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INTRODUCTION
Young people well-being has become a concern of many parties during the COVID-19 pandemic since many studies found that the COVID-19 pandemic has impacted young people’s mental health and well-being (Nurunnabi, Almusharraf, & Aldeghaither, 2021; O’Connor et al., 2021). World Health Organization (WHO) takes the impact of the crisis caused by the COVID-19 pandemic on people’s mental health seriously (World Health Organization, 2020). Previous research on students in Jordan and the United States found that these students experienced the increasing levels of stress, anxiety, and depression during the COVID-19 pandemic (Basheti, Mhaidat, & Mhaidat, 2021; Hamaideh, Al-Modallal, Tanash, & Hamdan-Mansour, 2021; Son, Hegde, Smith, Wang, & Sasangohar, 2020). An increase in symptoms of depression, anxiety, and stress is associated with a decrease in well-being (Schönfeld, Brailovskaia, Zhang, & Margraf, 2019).
Ryan and Deci (2001) define well-being as an optimal psychological functioning and experience. From the construct of hedonic, well-being means maximum happiness but from a eudaimonic context, well-being addresses life satisfaction, and psychological health (Ryan & Deci, 2001). Well-being includes feeling in control of things and making progress toward goals, through engaging in pleasurable activities and building positive social relationships (Diener, Sapyta, & Suh, 1998). A measurement of students’ well-being describe the degree to which they can function effectively at home, school, and in the community (Frydenberg, 2018).
Negative and positive emotions are important well-being experiences (Diener et al., 2009). Positive emotions have the ability to increase the capacity to think and act in momentary situations, and negative emotions are useful for immediate adaptation to life-threatening situations (Fredrickson, 2001). Kuppens, Realo, and Diener (2008) found that across nations the experience of positive emotions more related to life satisfaction than the absence of negative emotions. Individual well-being can be influenced by strategies to regulate positive and negative emotions (Gross & John, 2003).
The variable that is possible to have a relationship with well-being is self-efficacy. Self-efficacy is an individual’s belief to cope with various situations or complete a task (Bandura, 1978; Pajares, 1996; Tsang, Hui, & Law, 2012). Bandura (1978) explained that perceived self-efficacy has an influence on choice of activities and environment, which leads to success as the intended outcome. In other words, self-efficacy beliefs enable people to interpret threatening situations as significant challenges that can be managed and help reduce stress in those situations (Bavojdan, Towhidi, & Rahmati, 2011).
According to Bandura (1978) self-efficacy consists of three important dimensions: magnitude, generality, and strength. The magnitude dimension refers to individual efficacy in completing tasks with varying levels. Some individuals have confidence in completing tasks with low difficulty, while other individuals have confidence for completing difficult tasks. Generality explains how an individualʼs experience in solving problems in one situation generalized to other situations. Some experiences create a belief in mastery that is limited to one situation, while other experiences may create an individual belief in a wider situation. Strength refers to the individual beliefs of his potentials. Weak beliefs are easily decreased by unpleasant experiences, while strong beliefs make individuals persist despite experiencing disconfirming experiences.
Based on the direction of the correlation, self-efficacy is possible to have a positive relationship with well-being. In other words, when the level of self-efficacy increases, mental health also improves (Bavojdan et al., 2011). Vice versa, people with low self-efficacy or who are unable to manage threatening events tend to experience high levels of anxiety (Bandura, 1988) and various aspects of mental health (Tahmassian & Moghadam, 2011). In the educational setting, low self-efficacy impede academic achievement and in the long run it can trigger learned helplessness which disrupt psychological well-being (Margolis & Mccabe, 2006).
Findings have consistently found a correlation between self-efficacy and psychological well-being, which is characterized with good mental health or a lower risk of depression, anxiety, and stress (Cattelino et al., 2021; Melato, van Eeden, Rothmann, & Bothma, 2017; Parto & Besharat, 2011). Although many studies have found a correlation between self-efficacy and well-being, measurements made on young people in Indonesia during the COVID-19 outbreak are limited. Given the importance, we would like to fill the gap.
We provide an overview of the condition of the COVID-19 pandemic in Indonesia since it is related to our respondents in this study. The number of deaths due to COVID-19 pandemic in Indonesia reached a peak at the second wave on July 27, 2021 with as many as 2069 cases (COVID-19 Task Force, 2021). Therefore, based on the level of spread of COVID-19 in Indonesia, the Indonesian government has divided three risk zones: high-risk zone, medium-risk zone, and low-risk zone. The respondents in this study were spread across the three zones with 250 students (68.49%) were in the high-risk zone, 97 students (26.57%) were in the medium-risk zone, and 18 students (4.93%) were in the low-risk zone. In addition, 17 students (4.66%) confirmed that they had been infected with COVID-19 and 24 students (6.58%) confirmed that their family members were also infected with COVID-19. Even though these students are in a high-risk zone, they apply strict health protocols, increase their immune system by consuming healthy foods and vitamins, and doing exercises (Valentina & Nurcahyo, 2021). This is in line with the Indonesian Governmentʼs policies, which conveyed through various media including social media and television so that people strictly implement health protocols.
Previous research on working people found that women experienced lower mental health and well-being than men during the COVID-19 pandemic (Borrescio-Higa & Valenzuela, 2021; Mascherini & Nivakoski, 2021). In addition, female students in the North of England were found to have higher levels of anxiety and depression than male students (Chen & Lucock, 2022). However, existing research limits information about the well-being of young men and women in Indonesia. This condition led us to conduct research on differences in psychological well-being between Indonesian men and women.
Research on high school and college students found a significant decline in mental health during the pandemic (Chen & Lucock, 2022; Rao & Rao, 2021; Villani et al., 2021). However, research measuring the well-being of high school and college students in Indonesia is still limited. We want to address this issue by measuring the difference in well-being of high school students and college students.
METHOD
Participants
A sample of 392 respondents participated in this study by filling the google form online. Since 27 participants do not meet the criteria based on the age of young people, there were as many as 365 young people aged 15-23 years (M = 18.57; SD = 1.95) included in this study. They were high school and college students from around Indonesia with the number of high school students are 143 (39.18%) and 222 (60.82%) college/university students. They were asked to fill in the name of the school/university where they are studying and their level of education. Of all respondents, 95 men (26.08%) and 270 women (73.92%).
All respondents implemented academic activities online from home. During the online learning from home, 291 students (79.73%) stated that they lived with their father and mother, 39 students (10.68%) lived with one of their parents, and 35 students (9.59%) lived with their relatives. Table 1 shows the sociodemographic of the respondents in this study.
Measurements
We delivered scales to measure self-efficacy and well-being of young people in Indonesia in the form of an online survey. We used a google form, which distributed through various social media platforms such as Facebook, Instagram, and WhatsApp groups during May-July 2021.
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Self-efficacy. We measure participants’ self-efficacy to find out the level of students’ confidence toward their capacity to deal with the challenges experienced during the COVID-19 pandemic. The Self-Efficacy Scale used in this study was developed by Utami (2022) from the theory of self-efficacy proposed by (Bandura, 1978; 1995). The Self-Efficacy Scale consists of 11 items, which were developed from three dimensions of self-efficacy, namely magnitude, generality, and strength. The magnitude dimension consists of four items (two favorable and two unfavorable), the generality dimension has four items (two favorable and two unfavorable), and the strength dimension has three items (two favorable and one unfavorable). Each item has five answer choices from 1 to 5, ranging from “Strongly disagree” to “Strongly agree”. For the favorable item, the higher the respondent’s score, the higher the respondent’s self-efficacy. Examples of items from the Self-Efficacy Scale is “I believe I can rise from great pressure”.
We estimate the reliability of all three dimensions of self-efficacy with the Cronbach Alpha. The Cronbach Alpha resulted for the Magnitude dimension was .781, for the Generality dimension was .650 and for the Strength dimension was .727. The reliability for the total item on the Self-Efficacy scale was .851. We also examined the factor structure of the Self-Efficacy scale by performing a Confirmatory Factor Analysis (CFA). The results of CFA with three factors showed a fit model with CFI = .938, GFI = .944, and RMSEA = .081. All factor loading of the items showed significant results ranging from .377 - .816.
Well-being. We measure the well-being of participants with the Flourishing Scale developed by Diener et al. (2009). The Flourishing Scale contains eight statements that measure the participant’s self-perceived success in important areas such as relationships, self-esteem, purpose, and optimism
Statistical analysis
We use the total scores of the self-efficacy and well-being scales for the analysis. Descriptive statistical analysis conducted on self-efficacy and well-being scores so that the mean and standard deviation obtained for each score.
We also categorize the self-efficacy and well-being scores. For the categorization of self-efficacy’s score we use the formula suggested by Azwar (2012):
Since the self-efficacy scale items consist of 11 items with a score of 1-5 for each item, theoretically the minimum score was 11 while the maximum score was 55. The score range is 44, which obtained from the difference between the highest score and the lowest score. Since the normal curve divides data into six areas, the range of the scores divided into six resulting in a Standard Deviation (SD) = 7 with a Mean (M) = 33.
For the Flourishing Scale, Diener et al. (2009) provided norms for the scales based on the percentiles. The norms for FS based on the 10th, 20th, 50th, 80th, and 90th percentiles i.e. 36, 40, 46, 50, and 52 (Diener et al., 2009; 2010). The smaller the percentile, the lower the well-being of the respondents and vice versa. Percentile less than 10 indicates very low well-being, while percentile more than 90 indicates very high well-being.
We correlated the scores of self-efficacy and well-being as well as performed regression analysis to determine the contribution of self-efficacy to well-being. T-test used to compare the self-efficacy and well-being scores by gender and education level. The two-way ANOVA conducted to compare well-being scores based on education level of participants (i.e. high school and college), gender, as well as the interaction of gender and education level. All of the analysis were performed with SPSS 24.
Ethical considerations
This research has obtained approval from the Ethics Committee of the Faculty of Medicine, Udayana University with number 1668/UN14.2.2.VII.14/LT/2021. We asked for the participants’ consent to participate in this research voluntarily and to publish the study findings anonymously before they filled out the questionnaires.
RESULTS
Descriptive analysis
The result of the descriptive analysis of the self-efficacy score resulted in a mean of 41.18 with a standard deviation of 6.49. Meanwhile, the mean of well-being was 44.28 with a standard deviation of 7.18.
The categorization of the self-efficacy scale shows that .5% of the respondents in the very low category, 3.6% in the low category, 18.9% in the moderate category, 41.1% in the high category, and 35.9% in the very high category. The percentage of the number of respondents for FS based on the 10th, 20th, 50th, 80th, and 90th percentiles were 13.97%, 10.68%, 32.60%, 25.20%, and 7.67%, while 9.86% of the respondents was above the 90th percentile.
Multivariate analysis
We conducted a correlation analysis between the three dimensions of the self-efficacy scale and the well-being scale. Table 2 shows the results of the correlation of the three dimensions of the self-efficacy scale with the well-being scale. The three dimensions of the self-efficacy scale have a significant correlation (p < .01) with the well-being scale. Of the three correlation results, the correlation of the magnitude dimension with the well-being scale shows the highest correlation coefficient (r = .327).
Data analysis then continued with testing for the normality. The normality test using the Kolmogorov Smirnov test on the variables of self-efficacy and well-being showed the two data were not normally distributed (p < .05). We also conducted a normality test on the well-being data based on gender due to the unequal number of men and women in this study. For men respondents, the results of the Kolmogorov Smirnov test showed that the self-efficacy variable was normally distributed (p > .05), while the well-being variable was not normally distributed (p < .05). For women respondents, both self-efficacy and wellbeing scores were not normally distributed (p < .05).
Since not all data were normally distributed, we use Spearman’s correlation to analyze the correlation between self-efficacy and well-being. The result showed that there was a positive correlation between self-efficacy and well-being (r = .547, p < .01). Linear regression analysis conducted to follow up the result of the correlation analysis. The results of linear regression analysis showed significant results (F = 183.138, p < .01). Self-efficacy significantly contributed to wellbeing (B = .641, p < .01) with the contribution percentage of 33.5%.
We tested differences in self-efficacy and well-being scores by gender and education level (Table 3). We found a difference in self-efficacy scores between men and women (t = -2.663, df = 363, p = .008), men had a higher mean score than women (42.69 vs 40.65). We found no difference between men and women in WB (t = -.119, df = 363, p = .905). The differences between high school students and college students were found in WB scores (t = 3.333, df = 363, p = .001), college students had higher scores than high school students (45.27 vs 42.74). We found no difference between high school students and college students in self-efficacy scores (t = .146, df = 363, p = .884).
Table 3 The differences in self-efficacy and well-being scores by gender and education level
| Measures |
Mean (SD)
Overall |
Women | Men |
Gender t-test
p |
High school
students |
College
students |
Education t-test
p |
|---|---|---|---|---|---|---|---|
| Self-efficacy | 41.18 (6.49) | 40.65 (6.25) | 42.69 (6.95) | .008** | 41.12 (6.26) | 41.22 (6.65) | .884 |
| Well-being | 44.28 (7.18) | 44.26 (6.91) | 44.36 (7.96) | .905 | 42.74 (7.59) | 45.27 (6.74) | .001** |
*p < .05;
**p < .01
We also conducted a two-way ANOVA to determine the effect of gender and education level on well-being (Table 4). The result shows that there was an effect of education level on wellbeing (F = 12.956, p < .05). The average scores of well-being of the college students (M = 45.556) was higher than the average scores of well-being of the high school students (M = 42.454). However, there was no gender effect on well-being (F = .006, p > .05). The interaction effect between gender and education level on well-being was also not significant (F = 1.943, p > .05).
DISCUSSION AND CONCLUSION
In this research, we measure the self-efficacy and well-being of high school students and college students during the second wave of the COVID-19 pandemic in Indonesia. The result show that there was a positive correlation between self-efficacy and well-being. We conclude that a higher score in self-efficacy is associated with a better well-being. This finding consistent with previous research that found the association between self-efficacy and well-being (Al-Dwaikat, Rababah, Al-Hammouri, & Chlebowy, 2021; Andretta & McKay, 2020; Siddiqui, 2015).
The result of this study indicates that self-efficacy has a contribution to well-being. This contribution emphasizes that efforts to increase self-efficacy can have an impact on well-being. This result support the previous research finding which found that self-efficacy contributed to well-being (Milam, Cohen, Mueller, & Salles, 2019).
Several studies on self-efficacy in Indonesian adolescents reported the level of self-efficacy in the category of moderate to high level (Damri, Engkizar, & Anwar, 2017; Prawitasari & Antika, 2022; Pristanti, Syafitri, & Reba, 2022). The result of our study shows that 77% of respondents were in the high and very high category of self-efficacy level. This finding confirms the results of the previous studies. However, there were 23% respondents have a low to moderate category of self-efficacy level. This finding indicates that the self-efficacy of the respondents needs to be developed.
Self-efficacy can be developed in four ways, namely mastery experiences, social modelling, social persuasion and physical, and emotional state (Bandura, 2012). The development of self-efficacy requires individual overcoming obstacles through persistent effort. From the perspective of social modelling, seeing people who are similar to the individual’s success with persistent efforts can increase the individual’s efficacy towards him/herself. In addition, if individuals persuaded to believe in themselves, they tend to be more persistent in overcoming obstacles. Self-efficacy also developed by reducing anxiety and depression as well as maintaining physical strength.
The development of self-efficacy needs to adapt to the conditions of the adolescents in Indonesia. Research conducted by Chairani, Hamid, Sahar, and Budhi (2019) on Indonesian adolescents showed that the respondents’ self-efficacy was dominantly influenced by the experience of mastery and emotional stimulation. The characteristics of adolescents who tend to imitate what their peers do can also be the basis for developing self-efficacy through social modelling (Chairani et al., 2019).
Strengthening self-efficacy in educational setting is important since it has an important role in students’ well-being. Teacher can contribute to strengthening students’ self-efficacy. Margolis and Mccabe (2006) proposes general strategies that teachers can do to strengthen students’ self-efficacy, such as plan moderately challenging tasks, use peer models, teach specific learning strategies and reinforce effort, and correct strategy use. Bartimote-Aufflick, Bridgeman, Walker, Sharma, and Smith (2016) suggested some teaching strategies to strengthen college students’ self-efficacy such as provide a good amount of structure when using mapping concept activities, solving problems model, provide positive feedback, and support students based on positive psychology.
During the COVID-19 lockdown, well-being is an indicator of mental health (Mota González, Calleja, Sánchez Bravo, Gómez López, & Carreño Meléndez, 2021). The results of descriptive analysis on the well-being scale showed that 43% of the respondents were in very moderate to very high categories. This result indicates that those respondents tend to have a positive well-being. Our findings support Israelashvili (2021) that the presence of positive emotions is essential for mental health during the COVID-19 pandemic.
The result of this study shows that the score of well-being of the college students was higher than the score of the high school students. Compared to high school students, college students are believed to have more ability to regulate their emotions during the COVID-19 pandemic to improve their psychological well-being. In line with the study conducted by Nurcahyo and Valentina (2020) that found college students who were completing their thesis during the pandemic had good psychological well-being which was supported by self-efficacy, coping strategies, self-regulation, family support, and creative adaptation. Self-efficacy beliefs motivate students to learn through the use of self-regulatory processes such as goal setting, self-monitoring, self-evaluation, and the use of various learning strategies (Zimmerman, 2000).
The result of this study indicates that there was no gender effect on well-being. The initial hypothesis predicting differences in well-being between men and women was rejected. Based on the research findings, Diener and Ryan (2009) suggested that women and men do not differ substantially in terms of psychological well-being. The tendency for women’s higher psychological well-being than men is possible because women are considered to experience negative and positive feelings more frequent compared to men. The COVID-19 pandemic that forces individuals to change life activities seems to be a problem faced by both men and women. The discomfort impacted by the COVID-19 pandemic is possible perceived equally in men and women.
The absence of differences in well-being based on gender in this study is possible due to the characteristics of young Indonesians, both men and women, who maintain the value of religiosity as a coping strategy in difficult times, especially during the COVID-19 pandemic (Saud, Ashfaq, Abbas, Ariadi, & Mahmood, 2021). Religion has become a source of noble cultural values in Indonesian society regardless of gender (Ahimsa-Putra, 2002). This is also supported by research released by Pew Research Center that Indonesia is one of the religious country who believe that religion has a big impact in their live (Poushter & Fetterrolf, 2019). Valentina and Nurcahyo (2021) found that during the COVID-19 pandemic, individuals as well as families in Indonesia had more opportunities to worship God, such as praying with all family members at home. Prayer indicates believing that God will protect and provide a way out of facing problems caused by the COVID-19 pandemic.
The findings of this work are important for the community, schools and universities since these results feed the theory about the self-efficacy and well-being. With the aim of dealing with life’s uncontrollable pressures such as the COVID-19 pandemic, developing self-efficacy of young people is essential to promote well-being.
We also recognize the limitations of this research. The use of self-reports in this study may be a source of bias that can underestimate the results of the study. In addition, the number of respondents in this study needs to be increased so that the results of the study can be generalized to a larger population. Furthermore, the generality dimension of the self-efficacy scale has a low Cronbach Alpha coefficient that needs to be improved. We are also aware that this research was conducted during the second wave of the COVID-19 pandemic in Indonesia. It is advisable to measure the well-being of young people also in the first wave and after the second wave subsides.
