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The Single and Joint Contributions of Temperament and Family Functioning to Subjective Happiness in Spanish College Students

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  • 01.04.2025
  • Research Paper
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Abstract

Der Artikel untersucht die Faktoren, die das subjektive Glück spanischer College-Studenten beeinflussen, und konzentriert sich dabei auf die Rolle des Temperaments und die Funktionsweise der Familie. Sie unterstreicht den Rückgang des Wohlbefindens, der in den letzten Jahrzehnten insbesondere unter erwachsenen Bevölkerungen zu beobachten war, und die einzigartigen Herausforderungen, vor denen junge Erwachsene stehen. Die Studie verwendet einen personenzentrierten Ansatz, um zu analysieren, wie unterschiedliche Temperamentsprofile - belastbar, zurückhaltend und nicht wünschenswert - das subjektive Glück beeinflussen. Sie untersucht auch die Funktionsweise der Familie anhand des Circumplex-Modells und identifiziert gesunde und ungesunde Familienprofile sowie deren Auswirkungen auf das Wohlbefinden der Schüler. Die Forschung zeigt, dass belastbare und zurückhaltende Temperamente, zusammen mit einem gesunden familiären Umfeld, mit einem höheren Maß an subjektivem Glück einhergehen. Umgekehrt korrelieren unerwünschte Temperamente und eine ungesunde Familiendynamik mit einem niedrigeren Glücksniveau. Das Zusammenspiel zwischen Temperament und familiärer Funktionsweise wird untersucht und zeigt, wie bestimmte Kombinationen den Einfluss auf das subjektive Glück puffern oder verstärken können. Die Ergebnisse unterstreichen die Bedeutung des kulturellen Kontextes für das Verständnis von Glück und liefern praktische Implikationen für die Gestaltung von Interventionen zur Unterstützung des Wohlergehens von College-Studenten.

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1 Introduction

Though it is expected that the improvement in living conditions in recent decades would correlate with higher levels of well-being in today's society, some studies point to a decrease in these levels, particularly in adult populations (Barr et al., 2005; Breiner et al., 2015; Steptoe et al., 2015; Twenge et al., 2016). In emerging adulthood, a developmental stage ranging from adolescence to adulthood characteristic of Western societies (Arnett, 1998), an array of studies reports a decrease in levels of well-being and psychological balance of individuals, specifically in college students (Alandete, 2013; Bewick et al., 2010; Cooke et al., 2006; Sandoval et al., 2017; Stallman, 2010). Moreover, numerous studies report mental health issues during the college stage (Lipson et al., 2019, 2022), especially since the COVID-19 pandemic (Copeland et al., 2021; Lee et al., 2021; Salimi et al., 2023). This scenario, added to the fact that college students deem happiness and well-being as crucial life-values ​​(Kim-Prieto et al., 2005), has brought increasing interest from the scientific community in studying factors explaining the happiness of this group. Along these lines, this study aims to analyze how certain individual characteristics (temperament) and environmental characteristics (family functioning) contribute to explaining the subjective happiness of emerging Spanish youth. We believe this can help in design of programs and tools aimed at increasing the well-being of college students, given their greater vulnerability at present.

1.1 Subjective Happiness as a Measure of Well-Being

Interest in human well-being has increased exponentially in recent decades with contributions from diverse scientific fields which have brought new approaches to its study and conceptualization. In this regard, a recent revision by Diener et al. (2018) highlighted those subjective evaluations about life satisfaction which may provide a better mechanism for well-being assessment than objective approaches, as they reflect idiosyncratic reactions to objective life circumstances. Consistent with this approach, Subjective Happiness (SH) has emerged as an interesting measure of people’s well-being, and is defined as a global, subjective assessment of happiness (Lyumorsky & Lepper, 1999). Though their close correlation has often led to their being treated as equals, it must be clarified that the concept of subjective happiness is not comparable to that of subjective well-being (SWB; Diener, 2000). Thus, while the former refers to a relatively enduring global state of how happy a person feels, the latter is a broader concept including an affective component (the prevalence of positive emotional experiences over negative; Diener, 2000) and a cognitive component (evaluation of one's life satisfaction; Diener, 2000). We consider this distinction important, as it confirms the view of many authors who do not recognize overlap between both concepts when evaluating different aspects of the individual's well-being (Gallagher et al., 2009; Howell et al., 2010; Iani et al.., 2013; Lyubomirsky & Lepper, 1999; Purvis et al., 2011).
New questions on subjective happiness have arisen from behavioral science, one of which is to examine the individual and environmental factors that contribute to its experience, taking into account the developmental stage or culture of the individual (Buehler, 2020; Suh, 2000). As stated, for various reasons, study of these factors is particularly relevant in the emerging adulthood stage which is transitional and involves reassessment of vital goals (Uriarte, 2005), and is associated with higher levels of academic pressure due to adaptation to new forms of learning (Morales et al., 2020). As a result, increasingly more SH researchers are focusing on this particular collective, trying to understand mechanisms involved in their happiness, and how their interaction may affect this subjective experience (Karris et al., 2020; Yildirim & Tanriverdi, 2021).

1.2 Subjective Happiness and Temperament from a Person-Centered Approach

Among the personal determinants proven to be strongly predictive of an individuals’ subjective happiness, temperament is worth highlighting since it contributes significantly to how people evaluate their lives (Blatny et al., 2015; García & Moradi, 2013). According to Rothbart’s model, temperament is defined as constitutionally individual differences in reactivity and self-regulation, which in adults are explained by four-broad dimensions (Rothbart et al., 2000): surgency/extraversion (SE—sociability, pleasure in social interaction, enjoyment of intense stimulation and positive emotionality), negative affect (NA—heightened sensitivity to a broad spectrum of negative stimuli), effortful control (EC—ability to suppress a dominant response to perform a subdominant one), and orienting sensitivity (OS—ability to be conscious of a neutral or emotional stimulation of low intensity from surroundings).
As regards SH, the scarce research based on Rothbart’s temperament model has mainly arisen from a variable-centered approach, which analyzes the impact of each isolated temperament dimension on individual well-being. In this line, higher levels of surgency and effortful control, and lower levels of negative affect have been related to higher levels of both subjective well-being and subjective happiness at different developmental stages (Galián & Ato, 2023; Kornienko et al., 2018; Slobodskaya et al., 2019). However, the variable-centered approach assumes that temperament dimensions (and their effects) are independent, though traits such as negative emotionality and self-regulation have been believed to influence one another (Laible et al., 2014). Furthermore, the variable centered-approach offers a partial vision of the relationship between temperament and SH given that it ignores the organization of multiple temperament traits within an individual and their particular effect on subjective happiness. Thus, this approach may be inappropriate for drawing conclusions on single individuals, since results are based on variables and not on people (Crockett et al., 2006).
On the contrary, the person-centered approach analyzes the contribution of a specific combination of variables on a given outcome, without the required least squares analyses assumption that variables are orthogonal. Therefore, each dimension takes on meaning based upon its role within the entire organization of the individual, implying a holistic perspective where the individual is taken as the unit analysis (Bergman & Magnusson, 1997). In short, this perspective allows identification of “types” which describe the individual in a more complete way conceptually than when based on isolated traits. Furthermore, conceptualization of personal characteristics based on types appears associated with greater predictive validity (Robins & Tracy, 2003).
In this connection, some researchers of temperament have tried to establish a typology parallel to that of a personality based on the Big Five traits. As a result, the resilient, undercontrolled and overcontrolled categories have been identified (Berry & Schwebel, 2009; Komsi et al., 2006; Puonti et al., 2021), a typology widely used in the field of personality development (Alessandri et al., 2014; Asendorpf et al., 2001; Donnellan & Robins, 2010; Robins et al., 1996). Individuals with resilient temperament are characterized by high levels of surgency and effortful control, and low levels of negative affect. Overcontrolled individuals exhibit high effortful control and negative affect and very low surgency. Lastly, undercontrolled individuals show high emotionality intensity, both positive and negative, and low self-regulation skills.
While the resilient profile is easily identifiable in studies on personality types/temperament, the overcontrolled and undercontrolled profiles are more problematic to replicate in the same terms (Mammadov, 2021). Thus, alternative personality types have recently been identified, such as reserved or non-desirable profiles (Grumm & von Collini, 2009; Hirvonen et al., 2018). Extrapolating to temperament dimensions, the reserved individuals would be characterized with high levels of effortful control, and low levels of negative affect and surgency, while the non-desirable individuals would show high levels of negative affect and low levels of effortful control and surgency (see Table 1 for a summary of expected values). As observed, none of the profiles described considers the Rothbart's temperament dimension of Orienting Sensitivity. This is because dimensions of surgency, effortful control and negative affect allow for configuration of temperament profiles similar to those proposed from the Big Five model, which have traditionally focused on extraversion, conscientiousness, and neuroticism personality traits. On the contrary, the trait of openness to experience has not been significant in configuration of most personality profiles described in the literature (Alessandri et al., 2014; Asendorpf et al., 2001; Donnellan & Robins, 2010; Robins et al., 1996). Considering that in Rothbart's model, the factor of orienting sensitivity would be the “counterpart” to the personality trait of openness, we believe its exclusion is sufficiently justified in the temperament profiles configuration.
Table 1
Expected pattern for temperament profiles
 
1. Resilient
2. Reserved
3. Non-desirable
Negative affect (NA)
Low
Low
High
Effortful control (EC)
High
High
Low
Surgency/Extraversion (SE)
High
Low
Low
In either case, temperament profiles have mostly been used to explain social and school adjustment in childhood and adolescence (Komsi et al., 2006; Puonti et al., 2021; Robins et al., 1996), but never to explain subjective happiness in adulthood. This typological approach can shed light on the still little-known relationship between temperament and subjective happiness in emerging adulthood.
In a more exact description, the “resilient” profile would be characteristic of individuals with good social skills, who enjoy interaction with others, are not very impulsive, have good control of negative emotions, and a predominance of positive emotions. We believe the positive and sociable nature of this profile can benefit emerging adults in facing the social challenges characteristic of this stage, such as starting to build romantic and professional relationships. Moreover, resilient young people demonstrate strong self-regulation abilities, which can be highly beneficial in the face of increased academic pressure and the new forms of learning required at this stage. Therefore, it is a profile which is expected to predict higher levels of subjective happiness. The “reserved” profile would also be characterized by good control of negative emotions and little impulsivity, but it would be typical of individuals who are shy and inhibited in social relationships. In this regard, the low emotional intensity and strong self-regulation characteristic of this profile can be beneficial when facing academic studies but may pose a challenge for the young person's social life, potentially reducing their perceived level of happiness. Finally, the “non-desirable” individual would be characterized by high impulsivity, predominance of negative emotions, poor control of emotions and behavior. Young people with this profile would be expected to be negatively affected in both social and academic areas, as high impulsivity can impair the individual's academic organization and high negative emotionality can decrease the quality of social relationships, which will ultimately bring a decrease in happiness levels.

1.3 Subjective Happiness and Family Functioning

There is abundant data confirming the strong connection between family functioning and subjective happiness or subjective well-being in child and adolescent populations. SH is particularly related to family cohesion (Fosco et al., 2020; Goswami, 2012; Leto et al., 2019; Xiang et al., 2020), parental warmth (Kazarian et al., 2010), family support (Hellfeldt et al., 2019; Rodriguez-Rivas et al., 2022), family conflict (Fosco et al., 2020) or parental rejection (Kazarian et al., 2010). After adolescence, however, the link between family functioning and SH is much less explored. In this context, data suggest that healthier family patterns are linked to higher levels of subjective happiness or subjective well-being in youth and adults (Asici & Sari, 2021; Brannan et al., 2013; Galián & Ato, 2023; Schnettler et al., 2014; Xiang et al., 2020), but further research is required for better understanding of these relations.
For this purpose, an interesting paradigm for the study of family functioning is offered by the Circumplex Model (Olson, 2000), structured around the concepts of cohesion (emotional bonding of family members) and flexibility (quality and expression of leadership, role relationships and relationship rules), and proceeds from the idea that balanced levels of both scales lead to healthier family functioning, while unbalanced levels are associated with the opposite pattern (Olson & Gorall, 2003). In other words, healthy functioning will occur in families who can functionally balance independence and togetherness and also change and stability, while unhealthy functioning will be typical of families who do not achieve this balance, and who are too disengaged, emmeshed, rigid or chaotic (Olson, 2000). One advantage of the Circumplex model is that it contains a highly reliable scale (FACES) which assesses balanced (cohesion and flexibility) and unbalanced scales (disengaged, enmeshed, rigid and chaotic) of family functioning. In addition, its latest version (FACES-IV; Olson & Gorall, 2006) allows obtaining family profiles, which can offer valuable information in the explanation of individual developmental outcomes. Despite its extended use in both empirical research and clinical settings (Kouneski, 2002), evaluation of family functioning from the Circumplex model is scarcely used in SH research (Galián & Ato, 2023), therefore it remains to be explored.
Although previous studies have focused on early stages, it is logical to expect healthy family functioning would also increase levels of subjective happiness in young adults. In this regard, a recent meta-analytic study focused on children and adolescents highlights the importance of family cohesion in individual happiness (Izzo et al., 2022). Similarly, we believe that optimal levels of cohesion will help emerging adults who still live with parents to face the challenges of this stage with more confidence and security, thus increasing their perceived happiness. As for the dimension of flexibility, it would be expected that an excessively rigid and resistant family environment could hinder transition to new forms of learning required at college level, while a chaotic and disorganized one could pose an obstacle to achieving academic goals. However, it would be expected that a structured and organized family environment would help young people face these challenges in a more adaptive way. As a result, we expect that the healthy family functioning profile will significantly predict higher scores in subjective happiness during emerging adulthood.

1.4 The Joint Contribution of Temperament and Family Functioning on Subjective Happiness

Although studying the single contribution of temperament and family environment to SH is deemed relevant, from transactional approaches (Sameroff & Chandler, 1975; Sameroff & MacKenzie, 2003) interaction of both variables must also be considered. The concept of goodness of fit (Thomas & Chess, 1977) provides a rationale of how temperament and family interact in explaining several developmental outcomes, and according to Chess and Thomas (1999, pp. 3), “results when the properties of the environment and its expectations and demands are in accord with the organism´s own capacities, characteristics and style of behaving”. In summary, the concept of goodness of fit helps us understand why a “good” or “bad” temperament does not always result in the expected “better” or “worse” adjustment, but rather depends on how it aligns with certain environmental characteristics, such as the family context.
Corroborating the goodness of fit hypothesis, there is a vast line of reporting in childhood and adolescence that certain temperament characteristics produce positive outcomes in interaction with supportive parenting but lead to maladjustment combined with negative parenting (Kiff et al., 2011; Lahdelma et al., 2021; Lengua, 2006; Oldenhinkel et al., 2006). Unfortunately, this line of results has not been replicated in emerging adults, even though, in Spain, a large majority still live with parents. In this connection, it would be interesting to know if particular temperament profiles differ in impact on emerging adults´ subjective happiness when combined with different family functioning profiles. One way to do so would be to assign a temperament profile and a family functioning profile for each subject, and then analyze whether there is a significant variation in degree of subjective happiness in subjects with a certain temperament profile, when compared to other subjects with the same temperament profile but with different family functioning profile. This would allow us to assess the extent to which family functioning can buffer or enhance the impact of individual characteristics on subjective happiness in emerging adults.
In the context of our work, we could expect young people with a resilient temperamental profile to experience decreased levels of happiness in a poorly cohesive family environment compared to those with more balanced levels of family cohesion. In particular, the sociability and positive emotionality characteristic of this profile might be negatively affected in a family context which is either insufficiently or excessively cohesive, as it undermines self-esteem and a healthy relational model necessary for positive social interaction. In contrast, we might expect individuals with a non-desirable temperamental profile (impulsive, highly negative, and poorly self-regulated individuals) to exhibit higher levels of happiness when living in a healthy family environment, as opposed to individuals with the same profile but whose families demonstrate more unbalanced family functioning. Specifically, a family environment with clear and structured rules could help channel the self-regulation issues typical of this profile, while a chaotic or excessively rigid environment could intensify their negative emotional intensity. In the case of a reserved temperament (more neutral in emotional expression, highly regulated and social inhibited individuals), it would be logical to expect their well-being to vary depending on levels of family cohesion, being lower when families are excessively independent and detached. Thus, in a disengaged family environment, reserved young individuals might feel less emotionally secure and protected, in turn increasing their social insecurity.

1.5 The Present Study

In summary, though the decline in well-being levels in the adult population produces greater research focused on analyzing variables which explain this decrease, there remains scarce information on how temperament characteristics and family functioning contribute to the subjective happiness of emerging adults. Analysis of these relationships is especially relevant at this development stage, as its transitional and potentially stressful nature can increase the risk of psychological problems in young people, affecting their levels of well-being and/or happiness. In addition, there are no previous studies analyzing the relationship between temperament and subjective happiness from the person-centered approach, one which can be very useful in understanding how certain temperament profiles contribute differentially to perceived happiness in this period. On the other hand, the study of well-being in emerging adults often ignores the contribution of the family environment, understanding that the family is no longer important when it comes to explaining how young people perceive themselves in terms of their happiness. However, in Mediterranean cultures like the Spanish one, young people at this age still maintain close bonds with the family unit, therefore analysis of this relationship is of enormous importance for a fuller understanding of the well-being of individuals. Finally, no previous studies exist which have analyzed the joint contribution of temperament and family functioning on well-being, which we believe useful in designing intervention programs with emerging adults at "risk." It is our view that knowing how certain temperament profiles behave in different family contexts and their relationship with subjective happiness, can be key to a comprehensive approach to problems related to the well-being and happiness of young people. Based on the reviewed literature, we believe students with a more problematic (e.g., non-desirable) temperamental profile, whose family functioning is less balanced as regards cohesion and flexibility, will be at greater risk of social and academic problems in the emerging adulthood stage, which could impact their levels of perceived happiness.
Along these lines, this paper aims to analyze the single and joint contribution of temperament and family functioning to subjective happiness in a sample of Spanish college students. This objective can be further divided into the following: (a) Identify different temperament profiles from Rothbart´s model, and analyze their differential impact on students´ subjective happiness; (b) Identify different family profiles based on the Circumplex model, and analyze their differential impact on the subjective happiness of students´; and (c) Examine the joint contribution between temperament and family functioning profiles, analyzing the effect of this interplay on the explanation of subjective happiness in emerging adults.
We believe achievement of these aims can make an interesting contribution to the study of subjective happiness in the emerging adulthood stage enabling us to analyze how temperament and family functioning profiles are configured and which are most common in this developmental stage, and how they contribute individually and jointly to the subjective happiness of college students. As previously mentioned, this information will not only expand knowledge on happiness at this stage, but will be extremely useful for planning and development of intervention programs for risk profiles. Furthermore, this information can be applied in areas beyond the clinical setting. For example, it can assist college counselors in providing more precise guidance to young individuals with low levels of well-being, helping them reflect on how their personal characteristics and family context influence their adjustment issues both independently and jointly.

2 Method

2.1 Participants and Procedure

349 Students of Education from Murcia University volunteered to participate in the study. From the original sample, fifteen were excluded for not meeting the age criteria of between 18 and 25 years. Two students were also excluded for generalized non-response to all items. The remaining students numbered 332, with an average age of 19.38 and standard deviation of 1.17. The pattern of 2% of missing responses was imputed by the median of cases. Distributed by gender, 75 respondents were male (22.53%) and 258 female (77.47%).
Ethical approval was obtained by Murcia University ethics committee.Each participant provided written consent prior to the study and completed paper-based questionnaires helped by trained researchers. Any doubts regarding completion were answered.

2.2 Instruments

2.2.1 Temperament

College students self-assessed their temperament using the short form of the Adult Temperament Questionnaire (ATQ; Evans & Rothbart, 2007), which contains 77 items on a 7-point Likert scale (1 = extremely untrue, 7 = extremely true). This questionnaire measures the following four broad temperament dimensions: Effortful Control (activation, attentional and inhibitory control subscales), Negative Affectivity (fear, frustration, sadness and discomfort subscales), Surgency/Extraversion (sociability, high intensity pleasure and positive affect subscales) and Orienting Sensitivity (neutral perceptual, affective perceptual and associative sensitivity subscales). For our research purpose, only Effortful Control, Negative Affect and Surgency/Extraversion scales were used. Examples of items in the test for each scale would be: “Even if I don't feel like it, I can start doing a difficult task” (Effortful Control scale); “I feel frustrated or angry very easily” (Negative Affect scale); “I like conversations that involve several people” (Extraversion/Surgency scale).
We used R lavaan package (version 0.6.11; Rosseel, 2012) to perform a confirmatory factor analysis with MLR (Robust Maximum Likelihood) estimator to test the model of four factors for ATQ. Using conventional criteria (Hu & Bentler, 1998–99; Marsh et al., 2005, Kline, 2016), we obtained a satisfactory fit: \({\chi }^{2}\left(1739\right)=2053.8;p>.01,\) CFI = 0.918, TLI = 0.905, SRMR = 0.073 and RMSEA = 0.024 (90% CI: 0.022–0.028), p > 0.05. Measurement reliability of ATQ scales was obtained using R psych (version 2.2.9; Revelle, 2022) and R semTools (version 0.6.12; Jorgensen et al., 2022). Alpha reliabilities for ATQ scales were 0.79 (NA), 0.75 (EF), 0.71 (SE) and 0.68 (OS), and Omega 3 reliability were 0.73 (NA), 0.71 (EF), 0.69 (SE) and 0.59 (OS).

2.2.2 Family functioning

Family functioning was assessed using the Family Adaptability and Cohesion Evaluation Scale (FACES IV; Olson & Gorall, 2006), in its Spanish adaptation (Rivero et al., 2010). This version discarded some of the original 42 items, resulting in 24 items on a 7-point Likert Scale (1 = completely disagree, 7 = completely agree). Following the Circumplex model, the scale is divided into two delimited groups: two balanced scales (Cohesion and Flexibility) assessing the moderate and healthy regions of both dimensions, and four unbalanced scales (Disengaged, Enmeshed, Rigid and Chaotic) measuring the lower and upper extremes of Cohesion and Flexibility. Examples of test items for each scale would be: “We feel very close to each other” (Cohesion scale); “Our family tries to find new ways to deal with problems” (Flexibility scale); “We spend too much time together” (Enmeshed scale); “When we are at home, we seem to avoid contact with each other” (Disengaged scale); “There are strict consequences for those who break the rules in our family” (Rigid scale); “In our family we never seem to be organized” (Chaotic scale).
A confirmatory factor analysis with MLR estimation obtained a reasonable fit to the six-factor model of the Spanish version of FACES IV: \({\chi }^{2}\left(207\right)=314.09;p<.05,\) CFI = 0.953, TLI = 0.942, Robust RMSEA = 0.042 (90% CI: 0.032–0.051), p > 0.05 and SMSR = 0.053. Alpha reliabilities for FACES scales were 0.68 (Cohesion, FC1), 0.81 (Flexibility, FC2), 0.76 (Enmeshed, FC3), 0.75 (Disengaged, FC4), 0.58 (Ridig, FC5) and 0.77 (Chaotic, FC6), and Omega 3 reliability were 0.69 (FC1), 0.80 (FC2), 0.77 (FC3), 0.73 (FC4), 0.56 (FC5) and 0.76 (FC6).

2.2.3 Subjective happiness

To measure the subjective happiness of students, we used the Subjective Happiness Scale (Lyubomirsky & Lepper, 1999) in its Spanish version (Extremera & Fernández-Berrocal, 2014). This scale includes 4 items on a 7-point Likert scale (1 = very unhappy, 7 = very happy), where participants either self-rate their global subjective happiness or compare themselves to others.
We also performed a confirmatory factor analysis to test the one-factor model of the Subjective Happiness scale and also obtained a reasonable fit: \({\chi }^{2}\left(1\right)=1.883;p>.05,\) CFI = . 997, TLI = 0.979, robust RMSEA = 0.063 (90% CI: 0.01- 0.20) p > 0.05 and SRMR = 0.017. Measurement reliability obtained was alpha = 0.79 and omega 3 = 0.74.

2.3 Data Analysis

Composite (mean centered) scores for all subscales of ATQ, FACES and SH questionnaires were obtained. Descriptive statistics and Pearson correlation coefficients with Holm’s corrected probabilities were computed on these scores using R psych package (Revelle, 2022).
To answer the first two study aims, we used latent profile analysis (LPA) to identify temperament profiles from ATQ and family profiles from FACES IV questionnaires. LPA is a form of Gaussian Mixture Modeling, which attempts to identify groups, classes or clusters of individuals (latent profiles) from responses to a set of continuous items, treating the entire population of items as a mixture of subpopulations where individual elements are modeled by conditional probability distributions. For this purpose, we used R package mclust (version 6, see Scrucca et al., 2016), which provides functions for parameter estimation through EM (Expectation–Maximization) algorithm for maximum likelihood estimation of normal mixture models using 14 different covariance structures.
To select the best k-class latent profile, we first found the most parsimonious models using BIC and ICL criteria (Baudry et al., 2010), and then a better Brier Score (a proper score function used to measure the accuracy of probabilistic predictions, where lowest values are better; Gneiting & Raftery, 2007), the Averaged Posterior Class Probabilities, which also provide a measure of classification accuracy, where values > 0.70 are more desirable (Masyn, 2013), the Mean Uncertainty, which indicates the uncertainty of classification, and the Bootstrap Likelihood Ratio test (BLR; McLachlan, 1987; McLachlan & Rathnayake, 2014), where a nonsignificant result comparing adjacent classes supports the k−1 class over the k class model.
The general linear model was used to analyze the relationship between latent profiles and subjective happiness including gender as covariate. Firstly, we assessed the fulfilments of linear models with R gvlm package (Peña & Slate, 2006). Main analyses were run using emmeans R package (version 1.8.4; Lenth et al., 2023), to estimate population marginal means for factor combinations of models used, as suggested in Searle et al. (1980). R package effect-size (version 0.8.3., Ben-Shachar et al., 2020) was also used to report effect sizes for main results.

3 Results

Composite (mean centered) scores for 4 subscales of ATQ (Negative Affect, Effortful Control, Surgency/Extraversion and Orienting Sensitivity), and for 6 subscales of FACES IV and the SH scale were initially employed in this study. We used centered means to facilitate interpretation of results of the general linear model, as well as profiles. Alpha reliabilities for these composite scores ranged between 0.65 and 0.76. Descriptive statistics (global and by gender), Pearson correlations and Holm’s corrected probabilities between all subscales are shown in Table 2. Examination of the correlation matrix revealed that SH positively correlated with effortful control, surgency, cohesion, flexibility and enmeshed scales but negatively with negative affect, disengaged and chaotic scales, and was null with rigid scale. In addition, both effortful control and surgency scales positively correlated with cohesion, flexibility and enmeshed scales and negatively with negative affect, disengaged and chaotic scales. Correlation between Orienting Sensitivity subscale and all FACES subscales was also null (Table 2).
Table 2 
Descriptive analysis, correlations and corrected probabilities for all measures
 
Mean (SD)
Correlations (upper diagonal), Holm corrected probabilities (lower diagonal)
 
Male, n = 75
Female,n = 257
Total, n = 332
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(1) SH
4.95 (1.11)
4.73 (1.04)
4.78 (1.06)
 
 − .41
.24
.35
 − .16
.31
.30
 − .26
.16
 − .02
 − .23
(2) NA
4.07 (0.75)
4.42 (0.68)
4.34 (0.71)
.00
 
 − .39
 − .17
.30
 − .18
 − .13
.17
 − .03
.03
.13
(3) EF
4.03 (0.60)
3.94 (0.67)
3.96 (0.65)
.00
.00
 
.01
 − .05
.08
.09
 − .17
.07
 − .07
 − .20
(4) SE
4.82 (0.73)
5.16 (0.76)
5.09 (0.76)
.00
.02
1.00
 
.16
.34
.37
 − .30
.28
 − .07
 − .23
(5) OS
4.72 (0.69)
4.95 (0.66)
4.90 (0.67)
.03
.00
1.00
.02
 
-.02
.04
.08
.03
 − .01
 − .01
(6) FC1
3.49 (0.75)
3.56 (0.86)
3.55 (0.84)
.00
.01
1.00
.00
1.00
 
.61
 − .55
.38
 − .04
 − .50
(7) FC2
3.99 (0.64)
4.02 (0.83)
4.01 (0.79)
.00
.34
1.00
.00
1.00
.00
 
 − .76
.57
 − .11
 − .46
(8) FC3
2.29 (0.80)
2.11 (0.88)
2.15 (0.87)
.00
.06
.05
.00
1.00
.00
.00
 
 − .52
.02
.47
(9) FC4
2.74 (0.66)
2.98 (0.87)
2.92 (0.83)
.00
1.00
1.00
.00
1.00
.00
.00
.00
 
 − .02
 − .30
(10) FC5
2.72 (0.89)
2.57 (0.87)
2.60 (0.87)
.71
1.00
1.00
1.00
1.00
.49
.05
.74
.72
 
 − .03
(11) FC6
2.24 (0.82)
2.26 (0.88)
2.26 (0.87)
.00
.34
.01
.00
1.00
.00
.00
.00
.00
.65
 
SH: Subjective Happiness, NA: Negative affect, EC: Effortful Control, SE: Surgency/Extraversion, OS: Orienting Sensitivity, FC1: Cohesion, FC2: Flexibility, FC3:
Disengaged, FC4: Emmeshed, FC5 Rigid, FC6: Chaotic
In order to identify temperament profiles, we submitted composite scores of subscales Effortful Control, Negative Affect and Surgency (Orienting Sensitivity was excluded for theoretical reasons mentioned in the introduction of this work, reinforced for a null correlation with FACES scale, a modest correlation with Subjective Happiness and low reliability) to a latent profile analysis with mclust package. We focused our selection of an appropriate model among the 12 multivariate models with different geometric characteristics for the covariance structure, based on distribution, shape, volume and orientation that can be constrained to be equal or varying between groups (Banfield & Raftery, 1993; Celeux & Govaert, 1995; McNicholas, 2016). Using Bayesian Information (BIC; Schwarz, 1978) and Integrated Complete-data Likelihood criteria (ICL; Biernacki et al., 2000), we first discarded 8 models with general (or ellipsoidal) covariance structure because the greatest value of BIC pointed to a unique cluster/profile that assumes independence between variables. The remaining 4 models presented solutions with 3 (EVI and VVI models) or 4 (EEI and VVI models) cluster/profiles. Given that the literature on temperament profiles usually differentiates three clusters based on variables considered (resilient, undercontrolled and overcontrolled; or equivalent), we focused on analyzing solutions that included 3 clusters, in search of profiles similar to those found by previous authors (Grumm & von Collini, 2009; Hirvonen et al., 2018; Komsi et al., 2006; Puonti et al., 2021). Furthermore, the criteria used to detect the best combination of profiles supported the three-profile solution.
Table 3 is a summary of models for temperament profiles with greatest BIC highlighted in boldface. Relevant criteria used to finally select EVI model against VVI model were that it was more parsimonious (60 vs 62 df) and presented a lower BIC and ICL criteria, a lower Brier Score, lower averaged Posterior Class Probabilities (PCP) and also lower mean uncertainty. Unfortunately, in our sample BLR test we did not detect any appropriate model (with p > 0.05) but we tested one to five classes using an elbow plot as suggested in Masyn (2013, p. 572), and a barely-noticeable angle was detected with 3-class model.
Table 3
Criteria used to select a latent profile solution for temperament (ATQ) scales between some general/ellipsoidal models for multivariate data
Model,
# clust
Clusters size
BIC
ICL
df
Averaged
PCP
Brier score
Mean
Uncert
BLR test
P(BLR)
EEI, 2
139/193
− 9361
− 9422
31
.93/.92
.020
.078
314.0
.001
EEI, 3
117/103/112
− 9298
− 9391
42
.90/.87/.88
.032
.116
127.5
.001
EEI, 4
75/68/76/113
− 9262
− 9381
53
.86/.83/.88/.85
.042
.146
99.6
.001
EEI, 5
19/44/83/98/88
− 9294
− 9439
64
.83/.79/.82/.77/.84
.052
.177
32.0
.003
VEI, 2
139/193
− 9367
− 9426
32
.93/.92
.020
.077
314.5
.001
VEI, 3
110/111/111
− 9301
− 9390
44
.88/.90/.88
.030
.112
135.2
.001
VEI, 4
VEI, 5
78/68/79/10
29/51/90/68/94
− 9269
− 9293
− 9384
− 9427
56
68
.85/.85/.87/.87
.83/.82/.86/.79/.86
.040
.046
.141
.162
102.0
45.6
.001
.002
EVI, 2
145/187
− 9401
− 9463
40
.93/.92
.022
.078
326.8
.001
EVI, 3
106/81/145
− 9345
− 9438
60
.88/.88/.89
.032
.112
171.8
.001
EVI, 4
68/88/89/87
− 9353
− 9459
80
.84/.87/.91/.85
.036
.132
108.6
.001
VVI, 2
142/190
− 9406
− 9468
41
.93/.92
.022
.078
327.0
.001
VVI, 3
103/79/150
− 9352
− 9441
62
.88/.88/.90
.033
.114
176.1
.001
VVI, 4
63/90/89/90
− 9358
− 9463
83
.87/.86/.90/.85
.036
.130
115.3
.001
BIC: Bayesian information criterion; ICL: Integrated complete-data likelihood criterion; Averaged PCP: Averaged Posterior Class Probabilities; Mean Uncert: Mean Uncertainty, BLR test: Bootstrapped Likehood Ratio test
The selected EVI model solution identified: (1) a first cluster with 106 cases with scores well below average in Negative affect, above average in Effortful control and well above average in Surgency/Extraversion, which we call “resilient”, in line with previous authors (Hirnoven et al., 2018; Komsi et al., 2006; Puonti et al., 2021); (2) a second cluster with 81 cases with scores well below average in Negative Affect and Surgency/Extraversion, and above average in Effortful control, which we call “reserved”, in line with Hirvonen et al. (2018); and (3) a third cluster with 145 cases with scores well below average in Effortful control and Surgency/Extraversion, and well above average in Negative affect. We expected this third cluster to fit the “undercontrolled” profile previously described in the literature, but in our case, subjects scored well below average in Surgency, which does not occur in subjects identified by this profile in prior studies. For this reason, we call it “non-desirable”, as it has certain similarities with the personality profile described by Grumm & von Collini (2009). Figure 1 is a profile plot for this solution. For more detailed information, Table 4 summarizes the centered mean scores for each of the 10 temperament subscales in each profile.
Fig. 1
Temperament latent profile plot for EVI model with 3 clusters
Bild vergrößern
Table 4
Centered means of profiles for temperament (ATQ) subscales
 
Profiles of temperament
Temperament subscales
Resilient
Reserved
Non desirable
(NA1) Fear
− 0.5386
− 0.4054
0.6599
(NA2) Frustration
− 0.7422
− 0.0779
0.6067
(NA3) Sadness
− 0.1866
− 0.7764
0.6295
(NA4) Disconfort
− 0.1748
− 0.6417
0.5366
Mean Negative Affect
− 0.4106
− 0.4754
0.6082
(EC1) Activity control
0.3211
0.1545
− 0.3622
(EC2) Attention control
0.2110
0.4043
− 0.4360
(EC3) Inhibitory control
0.0316
0.5436
− 0.3190
Mean Effortful Control
0.1879
0.3675
− 0.3724
(SE1) Sociability
0.7421
− 0.0411
− 0.5306
(SE2) High intensity pleasure
0.6666
− 0.5931
− 0.1268
(SE3) Positive affect
0.9350
− 0.6977
− 0.2614
Mean Surgency/Extraversion
0.7812
− 0.4440
− 0.3063
(NA) Negative Affect; (EC) Effortful Control, (SE) Surgency/Extraversion dimensions
We followed the same procedure to find an appropriate profile solution for composite scores of 5 family functioning subscales (the Rigid scale was also deleted as it had null correlation with the rest of scales and Subjective Happiness and also had low reliability). Table 5 shows the best seven models with 2 or 3 clusters selected using BIC and ICL criteria. Best solutions for each model are highlighted in boldface. Excluding VEE, EEV and EVV models with non significant BLR test testing k-1 vs k profiles, the rest of models obtained the lowest BIC with 2 profiles, where Brier Scores, Averaged PCP and Mean Uncertainty were similar. We discarded the EEE and VVV models for being very restrictive, and finally selected VVE model over VEV model (with better BIC and ICL) as it presented lower df and better Brier and mean uncertainty scores. The selected solution identified: (1) a first cluster with 243 cases which we call “healthy”, with scores above average on the balanced cohesion and flexibility scales, and on the unbalanced enmeshed scale, and below average on the unbalanced disengaged and chaos scales; and (2) a second cluster with 89 cases, which we call “unhealthy” with scores well below average on the balanced cohesion and flexibility scales, below average on the unbalanced enmeshed scale and well above average on the unbalanced, disengaged and chaos scales. Figure 2 is a profile plot for this solution, made from the centered means collected in Table 6.
Table 5
Criteria used to select a latent profile solution for family functioning (FACES) scales between some general/ellipsoidal models for multivariate data
Model
Clusters size
BIC
ICL
df
Brier
Score
Averaged
PCP
Mean
Uncert
BLMR test
P(BLR)
EEE, 2
276/56
− 3486
− 3515
26
.009
.98/.89
.037
69.2
.001
EEE, 3
92/52/188
− 3512
− 3642
32
.047
.76/.91/.86
.162
9.6
.403
VEE, 2
242/90
− 3411
− 3474
27
.020
.93/.91
.083
150.7
.001
VEE, 3
153/87/92
− 3406
− 3540
34
.047
.80/.87/.85
.167
45.5
.006
VEE, 4
VEE, 5
98/48/65/121
71/49/53/42/126
− 3424
− 3447
− 3573
− 3611
41
48
.050
.056
.79/.79/.84/.85
.67/.83/.86/.79/.86
.182
.195
22.9
17.6
.035
.182
VVE, 2
243/89
− 3419
− 3476
31
.017
.94/.90
.074
229.8
.001
VVE, 3
156/84/92
− 3429
− 3545
42
.042
.84/.88/.86
.144
36.6
.938
EEV, 2
277/55
− 3491
− 3516
36
.008
.97/.92
.033
122.7
.001
EEV, 3
246/39/47
− 3529
− 3613
52
.030
.92/.90/.79
.105
54.9
.001
EEV, 4
214/36/29/53
− 3518
− 3674
68
.058
.81/.85/.90/.74
.190
104.1
.001
VEV, 2
215/117
− 3399
− 3470
37
.024
.91/.90
.091
220.5
.001
VEV, 3
165/96/71
− 3459
− 3569
54
.039
.85/.91/.81
.139
38.8
.129
EVV, 2
273/59
− 3505
− 3537
40
.012
.97/.91
.039
131.6
.001
EVV, 3
EVV, 4
247/43/42
239/23/30/40
− 3550
− 3613
− 3625
− 3693
60
80
.026
.028
.93/.88/.78
.93/.85/.89/.79
.095
.099
71.4
52.4
.001
.022
VVV, 2
216/116
− 3418
− 3485
41
.022
.92/.90
.087
224.9
.001
VVV, 3
174/99/59
− 3494
− 3586
62
.031
.88/.92/.82
.117
45.5
.273
BIC: Bayesian information criteria; ICL: Integrated complete-data likelihood; Averaged PCP: Averaged Posterior Class Probabilities; Mean Uncert: Mean Uncertainty, BLR test: Bootstrapped Likehood Ratio test
Fig. 2
Family functioning latent profile plot for VVE model with 2 clusters
Bild vergrößern
Table 6
Centered means of profiles for family functioning (FACES) scales
Centered means
Healthy family
Unhealthy family
1. Cohesion (FC1)
.290
− .729
2. Flexibility (FC2)
.323
− .809
3. Disentangled (FC3)
− .357
.883
4. Enmeshed (FC4)
.217
\(-\hspace{0.17em}.\)541
5. Chaotic (FC6)
\(-\hspace{0.17em}.\)292
.738
A general linear analysis was also run in order to learn the independent effects of temperament and family functioning profiles on Subjective Happiness (SH), using gender as covariate. After testing that assumptions of linear models were complied with, we found a sound effect of temperament profile on SH: F(2, 328) = 91.43; p < 0.001, \({\eta }^{2}=\) 0.25, but not a significant gender effect. Specifically, significantly higher subjective happiness scores were observed for the “resilient” profile, followed by the “reserved” profile, which also positively explained happiness. In contrast, the “non-desirable” profile was associated with a significant decrease in subjective happiness reported by young people. Similarly, we found a more modest effect of family functioning profile on SH: F(1, 329) = 27.78; p < 0.001, \({\eta }^{2}=\) 0.08 but no significant gender effects. In this case, significantly higher subjective happiness scores were observed for the “healthy” profile, with the opposite pattern seen for the “unhealthy” profile. Table 7 shows the estimated centered means, paired contrasts between levels of profiles with Tukey t-test Holm-adjusted for multiple comparisons and a measure of effect size (Cohen’s delta).
Table 7
Independent effects of temperament (ATQ) and family functioning (FACES) latent profiles on subjective happiness
Profiles
Means
C.I. 95%
Contrasts
Tukey t (df)
Adjusted P
Cohen’s δ
ATQ
      
1: Resilient
0.585
0.414/0.757
1–2
2.025 (329)
 > .05
0.305
2: Reserved
0.305
0.093/0.517
2–3
6.641 (329)
 < .001
0.951
3: Non-desirable
 − 0.572
 − 0.712/− 0.422
1–3
10.01 (329)
 < .001
1.256
FACES
      
1: Healthy family)
0.178
0.048/0.308
1–2
4.850 (330)
 < .001
0.599
2: Unhealthy family
 − 0.437
 − 0.650/− 0.224
    
Finally, we tested the joint effects of temperament and family functioning profiles on SH. We found that interaction was not significant and proceeded to test the additive effects of both profiles. Table 8 shows the centered means, paired contrasts between levels of profiles with Tukey t-test Holm-adjusted for main comparisons and Cohen’s delta effect sizes. As expected, we observed significant differences of SH between both profiles: F(3, 328) = 42.63; p < 0.001, \({\eta }^{2}=\) 0.27. ANOVA results for ATQ profiles were: F(2,328) = 56.99; p < 0.001, \({\eta }^{2}=\) 0.26, and for FACES profiles: F(1,328) = 13.91; p < 0.001, \({\eta }^{2}=\) 0.04.
Table 8
Joint effects of temperament (ATQ) and family functioning (FACES) profiles on Subjective Happiness
FACES-ATQ profiles
Means
C.I. 95%
Contrasts
Tukey t (df)
Adjusted P
Cohen’s δ
Healthy families
      
1. Resilient
0.631
0.459/0.803
1–2: 0.242
1.760 (328)
 > .05
0.266
2. Reserved
0.388
0.172/0.606
2–3: 0.828
6.298 (328)
 < .001
0.910
3 Non-desirable
 − 0.439
 − 0.612/− 0.267
1–3: 1.070
9.070 (328)
 < .001
1.175
Unhealthy families
      
1. Resilient
0.290
 − 0.029/0.550
    
2. Reserved
 − 0.047
 − 0.224/0.319
    
3 Non-desirable
 − 0.781
 − 0.984/− 0.577
    
Resilient
      
1. Healthy families
0.631
0.459/0.811
1–2: 0.341
2.938 (328)
.003
0.375
2. Unhealthy families
0.290
 − 0.029/0.462
    
Reserved
      
1. Healthy families
0.389
0.172/0.606
    
2. Unhealthy families
 − 0.047
 − 0.224/0.319
    
Non-desirable
      
1. Healthy families
 − 0.439
 − 0.612/− 0.267
    
2. Unhealthy families
 − 0.781
 − 0.984/− 0.577
    
Table 8 shows the estimated means of temperament profile for healthy and unhealthy families. For the former, the trend is similar to that found in the general case, positive and highest for resilient temperaments, followed by reserved and negative and lowest for non-desirable ones. This trend is also similar but much more reduced for resilient and non-desirable temperaments in unhealthy families. In the case of reserved students, an opposite trend was observed in unhealthy families, with negative scores in subjective happiness.

4 Discussion

The aim of our work was to analyze the single and joint contributions of temperament and family functioning to subjective happiness in a sample of Spanish college students. Our findings indicate that resilient and reserved temperaments expressed higher levels of subjective happiness than those which were non-desirable. As for family functioning, students living in healthy families showed higher levels of subjective happiness than those in unbalanced family systems. Furthermore, resilient students living in healthy family systems reported the highest level of SH, while non-desirable students in unhealthy families experienced lowest levels of subjective happiness. Reserved students reported positive levels of SH in the context of balanced families, but negative scores in combination with unbalanced families. As regards gender, our study reported no significant differences in subjective happiness between males and females.

4.1 Temperament Profile Contribution to Subjective Happiness of Students

As for temperament dimensions, students were grouped in three clusters: resilient, reserved and non-desirable, all profiles previously identified in several personality and temperament studies (Grumm & von Collani, 2009; Hirvonen et al., 2018; Komsi et al., 2006; Rammstedt et al., 2004). As reflected in Fig. 1 and Table 4, the resilient profile was typical of highly sociable students with good self-regulatory abilities who exhibited a high frequency and intensity of positive emotions and few negative emotions. In contrast, the non-desirable profile described students with little social orientation, who frequently and intensely exhibited emotions such as anger, fear or frustration, and showed little ability to regulate these at optimal levels. Finally, the reserved profile was typical of shy and unsociable young people who were more emotionally neutral and very well regulated. Our data revealed a rather equitable distribution between the three temperament profiles.
Resilient and reserved students reported significantly higher levels of subjective happiness, emphasizing the protective role of high levels of effortful control and low levels of negative affect on individuals´ adaptation to their environment (Asendorpf et al., 2001; Dollar et al., 2017; Grumm & von Collani, 2009; Hirvonen et al., 2018; Janson & Mathiesen, 2008; Keogh, 2003; Puonti, 2021; Vitiello et al., 2012). Therefore, it is assumed the more self-regulated and less negative the students, the more efficiently they can face social and environmental stressors, and so the greater their levels of subjective happiness. Moreover, since resilient students scored much higher than average in surgency and reported highest levels of subjective happiness, it appears that being extrovert might be relevant in the experience of students' SH. A plausible explanation for this effect may be provided by cultural beliefs on the role of social networks in an individual´s life. In this connection, social relations are considered of great importance in Spanish culture, which may increase the life satisfaction of extroverts who meet cultural expectations. Nevertheless, emerging adults can particularly benefit from higher levels of extraversion, since they are in the process of building significant relationships in their lives, such as partnerships, friendships or professional relations.
Alternatively, the non-desirable profile was linked to significantly lower levels of subjective happiness. Other studies reported poor adaptation and maladjustment in individuals with this pattern of temperament/personality traits (Grumm & von Collani, 2009; Hirvonen et al., 2018; Janson & Mathiesen; Klimsta et al., 2010; Puonti et al., 2021; Robins et al., 1996). In contrast to resilient students, non-desirable young people are more negative and less self-regulated, making them more vulnerable to social conflict and behavioral problems. In addition, non-desirable students showed low levels of extraversion, which may worsen their social self-concept, especially in a highly socially oriented culture as the Spanish one. All these factors can increase non-desirable students' vulnerability to stress and socioemotional problems, which may explain lower levels of subjective happiness reported for this temperament profile.

4.2 Family Functioning Profile Contribution to Subjective Happiness of Students

Taking the FACES-IV version as reference, Olson and Gorall (2006) described six family types ranging from the most healthy and happy to the most unhealthy and problematic (balanced, rigidly cohesive, midrange, flexibly unbalanced, chaotically disengaged and unbalanced). However, this cluster assignment was set manually and guided by the Circumplex model theory, which may be hard to extrapolate when the cluster assignment is not pre-determined. In our sample, the best fit model comprised two family system clusters which we call healthy and unhealthy, as seen in Fig. 2. Healthy families scored higher than average in cohesion and flexibility scales, slightly above average in enmeshed scale, average in rigid scale, lower than average in chaos scale, and much lower than average in disengaged scale, while unhealthy families showed the opposite pattern. If we compare our clusters with those described in the Spanish adaptation of the test (Rivero et al., 2014), the healthy profile has close similarities with the so-called “rigidly cohesive” profile, while the unhealthy profile would be quite similar to the profile called “chaotically disengaged.”. By eliminating the rigidity scale of the profiles in our case (given its null relationship with the rest of scales), we do not deem it appropriate to use the same terminology to identify our profiles. We do however, consider it interesting to highlight that the “rigidly cohesive” profile is associated with a high level of family satisfaction (Rivero et al., 2014), as noted in our study for the “healthy” profile. In contrast to temperament profiles, family cluster distribution was not equitable. The higher proportion of healthy families may be explained by the idiosyncrasy of our sample, which includes a population with higher socio-economic status and cultural background.
Our family profile configuration was unexpected not just for the number of clusters that apparently better explained our sample distribution, but also for how the enmeshed scale scored in both healthy and unhealthy profiles. Considering that this scale is described from the circumplex model as unbalanced (upper extreme of cohesion scale), it was noticeable that in our sample its higher and lower scores correspond to healthy and unhealthy families respectively. This striking result is due to several reasons. Firstly, the paradigm proposed by Olson maintains that when cultural norms or expectations are in tune with family patterns considered “unbalanced”, the family can function adequately in line with these expectations (Olson et al., 2019). In this regard, Spanish culture has deep collectivistic roots, placing great importance on cohesion and attachment among family members. Accordingly, it appears reasonable that Spanish families interpret enmeshed and dependent behaviors as a natural expression of love and cohesion, and never as unhealthy or toxic as perceived in other cultures. Furthermore, the vast majority of college students in Spain still live with parents, therefore it is more likely they have standardized enmeshed family behaviors, unlike adults who have started the separation process from their families and may perceive these behaviors as unnatural or intrusive, as occurs in other cultures (Manzi et al., 2006). The enmeshed scale also scored very high on the profile described as “rigidly cohesive”, in the Spanish adaptation of the scale which bears close similarities to our “healthy” profile and was also associated with high levels of family satisfaction (Rivero et al., 2010). This parallelism appears to corroborate the idea that cultural beliefs largely determine the “functionality” of the scales, and that what may be dysfunctional or toxic in one culture might be perceived as beneficial in another.
Concerning subjective happiness, our results revealed that students' family environment plays a relevant role in this issue. From the bioecological model, the developmental trajectories of an individual are explained largely by the influences of a microsystem like family environment (Bronfenbrenner & Morris, 2006). In particular, we found that students living in healthy families with higher levels of cohesion, flexibility and attachment, and lower levels of disengagement and chaos, reported higher levels of subjective happiness. On the contrary, the opposite family pattern functioning would most likely be observed in students with lower levels of SH. In this line, when emerging adults live in cohesive and supporting families, they might feel more confident and loved, which may have a direct and positive impact on their happiness. A small number of studies have examined the role of family functioning on emerging adult SWB, reiterating our line of results on the importance of family cohesion and involvement in individual well-being (Asici & Sari, 2021; Brannan et al., 2013; García-Mendoza et al., 2017; Schnettler et al., 2014; Xiang et al., 2020).

4.3 Joint Effects of Temperament and Family Functioning on Subjective Happiness of Students

Once we analyzed the independent contribution of temperament and family functioning on student subjective happiness, we were interested in studying how temperament and family functioning profiles interact in explaining the SH of young people. At this point, the three temperament profiles varied significantly in their contribution to subjective happiness depending on student family profile. Specifically, our data showed that resilient students living in unhealthy families reported lower levels of SH, compared with those in healthy families, while non-desirable students in healthy families reported higher levels of SH (although still low), compared with those in unhealthy ones. In relation to the reserved temperament profile, its contribution to SH was positive in healthy families, but negative in the context of unhealthy family functioning.
The cross-sectional nature of our data does not allow identification of a causal relation between temperament and family functioning; thus, interpretation of this result should be treated with caution. Whether we consider that temperament dispositions shape family functioning or the opposite, our data enables us to suggest that certain combinations between temperament and family profiles are more beneficial than others in explaining subjective happiness. In reserved temperaments, the combination seems particularly relevant since its contribution to subjective happiness turned from negative to positive depending on family profile. A likely explanation for this result is that reserved students in healthy families may feel secure and supported, mitigating the negative impact of low extraversion on social relations, and therefore improving satisfaction with life. On the contrary, less cohesive and unsupportive families may reinforce social maladjustment of reserved students, increasing the likelihood of experiencing socioemotional problems and subjective unhappiness. In line with the goodness-of-fit hypothesis, previous studies have demonstrated that temperament dispositions may lead to positive or negative developmental outcomes, depending on an individual´s family environment (Kiff et al., 2011; Lahdelma et al., 2021; Lengua, 2006; Oldenhinkel et al., 2006).

4.4 Practical Implications, Limitations and Future Directions

The present study supports the hypothesis that both temperament and family functioning contribute to subjective happiness in emerging adulthood, a development stage in which these relations have been scarcely studied. Several strengths and practical implications could be drawn from our study. First, the person-centered approach considers temperament a constellation of traits whose joint work produces certain outcomes and developmental trajectories (Robins & Tracy, 2003) which enables capturing more precisely the complexity of the individual, by going beyond specific risk markers that can function differently depending on the subgroup. In our study in particular, interaction between dimensions of Effortful control, Surgency/Extraversion and Negative affect have allowed us to discriminate three temperament profiles whose impact on subjective happiness is significantly different, revealing patterns providing quite relevant information on the intra-individual temperament structure in the emerging adulthood stage, and on subjective happiness reported by young people. This approach in turn helps us to configure high-risk profiles more useful for planning interventions (Hawes et al., 2022), as in our case with the “non-desirable” profile. Since this profile combines low effortful control and surgency and high negative affect, it seems quite relevant to detect it in family and educational contexts, and design interventions where both self-regulation and social skills can improve socioemotional functioning.
Additionally, Spanish families should be helped in the development of adequate flexibility and cohesion levels, which are proven to explain students' subjective happiness. This learning could be particularly useful in families with reserved students, as an unbalanced family profile places them at higher risk of subjective unhappiness, compared with balanced families. Finally, our results highlight the role of cultural values in understanding of the relationship between temperament, family environment and subjective happiness. Spanish resilient students exhibited particularly high levels of extraversion, implying that this temperament trait can play a more relevant role in SH for Spanish students than for those from different cultures. Likewise, enmeshed family behaviors lead to higher levels of subjective happiness in Spanish college students, which seems unlikely in those from individualistic cultures. Taken together, this line of results may be of particular interest in designing clinical interventions aimed at improving the subjective well-being of young people.
Apart from novel findings provided by current research, there are also some limitations to be considered. Firstly, the CFA performed which included all scales of ATQ and FACES-IV questionnaires showed some problems in adjustment and low reliability that were corrected when the Orienting sensitivity (ATQ) and Rigid (FACES-IV) scales were eliminated for conceptual and methodological reasons. We also focused on Spanish college students, which implies some bias regarding socioeconomic status and cultural background. Although we consider our findings useful for upper-middle class emerging adults from collectivistic cultures, more heterogeneous samples should be investigated in future studies, so results can be generalized to other socioeconomic/age groups and cultural contexts. Another limitation is that all variables were studied through self-report, a source of potential reporting bias. To overcome this, parental reports about family functioning as well as laboratory measures of student temperament should be included in future studies. Finally, the cross-sectional nature of our study can provide preliminary but limited information on the causal relationship between temperament and family functioning. For better understanding of this relationship, it is necessary to examine mutual prediction of change for both temperament and family profiles. However, we consider our results offer an interesting starting point on how temperament and family functioning profiles interact in explaining subjective happiness, since they suggest better and/or worse combinations of profiles for individual well-being.
In summary, we believe our study makes a significant contribution to research on happiness in emerging adulthood for several reasons. First, it recognizes the continued importance of the relationship with parents in the subjective perception of happiness of young people, thus dismantling the myth that the family loses influence after adolescence. Secondly, it elucidates which combination of personal traits has better and/or worse impact on the subjective happiness of emerging adults, offering useful information to understand the intrapersonal structure of the emerging adult's temperament and their contribution to well-being. Likewise, our study sheds light on which profiles of family functioning contribute to greater subjective happiness in college students, and how these profiles can buffer or enhance the effect of temperament profiles on this happiness. Finally, we believe our work provides interesting data on how culture determines the “happiest” temperament and family profiles based on existing beliefs on sociability or attachment between family members, which is necessary and useful in understanding the context in which happiness is built at this stage of the life cycle. Taken together, we believe these contributions to be highly valuable in both clinical and academic settings, in the pursuit of greater well-being and happiness for young people.

Declarations

This work has not been published previously and is not under consideration for publication elsewhere.

Ethical Approval

The Murcia University ethic committee approved the study.
Participation was voluntary and an informed consent was obtained by the participants.
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Titel
The Single and Joint Contributions of Temperament and Family Functioning to Subjective Happiness in Spanish College Students
Verfasst von
Ester Ato
Maria Dolores Galián
Publikationsdatum
01.04.2025
Verlag
Springer Netherlands
Erschienen in
Journal of Happiness Studies / Ausgabe 4/2025
Print ISSN: 1389-4978
Elektronische ISSN: 1573-7780
DOI
https://doi.org/10.1007/s10902-025-00887-3
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