THE INFLUENCE OF ACTORS' ONSCREEN ALCOHOL CONSUMPTION AND SMOKING ON THEIR FANS FROM SOCIAL LEARNING PERSPECTIVE

Venkatesh M ¹ , Dr. Sripriya M ²

¹Full-Time Research Scholar, Department of Mass Communication and Journalism, PSG College of Arts and Science, Coimbatore, Tamil Nadu, India

²Assistant Professor, Department of Mass Communication and Journalism, PSG College of Arts and Science, Coimbatore, Tamil Nadu, India

		ABSTRACT
		In recent years, every movie has begun with the statutory warning saying, “Smoking Causes Cancer and Smoking Kills; Liquor Drinking is Injurious to Health." These statutory warnings are shown to the cinema audience to raise awareness that drinking and smoking are not socially accepted behaviours. This research aims to find out whether the actors' on-screen alcohol consumption and smoking in films had an influence on their fans. The study was conducted between the period August 2023 to October 2023.This study adopted a quantitative method with purposive sampling technique and the responses were collected through a survey from 254 male respondents from the state of Tamil Nādu. The study has found that such as age and locality are found to have high influence on the behaviour change at 0.01 level, Besides the age, locality, educational qualification, and occupation has high chances of fans Imitation by watching films 0.01 level. The impact of age, locality, and educational qualification on reinforcement and self-efficacy has significant relationships at the 0.01 level of significance thus shows how fans support and oppose actors' similar actions. Movie watching in theatre compared with self-efficacy does not have significant relationship because fans does not resist in influencing by watching their favourite actors. The findings revealed many significant associations and thus shows the relationship between movie-watching habits had influence on adoption of onscreen behaviours of their favourite actors. As a result, the representations of drinking and smoking by the actors have the potential to have a negative influence on fans health and lifestyle.
Corresponding Author Venkates M, 22pmcf02@psgcas.ac.in DOI 10.29121/shodhkosh.v5.i ICITAICT.2024.1242 Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Copyright: © 2024 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License. With the license CC-BY, authors retain the copyright, allowing anyone to download, reuse, re-print, modify, distribute, and/or copy their contribution. The work must be properly attributed to its author.
		Keywords: Actors, Onscreen Behaviour, Alcohol Consumption, Smoking, Social Learning Theory

1. INTRODUCTION

Films are powerful instrument that can change views in societies, changing the way youth perceive the world and influence politics, law, society, and history (Gogoi, 2022). In the entertainment industry, the representation of specific behaviors by famous individuals has long been seen to play an important influence in influencing society standards and individual perspectives. Recent films such as "Joe," "Animal," and "Lover" have led to debate over their portrayals of smoking, drinking, and drug use. Critics firmly believe these films glorify hazardous behaviours, potentially influencing audiences, particularly young people. Thus, Films enhance the learning process in organizational behaviour and management courses by delivering unique communication features that are unavailable in other media. (Champoux, 1999). Concerns have been raised concerning the normalizing of such acts on the big screen, as well as the possible impact on society views about substance usage. This has sparked debates about filmmakers' responsibilities in presenting these practices, as well as the importance of raising awareness about their potential effects. Modern cinema media can have both positive and negative effects on people's consciousness and behaviour. (Petrash, 2023).

The 2023 Tamil film LEO faced controversy for its song "Naa Ready," which was criticized for glorifying drug use and promoting drinking and smoking. The Central Board of Film Certification (CBFC) recommended changes to the lyrics related to smoking and alcohol. (Staff, 2023). The influence of movies in shaping society norms and habits is of highest relevance in the world of entertainment. The impact of onscreen characters and their activities regularly goes beyond the bounds of the screen, impacting fashion trends and lifestyle choices. When celebrities drink alcohol or smoke in movies or on Television, it can make these habits seem cool or normal. People, especially young ones, might copy what they see famous people do. This can be a problem because it could encourage unhealthy behaviours. It's important for celebrities to think about the example they're setting and for movies and Television shows to show healthier choices.

2. RESEARCH OBJECTIVES

The major purpose of this study is to examine whether the consumption of alcohol and smoking of the film actors on screen is influencing their fan base based on the framework of Social Learning Theory. The study's purpose is to evaluate the links between quantitative variables involved with behaviour change (observational learning), imitation, reinforcement, and self-efficacy. The Research further explores the effect of actors' onscreen alcohol drinking and smoking practices among fans. Investigate how fans' certainty about their ability to get involved in these activities affects their chances of imitation by watching their favourite actors’ activities onscreen.

3. CONCEPTUAL FRAMEWORK

Figure 1

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Figure 1 Conceptual Framework of Bandura Social Learning Theory (1971)

Albert Bandura's social learning theory involves numerous factors that alter behaviour. Behaviour change, imitation, reinforcement, and self-efficacy are key factors adopted for this study. Behaviour change is caused by learning and observation. This theory highlights the role of observational learning in altering behaviour as individuals watch and mimic others. Imitation involves closely monitoring and replicating another's actions, behaviours, and attitudes. Bandura suggests that humans learn by imitating role models and prominent personalities in their immediate surroundings. According to Bandura's social learning theory, reinforcement is crucial for behaviour. Positive reinforcement, like praise or prizes, promotes a behaviour, while negative reinforcement discourages it. Self-efficacy is the belief in one's own ability to carry out and resist an action or reach an objective. According to Bandura's thesis, self-efficacy is vital to behaviour change because individuals with high self-efficacy are more willing to do what they can do effectively. The conceptual framework of social learning theory posits that these elements interact with one another to influence behaviour change. Observational learning, imitation, reinforcement, and self-efficacy all play key parts in the process of learning and behaviour modification. This study examines how a fan is influenced by the bandura social learning factors. (Bandura, 1971)

4. FILM AS AN INFLUENCER IN ALCOHOL CONSUMPTION AND SMOKING BEHAVIOUR

The media influence how we live, including encouraging unhealthy behaviours like alcohol consumption and smoking (Atkin, 1990). Adolescents who admire movie stars that use tobacco on-screen are significantly more likely to become regular smokers and hold positive attitudes towards smoking, compared to those who admire non-smoking stars. The representation of tobacco uses in modern films, especially by performers who are popular among teenagers, promotes to adolescent smoking (Tickle, 2001). Watching films that show characters smoking increases the likelihood of teenagers becoming more susceptible to smoking and developing positive expectations about smoking as a normal practice for adults. (Sargent, 2002) Substances are often shown in media, viewed by young people, and may have adverse effects on their health and overall welfare. (Kimberly M. Thompson, 2005). Alcohol use in movies has been shown to have a major impact on adolescent alcohol use (Cin, 2009). Glamorisation versus reality in performing arts is tricky, as favourable depictions can attract audiences and even push drug consumption above any consequences. Different media consequence may develop for different negative conduct such as smoking and drinking (Griffiths, 2010). Tobacco use among adolescents is associated with exposure to smoking role models, (Rahul Sharma, 2010). Viewing smoking scenes in movies is directly linked to immediately following smoking behaviour. (Dikla Shmueli, 2010) Viewing a film that depicts alcohol consumption has been found to correlate with increased alcohol intake among male viewers. (Renske Koordeman D. J., 2010). Young individuals who are exposed to cinematic visuals depicting alcohol and drug use are more likely to engage in heavy drinking, binge drinking, and drug usage (Hunt, 2011). Adolescents who are exposed to smoking scenes in movies are more likely to start smoking, and the risk increases in proportion to the amount of exposure (Waylen, 2011). Celebrities considerably influence adolescents' behaviour, attitudes, culture, moral values, fashion, and way of life. Their impact depends on the adolescents themselves and parental engagement. While celebrities may inspire confidence and transparency, they can also negatively impact social decorum and language (Amit Jain, 2015).

5. METHODOLOGY

This study adopts a quantitative method for this research, utilizing purposive sampling to considering 254 male participants from different age groups who are actively involved in watching movies of their favourite actors. Using surveys and structured interviews with a questionnaire grounded in Bandura's Social Learning Theory variables, the study examines the influence of actors' onscreen behaviours on fans. Independent variables are demographic variables such as age, gender, education, occupation, and locality are considered. While dependent variables encompass behaviour change, imitation, reinforcement, and self-efficacy. The study used a survey questionnaire that employs the Likert scale to obtain data. Data analysis involves descriptive statistics and the Pearson chi-square test for association, facilitated by SPSS statistical software. The study aims to present results through tables, offering conclusions, acknowledging limitations, and proposing practical recommendations for interventions. The research is scheduled for a specified data collection period from August 2023 to October 2023 to ensure clarity and focus on its findings. This study design enables the methodical analysis of numerical data to establish associations between variables.

6. DATA ANALYSIS AND INTERPRETATION

Table 1

Table 1 Influence of Age, Locality, Educational Qualification and Occupation on Behaviour Change
DEMOGRAPHIC VARIABLES WITH BEHAVIOUR CHANGE (SOCIAL LEARNING VARIABLES)	N of Valid Cases	Pearson Chi-Square Value	df	Significance levels	P - Value
AGE	254	38.294^a	8	.000	0.01
LOCALITY	254	30.051^a	6	.000	0.01
EDUCATION QUALIFICATION	254	12.515^a	8	0.13	0.130
OCCUPATION	254	8.407^a	6	0.21	0.210

The table 6.1 shows that there is a significant relationship at 5-point level significance between demographic variables of age and locality with behaviour change (χ²=38.294^a, df=8, P <.000) (p=0.01), (χ²=30.051^a, df=6, P <.000) (p=0.01) which is highly significant level. Demographic variables of education qualification and occupation with behaviour change does not have a significant relationship at less than <5% (χ²=12.515^a, df=8, P >.130) (p=0.130), (χ²=8.407^a, df=6, P >.210) (p=0.210).

Table

Table 2 Influence of Age, Locality, Educational Qualification and Occupation on Imitation
DEMOGRAPHIC VARIABLES WITH IMITATION	N of Valid Cases	Pearson Chi-Square Value	Df	Significance levels	P - Value
AGE	254	42.774^a	8	.000	0.01
LOCALITY	254	38.169^a	6	.000	0.01
EDUCATION QUALIFICATION	254	24.206^a	8	.002	0.03
OCCUPATION	254	38.345^a	6	.000	0.01

The table 6.2 shows that there is a significant relationship at 5-point level significance between demographic variables of age, locality, educational qualification, and occupation with imitation (χ²=42.774^a, df=8, P <.000) (p=0.01) , (χ²=38.169^a, df=6, P <.000) (p=0.01), (χ²=24.206^a, df=8, P <.002) (p=0.03), (χ²=38.345^a, df=6, P <.000) (p=0.01).These results are highly significant at 1 level.

Table 3

Table 3 Influence of Age, Locality, Educational Qualification and Occupation on Reinforcement
DEMOGRAPHIC VARIABLES WITH REINFORCEMENT	N of Valid Cases	Pearson Chi-Square Value	Df	Significance levels	P - Value
AGE	254	23.845^a	8	.002	0.03
LOCALITY	254	32.320^a	6	.000	0.01
EDUCATION QUALIFICATION	254	24.050^a	8	.002	0.03
OCCUPATION	254	6.942a	6	.326	0.326

The table 6.3 shows that there is a significant relationship at 5-point level significance between demographic variables of age, locality, education qualification with reinforcement (χ²=23.845^a, df=8, P <.002) (p=0.03), (χ²=32.320^a, df=6, P <.000) (p=0.01), (χ²=24.050^a, df=8, P <.002) (p=0.03), these results are highly significant at 1 level and demographic variable of occupation with reinforcement does not have a significant relationship at less than <5% (χ²=6.942^a, df=6, P >.326) (p=0.326).

Table 4

Table 4 Influence of Age, Locality, Educational Qualification and Occupation on Self Efficacy
DEMOGRAPHIC VARIABLES WITH SELF EFFICACY	N of Valid Cases	Pearson Chi-Square Value	df	Significance levels	P - Value
AGE	254	27.585^a	8	.001	0.01
LOCALITY	254	21.852^a	6	.001	0.01
EDUCATION QUALIFICATION	254	25.237^a	8	.001	0.01
OCCUPATION	254	11.949^a	6	.063	0.063

The table 6.4 shows that there is a significant relationship at 5-point level significance between demographic variables of age, locality, education qualification with self-efficacy (χ²=27.585^a, df=8, P <.001) (p=0.01), (χ²=21.852^a, df=6, P <.001) (p=0.01), (χ²=25.237^a, df=8, P <.001) (p=0.01), These results are highly significant at 1 level and demographic variable occupation with self-efficacy does not have a significant relationship at less than <5% (χ²=11.949a, df=6, P >.063) (p=0.063).

Table5

Table 5 Influence of Watching Movies in Theatres and Social Learning Variables (Behaviour Change, Imitation, Reinforcement, Self-Efficacy)
WATCHING MOVIES IN THEATRE WITH SOCIAL LEARNING VARIABLES	N of Valid Cases	Pearson Chi-Square Value	df	Significance levels	P - Value
BEHAVIOUR CHANGE	254	13.861^a	2	.001	0.01
IMITATION	254	19.701^a	2	.000	0.01
REINFORCEMENT	254	27.691^a	2	.000	0.01
SELF EFFICACY	254	.753^a	2	.686	0.686

The table 6.5 shows that there is a significant relationship at 5-point level significance between movie watching in theatre with behaviour change, imitation and reinforcement (χ²=13.861^a, df=2, P <.001) (p=0.01), (χ²=19.701^a, df=2, P <.000) (p=0.01), (χ²=27.691^a, df=2, P <.000) (p=0.01), These results are highly significant at 1 level and movie watching in theatre with self-efficacy does not have a significant relationship at less than <5% (χ²=.753^a, df=2, P >.686) (p=0.686).

Table 6

Table 6 Influence of Watching Movies First Day First Show and Social Learning Variables (Behaviour Change, Imitation, Reinforcement, Self-Efficacy)
WATCHING MOVIES IN THEATRE WITH SOCIAL LEARNING VARIABLES	N of Valid Cases	Pearson Chi-Square Value	df	Significance levels	P - Value
BEHAVIOUR CHANGE	254	13.861^a	2	.001	0.01
IMITATION	254	19.701^a	2	.000	0.01
REINFORCEMENT	254	27.691^a	2	.000	0.01
SELF EFFICACY	254	.753^a	2	.686	0.686

The table 6.6 shows that there is a significant relationship at 5-point level significance between watching movies fdfs with behaviour change, imitation, reinforcement, and self-efficacy (χ²=29.158^a, df=2, P <.000) (p=0.01), (χ²=20.888^a, df=2, P <.000) (p=0.01), (χ²=15.365^a, df=2, P <.000) (p=0.01), (χ²=7.626^a, df=2, P <.022) (p=0.03). These results are highly significant at 1 level.

7. FINDINGS

The association is tested between the demographic variables and the variables adopted from Albert Bandura’s social learning theory, such as behaviour change, imitation, reinforcement, and self-efficacy. Based on the Pearson chi-square association tests conducted between demographic variables and Social Learning Theory (SLT) variables, several significant results were obtained. Let's break down the findings:

1) Demographic variables with Behaviour Change:

The Pearson chi-square test revealed a significant association between behaviour change with age and locality (χ² = 38.294^a, df = 8, p < 0.00) (p=0.01) & (χ² = 30.051^a, df = 6, p < 0.00) (p=0.01).This suggests that there is a relationship between the respondents' level of age, locality, and their likelihood to exhibit behaviour change influenced by onscreen alcohol consumption and smoking by actors.

Non-significant result: It could suggest that educational qualifications and occupation (χ²=12.515^a, df=8, P >.130) (p=0.130), (χ²=8.407^a, df=6, P >.210) (p=0.210) might not be a significant predictor of behaviour change in the context of onscreen alcohol consumption and smoking. This is interesting as it challenges the assumption that higher education levels might lead to more discerning or resistant behaviours.

2) Demographic variables with Imitation:

The analysis showed a statistically significant association between imitation with age, locality, educational qualifications, and occupation (χ²=42.774^a, df=8, P <.000) (p=0.01), (χ²=38.169^a, df=6, P <.000) (p=0.01), (χ²=24.206^a, df=8, P <.002) (p=0.03), (χ²=38.345^a, df=6, P <.000) (p=0.01).This suggests that there is a relationship between the respondents' level of age, locality educational qualifications and occupation and their likelihood to exhibit imitate onscreen alcohol consumption and smoking by actors.

3) Demographic variables with Reinforcement:

The analysis showed a statistically significant association between reinforcement with age, locality and educational qualifications (χ²=23.845^a, df=8, P <.002) (p=0.02), (χ²=32.320^a, df=6, P <.000) (p=0.01), (χ²=24.050^a, df=8, P <.002) (p=0.01).This implies that individuals' age, locality, and educational qualifications may influence the reinforcement aspects of the Social Learning Theory in the context of onscreen alcohol consumption and smoking by actors.

Non-significant result: This implies that occupation (χ²=6.942^a, df=6, P >.326) (p=0.326). may not significantly influence the reinforcement aspect of social learning in the context of onscreen alcohol consumption and smoking. It's worth exploring whether other factors such as personal values or workplace environment could play a more critical role in shaping reinforcement patterns.

4) Demographic variables with Self-Efficacy:

The results demonstrated a significant association between self-efficacy with age, locality, and educational qualifications (χ²=27.585^a, df=8, P <.001) (p=0.01) , (χ²=21.852^a, df=6, P <.001) (p=0.01), (χ²=25.237^a, df=8, P <.001) (p=0.01).This indicates that there is a connection between the respondents' age, locality, and educational qualifications and their perceived self-efficacy in resisting the influence of onscreen behaviours related to alcohol consumption and smoking.

Non-significant result: The lack of significance might suggest that occupation (χ²=11.949a, df=6, P >.063) (p=0.063) doesn't have a direct impact on individuals' confidence in their ability to resist the influence of onscreen behaviours related to alcohol and smoking.

5) Movie Watching in Theatre with Social Learning Theory Variables (SLT):

The Pearson chi-square test has yielded a significant association (p > 0.05), between movie watching in the theatre and Social Learning Theory variables with Behaviour change (χ²=13.861^a, df=2, P <.001) (p=0.01), Imitation (χ²=19.701^a, df=2, P <.000) (p=0.01) and Reinforcement (χ²=27.691^a, df=2, P <.000) (p=0.01). This implies that the location of movie watching (theatre vs. other settings) may significantly impact and has association between SLT variables with Behaviour change, Imitation and Reinforcement and so respondents in resisting onscreen influences.

Non-significant result: This result (χ²=.753^a, df=2, P >.686) (p=0.686) indicates that the location of movie-watching (theatre or elsewhere) may not have a significant association with social learning variables and self-efficacy. It raises questions about whether the physical context of movie-watching has a direct impact on the process of social learning and has the effect and development of self-efficacy.

6) Watching FDFS with Social Learning Theory Variables:

The Pearson chi-square test has yielded a significant association (p > 0.05) between movie watching in FDFS and Social Learning Theory variables with Behaviour change (χ²=29.158^a, df=2, P <.000) (p=0.01), Imitation (χ²=20.888^a, df=2, P <.000) (p=0.01) and Reinforcement (χ²=15.365^a, df=2, P <.000) (p=0.01).This implies that the location of movie watching FDFS significantly impact the relationship between Social learning variables such as Behaviour Change, Imitation and Reinforcement. So, the respondents got onscreen influences on FDFS.

Non-significant result: This result (χ²=7.626^a, df=2, P <.022) (p=0.022) indicates that the FDFS of movie-watching may not have a significant association with social learning variable self-efficacy. So that the physical context of movie-watching has a direct impact on the process of social learning or the development of self-efficacy. These results suggest that demographic factors, particularly educational qualification, and occupation, play a noteworthy role in influencing the dynamics of Social Learning Theory variables in the context of onscreen alcohol consumption and smoking. These associations have contributed to a more nuanced comprehension of how media portrayals influence behaviour change, imitation, reinforcement, and self-efficacy among fans.

8. DISCUSSION

This study delved into the influence of onscreen alcohol and smoking by actors on fans, using Social Learning Theory variables such as behaviour change, imitation, reinforcement, and self-efficacy. Most demographic factors showed significant associations with Social Learning Theory variables, affirming the theory's relevance. The findings revealed noteworthy associations between actors' onscreen behaviours and fans' responses. Fans, who were exposed to actors depicting alcohol consumption and smoking, had higher tendencies toward behaviour change and imitation, indicating the potential influence of onscreen portrayals on real-life actions (P <.005). Additionally, reinforcement played a role, as fans who perceived positive or negative consequences associated with onscreen behaviours showcased varying desires to engage in similar activities. Demographic variables such as age, education, occupation, and locality, were considered in the analysis and that has association with most of the social learning theory variables. Fans with the age group of 24-29 in Urban locality are more likely to exhibit behaviour change by watching their favourite actors. Graduates in Urban Locality and salaried professionals are more likely to imitate the actions of their favourite actors by watching movies. Fans with the age group of 24-29 in Urban locality and qualified graduates are more likely to reinforce and also has the ability to resist exert control over the actions of their favourite actors by watching movies. The study identified nuanced associations between these demographics and fans' responses, emphasizing the need for tailored interventions. Notably, self-efficacy exhibited consistent, non-significant associations, suggesting that fans' confidence in resisting onscreen influences is influenced by factors beyond immediate viewing contexts.

9. CONCLUSION

Finally, using Albert Bandura's Social Learning Theory, this research provides insight into the influence of actors' on-screen alcohol use and smoking on their fans. The results show notable links between exposure to onscreen activities and fans' tendency for behaviour modification, imitation, and reinforcement. Demographic characteristics, including age, education, employment, and location, add to the complexities of these relationships. According to the research, fans who are exposed to actors' onscreen activities are more likely to modify their own behaviours, imitate them, and get reinforcement, confirming the impact of media representations on real-life actions. The found relationships highlight the need for varied interventions that consider the audience's different features. While consideration should be used when generalizing results, the data suggests that onscreen depictions have a substantial influence on fan behaviour. While the study provides valuable insights, it also opens avenues for further exploration. A study conducted by (Distefan, 1999) provides initial evidence suggesting that celebrities who smoke both on and off screen could potentially influence young individuals to start up smoking. This observation has ramifications for media producers, health campaigns, and legislators, underscoring the significance of responsible media representations and tailored interventions to encourage beneficial fan behaviour. The research urges more investigation into the intricate interaction between on-screen activities and audience responses. The long-term consequences of media influences, future research should use longitudinal designs and consider other contextual elements. Youth are often exposed to depictions of drug use in media and advertising, which may lead to increased substance use. Implementing media literacy programs can help reduce this impact (Kristina M. Jackson, 2018). We may devise more effective techniques for navigating the junction between media depiction and real-life actions, resulting in a more educated and accountable media environment.

CONFLICT OF INTERESTS

None.

ACKNOWLEDGMENTS

None.

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