Introduction

Alcohol contributes to over three million deaths per year, and given the health and societal costs of alcohol misuse, reducing alcohol use is an international priority (World Health Organization, 2018). However, this is difficult due to alcohol’s omnipresence in media (such as popular movies) and the link between alcohol exposure and alcohol use (Bigman et al., 2020).

The Link Between Alcohol Exposure and Alcohol Use

Alcohol exposure in popular movies is one of several elements in the environment that can influence drinking behavior. Content analyses have found that alcohol is present in around 85–90% of movies (El-Khoury et al., 2019; Tickle et al., 2009). Compared to traditional advertising, movies are perceived as entertainment, and alcohol messaging is not as explicit (e.g., characters may drink without drawing attention to it; Dal Cin et al., 2009). Additionally, movie exposure may be more persuasive as viewers may perceive movie characters as super-peers, increasing identification if the character is evaluated similarly to themselves, positively, or if they wish/want to be like them (Elmore et al., 2017; Morojele et al., 2018).

Most of the previous research has established the link between alcohol exposure in movies and drinking behavior (for an exception, see Stautz et al., 2016). For example, adolescents exposed to the highest quartile of movie alcohol exposure were at increased risk for every drinking milestone, including sipping (7% increased risk for every extra hour of movie alcohol exposure), initiation (risk increased by 49% to 53% over 2 years), consuming a full alcoholic beverage (increased risk by 6% for each hour of movie alcohol exposure), weekly drinking (2.4 times more likely), heavy episodic drinking (8% additional risk per hour of movie alcohol exposure), and binge drinking (1.7 times more likely; Bigman et al., 2020; Jackson et al., 2018; Waylen et al., 2015). Complementing this, exposure to alcohol in popular media can limit the effectiveness of alcohol interventions (Boyle et al., 2021).

Given research highlighting that movie alcohol exposure was related to increased alcohol consumption, reducing exposure may be an effective option to reduce alcohol-related risk. However, it is currently unclear to what degree people are aware of alcohol exposure in movies and how influential it is.

The Dual Process Model

Previous research has showed strong support for the exposure-behavior relationship, but less is known about the mechanisms or theoretical perspective behind this effect. This may be explained through the lens of the Dual Process Model (Strack & Deutsch, 2004), which posits that exposure can lead to alcohol use through two distinct pathways, a slow system (conscious, accessible, and intentional cognitions) and a fast system (automatic, faster, unconscious cognitive processes; Larsen et al., 2012; Pieters et al., 2010; Strack & Deutsch, 2004). Alcohol attitudes could be shaped or changed through both systems. Via the slow system, repeated movie alcohol exposure may promote pro-alcohol beliefs by providing information about the role, normativity, acceptability, and positive consequences of alcohol use (Dal Cin et al., 2009; Jackson et al., 2018; Koordeman et al., 2011a). Repeated alcohol exposure in movies may elicit conditioned responses via the fast system of the Dual Process Model, increasing alcohol use, without awareness via our slow, deliberate, and intentional system. If individuals are mostly unaware of the amount of alcohol they are exposed to in movies, this study can provide a new understanding for this theoretical perspective.

The first step is to show whether viewers are actually aware of and can correctly estimate movie alcohol exposure events. It could be difficult to implement strategies to reduce awareness (such as avoiding alcohol exposure) if individuals greatly underestimate alcohol exposure. This may be particularly important for people undergoing alcohol treatment or for parents wanting to limit the amount of alcohol their children are exposed to.

This study investigated whether viewers can recall how many times they have seen alcohol in movies they remember well.

Which Factors Predict Movie Alcohol Exposure?

Although it is important to demonstrate whether people underestimate the amount of alcohol they are exposed to, it is also important to determine what factors might predict underestimation. By including information about the movie, (such as movie classification, the amount of alcohol exposure, and when the movie was last viewed) and about the individual (such as gender, age, and drinking habits), this could help identify where or what type of people would most benefit from resources. Although this research question is exploratory, there is reason to believe that people will underestimate alcohol exposure more in movies aimed at children, that those who drink less will underestimate movie alcohol exposure more than those who drink more, and that participants will be no more accurate estimating movie alcohol exposure irrespective of when the movie was last viewed.

For example, movie classifications (which refer to both advisory and restricted categories) in Australia classify movies based on drug usage, themes, sex, language, violence, and nudity, with no independent alcohol category (Australian Government, 2020). Based on the USA classification, almost half of 81 (47%) General-rated movies (G) depict some form of alcohol use (Thompson & Yokota, 2001). G and Parent-Guidance-Suggested (PG) are movies mostly aimed at children audiences, where all ages are either admissible or with parental guidance (Motion Picture Association, 2022). Parent-Strongly-Cautioned (PG-13) movies portray some content considered inappropriate for children and pre-teen audiences, and Restricted (R) movies portray adult material (Motion Picture Association, 2022). Due to the unexpectedly high amount of alcohol exposure events in G/PG-rated movies, it is likely that individuals underestimate movie alcohol exposure more in movies for children (G/PG) than those aimed towards an adult or mature audience (PG-13, R movies).

Similarly, the amount of alcohol that is remembered in popular movies may differ by different drinking groups. People who drink more may be more likely to correctly estimate alcohol exposure events, due to the unique cognitive impact alcohol cues has on memory processing (Brown et al., 2016). For example, people who drink more may react differently towards alcohol cues due to its increased salience and motivational importance (Brown et al., 2016; Witteman et al., 2015). This could potentially coincide with increased awareness of alcohol exposure in movies; those who drink may be more aware of alcohol when it is presented in a popular movie. Additionally, previous research has highlighted strong but inconsistent evidence investigating recall biases for alcohol use, yet no evidence has investigated recalling estimates of movie alcohol exposure. Recall biases (underreporting past alcohol use due to reduced, forgotten, or minimized salience) suggest that recall ability declines substantiality over time (Greenfield & Kerr, 2008). Previous research shows that shorter recall periods provide less biased and more accurate consumption estimates than longer recall periods; yet, longitudinal studies have incongruously indicated relatively reliable relationships between concurrently reported and recalled consumption (Chu et al., 2010; Ekholm, 2004; Gmel & Daeppen, 2007; Krenek et al., 2016; Kuntsche & Labhart, 2012; Liu et al., 1996; Merrill et al., 2020). While participants estimation of movie alcohol exposure may be suspectable to recall errors, it may be likely that if participants are unaware of movie alcohol exposure, they underestimate regardless of the last recall period (the last time participants saw the movie).

Current Study

This study aims to determine whether (and to which amount) people are aware of alcohol exposure in popular movies. Our first and main hypothesis was that participants would underestimate the amount of alcohol exposure in movies, and this hypothesis and the methods described below were pre-registered on the Open Science Framework (10.17605/OSF.IO/NQ9BT; any deviations from the pre-registered protocol are noted). Additionally, we aimed to explore which factors predicted estimation (gender, age, alcohol use, movie classification, total alcohol exposure, and time since the movie was last viewed). Although we pre-registered no hypotheses and the research question was largely exploratory, we anticipated that (i) participants would underestimate the amount of alcohol more in children’s movies (classified as G/PG) than adult movies (PG-13, R), that (ii) people who drink more will underestimate less (compared to those who drink less), and that (iii) participants will be no more accurate estimating alcohol exposure in movies viewed recently or longer in the past.

Method

Participants

Participants were recruited in July 2021 via targeted social media advertisements on Facebook and Instagram. Participants were eligible if they were residing in Australia, over 18 years old, and proficient in English. Participants were included in the analyses for the first research question (do people underestimate movie alcohol exposure) if they had provided any alcohol movie estimates (n = 609) and for the second (what factors predict greater underestimation) if they provided both movie estimates and information about their gender, age, and alcohol use (n = 395, 64.9% of the overall sample, mean age 44.08, SD = 16.3, 52% female, 44% male and 4% other).

Measures

Movie Selection

The movie list included 102 movies (see the Supplementary material for a full alcohol exposure list). Overall, ninety-seven movies were sourced from a previous study (ninety-three were retained), where researchers watched and content analyzed each movie to provide an estimate of alcohol exposure (Hanewinkel et al., 2014). Hanewinkel et al. (2014) defined alcohol exposure by counting when major or minor characters used or handled alcohol, or when it was used in the background (counted after it first appeared on screen). A total of 56% of the movies had previously been coded by researchers at the Dartmouth Media Research Laboratory, and the remaining were coded by trained coders from six study centers in Europe (Hanewinkel et al., 2014). Interrater reliability was calculated in two ways: (a) by comparing the coding results between the European trainers and coders on training movies (ranging from r = 0.93 to r = 0.99) and (b) by comparing the European trainers and the original coders from Dartmouth Media Research Laboratory, in a blinded random sample of movies (r = 0.87; Hanewinkel et al., 2014). For more information, please view the original article (Hanewinkel et al., 2014). Twelve more recent movies (nine were retained) were also coded for the purposes of this study using the same criteria as Hanewinkel et al. (2014). This study selected only the most popular movies in Australia based on the Screen Australia rankings (Australian government agency, reporting the top 50 grossing movies in the Australian box office for each year; Screen Australia, 2018). Firstly, it was checked whether the previously coded movie was included in the ranking for the year it was released, and movies were then randomly selected (Screen Australia, 2018). This ensured the movie was popular and likely viewed by many Australians.

The newly coded movies were chosen based on Screen Australia rankings from 2015 to 2020, choosing the top two highest grossing movies released for each year and randomly choosing the rest to fill each classification. This was conducted by one researcher on the team (M.P). On average, the 102 movies contained 42.95 alcohol exposure events (SD = 48.57, median = 28). One deviation from the pre-registered outcomes is that we removed 7 movies because they were animated movies and did not include any prominent human characters (e.g., Cars 2, the Lion King). This reduced the total amount of movies from 109 (previously and newly coded) to 102 (see Fig. 1 in the Supplementary material for additional information about the movie selection process).

Gender

Participants reported whether they identified as male, female, non-binary, or rather not say (recoded in data analysis to male, female, or other).

Age

Participants selected from seven categories, ranging from 1 (18–24) to 7 (75 years or older). To calculate mean age, midpoints of categories were used with the highest category of 75 plus being recoded to 79.5 (75 + half to the adjunct category; Kuntsche et al., 2007, 2008).

Estimation of Alcohol Exposure in Movies

Participants were asked to select up to 10 movies (from the 102 movies on the list) they remembered the best. Participants were asked to estimate how many times alcohol was visible in each chosen movie, on a nine-point scale from 1 (0) to 9 (200 +). Estimates were recoded by calculating the means for each response option (with the 200 + option scored as half to the adjunct category (being 249.5; Kuntsche et al., 2007; Kuntsche et al., 2008). Given that one movie had a higher number of exposure events than the top category (i.e., Inglorious Bastards with 617 alcohol events), we recoded this movie to 249.5. To calculate the difference (i.e., the under or overestimation), the actual exposure of alcohol in the movie was subtracted from the participants’ estimated exposure.

Time Since the Movie Was Last Seen

Participants were asked to rate how long ago they saw each selected movie the last time, on an 8-point scale, from 1 (in the last 2 months) to 8 (12 and more years ago). All categories were recoded in months since last watched by using midpoints of categories with the last category being recoded to 180 (= 12 years*12 months per year + 36 (half to the adjunct category; Kuntsche et al., 2007, 2008)).

Classification

The movie classification that participants selected and estimated was included. Movie classification (G/PG, PG-13, and R) was previously coded by Hanewinkel et al. (2014), according to the Motion Picture Association (the USA version; Motion Picture Association, 2022). The newly coded movies were classified using the same system. As in previous research (Dal Cin et al., 2008; Stoolmiller et al., 2012; Wills et al., 2009), G and PG movies were combined into a single category. G/PG movies represented the movies appropriate for children, and PG-13 and R movies represented adult/mature movies (see Table S1 in the Supplementary material for additional details on the classification guide for Australia in comparison to the USA’s rating system).

Alcohol Use

Alcohol use was assessed with the Alcohol Use Disorders Identification Test–Consumption (AUDIT-C; Bush et al., 1998) that consists of three items: frequency of drinking (rated on a 5-point scale, ranging from 1 (never) to 5 (4 or more times a week), typical drinking quantity, (scored on a 6-point scale from 1 (none) to 6 (10 or more), and frequency of binge drinking (scaled on a 5-point scale ranging from 1 (never) to 5 (daily or almost daily). Total scores were computed by summing all three sub-scales (minimum = 0, maximum = 12, Cronbach’s alpha = .76). Scores of 3 and 4 is an indicator of hazardous drinking for women and men, respectively (Fischer et al., 2021). To help with standard drink estimates, participants were shown a diagram depicting unit content and standard drink sizes for different alcoholic beverages.

Procedure

Participants were recruited through social media advertising to take part in a 15-min online survey hosted on Question Pro (QuestionPro, 2022). Participants who clicked the link in the advertisement were directed to the consent form, where they were informed that the study was about the “themes, acceptability, and ratings in movies.” Limited disclosure was used to ensure that participants would not deduce the true aim and bias their estimates of alcohol content in movies. All participants who provided consent then were asked to select up to 10 movies from the movie list of 102 movies that they remembered best. To avoid the tendency that participants may systematically chose movies on top of the list, two versions of the survey were administered with the order of movies presented reversed (otherwise surveys were identical). For each movie selected, participants then rated how long ago they saw each movie the last time and provided estimates for the amount of alcohol exposure in all chosen movies. Participants also provided smoking, violence, and swearing estimates to disguise that the true focus was on alcohol. Finally, participants completed the AUDIT-C and demographic information. After completion, participants received a debriefing statement outlining the survey’s real purpose. Participants were offered a prize entry to win one of five $50 e-vouchers. All methods were approved by the La Trobe University Human Research Ethics Committee (HEC21089).

Analysis Strategy

To determine whether participants underestimated alcohol exposure in movies, an intercept-only multi-level model was estimated using the lme4 package in the R statistical software (Bates et al., 2015; The R Foundation, 2021). Note that although we initially pre-registered a one-sample t-test on the Open Science Framework, the intercept-only multi-level model allows us to account for multiple observations per participant and was preferred. In order to determine which factors predict greater underestimation in movies, an additional multi-level model was estimated with the difference score as the outcome variable and gender, age, alcohol use, when the movie was last viewed, classification, and the total frequency of alcohol in the movie as predictors. Dummy codes were used for the gender variable (with females as the reference), classification variable (with G/PG classifications as the reference), and for the movies with the most alcohol exposure (where 1 = movies with one standard deviation above the mean for exposure, otherwise 0).

Results

On average, the participants saw the movies just over 3 years ago and had an AUDIT-C score of 2.8 (SD = 2.4; slightly under the AUDIT-C cutoff for hazardous drinking of 3 and 4 for women and men, respectively). Using the AUDIT-C cutoffs, 19.0% of men in the study and 19.7% of women were drinking hazardously. Additionally, the 609 participants rated on average 7.0 movies resulting in 4251 movie alcohol estimates and rated a mix of G/PG (20%), PG-13 (43%), and R-rated movies (37%). On average, participants estimated that alcohol exposure occurred 9.3 times in the movies (SD = 23.4). However, alcohol was actually shown in these movies 44.6 times (SD = 54.6) on average. Therefore, participants underestimated the amount of alcohol by 35.4 alcohol exposure events per movie on average (SD = 23.4; see Table 1 for estimate breakdowns by gender, age, and movie classification). An intercept-only multi-level model found that this underestimation was statistically significantly different from zero (intercept =  − 35.3, 95% confidence interval =  − 37.4, − 33.3, p < 0.001).

Table 1 Descriptive summary means for true alcohol exposure, participants’ estimations, and the difference, by gender, age (median split), and movie classification
Full size table

What Predicts Greater Underestimation?

As seen in Table 2, participants were also more likely to underestimate the amount of alcohol in PG-13 and R-rated movies compared to G/PG movies. Additionally, movies with the most alcohol exposure were underestimated more than other movies. Neither gender, time since when the movie was last viewed, age, nor participants’ alcohol use (AUDIT-C scores) impacted alcohol estimates.

Table 2 Model for different factors predicting greater underestimation
Full size table

Discussion

The aims of this study were to investigate participants’ estimation of alcohol exposure in popular movies and what factors contributed to greater underestimation. The results revealed that participants greatly underestimated the amount of alcohol in movies, and that PG-13 and R-movie classification and amount of alcohol exposure accounted for greater underestimation.

Although it was expected that participants would underestimate the amount of alcohol in movies, the magnitude of their underestimation was striking, as the actual average alcohol exposure in movies was nearly five times higher than the participants’ average estimation of alcohol events. This highlights that despite the high contents of alcohol, even in children’s movies, participants underestimate its prevalence. Potentially, among our Australian sample, and given that alcohol use in Western societies is embedded as a form of sociability, alcohol may be so normalized and tolerated that it may be perceived as ordinary and unremarkable (Kuntsche et al., 2021). This study has showed that underestimating alcohol use may unwittingly expose viewers to increased alcohol-related risk, occurring without their knowledge. Thus, individuals (or parents of children) cannot implement strategies to reduce their exposure to alcohol or to decrease their related risk if they underestimate its exposure amounts. Furthermore, alcohol underestimation may be harmful because repeated alcohol exposure in movies may elicit conditioned responses, e.g., via the fast system of the Dual Process Model (Strack & Deutsch, 2004), increasing alcohol use without awareness. Increasing awareness of alcohol exposure events via the slow system of the Dual Process Model (such as informing people about underestimation and the consequences of alcohol exposure) can enable informed decision-making before viewing movies.

For our second exploratory hypothesis (what predicts underestimation), we found some interesting and unexpected findings, i.e., all three of our individual-level predictors (gender, age, and alcohol use) were non-significant. This highlights how common and generalized the underestimation of alcohol exposure was among our participants. We believe that the social normalization of alcohol, and the sheer volume of alcohol exposure in movies, led our participants to be less aware of its presence and this occurred regardless of their age, gender, or alcohol use. We speculate that as alcohol is so normal and socially accepted, movie alcohol exposure may not evoke the same reaction or be as memorable as other more salient events (i.e., than drug exposure or violence would). This may have serious implications for specific sub-populations; for example, for alcohol use, people who drank more alcohol did not recall alcohol any better than those who did not drink or drank less. Thus, while people drinking heavily can make a conscious effort to avoid drinking establishments or choose non-alcoholic drinks, unfortunately, they will be just as poor (as people drinking at lower levels) at avoiding alcohol-related media, which potentially could induce craving, as seen in previous research investigating alcohol-dependent patients and alcohol advertisements (Witteman et al., 2015).

Interestingly, we found no significant differences for the estimation for gender, despite prior experimental research showing that males may be particularly suspectable to alcohol imagery (Koordeman et al., 2011a, b). Our findings may show no differences because it was based on estimating alcohol exposure, rather than the outcome of increased drinking.

While it was mainly exploratory, participants underestimated alcohol exposure more in adult audience/mature movies (PG-13 or R) than in children’s movies (G/PG). It appears that while participants believed that there was more alcohol in PG-13 and R movies, they still believed that there were very few alcohol presentations in all classification movies. One possible explanation is that participants underestimated PG-13 and R-rated movies more than G/PG-rated movies because PG-13 and R movies typically had more alcohol exposure.

Consistently, participants were significantly more likely to underestimate alcohol in movies containing more alcohol exposure. One possible explanation is that participants may have an average or norm of alcohol exposure they expect to be in movies; that is, they expect a certain amount in PG-13 movies and even more for R movies. However, as they are unaware of the true exposure amounts, and given that the true exposure is much higher, this creates the large discrepancy. Previous research has established clear links between alcohol exposure and use (Bigman et al., 2020; Jackson et al., 2018; Waylen et al., 2015), and this study has contributed by highlighting that participants even underestimate exposure in adult movies, highlighting their unawareness of the very high prevalence. Therefore, it is important to include alcohol as its own category during classification decisions, which is currently not the case in Australian movie classifications (Australian Government, 2020). This could help alert or increase participant awareness of alcohol exposure in movies.

Participants underestimate alcohol exposure regardless of the last time they viewed the movie. This result was inconsistent with the recall bias literature, which suggested that shorter periods between an event and retrospective reporting improved accuracy and relatively reliable longitudinal associations (Chu et al., 2010; Ekholm, 2004; Gmel & Daeppen, 2007; Krenek et al., 2016; Kuntsche & Labhart, 2012; Liu et al., 1996; Merrill et al., 2020). The results of this study may have differed from previous research as it instead investigated recall of alcohol exposure in movies, instead of retrospective assessments for alcohol consumption. Our study emphasized that participants’ estimate of alcohol exposure was not degraded by recall biases, nor did it improve, suggesting no significant differences between participants estimating recently and over a decade ago. This highlights that instead of being impacted by recall biases, participants generally underestimate alcohol exposure in movies, regardless of when the movie was last viewed. This circumvented the potential limitation of recall biases implicating potential results, as the predictor was non-significant in the final model.

Implications

To increase participant awareness of alcohol exposure, warnings could be placed before movies or on ticketing websites before purchasing. Our results could inform treatment and recovery decisions by including recommendations of safe movies (with low alcohol) alongside treatment; similar to the public websites presenting smoking exposure, new websites could be created to account for low alcohol or alcohol-free movies (Rauchfreie-filme, 2021).

Increasing people’s awareness of alcohol exposure in movies (and its impact) may help viewers make conscious and informed decisions before they expose themselves to movies with high alcohol. In relation to movie regulations, Australia’s Classification Board could independently include alcohol in its classification decisions, or provide more contextual information on websites or before watching the movie. This could include examples of binge drinking, alcohol dependence, the age of the characters drinking, or if alcohol was generally framed as being positive or negative (Australian Government, 2015, 2020).

Limitations and Future Research

One limitation of our study is the use of a convenience sample of Australian adults, which may have limited generalizability and may not be representative of all Australian adults. Another limitation is that we focused on movies exclusively. Future research should include other media sources, to examine if underestimation is specific to movies or generalized across media forms (e.g., social media, alcohol advertising). Testing whether this effect holds over multiple media sources may be important for policy (like reducing advertising) or treatment (incorporating social media breaks as part of treatment).

Conclusion

We found that participants underestimated the amount of movie alcohol exposure by a near factor of five and that amount of alcohol exposure and movie classification accounted for greater underestimation. These results have important implications; people (e.g., parents of children) cannot implement strategies to reduce their exposure to alcohol and decrease their related risk (of alcohol consumption) if they underestimate how much alcohol is in a given movie. Thus, alcohol exposure should be reviewed by governmental organizations, such as being included in movie classifications.