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Abstract

Subjective well-being, influenced by various factors such as personality and interpersonal relationships, is crucial to the happiness of everyone. This article presents the findings of a mixed-method and exploratory study on subjective well-being among university students, focusing on understanding their individual perceptions and how these influence their happiness. Utilizing social representations theory and Reinert’s lexical analysis method, the study examined conceptions of happiness and the contributing factors among participants. The findings revealed that perceptions of happiness among university students clustered into four distinct classes, highlighting two primary dimensions: personal life evaluation and emotional experience. These dimensions influence personal balance and participants’ basic needs. Additionally, the analysis identified three classes of factors influencing happiness, including life circumstances, personal factors, and social environment. The importance of mental health and interpersonal relationships in the emotional well-being of young university students was underscored. These findings emphasize the complexity of subjective well-being and the significance of addressing both emotional and contextual aspects to understand and enhance happiness and life satisfaction in this population.

Keywords

subjective well-being happiness well-being social representation Iramuteq

Introduction

Subjective well-being (SWB), as conceptualized by Diener (1984), is understood as a personal assessment of life that encompasses both emotional and cognitive dimensions (Diener et al., 1999). It involves perceptions of happiness, life satisfaction, and the balance between positive and negative emotions, which form the basis for one’s subjective experience of quality of life (Diener et al., 1999, 2015). According to the hedonic model of well-being, SWB reflects the belief or feeling that life is progressing positively, a broad and holistic indicator of general well-being (Diener et al., 2018; Vezzoli et al., 2022). This model encompasses both affective and cognitive evaluations, where the affective component relates to daily emotions, and the cognitive component evaluates life satisfaction in relation to personal ideals (Diener, 1984; Gallagher et al., 2009; Layard, 2011). Such comprehensive evaluations are crucial as they link SWB to a range of positive outcomes: higher SWB is consistently associated with improved health, enhanced productivity, stronger relationships, and greater life satisfaction (Boehm et al., 2011; Diener et al., 2002; Lyubomirsky, King, & Diener, 2005). Research has found that elevated SWB contributes to physical health through better immune function and lower stress levels, thereby reducing the risk of chronic diseases (Diener & Chan, 2011). The economic impact of SWB is also noteworthy; higher SWB has been correlated with increased workforce productivity, lower absenteeism, and reduced healthcare costs, highlighting its broader societal benefits (Helliwell & Putnam, 2004). Understanding SWB as a global life assessment thus provides insight into well-being’s extensive effects on both individual and societal levels (Hupper, 2014; Veenhoven, 1984).

Although closely related, happiness and SWB are not identical constructs. Happiness is often defined as a key dimension within SWB, focusing on positive emotions and high life satisfaction (Lyubomirsky, 2019). SWB, however, is a more holistic measure that includes but is not limited to happiness. Research suggests a positive feedback loop: happiness serves as both a contributor to and an outcome of SWB, reinforcing factors such as successful interpersonal relationships and positive health outcomes (Fredrickson, 2013). Happiness contributes to success across multiple domains, including work, relationships, and health (Lyubomirsky, Sheldon, & Schkade, 2005), but factors like personality traits and social support can significantly shape individual happiness levels (Steel et al., 2008). The cultural and socioeconomic context also plays a critical role in how individuals perceive and pursue happiness. For instance, in collectivist cultures, happiness often arises from social harmony, whereas, in individualist societies, it tends to be linked to personal achievement and autonomy (Oishi & Diener, 2014). Longitudinal studies demonstrate that happiness-focused interventions, such as gratitude practices, can sustainably elevate SWB (M. E. Seligman et al., 2019), further underscoring the complex interplay between happiness and well-being.

Determinants of SWB include both personal and contextual factors, such as personality, social relationships, health, and socioeconomic status (Helliwell et al., 2020; Ryff, 2014). Personality traits, particularly neuroticism and extraversion, have shown significant correlations with SWB levels, influencing individuals’ life satisfaction and general well-being (Costa & McCrae, 1980). Neuroticism, a personality trait characterized by a tendency to experience negative emotions such as anxiety, anger, and sadness (Costa & McCrae, 1980), has been significantly associated with lower levels of subjective well-being (SWB). Individuals with high levels of neuroticism tend to interpret events more pessimistically and may struggle to achieve the emotional balance required for a positive perception of well-being (Diener & Chan, 2011). Social support, whether from family, friends, or community networks, is also critical; individuals with strong social ties report higher SWB (Diener & Seligman, 2002). Moreover, health is a primary determinant of SWB, as chronic illness and poor mental health can drastically reduce well-being levels (Ryff & Singer, 2008). Economic factors such as income have a moderate impact, where higher income generally correlates with higher SWB, though this effect plateaus at a certain point (Diener & Oishi, 2000). Additionally, individuals who report a strong sense of purpose or community belonging tend to experience elevated levels of SWB, highlighting the importance of these psychosocial factors (Steger et al., 2008). This diverse range of determinants illustrates the multifaceted nature of SWB, encompassing both internal and external influences.

Young people are a critical demographic in the study of SWB, given the numerous transitions they face during this formative stage. Compared to adults, young people may experience more fluctuations in SWB due to challenges such as academic pressures, evolving relationships, and the process of identity formation (Arnett, 2000; Lerner & Steinberg, 2017). Recent research has shown that traumatic events, like the COVID-19 pandemic, have disproportionately impacted youth well-being, with disruptions in education and social life leading to increased stress, anxiety, and feelings of isolation (Loades et al., 2020). Young people’s well-being often hinges on social relationships and a sense of belonging, which are central to their identity and life satisfaction (Furman & Buhrmester, 2009; Park, 2004). The unique nature of these challenges, along with the key developmental phase they represent, underscores the importance of studying SWB among young people and comparing it to adult experiences to address the specific needs of this group effectively.

Qualitative research methods offer unique insights into SWB, especially for exploring the nuanced and subjective experiences of young people. Despite the significant body of quantitative research on SWB, such as those by Diener et al. (1999) and Helliwell et al. (2020), which provide generalizable patterns and correlations, these studies often overlook the deeper, nuanced understanding of subjective experiences. Qualitative research can bridge this gap, providing rich detail that enhances understanding beyond statistical trends. Studies like those by Huebner (2004) and Proctor et al. (2009) illustrate how qualitative research, including interviews and focus groups, can capture the diversity of young people’s well-being experiences, especially concerning social relationships and belonging. Fattore et al. (2007) revealed through qualitative analysis that adolescents value relationships and community connection, which are often overlooked in quantitative measures. Similarly, Eccles and Roeser (2011) emphasized the importance of the school context and relationships with peers and teachers in shaping young people’s subjective well-being. Savage et al. (2014) also employed qualitative methods to examine well-being experiences. The study by Huppert and So (2013) used in depth interviews to investigate well-being perceptions across different demographic groups, uncovering the diversity of experiences and meanings associated with subjective well-being. However, despite its richness, qualitative research on SWB remains comparatively scarce, pointing to a significant gap in the literature and an opportunity to enrich our understanding of SWB by incorporating qualitative insights.

The theory of social representations, proposed by Moscovici (1993), offers a framework well-suited to understanding the collective meanings individuals attribute to well-being, facilitating an exploration of SWB as shaped by social and cultural environments. This theory emphasizes that individuals construct mental representations that reflect their social environments, which shape their understanding of complex phenomena like well-being (Rodríguez-Araneda, 2014). By examining the collective representations of well-being, this theory aligns well with the study’s qualitative approach, revealing how societal norms and cultural contexts influence personal well-being perceptions. Understanding these representations is essential, particularly for young people, who often internalize societal norms and values in their assessments of SWB (Van Dijk, 2000). Discussing social representations within the context of SWB provides an explanatory model for how social roles, cultural beliefs, and community expectations influence individual perceptions of happiness and well-being.

In light of these considerations, this study addresses a critical gap in SWB research by focusing on insights specific to young adults through a mixed-methods approach. Unlike previous research that relies primarily on quantitative measures, this study integrates both qualitative analysis and computational lexical analysis to explore subjective interpretations of SWB within this demographic. By employing social representations theory and Reinert’s method through IRaMuTeQ software, the study identifies culturally and socially grounded perceptions of well-being that are underrepresented in the literature. The study aims to explore how young people conceptualize and interpret their happiness, considering both individual and social factors that shape their perceptions. Through this combined methodological approach, the research seeks to uncover the social representations influencing SWB in youth, contributing to a more nuanced understanding of SWB that could inform interventions and policy efforts tailored to support young people’s happiness and well-being effectively.

Method

A mixed-methods and exploratory study was conducted, as this approach allows for a deep dive into the specificities of a new, particular, or open reality, highlighting defining elements and providing relevant information committed to social transformation (Flick, 2022; Soares et al., 2021). The study employed Social Representations Theory, which concerns how groups of people construct and share knowledge and meanings about a common topic of interest. This theory is based on the notion that social representations result from collective practices of creating and disseminating information within a social group (Moscovici, 2001). Regarding well-being, social representations can play a significant role in how individuals perceive and experience their own mental and emotional health, as well as how they interact with others and their environment. Jodelet (1989) has argued that social representations can influence how people perceive their own mental health and their ability to cope with mental health issues. Similarly, Tuan (1998) investigated how social representations can affect how people interact with others and experience stress and emotional well-being.

To analyze social representations of well-being, a combination of qualitative thematic analysis and quantitative lexical analysis was used. The study applied Reinert’s lexical analysis method through IRaMuTeQ software, which allows for the grouping of words and expressions into semantic categories to identify the meanings associated with a specific theme. This approach integrates qualitative interpretative analysis with computational quantitative processing, ensuring a systematic identification of dominant themes in participants’ discourses (De Alba, 2004; Reinert, 1990). The combination of these methods strengthens the study’s ability to uncover both deeply subjective interpretations and broader linguistic patterns, providing a comprehensive understanding of the social representations of well-being.

Participants

A total of 203 students from the Autonomous University of Madrid and the University of Las Palmas de Gran Canaria participated in the study. Table 1 presents the sample characteristics, characterized by being female (84.7%), with a mean age of 21.16 years, not employed (56.2%), and from a lower middle-class background (61.1%). Additionally, as shown in the table, two ad hoc categorical variables were included to ask the participants about their subjective levels of well-being and life satisfaction. This approach allowed us to assess those participants reported moderate well-being overall, with higher life satisfaction scores (43.3% indicating a moderate level of well-being vs. 38.4% with higher life satisfaction).

Table 1.

Sociodemographic Characteristics of the Sample.

Variable	Categories	%/[x−χ-, DS]
Age		[21.16, 3.72]
Sex	Male	15.2%
Sex	Female	84.7%
Employment status	Study and work occasionally	22.7%
	Study and work regularly	21.1%
	Do not work	56.2%
Subjective social class	Low	1%
	Lower middle	61.1%
	Upper middle	37.9%
Well-being level	Very poor	0%
	Poor	3.9%
	Fair	13.3%
	Average	43.3%
	Good	31.5%
	Very good	7.9%
Life satisfaction level	Very poor	0%
	Poor	3.9%
	Fair	15.3%
	Average	33.0%
	Good	38.4%
	Very good	9.4%

Source. Own elaboration. (%) percentage for categorical variables or [M, SD] mean and standard deviation for continuous variables.

Measures

A structured interview guide was designed for data collection, consisting of sociodemographic questions (age, gender, employment status, subjective social class, perceived well-being level, and life satisfaction level), as well as open-ended textual questions addressing the research objectives: “What does happiness mean to you?” and “What factors determine your happiness?” The choice to frame open-ended questions around “happiness” rather than “well-being” was intentional, as happiness is often a more accessible term for participants, aligning with the need for straightforward language in qualitative research. This choice also complements the study’s broader focus on subjective well-being by approaching happiness as a key component within the SWB construct.

Procedure

A digital questionnaire was developed and self-administered, requesting voluntary participation from students at the university of Las Palmas de Gran Canaria, Spain. Before completing the questionnaire, participants were required to provide written informed consent, in which they explicitly acknowledged their understanding of the research objectives, the anonymity of their responses, and the exclusive academic use of their contributions.

The fieldwork was conducted from October 27 to November 14, 2023. This questionnaire was previously reviewed by three judges who assessed its validity in terms of study objectives and instrument coherence. Additionally, the instrument was tested with five participants to evaluate its clarity and verify that the results aligned with the concepts of well-being and happiness, as represented in social representations theory.

Upon obtaining responses, textual variables (open-ended) were refined for the analysis of social representations. The final corpus collected 203 texts comprising 457 text segments, 5,563 occurrences of 868 different forms, of which 480 were hapax or words with a single frequency. Hapax refers to words that appear only once in the text, highlighting unique or infrequent language used by participants. Subsequently, two sub-corpora were created based on the research objectives: one for the analysis of how participants define happiness (222 text segments with 2,526 occurrences of 501 forms) and another for the factors determining that happiness (235 text segments with 3,037 occurrences of 622 forms).

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Scientific Committee of the Recognized Research Group: Inclusive Education, Society and Family of the University of Las Palmas de Gran Canaria (GIEI-2022-10).

Analysis

Initially, the sample characteristics of the study were defined by analyzing the frequency and distribution according to sociodemographic variables using SPSS software (version 25) (IBM Corp, 2017).

Subsequently, lexical analysis of the two sub-corpora was conducted using the Reinert method, through IRAMuTeQ software (Interface de R pour les Analyses Multidimensionnelles de Textes et de Questionnaires) (Ratinaud, 2009), version 0.7 alpha 2. This choice was made because it allows for the analysis of the structure and organization of lexical worlds present in text segments. This method has been frequently utilized for studying open-ended questions (Kalampalikis, 2005), as it eliminates reliability and validity issues in text analysis (Klein & Licata, 2003). With this method, which employs a descending hierarchical clustering analysis format, researchers obtain a series of classes and statistical signals in the form of typical words and text segments. The most significant ones appear with the highest chi-square (Mondragon et al., 2020), with a margin of error less than .05.

Class analysis is a technique that identifies groups or classes of units of analysis (e.g., texts) sharing similar characteristics. This approach is based on identifying patterns and similarities among data through the analysis of word frequency and co-occurrence in texts (Alexandre et al., 2019; Gaviria et al., 2020). The information resulting from class analysis is presented in a dendrogram, a graphical representation of the hierarchy of identified classes. This dendrogram displays the total percentage of text segments included in the result and per class, along with the strength of the relationship of words with each class. The naming of each class is qualitatively established based on the associated keywords, the interpretation of text segments, and the context in which contributions are inserted (Magalhães et al., 2018; Nguyen et al., 2020). Each class is identified by analyzing keywords with the highest chi-square values, representing the strongest associations within the text segments, which aids in establishing coherent and meaningful class labels. A reliable and suitable tool for textual analysis was employed, utilizing Descending Hierarchical Analysis.

Results

What is Happiness?

The Descending Hierarchical Analysis of the definition of happiness classified 148 segments out of 222 (66.67%) into four classes (see Figure 1). Specifically, two main dimensions are recognized. On one hand, the dimension related to emotional aspects, represented by the class termed “personal experience.” On the other hand, classes defined by personal evaluation, encompassing various aspects, distinguish themselves. Within this latter dimension, distinctions are made among “basic needs” which encompass cognitive aspects, “emotional balance,” and “personal evaluation of life.” Classes based on personal balance are highlighted in terms of importance, followed by personal life evaluation.

Figure 1.

Dendrogram of the Descending Hierarchical Classification of the definition of happiness, including words whose criterion of relationship with the class (χ²) was significant (p < .05).

The first class was labeled “personal evaluation” (28.38% of text segments) and is characterized by considerations such as: “being happy in all or the vast majority of important aspects of my life” (χ² = 38); “feeling comfortable and well in all daily life aspects emotionally and physically” (χ² = 22.86); “well-being for me is feeling comfortable with what you do and with who you are as a person” (χ² = 20.14).

The second class was labeled “personal experience” (25% of text segments). Some contributions associated with this class include: “feeling good about myself” (χ² = 76.31); “feeling fulfillment and satisfaction with myself and feeling fulfilled” (χ² = 69.38); “feeling comfortable, well, feeling good in terms of physical health, mental health, and living conditions” (χ² = 51.41).

The third representation holds the highest weight by number of segments (30.41%) and was defined as “emotional balance.” It is characterized by contributions such as: “a state of satisfaction that depends on many mental, social, cultural, and physical conditions and factors” (χ² = 81.01); “well-being is synonymous with balance, harmony, finding a balance between your mental and physical state, your work, family, friendships, partner” (χ² = 51.67); “well-being for me is having mental, physical, and social health and also having a home in harmony with my family members” (χ² = 17.29).

Lastly, the fourth class was termed “basic needs” (16.22% of text segments) and includes contributions such as: “having basic needs covered first and then having the opportunity for self-realization” (χ² = 960.98); “such as having access to basic resources like food, a home to live in, opportunities for personal and professional development” (χ² = 60.73); “having basic needs covered” (χ² = 49.51).

What Does Happiness Depend on?

Regarding the factors that happiness depends on, the Hierarchical Descending Analysis classified 127 segments out of 235 (54.04%) into 3 classes, following the Reinert method (see Figure 2).

Figure 2.

Dendrogram of the Hierarchical Descending Classification of the criteria for factors influencing happiness, including words whose relationship criterion with the class (χ²) was significant (p < .05).

Two distinct dimensions are identified. On one hand, there is the dimension related to personal factors (class 1), and on the other hand, classes that include contextual factors (classes 2 and 3).

The first class was labeled “Personal factors” (29.92% of text segments), with notable quotes such as: “from the things I do during the day, the worries, the stress, the joys that I have…” (χ² = 45.97); “it depends on how I overcome day by day and how gradually I change toward the person I want to become in the future” (χ² = 17.76); “from what happens to me on a daily basis” (χ² = 14.75).

The second class was named “Life circumstances” (34.65% of text segments) and is characterized by contributions such as: “my well-being depends on my health, the health of those around me, and that all needs are met, both mine and those of my family and friends” (χ² = 25.81); “on my social relationships, self-esteem, level of fatigue, my family and friends” (χ² = 20.33); “health, friends, family, studies, work life, love life” (χ² = 18.27).

The third class, which has the highest number of segments (35.43%), is characterized by quotes such as: “on how my mental health or my interpersonal relationships are” (χ² = 40.71); “for me, well-being depends on various factors ranging from health, emotional state, economics” (χ² = 39.69); “depends largely on my mental and physical health” (χ² = 15.56). It is labeled “Social Environment,” understood as the social support encompassing social and interpersonal relationships.

Discussion

The objective of this study was to explore the subjectivity of well-being in young people, focusing on how they conceptualize this term and how they interpret and value their own well-being, understood as happiness.

The results of the hierarchical descending analysis suggest that there are different dimensions and classes that combine to shape it. Particularly notable is the importance of the emotional and cognitive dimensions of well-being, such as life satisfaction and the frequency of positive and negative emotions, which are closely related (Diener et al., 1999). Additionally, it is observed that emotional balance is a central dimension of happiness (Kahneman & Krueger, 2006), along with personal evaluation and experience, while basic needs occupy a more distant and less relevant dimension. University students place greater importance on achieving emotional balance and being satisfied with what they do in their lives, prioritizing the subjective aspect related to personal evaluation of their lives over basic needs that are more oriented toward cognitive aspects.

These findings are consistent with previous literature that has emphasized the importance of emotional and cognitive aspects of well-being, as well as the relevance of life satisfaction as a central dimension of well-being (Diener et al., 1999; Ryan & Deci, 2001; Waterman, 1993). Furthermore, other studies have highlighted the importance of factors such as resilience, autonomy, and personal fulfillment in well-being (Fredrickson, 2013; Keyes, 2007; Ryff & Singer, 2008). As stated by Veenhoven (1984), subjective well-being should be understood from a global judgment perspective, as young people emphasize the importance of personal evaluation and experience alongside emotional balance.

On the other hand, the results obtained from the hierarchical descending analysis on the factors influencing happiness suggest that there are two distinct dimensions contributing to well-being: daily circumstances, understood as having a purpose in life (Helliwell et al., 2020), and social support, understood as social and interpersonal relationships (Steel et al., 2008). These dimensions consist of various factors such as daily routines, social relationships, mental health, and family, which are essential in determining an individual’s happiness. For a young university student to maintain good well-being, it is crucial to nurture healthy social and personal relationships, as these contribute significantly to their emotional development (M. E. P. Seligman, 2018).

The PERMA model proposed by M. E. P. Seligman (2011) identifies five essential elements for well-being: positive emotions, engagement, relationships, meaning, and accomplishments. Other authors have underscored the importance of factors such as life satisfaction (Diener et al., 1999), resilience (Fredrickson, 2013), autonomy (Deci & Ryan, 2000), and personal fulfillment (Waterman, 1993) in well-being.

Ryff and Singer (2008) have proposed that well-being consists of six dimensions, including emotional aspects, personal experience, and life evaluation. Furthermore, other studies have emphasized the significance of factors such as physical and mental health, interpersonal relationships, and a sense of purpose in life for an individual’s well-being (Diener et al., 2015; Keyes, 2007).

Thus, the results suggest that the well-being of young university students not only depends on cognitive aspects such as their economic and employment situation (Diener & Oishi, 2000). In fact, according to Diener and Seligman (2002), subjective well-being is not solely dependent on economic factors, as an increase in economic status in a social context does not necessarily correspond to a proportional increase in well-being and may even exacerbate symptoms of depression. Young people place more emphasis on emotional aspects, which carry greater weight.

They value more what they are doing with their lives, the meaning behind their actions related to life satisfaction and happiness (Park, 2004), and with whom they can share these experiences, related to relationships with others, which leads to having a purpose in life (Steger et al., 2008). This implies that policies and well-being programs for young university students must consider these multiple dimensions and factors to be effective, understanding that young people prioritize these elements when conceptualizing their well-being.

It is important to pay attention to the life satisfaction, happiness and subjective well-being of young university students, as well as their emotional aspects, and personal and contextual factors. Additionally, the importance of factors such as resilience, autonomy, and personal fulfillment in the well-being of young university students should be considered. Rodríguez-Muñoz et al. (2020) found that resilience and life satisfaction were significant predictors of well-being among young university students. A study by Houle et al. (2018) found that young university students who had a greater sense of purpose in life and higher autonomy experienced greater psychological and social well-being.

The results of this research suggest that the determinants of subjective well-being among young university students are complex and depend on multiple factors (Ryff, 2014). It will be necessary to consider these factors in research and well-being practices to better understand the experiences and needs of this population, using a holistic approach to comprehend and enhance the well-being of young university students (Diener et al., 2018). Thus, to promote this well-being, it is essential to consider both cognitive and emotional aspects, in addition to personal and contextual factors, and develop policies and programs that address these multiple dimensions of well-being.

An important aspect of this study is that it considered the social representation of individuals for the analysis of their happiness. Understanding the perspective that individuals have about their reality is crucial, using the theory of social representations (Moscovici, 2001). In well-being research, standardized scales are often used, and individuals are typically asked less about their own judgment of their well-being, as investigated by several authors (Caunt et al., 2012; Lea & MacLeod, 2019; Luhmann et al., 2013; Schimmack et al., 2002). This subjective perspective, combined with lexical analysis, allowed valuable conclusions to be drawn about how individuals feel and assess their subjective well-being, understood as happiness, as this question is more accessible for young people. By enabling individuals to define what subjective well-being means to them and choose how to maximize it through language and knowledge, we promote well-being literacy, understood as a capability derived from the capabilities approach of Sen (1993) and Nussbaum (2011), which promotes freedom and choice in the experience of well-being. Young people consciously use language to promote such well-being (Oades, 2017; Oades & Johnston, 2017).

Asking young university students about their well-being and happiness is important because it helps identify their needs and strengths, informs policies and programs to enhance their well-being, and promotes a university culture that supports mental health and well-being, as asserted by Keyes (2007) and Braun and Clarke (2006). These findings on emotional balance and personal life evaluation reflect shared social representations of well-being among young people, highlighting common patterns in how they perceive and prioritize their well-being. This framework of social representations allows us to interpret the uniformity in their well-being experiences, revealing the influence of social norms and cultural contexts on their conceptions of happiness and life satisfaction

However, it is understood that happiness is not the exclusive domain of anyone, as young people, elderly individuals, women, men, rich and poor, and working-class people can experience happiness, as it is a universal human experience, irrespective of biological, personality, or social characteristics (Myers & Diener, 1995).

In future studies, it would be valuable to delve deeper into this specific understanding of subjective well-being, examining differences across sociodemographic terms and categories, while also considering other age groups.

Conclusion

This study presents several limitations, such as the demographic composition of the sample, primarily middle-class female university students, which may not fully represent the broader young adult population in Spain. Additionally, the focus on “happiness” rather than a broader “well-being” construct may restrict certain interpretations, despite the conceptual overlap noted in the introduction. On the other hand, this study also presents strengths, such as the use of open-ended questions, allowing for the analysis of a larger sample size and richer, more varied responses, often beyond the scope of conventional interview-based qualitative studies. Although the term “happiness” was used in this study for its accessibility and comprehensibility among participants, it should be noted that this choice may have limited the scope of the research. Broader aspects of subjective well-being might have been omitted, as “happiness” does not fully capture the comprehensive construct of well-being.

The findings could inform the design of university-based interventions and public policies that specifically address the emotional and social priorities of young people, optimizing well-being programs and strengthening institutional support within the educational context for this demographic.

To advance in the field of subjective well-being, it is essential to understand how psychological factors interact with life circumstances to generate this well-being. It is crucial to identify the causal pathways leading to happiness, unravel the underlying processes, and develop theories that explain why certain variables have different effects. Happiness is a multidimensional construct influenced by a variety of factors, and understanding these determinants is essential for designing interventions that enhance people’s subjective well-being and, consequently, their lives.

Footnotes

ORCID iDs

Paula Morales Almeida

Pedro Alemán Ramos

Statements and Declarations

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