The purpose of this study was to test a model for intention to discontinuation drinking high caffeinated beverages among undergraduate students. This model was based on the Ajzen’s theory of planned behavior and Becker’s health belief model.
Participants consisted of 201 undergraduate students. Data were collected by questionnaires from March 11 to May 24, 2019. Collected data were analyzed using SPSS/WIN 22.0, AMOS 22.0 program.
The assessment of the model indicated an acceptable fit (normed
These results suggest that a need to increase awareness of adverse effects and potential risks of high caffeinated beverage consumption in undergraduate students. Besides, the university and government should provide education and campaigns to prevent excessive high-caffeinated beverage consumption.
Recent improvements in living standards and advances in food processing technologies have been accompanied by increasing demand and consumption of various kinds of prepared foods. Of particular note, highly caffeinated energy drinks have become very popular among teenagers, college students, and office workers [
Highly caffeinated drinks are known to enhance concentration, endurance, and performance [
Due to the problems posed by consuming highly caffeinated drinks, the Ministry of Food and Drug Safety [
Various theoretical approaches have been developed to predict human health behaviors, including the health belief model and the theory of planned behavior. The theory of planned behavior was developed by Ajzen in 1991 on the basis of the theory of reasoned action and has subsequently been used to explain various behaviors [
The health belief model [
Previous studies of highly caffeinated beverages have primarily focused on studying demographic factors related to high caffeine intake and the physiological and psychological effects of their consumption [
In light of these considerations, by applying the theory of planned behavior and the health belief model, we sought to identify the crucial variables that influence undergraduate students’ intention to stop consuming highly caffeinated drinks, to characterize the relationships between highly caffeinated drink consumption and related variables, and to explain the extent to which these variables influence intention to discontinue highly caffeinated beverage consumption. By doing so, we hope to provide a basic reference for guiding college students to engage in appropriate consumption of highly caffeinated beverages.
The purpose of this study was to establish a hypothetical model of the factors influencing college students’ intention to stop drinking highly caffeinated beverages based on Ajzen’s theory of planned behavior [
Our paper builds on the prior work by Ajzen [
Perceived benefits and perceived barriers affect subjective attitudes towards the intention to stop high caffeine intake, and subjective attitudes in turn affect the intention. Perceived benefits and perceived barriers of high caffeine intake affect subjective norms, which again affect the intention to discontinue high caffeine intake. The perceived benefits and perceived barriers of high caffeine intake affect perceived behavioral control, which affects the intention to stop high caffeine intake. A hypothetical path constructed on this basis is shown in
Based on the theory of planned behavior and health belief model, this study identified causal relationships among factors influencing college students’ intention to stop drinking highly caffeinated beverages, established a hypothetical model, and tested the hypothesis and the suitability of a structural equation model.
The participants of this study were 201 university students from five cities and provinces (Seoul, Gyeonggi, Gangwon, South Chungcheong, and South Gyeongsang Provinces). First, students from each location were randomly selected. We surveyed 405 students who had agreed to participate after receiving an explanation of the purpose of the study and selected 201 students who were suitable for the purposes of the study. Those who met at least one of the following three criteria were selected as participants: 1) having consumed highly caffeinated drinks in the past week, 2) consuming at least four caffeinated drinks daily, 3) responding that they were addicted to caffeine.
The number of participants in this study was based on the maximum likelihood method of selecting a sample size in a structural equation model, and 405 responses were first solicited in consideration of the exclusion rate because the data satisfied multivariate normality. Finally, 201 responses were selected and the remaining 204 were excluded because the responses were inappropriate or the respondents did not report high caffeine intake. Although scholars have expressed various opinions regarding appropriate sample sizes, a sample of 201 participants was deemed to be an appropriate number for this study according to evidence suggesting that an appropriate sample size is 150~400 on the basis of a classification of five factors that may influence the sample size [
We removed items with an average variance extracted (AVE) below .50 in confirmatory factor analysis (CFA) and then conducted the analysis. The final items included the general characteristics of the study participants, five items on perceived benefits, three items on perceived barriers, seven items on subjective attitudes, and four items on the intention to stop drinking highly caffeinated beverages. We followed the survey method described by Ajzen [
The general characteristics of the participants included age, grade, gender, and pattern of high caffeine intake, which consisted of the amount of caffeine consumed in the past week, the timing and place of highly caffeinated drink consumption, the presence and symptoms of side effects from high caffeine intake, and the reason why respondents perceived themselves to be caffeine addicts.
Perceived benefits refer to individuals’ beliefs that certain actions are beneficial for preventing them from developing a disease [
Perceived barriers refer to the degree to which individuals perceive negative factors that prevent them from implementing disease prevention actions [
Attitudes refer to the degree to which an individual positively or negatively evaluates the performance of a particular action [
After removing one of the items (optional/mandatory), for which an AVE of less than or equal to .50 was found in CFA, the remaining seven items were used. On the attitude measurement tool, 1 to 7 points were assigned to each pair of adjectives representing an individual’s assessment of an action. Attitudes were represented by the sum of the seven items, with the total score ranging from 7 to 49 points. Cronbach’s ⍺ for this tool was .85 in this study.
Subjective norms refer to the degree to which individuals subjectively perceive social pressure to perform certain actions [
Perceived behavioral control refers to the degree of difficulty that individuals perceive in certain actions. In this study, it referred to the degree of difficulty that individuals perceived in discontinuing highly caffeinated drink consumption [
Intention refers to the degree to which an individual intends to perform a specific action [
Data were collected from March 11, 2019 to May 24, 2019 after obtaining approval from the Institutional Life Research Ethics Committee (CKU-19-01-0101). In total, 410 university students who expressed their intention to participate in the study signed written consent forms and were given instructions on how to participate after receiving an explanation about the purpose and confidentiality of the study, the anonymity of the research, the academic purposes of data collection, and their ability to refuse to participate or withdraw from the study without any disadvantages. The time required to complete the survey was 10~15 minutes and small rewards were provided for the participants. Of the 410 surveys, 405 were returned and 201 of the responses (from individuals with high caffeine intake) were used for the final data analysis.
The collected data were analyzed using SPSS for Windows version 22.0 and AMOS version 22.0 (IBM Corp., Armonk, NY, USA). The variables related to participants’ general characteristics were analyzed in terms of frequency, percentage, mean, and standard deviation as descriptive statistics.
The multivariate normality of the sample was verified by mean values, standard deviation, skewness, and kurtosis using SPSS for Windows version 22.0. The model fit was validated using AMOS version 22.0. Model fit was tested using the
The general characteristics of the study participants are shown in
The mean score for the perceived benefits of high caffeine intake was 2.40, the mean score for perceived barriers was 1.87, the mean score for subjective attitudes was 29.46, the mean score for subjective norms was 3.53, the mean score for perceived behavioral control was 4.28, and the mean score for intention to stop was 3.29. Single-variable normality testing yielded skewness of -0.51 to 0.50 and kurtosis of -0.97 to 0.89. Since the absolute values of skewness and kurtosis were distributed between -2 and +2, the conditions of single-variable normality were met. CFA was conducted to assess the validity of normality, and demonstrated that the normalized standard factor loading was above the baseline value (λ>.50), the construct validity was above .80, and the AVE was above .50, indicating that there was no issue with convergent validity. We further examined the correlations between the correlation matrix and the AVE to verify discriminant validity. The correlation coefficients ranged between .07 and .53, with absolute values are less than .85 (
Prior to analyzing the hypothetical model, we conducted goodness-of-fit testing without modifying model. Because CFA confirmed the suitability of the model that included measurements of subjective attitudes, subjective norms, and perceived behavioral control over the discontinuation of high-caffeine intake. The following values were obtained from goodness-of-fit testing:
The results of the analysis of college students’ intention to stop drinking highly caffeinated drinks are shown in
Based on Ajzen’s theory of planned behavior [
These results show that perceived behavioral control over highly caffeinated beverage intake among college students had the most significant impact on their intention to discontinue consuming highly caffeinated beverages. Similar results were reported in a meta-analysis published in a major Korean academic journal [
This result supports previous findings that perceived behavioral control is affected by external control factors (e.g., time and opportunity) [
Subjective norms on highly caffeinated beverage intake were found to affect the intention to stop. The average score for subjective norms perceived by the subjects of this study was 3.53 points, and the average score for the item asking whether people who are close to the subjects were in favor of them stopping caffeine consumption within the next 2 weeks was 3.76, indicating that respondents felt particularly strong social pressure from certain people. Respondents with higher scores for subjective norms were more likely to intend to discontinue caffeine intake, which can be interpreted as the subjects seeing positive impacts from subjective norms on discontinuing highly caffeinated drink consumption.
Attitudes toward cessation of high levels of caffeine intake were found to have a significant effect on the intention to stop, which supports the results of a previous study that more positive subjective attitudes were associated with greater willingness to quit smoking [
In the present study, the score for attitudes toward stopping drinking highly caffeinated beverages was 29.46 points, showing a positive attitude toward discontinuing consumption.
In this study, lower scores for perceived benefits and higher scores for perceived barriers affected perceived behavioral control. The most popular timing of caffeine intake was before and after studying, and the most popular location was the library. Since the location of highly caffeinated drink consumption was inherently linked to academics, we conclude that the college students consumed highly caffeinated drinks in anticipation of a stimulating effect that would help them concentrate on their studies. This appears to be a result of anticipating the positive effects of caffeine on mental activity (i.e., a rapid pharmacological reaction and enhanced performance through its stimulatory effects) [
It was found that 39.3% of the participants in the present study had experienced side effects of caffeinated drink consumption, including sleep disorders, heart palpitations, skin roughness, anxiety, and others. These findings are similar to those of a previous study, which reported that sleep disorders were the most common side effect, followed by excess urination and palpitation [
Perceived barriers appeared to be higher than perceived benefits, as the mean score for perceived barriers was 1.87 out of 3 points. Perceived barriers do not directly or indirectly affect the intention to discontinue high levels of caffeine intake, but affect it through mediation by subjective norms. Perceived barriers also exert an effect by means of perceived behavioral control, along with perceived benefits. This is consistent with the findings of a prior study [
The subjects of this study were limited to those who consumed highly caffeinated beverages. We suggest that future studies should include subjects who do not consume highly caffeinated drinks and investigate their perceptions of susceptibility, severity, self-efficacy, and cues for behavior.
This hypothetical model built on the basis of the theory of planned behavior provides a suitable theoretical framework to explain the nature of college students’ intention to stop consuming highly caffeinated drinks, as its explanatory power was relatively high. Subjective attitudes, subjective norms, and perceived behavioral control explained 45.3% of college students’ intention to discontinue consumption of highly caffeinated beverages. This level of explanatory power is higher than was obtained in a Korean meta-analysis [
This study is meaningful in that it can be used as a basic reference for developing an intervention program to promote the discontinuation of highly caffeinated drink intake by identifying factors affecting college students’ intention to stop drinking highly caffeinated beverages.
In summary, subjective attitudes, subjective norms, and perceived behavioral control over the intention to cease high levels of caffeine consumption were found to affect the intention to stop, perceived benefits affected subjective norms, and perceived benefits and barriers affected behavioral control.
Therefore, in order to promote cessation of high levels of caffeine consumption among college students, it is necessary to emphasize attitudes toward discontinuing high levels of caffeine consumption, subjective norms relating to high caffeine intake, and improvements in perceived behavioral control. In particular, as behavioral control was found to be the most significant factor affecting the intention to discontinue high levels of caffeine intake, we expect that this study will be utilized to develop an intervention program to promote discontinuation of highly caffeinated drink consumption.
Based on Ajzen’s theory of planned behavior and Becker’s health belief model, this study confirmed that a structural equation model was appropriate for explaining university students’ intention to discontinue highly caffeinated drink consumption. The most influential factor was perceived behavioral control, and other significant factors included subjective norms and subjective attitudes. While most of the past research were related to caffeinated drink consumption has only been conducted on the fact finding, but this study is meaningful in that it established causal links between factors affecting the intention based on Becker’s and Ajzen’s theory to discontinue highly caffeinated drinks consumption in a sample of undergraduate students who were high caffein drinks users.
However, the limitations of this study are as follows. First, its generalizability is limited, as it does not represent all Korean university students, although subjects were selected from five geographically diverse cities and provinces. Second, it was not possible to objectively confirm heavy caffeine use because a self-reported survey was used to analyze participants’ caffeine drinking patterns and perceptions of themselves as caffeine addicts. Third, we were not able to confirm whether actions were taken to stop drinking highly caffeinated drinks by the subjects who expressed an intention to do so. These limitations need to be addressed by collecting a sample that properly represents Korean college students and identifying subjects with high caffeine intake through actual measurements in future studies applying the theory of planned behavior. In addition, we suggest that further studies utilizing the extended theory of planned behaviors, including social and psychological factors related to caffeine consumption, should be conducted in the future.
No existing or potential conflict of interest relevant to this article was reported.
Hypothetical model.
Effect analysis in the structural equation model.
General Characteristics of Participants (
Characteristics | Categories | n (%) or M±SD |
---|---|---|
Age (year) | 22.2±13.1 | |
Year in college | Freshman | 44 (21.9) |
Sophomore | 91 (45.3) | |
Junior | 35 (17.4) | |
Senior | 31 (15.4) | |
Sex | Male | 96 (47.8) |
Female | 105 (52.2) | |
Caffeinated beverage intake per week (cups) | 3.44±2.55 | |
Highly caffeinated beverage intake per week (cans) | 1.57±2.08 | |
Time of caffeine consumption | Before and after studying | 84 (41.8) |
When feeling drowsy | 56 (27.9) | |
Before and after meals | 61 (30.3) | |
Location of caffeine consumption | Library | 73 (36.3) |
House | 63 (31.3) | |
Classroom | 35 (17.5) | |
Bar | 5 (2.5) | |
Others | 25 (12.4) | |
Adverse experience with caffeine intake | Yes | 79 (39.3) |
No | 122 (60.7) | |
Symptoms of adverse effects |
Sleeplessness | 39 (49.4) |
Palpitation | 37 (46.8) | |
Skin roughness | 14 (17.7) | |
Anxiety | 10 (1.7) | |
Others | 6 (7.6) | |
Reasons for considering oneself a caffeine addict | I consume it at least once a day | 86 (42.8) |
I rely on caffeinated beverages | 64 (31.8) | |
If I don't drink caffeinated beverages, I become nervous | 30 (14.9) | |
Others | 21 (10.5) |
Duplicate responses.
Descriptive Statistics of Observed Variables (
Characteristics | M±SD | MR | Skewness | Kurtosis | SE | Estimate | CR | ||
---|---|---|---|---|---|---|---|---|---|
Perceptual benefits | 2.40±1.45 | 5.00 | 0.06 | -0.80 | 0.83 | - | - | - | |
Perceptual barriers | 1.87±0.94 | 3.00 | -0.51 | -0.59 | 1.00 | - | - | - | |
Subjective attitudes | 29.46±7.49 | 42.00 | 0.14 | 0.89 | |||||
Undesirable - desirable | 4.27±1.49 | 6.00 | -0.13 | -0.40 | 1.00 | - | - | - | |
Unimportant - important | 4.16±1.51 | 6.00 | -0.09 | -0.24 | 0.84 | 0.12 | 7.01 | <.001 | |
Unrealistic - realistic | 3.94±1.39 | 6.00 | -0.03 | 0.18 | 0.94 | 0.11 | 8.39 | <.001 | |
Harmful - beneficial | 4.36±1.52 | 6.00 | -0.06 | -0.57 | 1.00 | 0.12 | 8.15 | <.001 | |
Hard - easy | 4.00±1.56 | 6.00 | 0.03 | -0.50 | 1.02 | 0.13 | 8.14 | <.001 | |
Stupid - wise | 4.44±1.36 | 6.00 | -0.02 | -0.16 | 1.07 | 0.11 | 9.51 | <.001 | |
Joyless - joyful | 4.30±1.44 | 6.00 | -0.10 | 0.25 | 1.05 | 0.12 | 8.92 | <.001 | |
Subjective norms | 3.53±1.54 | 6.00 | 0.12 | -0.48 | |||||
Most people who are important to me think I should not drink highly caffeinated beverages within the next 2 weeks. | 3.22±1.74 | 6.00 | 0.27 | -0.87 | 1.00 | - | - | - | |
Most people who are important to me are in favor of me not drinking highly caffeinated beverages within the next 2 weeks. | 3.76±1.64 | 6.00 | -0.10 | -0.60 | 0.88 | 0.06 | 14.30 | <.001 | |
Most of the people who are important to me hope I don't drink highly caffeinated beverages within 2 weeks. | 3.62±1.70 | 6.00 | -0.04 | -0.85 | 0.97 | 0.06 | 15.45 | <.001 | |
Perceived behavioral control | 4.28±1.53 | 5.60 | 0.12 | -0.84 | |||||
It is difficult to control. | 4.18±1.92 | 6.00 | 0.03 | -1.21 | 0.79 | 0.09 | 9.28 | <.001 | |
It is manageable. | 4.22±1.90 | 6.00 | -0.06 | -1.13 | 1.00 | - | - | - | |
It is easy to control. | 4.92±1.65 | 6.00 | -0.51 | -0.69 | 0.70 | 0.07 | 9.52 | <.001 | |
I can control it through my will. | 4.04±1.87 | 6.00 | 0.04 | -1.14 | 1.21 | 0.07 | 16.60 | <.001 | |
It depends on what I do. | 4.03±1.90 | 6.00 | -0.03 | -1.09 | 1.22 | 0.07 | 16.48 | <.001 | |
Intention to stop | 3.29±1.70 | 6.00 | 0.31 | -0.76 | |||||
I plan to stop drinking highly caffeinated beverages. | 3.42±1.83 | 6.00 | 0.26 | -0.92 | 1.00 | - | - | - | |
I will do my best to stop drinking highly caffeinated beverages. | 3.49±1.83 | 6.00 | 0.23 | -0.97 | 1.12 | 0.03 | 35.71 | <.001 | |
I will aim to stop drinking highly caffeinated beverages. | 3.24±1.78 | 6.00 | 0.35 | -0.81 | 0.92 | 0.03 | 27.22 | <.001 | |
I will try to stop drinking highly caffeinated beverages. | 3.02±1.79 | 6.00 | 0.50 | -0.72 | 0.81 | 0.05 | 17.57 | <.001 |
MR=Measurement range; SE=Standardized estimate; CR=Critical ratio.
Model Fit, Estimates, and Standardized Effects of the Model (
Hypothetical model | 296.61 | 1.65 | .83 | .79 | .92 | .05 | .91 | .87 | .07 |
Endogenous variables | Exogenous variables | Estimate | Standardized estimate | Critical ratio | SMC | |
---|---|---|---|---|---|---|
Summary of structural model | Subjective attitudes | Perceptual benefits | -0.036 | 0.056 | -0.633 | 0.044 |
Perceptual barriers | 0.035 | 0.087 | 0.397 | |||
Subjective norms | Perceptual benefits | 0.060 | 0.079 | 0.759 | 0.090 | |
Perceptual barriers | 0.219 | 0.123 | 1.778 | |||
Perceived behavioral control | Perceptual benefits | 0.164 | 0.090 | 0.397 | 0.122 | |
Perceptual barriers | 0.092 | 0.138 | -0.663 | |||
Intention to stop | Perceptual benefits | 0.031 | 0.069 | 0.447 | 0.453 | |
Perceptual barriers | 0.085 | 0.106 | 0.801 | |||
Subjective attitudes | 0.223 | 0.100 | 1.804 | |||
Subjective norms | 0.427 | 0.070 | 6.138 | |||
Perceived behavioral control | 0.532 | 0.057 | 7.750 |
Endogenous variables | Exogenous variables | Direct effect |
Indirect effect |
Total effect |
||||
---|---|---|---|---|---|---|---|---|
B | B | B | ||||||
Direct, indirect, and total effects in the model | Subjective attitudes | Perceptual benefits | -.05 | .607 | - | - | -.05 | .607 |
Perceptual barriers | .03 | .771 | - | - | .03 | .771 | ||
Subjective norms | Perceptual benefits | .06 | .413 | - | - | .06 | .413 | |
Perceptual barriers | .13 | .046 | - | - | .13 | .046 | ||
Perceived behavioral control | Perceptual benefits | -.13 | .042 | - | - | .13 | .042 | |
Perceptual barriers | .09 | .034 | - | - | .09 | .034 | ||
Intention to stop | Perceptual benefits | .11 | .161 | .09 | .086 | .11 | .161 | |
Perceptual barriers | .07 | .275 | .03 | .611 | .07 | .275 | ||
Subjective attitudes | .22 | .031 | - | - | .22 | .031 | ||
Subjective norms | .38 | .004 | - | - | .38 | .004 | ||
Perceived behavioral control | .55 | .004 | - | - | .55 | .004 |
GFI=Goodness of fit index; AGFI=Adjusted goodness of fit index; CFI=Comparative normed of fit index; SRMR=Standardized root mean square residual; TLI=Tucker-Lewis index; NFI=Normed fit index; RMSEA=Root mean square error of approximation; SMC=Squared multiple correlation.