meta-analysis. Health Psychology Review, 5(2), 97-144. Conner, M., Norman, P., & Bell, R. (2003). Applying the Theory of Planned Behavior to young adults’ Intention to purchase Non-alcoholic Beverages. Health Psychology , 21(2), 194. Additional Declarations No competing interests reported. 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-5587615","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":389739700,"identity":"7f326502-bad6-49a9-b095-c06243bd4395","order_by":0,"name":"Sherifdeen Adams","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABJElEQVRIie2QP0vDQBiH3xDIdHLrhUD6FSIHAWkgX+U9AulS8AsIBoRMpa4B60codOpq4CBTwPUgDoJrKQFBghbxtKgdEnV0uAfef8MDP14Ag+E/wnRhZO8Poot+9K9zSEkPFDf7iwKHSlD+ooyuLqr2Hsc+9TKr3ZytY367lC08RyKjy7JPCe6qpECccHdR2u6iasRabVNmzVORsS32KmzKQXRSrBSCR5wGQ1WHYM0kB1YHvcGK00dAlOc3Cu0X8trEvKh5+5MCamq/KxgwdLyjvLFWdBYw6KQPeukNplKulclxoUR+cj1vRKFIyESW+g4jA8GSB6vD8YgWiVSbpyamlzpYu4sIpQPBvrGy/WT6TyIHcFjvw/qgpW67z8VgMBgM8AbQcWU5gEBKtwAAAABJRU5ErkJggg==","orcid":"","institution":"Ghana Health Service – Accra","correspondingAuthor":true,"prefix":"","firstName":"Sherifdeen","middleName":"","lastName":"Adams","suffix":""}],"badges":[],"createdAt":"2024-12-05 14:08:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5587615/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5587615/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":75405345,"identity":"3d67a049-0447-41bc-b09c-ff2089905101","added_by":"auto","created_at":"2025-02-04 08:46:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":24288,"visible":true,"origin":"","legend":"\u003cp\u003eModel of Theory of Planned Behaviour\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5587615/v1/b1b32f3ce6a29a9755f73b59.png"},{"id":75411514,"identity":"223bd3c0-16f6-4338-bb37-a17aad2b4f3e","added_by":"auto","created_at":"2025-02-04 09:10:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":701534,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5587615/v1/75afbb1e-d0b6-4615-9ae9-4b9d34b67a13.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predicting Intentions to Use Non-Alcoholic Drinks: Applying the Theory of Planned Behaviour (TPB)","fulltext":[{"header":" CONTRIBUTIONS TO THE LITERATURE","content":"\u003cul\u003e\n \u003cli\u003eGiven the fact that there is limited empirical research/ literature in the area of non-alcoholic drinks and the intentions of consumers towards different brands of non-alcoholic drinks. \u0026nbsp;Thereby the study seeks to address the paucity of literature in this area.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLess is known about consumers’ intention towards these drinks. Thus, this present study will provide a basis on which further research in the area could be carried out.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eA better understanding of predicting consumers’ intention to consume non-alcoholic drinks will be useful not only for the marketers in devising effective marketing strategies for an emerging market with great potential but also for agencies with interest in the promotion of healthy foods and drinks. Therefore, the information from this study may be helpful for marketers, planners and policymakers to build a more competitive brand in the market choice.\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"INTRODUCTION","content":"\u003cp\u003eNon-alcoholic drinks refer to products that either contain no alcohol or only minimal traces of ethanol-based alcohol [1]. Typically, a non-alcoholic drink has an alcohol content of 0.5% or less, or no alcohol at all, such as a 0% alcohol beer [2,3]. In some cases, small amounts of alcohol may be present, with specific limits varying by country. Non-alcoholic drinks must not exceed an alcohol percentage of 0.5% [4]. This category includes drinks traditionally free from alcohol, such as sodas, juices, beers, gins, wines, stouts, Heinekens, lagers, spirits, sparkling ciders, and pale ales, as well as drinks from which the alcohol has been removed, like non-alcoholic beers and de-alcoholized wines [5].\u003c/p\u003e\n\u003cp\u003eIn the US and Europe, beverages with minimal or no alcohol are typically labelled as non-alcoholic or alcohol-free [2,6]. In Europe, a non-alcoholic drink is defined as having an alcohol by volume (ABV) of less than 0.5% [7,8]. In contrast, the UK defines non-alcoholic beverages as those containing 0.05% ABV or less. In the UK, drinks with an ABV below 0.5% are not subject to licensing laws [2,9]. However, the UK government is currently reviewing regulations, which may alter the definition and labelling of low-alcohol beverages [6,9]. In the UK, these beverages are classified as follows:\u003c/p\u003e\n\u003cp\u003e1.\u0026nbsp; \u0026nbsp;Alcohol-free: contains 0.05% alcohol or less\u003c/p\u003e\n\u003cp\u003e2.\u0026nbsp; \u0026nbsp;De-alcoholised: contains 0.5% alcohol or less\u003c/p\u003e\n\u003cp\u003e3.\u0026nbsp; \u0026nbsp;Low-alcohol: contains more than 0.5% but no more than 1.2%\u003c/p\u003e\n\u003cp\u003e4.\u0026nbsp; \u0026nbsp;Non-alcoholic drinks: contains no alcohol at all (0%) [1].\u003c/p\u003e\n\u003cp\u003eIn the beverage market, the vast majority is covered by non-alcoholic drinks, making up a significant portion of the industry. Non-alcoholic drinks, including sodas, juices, beers, gins, wines, stouts, lagers, spirits, sparkling ciders, and pale ales, represent the fastest-growing area in the industry, with increasing investments driving rapid improvements in quality. Demand for these products is complex and changes over time as new brands enter the market [10]. In 2013, the non-alcoholic beverage sector generated approximately $531.3 billion in sales, reflecting its vast consumer base spanning centuries [11].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSocial interactions heavily influence drinking behaviours [5,12]. People commonly consume non-alcoholic drinks with family, friends, and colleagues, primarily for relaxation, refreshment, and thirst-quenching purposes [13,14,15]. Non-alcoholic mixed drinks, such as punches, \u0026quot;virgin cocktails,\u0026quot; and \u0026quot;mocktails,\u0026quot; are especially popular among children, individuals whose religious beliefs prohibit alcohol, those recovering from alcohol dependence, and anyone seeking flavorful drinks without alcohol content [14,16,17].\u003c/p\u003e\n\u003cp\u003eAccording to the Economic Research Service of the United States Department of Agriculture [18], there is a significant shift in the consumption patterns of non-alcoholic drinks. The introduction of new products has made the demand for these drinks more varied and complex over time. Factors such as demographics, taste preferences, marketing, climate, and ease of access are known to influence consumption trends for non-alcoholic beverages [19,20,21].\u003c/p\u003e\n\u003cp\u003eWith the growing focus on health and wellness, non-alcoholic beverages are likely to become a key driver of market growth in the future [19]. In recent years, consumers have become more conscious about their food choices due to health concerns [22]. This heightened awareness has led to an increased demand for healthier options [3]. In response, beverage manufacturers are now offering new, healthier non-alcoholic products, such as non-diet carbonated drinks, which could significantly influence future consumption patterns [19].\u003c/p\u003e\n\u003cp\u003eHowever, there is limited knowledge about consumers\u0026apos; intentions to consume non-alcoholic drinks, and social research on this topic remains scarce. The recent growth in the non-alcoholic drinks market has increased the need for studies on consumer intentions to use non-alcoholic drinks [23] and the various factors influencing their choices [17,24,25].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePredicting the intention to use non-alcoholic drinks is crucial for marketers, as it reflects the overall evaluation of the product and indicates both positive and negative feelings, as well as behavioural tendencies [25]. However, the relationship between intention and actual behaviour can be influenced by various factors. Consumers\u0026apos; attitudes, opinions, and perceptions of key decision-making influences\u0026mdash;such as perceived behavioural control, subjective norms, personal attitudes, emotional responses (affect and cognition), and cultural acceptance\u0026mdash;pose challenges for the industry. Consumers\u0026apos; purchasing decisions are also shaped by their buying power, which can guide non-alcoholic beverage companies and marketers in capturing market share [25]. This study utilizes the Theory of Planned Behavior (TPB) as its guiding framework.\u003c/p\u003e\n\u003cp\u003eThe concepts within the Theory of Planned Behavior (TPB) are designed to predict and explain specific behaviours within particular contexts [26]. As a general model, the TPB applies to a wide range of behaviours [27] and holds practical value [28]. Ajzen [29] suggests that the significance of attitudes, subjective norms, and perceptions of behavioural control in predicting intentions differs across behaviours and populations. Figure 1 illustrates the model, which highlights the three variables (attitude, subjective norms, and perceived behavioural control) that the theory posits as key predictors of the intention to engage in a behaviour.\u003c/p\u003e\n\u003cp\u003eConsumer attitude is a critical aspect of consumer behaviour, reflecting an individual\u0026rsquo;s overall evaluation of a product, which can be positive or negative. Subjective norms involve the social pressure to engage in certain behaviours, shaped by others\u0026rsquo; expectations and the judgments of those beliefs. Perceived Behavioral Control (PBC), reflects an individual\u0026rsquo;s confidence in their ability to perform a behaviour factoring in both external and internal influences, such as availability, price, and taste, particularly in non-alcoholic beverage consumption [29].\u003c/p\u003e\n\u003cp\u003eDespite this, research on consumer intentions regarding non-alcoholic drinks, particularly in the UK, remains sparse. This study aims to fill this gap by predicting consumers\u0026apos; intentions to use non-alcoholic drinks, thereby addressing the existing lack of literature, especially within the UK context. There are three hypotheses in this study:\u003c/p\u003e\n\u003cp\u003eHypothesis 1: Attitude will significantly predict intention to use Non-alcoholic Drinks.\u003c/p\u003e\n\u003cp\u003eHypothesis 2: Subjective norms will significantly predict the intention to use Non-alcoholic Drinks.\u003c/p\u003e\n\u003cp\u003eHypothesis 3: Perceived behavioural control (PBC) will significantly predict the intention to use Non-alcoholic Drinks.\u003c/p\u003e"},{"header":"METHOD","content":"\u003ch2\u003eStudy Design\u003c/h2\u003e\n\u003cp\u003eA cross-sectional design comprising a quantitative method was used in this study. A cross-section of the population was selected and measured only once. That is, the sample was selected across age groups, genders and among the general public who resides in the United Kingdom.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor this study, the dependent variable was intention while the independent variables were perceived behavioural control (PBC), subjective norms and attitude.\u003c/p\u003e\n\u003ch2\u003eStudy Participants\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe study participants were\u0026nbsp;among the general public,\u0026nbsp;aged between 18 to 50 years (\u003cem\u003eM\u003c/em\u003e=29.91, \u003cem\u003eSD\u003c/em\u003e=8.18) and who reside in the United Kingdom. Inclusion criteria for the study were, residing in the United Kingdom at the time of data collection; aged 18 or above; competent in English language; and able and willing to provide informed consent. Those who did not meet the above criteria were excluded from the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSampling and Sample Size\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA convenience sampling method was adopted to select study participants to collect data through an online survey. 200 respondents (n=104 male; n=90 female and n=6 of those preferred not to say) of different nationalities took part in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA link access to the online questionnaire was posted on social networking sites (via Facebook, Messenger, WhatsApp, Instagram and Twitter). \u0026nbsp;Descriptions, pictorial and visual prompts of what is meant by non-alcoholic drinks were presented to the study participants.\u0026nbsp; Participants were then presented with a 20 questionnaire to measure their behaviour regarding non-alcoholic drinks by indicating the degree to which each of the 20 statements\u0026nbsp;influenced their behaviour to use of non-alcoholic drinks on a 5-point Likert scale\u0026nbsp;which ranged from strongly disagree with a score of 1 to strongly agree with the score of 5.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe questionnaire is then divided into four sections; attitudes, subjective norms, perceived behavior control and intentions. A higher score on each section indicated a greater influence on behaviour to use non-alcoholic drinks. Therefore, the number beside each response became the value for that response and a participant’s total score was obtained by adding all the scores for each response attached to the respective Likert scale ticked or marked and the maximum score a person could get on the scale was 100 and for the minimum score 20.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasurements/ Data Variables/Tools\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe instrument of this study was developed by the researcher based on the TPB framework, which consists of three constructs namely attitude, subjective norms and perceived behavioural control (PBC). The questionnaires were adapted and modified from existing questionnaires to measure consumers’ intention to use Non-alcoholic Drinks. The first section of the questionnaire collected relevant demographic information such as age, gender and where participants are located in the UK.\u003c/p\u003e\n\u003cp\u003eThe second part comprised of questions concerning non-alcoholic drink use which consisted of four parts with each part comprising of a scale of five (5) item questions and a five-point Likert scale response which measures how a person assesses himself/herself to the statements on the scale. Measures of attitude, subjective norms, perceived behavioural control (PBC) and intention to use non-alcoholic drinks were devised specifically for the study as no existing measures were available. The questionnaire was constructed specifically for this study, according to the guidelines given in the manual for constructing questionnaires based on the TPB [30].\u003c/p\u003e\n\u003cp\u003eAttitude was measured by five (5) items of favourable or unfavourable respondents’ evaluation of non-alcoholic drinks. Total scores ranged from 5-25 points, the lower the score the more unfavourable the evaluation of non-alcoholic drink use and the higher the score the more favourable the evaluation of non-alcoholic drink use. The measurement of the subjective norm was designed to investigate whether recommendations or opinions from others or influence from a third party would affect participants’ decision to consume non-alcoholic drinks. Scores ranged from 5-25 points, the lower the score the more negative the perception of non-alcoholic drink use by significant others and the higher the score the more positive the perception of non-alcoholic drink use by significant others. Participants were asked to rate individuals that influenced their decision to consume non-alcoholic drinks which consisted of five (5) items.\u003c/p\u003e\n\u003cp\u003eTo assess participant’s perceived behavioural control (PBC) towards non-alcoholic drinks, participants were asked to answer a series of questions using five (5) items. Scores ranged from 5-25 points, the higher the score the more control a person perceived themselves to have over non-alcoholic drink use. Intention to use non-alcoholic drinks was also measured by five (5) items. Participants could score between 5-25 points, with a low score indicating no intention to use non-alcoholic drinks and a high score denoting an intention to use non-alcoholic drinks.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eData Management and\u0026nbsp;Analysis\u003c/h2\u003e\n\u003cp\u003eData were coded and summarized using Excel Spreadsheet in conformity with the study objectives and exported into Statistical Package for Social Science (SPSS) for analysis. Descriptive statistics employing frequencies, percentages, means and standard deviation were used in analyzing and interpreting the demographic data such as; age, gender, non-alcoholic drink brands and alcoholic drinks. Inferential statistics, involving the Multiple regression model was used to predict whether independent variables (attitude, subjective norms and perceived behavioural control) are associated with the dependent variable (intention). Statistical significance was set at 0.05 and confidence intervals were assessed.\u003c/p\u003e\n\u003ch2\u003eEthical Consideration\u003c/h2\u003e\n\u003cp\u003ePermission to conduct this study was obtained from the School of Psychology and Therapeutic Studies Ethics Approval Panel at the University of South Wales.\u0026nbsp;The study was performed by the Helsinki Declaration guidelines (The Helsinki Declaration guidelines are the World Medical Association (WMA) Declaration of Helsinki – Ethical Principles for Medical Research Involving Human Subjects).\u003c/p\u003e\n\u003cp\u003eInformation was also provided to study participants about their rights and responsibilities including rights to confidentiality, voluntary participation, and the right to withdraw at any time if they so wished. Informed consent was obtained from consenting participants. Participants who gave their consent were asked to tick “Yes” on the consent form to indicate their willingness to participate in the study.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total sample of 200 participants was used in all analyses. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e below summarizes the descriptive analysis of the demographic information of the respondents. Of the total 200 participants aged 18\u0026ndash;65 interviewed, the majority were males 52% (n\u0026thinsp;=\u0026thinsp;104). The mean age and standard deviation for the participants were 29.91 (SD\u0026thinsp;=\u0026thinsp;8.18). 85.5% (n\u0026thinsp;=\u0026thinsp;71) of the participants indicated that they consumed non-alcoholic drinks and 72% (n\u0026thinsp;=\u0026thinsp;144) indicated they don\u0026rsquo;t consume alcoholic drinks. With regards to the mean scores and standard deviations of the constructs used in this study according to the Theory of Planned Behavior. Mean scores are presented based on a five-point Likert scale (1\u0026ndash;5). In general, respondents perceived behavioural control was rated at 16.03 (SD\u0026thinsp;=\u0026thinsp;4.72), Subjective norm at 19.80 (SD\u0026thinsp;=\u0026thinsp;4.94) and attitude at 17.99 (SD\u0026thinsp;=\u0026thinsp;4.59). Subjective norm was identified with the highest mean score at 19.80, showing that the majority of respondents had a more positive perception of non-alcoholic drink use by significant others. This is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e below.\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\u003eSummary table of frequencies, percentages, Means and Standard deviations of variables.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"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\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRespondents\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104 (52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90 (45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrefer not to say\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.91(8.18)\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\u003eConsume non-alcoholic drink\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71 (85.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29 (14.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConsume alcoholic drink\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56 (28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e144 (72)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePerceived behavioural control\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.03 (4.72)\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\u003eSubjective norms\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.80 (4.94)\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\u003eAttitude\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.99 (4.59)\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e below shows the test of association between variables (independent variables) and intention (dependent variable). Apart from Subjective norms (\u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.423; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001) which is significantly associated with intention, the other covariates (Perceived behavioural control and attitude) are not. In other words, Subjective norms score is the best predictor of intention to use non-alcoholic drinks. Perceived behavioural control score and attitude score are not significant predictors of intention to use non-alcoholic drinks. All the tolerance values for each variable in the table are acceptable, thus, this indicates no problem with collinearity. The overall model was significant and explained 28% of the variance in intention. (F (5,199)\u0026thinsp;=\u0026thinsp;16.176, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, Adjusted R square\u0026thinsp;=\u0026thinsp;0.276). This is shown in the table below.\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 table showing the association between study variables (Multiple Regression).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR Square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStd. error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTolerance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived behavioural control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.778\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubjective norms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.734\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAttitude\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.631\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study aimed to predict consumers\u0026apos; intention to use non-alcoholic drinks based on the Theory of Planned Behavior (TPB). The study investigated whether attitude would significantly predict the intention to use non-alcoholic drinks. Additionally, it explored whether subjective norms would be a significant predictor of this intention, and finally, it hypothesized that perceived behavioural control would also significantly influence the intention to use non-alcoholic drinks.\u003c/p\u003e\n\u003cp\u003eThe study findings did not support the first hypothesis, as no significant association was found between attitude and intention. Similarly, the third hypothesis was not supported, with the results indicating no significant link between perceived behavioural control and intention. However, the second hypothesis was supported, revealing a significant association between subjective norms and intention. A comprehensive discussion of each hypothesis is provided, comparing the current results with similar findings from previous research, along with an examination of the theoretical and practical implications of the study.\u003c/p\u003e\n\u003cp\u003eThe findings related to the second hypothesis of this study align with previous research, demonstrating that subjective norms are a predictor of intentions to consume non-alcoholic beverages. The results are consistent with those of Nada et al. [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e], who found a significant association between subjective norms and consumption intentions. In their study, parents and friends had a strong influence on adolescents\u0026rsquo; beverage choices, with both male and female adolescents consuming soft beer as a way to enjoy leisure time with peers and family. Additionally, several other studies example, [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e] have reported that adolescents\u0026apos; beverage preferences are heavily influenced by their parents.\u003c/p\u003e\n\u003cp\u003eSimilarly, the study by Kit et al. [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e] found that \u0026quot;health professionals now tend to influence the consumption of non-alcoholic beverages among youth and young adults in the United States.\u0026quot; They concluded that subjective norms are the strongest predictor of intentions to consume non-alcoholic drinks. The similarity in findings between the current study and Kit et al. [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e] may be attributed to the comparable sample sizes, with the current study involving 200 participants and Kit et al. [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e] using a sample of 209.\u003c/p\u003e\n\u003cp\u003eSimilarly, Khalek and Ismail [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e] conducted a study using the Theory of Planned Behavior (TPB) to examine factors influencing urban Generation Y\u0026rsquo;s intentions to consume non-alcoholic drinks in Malaysia. Their findings indicated that subjective norms were a primary influence on these intentions. The strong impact of subjective norms observed in the current study may be linked to participants\u0026rsquo; social behaviours and the potential influence of health professionals on their choices to consume non-alcoholic beverages. Thus, social influences\u0026mdash;such as family, friends, health professionals, role models, and social media\u0026mdash;are generally key factors shaping non-alcoholic beverage consumption in the UK.\u003c/p\u003e\n\u003cp\u003eIn this study, the first determinant, attitude, played an insignificant role in predicting intentions to consume non-alcoholic drinks. This result contradicts the findings of Nada et al. [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e], which showed that attitude had a statistically significant positive relationship with intention. Nada et al. [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e] found that although all determinants were significant predictors, the attitude was the strongest, accounting for 49% of the variance in regular consumption intentions.\u003c/p\u003e\n\u003cp\u003eThe findings of the current study do not align with those of Muzakkeerul and Alam [\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e], who reported that consumers have a highly positive attitude towards non-alcoholic beverages. Their study assessed consumer attitudes towards popular non-alcoholic beverages in Bangladesh using the theory of planned behaviour. They concluded that their results could benefit non-alcoholic beverage industries, academics, marketing firms, and applied researchers by utilizing attitude constructs to enhance beverage quality and develop effective marketing strategies [\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eThe differences between the findings of the current study and those of Nada et al. [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e] and Muzakkeerul \u0026amp; Alam [\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e] may be attributed to variations in variable categorization, comparisons, and sample size. In Nada et al.\u0026apos;s [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e] study, participants were grouped based on age and gender, and these groups were then compared. In contrast, the current study did not categorize participants by age, nor did it involve group comparisons. Additionally, Muzakkeerul \u0026amp; Alam [\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e] utilized a larger sample size of 620 participants, while the current study had a sample size of 200.\u003c/p\u003e\n\u003cp\u003eIn the present study, perceived behavioural control was found to be insignificant in predicting the intention to consume non-alcoholic drinks. This finding contrasts with the results of [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e], whose studies identified several factors, such as taste, price, flavour, availability of information, accessibility, and availability, as influencing consumers\u0026apos; intentions to consume or purchase non-alcoholic beverages.\u003c/p\u003e\n\u003cp\u003eIn addition, the current study\u0026apos;s findings regarding perceived behavioural control do not align with those of McEachan et al. [\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e], whose meta-analysis found that attitudes, subjective norms, and perceived behavioural control explained 41% of the variance in behavioural intentions, with perceived behavioural control being the strongest predictor. Similarly, Conner et al. [\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e] applied the theory of planned behaviour to examine young adults\u0026apos; intentions to purchase non-alcoholic beverages, finding that perceived behavioural control was a significant predictor of these intentions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSTRENGTH \u0026amp; LIMITATION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe strength of the current study is that the general population who participated are not exclusively within Wales but also from other parts of the United Kingdom. Participation was cross-cultural, and the population was suitable for the study because of its heterogeneity in terms of its characteristics. That is the participants hail from different socio-economic backgrounds. This helps the study to gain strong internal as well as external validity.\u003c/p\u003e\n\u003cp\u003eAlso, in the current study participants were recruited through an online survey. An online survey method of data collection is generally considered a reliable source of data collection and gives accurate results. It is less time-consuming, flexible, and economical, higher response rate, convenient and easy for participants to respond to questions as everything is automated and electronic. It also captures and analyses data more quickly. Obtaining data quickly plays a role in determining the efficiency of a survey and addresses the right kind of issues at the right time.\u003c/p\u003e\n\u003cp\u003eThis study, as with any other research, has some limitations. First, the findings presented in this study involve a relatively small size that may not be statistically representative of the general population in the study area. The sample size was also used partly because this study was time-bound and primarily conducted for academic purposes. For this reason, the researcher had to work with a sample size that could be manageable within the period. The main constraint of small studies is their inability to represent an entire population. It is therefore necessary for additional research works to be done on the topic with a larger sample size and a more diverse population to enable generalization of the observations.\u003c/p\u003e\n\u003cp\u003eAlso, there was limited time constraint to collect data. The study proposal was submitted for ethics approval but it was being delayed for approval. It was therefore not possible for the study to have access to the University of South Wales online surveys account without ethics approval. For this reason, the researcher had to work with a limited time that could be manageable within the period. The limited time constraint resulted in a small sample size used, which might have affected the results.\u003c/p\u003e\n\u003cp\u003eIn addition, this study was limited to only people 18 years and above. People who were below 18 years of age (teenagers) could not take part in the study. This might have jeopardized the generalizability of the study findings and future studies should consider having teenagers (below 18 years of age) take part to enable different varied views.\u003c/p\u003e"},{"header":"RECOMMENDATION \u0026 CONCLUSION","content":"\u003cp\u003eThe study highlighted several determinants associated with intention based on the Theory of Planned Behavior (TPB). Generally, subjective norm was significantly associated with consumers’ intention to use non-alcoholic drinks. In other words, the subjective norm is the best predictor of intention to consume non-alcoholic drinks. It was demonstrated that people's choices of consuming non-alcoholic drinks were largely influenced by family, friends, health professionals, role models, and social media. The result of this study showed that the Theory of Planned Behavior (TPB) is an effective model that can be used to predict the intention to consume non-alcoholic drinks. Therefore, this study suggests that the Government, non-alcoholic industries, investors, marketers, planners and policymakers may incorporate the element of social influence/ pressure in their non-alcoholic beverages campaign and advertisement. The availability and variety of non-alcoholic drink brands also need to be given attention by the non-alcoholic industry. Future research may broaden the population and expand the geographical locations to other countries within Europe.\u003c/p\u003e"},{"header":"DECLARATIONS","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the School of Psychology and Therapeutic Studies Ethics Approval Panel at the University of South Wales. Informed written consent was obtained from all the participants of the study and confidentiality was assured and ensured.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work received no funding support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNot applicable\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSA conceived the study\u0026nbsp;and\u0026nbsp;drafted and reviewed the manuscript. SA also analyzed the data.\u003c/strong\u003e\u003c/p\u003e\n\u003ch4\u003eAcknowledgements\u003c/h4\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"REFERENCES","content":"\u003col\u003e\n \u003cli\u003eHumphreys, C. (2018). What is meant by Alcohol-Free?\u003c/li\u003e\n \u003cli\u003eHallett, T. (2019). What\u0026rsquo;s in Alcohol-Free Beer? (Ingredients and Nutritional Content).\u003c/li\u003e\n \u003cli\u003eCapps, O.Jr., Clauson, A. Guthrie, J., Pittman, G. \u0026amp; Stockton, M. (2005). Contributions of Non-alcoholic beverages to the U.S. diet. United States Department of Agriculture, \u003cem\u003eEconomic Research Service Report Number\u003c/em\u003e 1, March 2005.\u003c/li\u003e\n \u003cli\u003eOkaru AO, Lachenmeier DW. Defining No and Low (NoLo) Alcohol Products. Nutrients. 2022 Sep 19;14(18):3873. doi: 10.3390/nu14183873. PMID: 36145249; PMCID: PMC9506306.\u003c/li\u003e\n \u003cli\u003eKassem, N.O., Lee, J.W., Modeste, N.N., \u0026amp; Johnston, P.K. 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UK: \u003cem\u003eCentre for Health Service Research\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eNada, T. B., Bell, R. A., Stephenson, J. J., \u0026amp; Purifoy, F. E. (2003). Investigating alcoholic free drink consumption among female adolescents by using the Theory of Planned Behaviour.\u003cem\u003e\u0026nbsp;Academic Psych\u003c/em\u003e, 65, 464-466. \u003cem\u003ePsych Web of Science\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eStory, M., Neumark-Sztainer, D., \u0026amp; French, S. (2002). Individual and Environmental Influences on Adolescent Drinking Behavior. \u003cem\u003eJournal of the American Dietetic Association\u003c/em\u003e, 102(3), S40-S51.\u003c/li\u003e\n \u003cli\u003eKirk, K.H., \u0026amp; Gillespie, K.A. (1990). The Relationship of Social Context of Drinking, Perceived Social Norms, \u0026amp; Parental Influence to various drinking patterns of adolescents. \u003cem\u003eAddictive Behaviors\u003c/em\u003e, 21(5), 633-644.\u003c/li\u003e\n \u003cli\u003eKit, B.K., Fakhouri, T.H., Park, S., Nielsen, S.J., \u0026amp; Ogden, C.L. (2012). Trends in Alcoholic Free Beverages Consumption among Youth and Adults in the United States: 1999-2010. \u003cem\u003eThe American Journal of Clinical Nutrition\u003c/em\u003e, 98(1):180-188.\u003c/li\u003e\n \u003cli\u003eKhalek, A.A., \u0026amp; Ismail, S.H.S. (2014). Why are we eating Halal using the Theory of Planned Behavior (TPB) in predicting Halal food consumption among Generation Y in Malaysia? \u003cem\u003eInternational Journal of Social Science and Humanity, Vol. 5, No. 7, July 2015.\u003c/em\u003e\u003c/li\u003e\n \u003cli\u003eMuzakkeerul, H. \u0026amp; Alam. (2007). 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The Theory of Planned Behavior and Healthy Drinking: Examining addictive and moderating effects of social influence variables. Psychology \u0026amp; Health, 14(6), 991-1006.\u003c/li\u003e\n \u003cli\u003eMcEachan, R.R.C., Conner, M., Taylor, N.J., \u0026amp; Lawton, R.J. (2004). Prospective Prediction of Health-related Behaviors with the Theory of Planned Behavior: A meta-analysis. Health Psychology Review, 5(2), 97-144.\u003c/li\u003e\n \u003cli\u003eConner, M., Norman, P., \u0026amp; Bell, R. (2003). Applying the Theory of Planned Behavior to young adults\u0026rsquo; Intention to purchase Non-alcoholic Beverages. \u003cem\u003eHealth Psychology\u003c/em\u003e, 21(2), 194.\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":"Non-Alcoholic Drinks, Predicting Intentions, Theory of Planned Behaviour (TPB)","lastPublishedDoi":"10.21203/rs.3.rs-5587615/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5587615/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction: \u003c/strong\u003eNon-alcoholic drinks brands such as; sodas, juices, beers, gins, wines, stouts, Heinekens,\u003cstrong\u003e \u003c/strong\u003elagers, spirits, sparkling ciders, and pale ales, etc. are the fastest growing area in the industry, and investment has meant the quality of such drinks is improving rapidly. The demand for these beverages is complex and changes over time with the introduction of new brands. However, little is known about consumers’ intention to use these drinks, and very little social research has explored this to date. Recent developments in non-alcoholic drinks markets have heightened the need for research on consumers’ intention to use non-alcoholic drinks and how different attributes influence these behaviours. This study sought to predict consumers’ intention to use non-alcoholic drinks based on the Theory of Planned Behavior (TPB).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThe study adopted a cross-sectional design comprising a quantitative method. Ajzen’s Theory of Planned Behavior is used as a theoretical framework and postulates three components: attitude, subjective norms, and perceived behaviour control. Data were collected online from 200 participants using a self-administered questionnaire. The participants were between 18 and 50 years old and residing in the United Kingdom. Results were presented in frequencies, percentages, means, and standard deviation. The multiple regression model was used to predict whether independent variables are associated with the dependent variable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe findings of this study demonstrate that subjective norms predominantly influence the intention to use non-alcoholic drinks. Hence subjective norms (\u003cem\u003ep\u003c/em\u003e\u0026lt;.001) had a significant association with intention. The other covariates were not statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThis study's practical implications contribute knowledge to investors, industries, and manufacturers in expanding their market and to governmental organizations in stimulating non-alcoholic consumption in the country.\u003c/p\u003e","manuscriptTitle":"Predicting Intentions to Use Non-Alcoholic Drinks: Applying the Theory of Planned Behaviour (TPB)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-04 08:46:41","doi":"10.21203/rs.3.rs-5587615/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":"dba04ccc-4394-4a10-a67a-d6df0fdbeec3","owner":[],"postedDate":"February 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-04T08:46:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-04 08:46:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5587615","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5587615","identity":"rs-5587615","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}