Affective Profiles and Anxiety or Non-Anxiety-Related Reasons for School Refusal Behavior: Latent Profile Analysis in Spanish Adolescents

Little has been studied on the relationship between affect and school problems related with attendance. This study aims to identify different affective profiles and to determine whether these profiles differ from each other based on the four functional conditions of school refusal behavior. Participants comprised 1,816 Spanish adolescents aged 15-18 years (M = 16.39; SD = 1.05). The Positive and Negative Affect Schedule for Children-Short Form and the School Refusal Assessment Scale-Revised for Children (SRAS-R-C) were administered. Latent profile analysis revealed five affective profiles: low affective profile, self-fulfilling profile, low positive affect profile, self-destructive profile, and high affective profile. The self-destructive profile revealed the highest average scores in the first three factors of the SRAS-R-C, whereas the high affective profile reached the highest average score in the fourth factor. On the contrary, the self-fulfilling profile obtained the lowest average scores in the first two factors of the SRAS-R-C, whereas the low affective profile revealed the lowest average scores in the last two factors. Findings suggest the relevance of developing more adaptative affective profiles, such as the self-fulfilling profile, which would contribute to diminishing school attendance problems.

Factorial Invariance, Latent Mean Differences of the Panas and Affective Profiles and Its Relation to Social Anxiety in Ecuadorian Sample

Positive (PA) and negative affect (NA) are related with aspects that are part of people’s psychological well-being, and the possibility of combining both dimensions to create four affective profiles, self-fulfilling (high PA and low NA), low affective (low PA and low NA), high affective (high PA and high NA) and self-destructive (low PA and high NA), has recently appeared. The current work aims to validate the short version of the Positive and Negative Affect Schedule (PANAS) in Ecuador, test the existence of the four affective profiles and analyze its relation with social anxiety. The Positive and Negative Affect Schedule for Children and the Social Anxiety Scale for Adolescents was employed in a sample of 1786 Ecuadorian students aged from 15 to 18 years (M = 16.31, SD = 1.01). The factorial invariance of the scale across sex and age groups was proved and latent mean analyses showed that girls and 18-year-old students obtained the highest scores in negative affect. With regard to the affective profiles, the cluster analyses confirmed the existence of the four mentioned profiles, and the self-fulfilling profile obtained the lowest scores in all the dimensions of social anxiety, whereas the self-destructive profile obtained the highest scores.

Positive and Negative Affect Schedule-Short Form: Factorial Invariance and Optimistic and Pessimistic Affective Profiles in Spanish Children

The distinction in recent years between positive affect (PA) and negative affect (NA) is becoming increasingly important due to their relationship with depression and anxiety. This work is composed of two studies. The first study aimed to validate the brief version of the Positive and Negative Affect Schedule for Children-Short Form (PANAS-C-SF) in a Spanish child sample. The second study sought to check the existence of four affective profiles: self-fulfilling (high PA and low NA), low affective (low PA and NA), high affective (high PA and NA), and self-destructive (low PA and high NA) and to relate them to optimism and pessimism. Samples for both studies were composed of 647 and 1,296 Spanish students (between 8 and 11 years), respectively. Through various multigroup confirmatory factor analyses (MCA), the invariance of the PANAS-SF and the lack of significant gender differences in the latent means were verified. In addition, cluster analysis confirmed the existence of the appropriate profiles. In this case, the self-fulfilling profile correlated with high scores in optimism and low scores pessimism, whereas the self-destructive profile correlated in the opposite direction. These contributions represent an advance in the study of child affect.

Aggression Profiles in the Spanish Child Population: Differences in Perfectionism, School Refusal and Affect

The aim of this study was to identify the existence of combinations of aggression components (Anger, Hostility, Physical Aggression and Verbal Aggression) that result in different profiles of aggressive behavior in children, as well as to test the differences between these profiles in scores of perfectionism, school refusal and affect. It is interesting to analyze these variables given: (a) their clinical relevance due to their close relationship with the overall psychopathology; and (b) the need for further evidence regarding how they are associated with aggressive behavior. The sample consisted of 1202 Spanish primary education students between the ages of 8 and 12. Three aggressive behavior profiles for children were identified using Latent Class Analysis (LCA): High Aggression (Z scores between 0.69 and 0.7), Moderate Aggression (Z scores between -0.39 and -0.47) and Low Aggression (Z scores between -1.36 and -1.58). These profiles were found for 49.08%, 38.46% and 12.48% of the sample, respectively. High Aggression scored significantly higher than Moderate Aggression and Low Aggression on Socially Prescribed Perfectionism (SPP), Self-Oriented Perfectionism (SOP), the first three factors of school refusal (i.e., FI. Negative Affective, FII. Social Aversion and/or Evaluation, FIII. To Pursue Attention), and Negative Affect (NA). In addition, Moderate Aggression also reported significantly higher scores than Low Aggression for the three first factors of school refusal and NA. Conversely, Low Aggression had significantly higher mean scores than High Aggression and Moderate Aggression on Positive Affect (PA). Results demonstrate that High Aggression was the most maladaptive profile having a high risk of psychological vulnerability. Aggression prevention programs should be sure to include strategies to overcome psychological problems that characterize children manifesting high levels of aggressive behavior.

Two different approaches to the affective profiles model: median splits (variable-oriented) and cluster analysis (person-oriented)

Background. The notion of the affective system as being composed of two dimensions led Archer and colleagues to the development of the affective profiles model. The model consists of four different profiles based on combinations of individuals’ experience of high/low positive and negative affect: self-fulfilling, low affective, high affective, and self-destructive. During the past 10 years, an increasing number of studies have used this person-centered model as the backdrop for the investigation of between and within individual differences in ill-being and well-being. The most common approach to this profiling is by dividing individuals’ scores of self-reported affect using the median of the population as reference for high/low splits. However, scores just-above and just-below the median might become high and low by arbitrariness, not by reality. Thus, it is plausible to criticize the validity of this variable-oriented approach. Our aim was to compare the median splits approach with a person-oriented approach, namely, cluster analysis.

Method. The participants (N = 2, 225) were recruited through Amazons’ Mechanical Turk and asked to self-report affect using the Positive Affect Negative Affect Schedule. We compared the profiles’ homogeneity and Silhouette coefficients to discern differences in homogeneity and heterogeneity between approaches. We also conducted exact cell-wise analyses matching the profiles from both approaches and matching profiles and gender to investigate profiling agreement with respect to affectivity levels and affectivity and gender. All analyses were conducted using the ROPstat software.

Results. The cluster approach (weighted average of cluster homogeneity coefficients = 0.62, Silhouette coefficients = 0.68) generated profiles with greater homogeneity and more distinctive from each other compared to the median splits approach (weighted average of cluster homogeneity coefficients = 0.75, Silhouette coefficients = 0.59). Most of the participants (n = 1,736, 78.0%) were allocated to the same profile (Rand Index = .83), however, 489 (21.98%) were allocated to different profiles depending on the approach. Both approaches allocated females and males similarly in three of the four profiles. Only the cluster analysis approach classified men significantly more often than chance to a self-fulfilling profile (type) and females less often than chance to this very same profile (antitype).

Conclusions. Although the question whether one approach is more appropriate than the other is still without answer, the cluster method allocated individuals to profiles that are more in accordance with the conceptual basis of the model and also to expected gender differences. More importantly, regardless of the approach, our findings suggest that the model mirrors a complex and dynamic adaptive system.

A happier and less sinister past, a more hedonistic and less fatalistic present and a more structured future: time perspective and well-being

Background. Previous studies have established a link between how people relate to their past, present, and future (i.e., time perspective) and subjective well-being (i.e., life satisfaction, positive and negative affect). Time perspective comprises five dimensions: Past Positive, Past Negative, Present Hedonistic, Present Fatalistic, and Future. Life satisfaction can also be evaluated in relation to different time frames. Moreover, approach related positive affect is associated to a different concept of well-being labeled psychological well-being. In the present study we extend previous findings by investigating the effect of time perspective on the time frame of evaluations of life satisfaction (past, present, future) and by investigating the relationship between time perspective and psychological well-being. Method. Questionnaires on time perspective (Zimbardo's Time Perspective Inventory), temporal life satisfaction (Temporal Satisfaction with Life Scale), affect (Positive Affect and Negative Affect Schedule), and psychological well-being (Scales of Psychological Well-Being-short version) were answered by 453 individuals. Two different structural equation models were tested, one of the relationship between time perspective and temporal life satisfaction, and the other of the relationship between time perspective, affect and psychological well-being. Results. Time perspective affected life satisfaction depending on the time scale on which it was evaluated-memory of a negative past influenced life satisfaction in all time frames, and a positive view of the past influenced both past and future life satisfaction. Moreover, less rumination about past negative events (i.e., low score on Past Negative), the tendency to take risks in the present to achieve happy feelings and/or avoid boredom (i.e., high scores on Present Hedonistic), and a less hopeless and pessimistic view about the present (low scores on Present Fatalistic) were associated with higher levels of psychological well-being and positive affect. These same time perspective dimensions were associated with lower levels of negative affect. The Future time perspective dimension (i.e., approaching life with self-control, punctuality, and planning for the future) was associated with both psychological well-being and positive affect. Conclusions. High levels of both subjective and psychological well-being are related to a happier and a less sinister past, a more hedonistic and less fatalistic present, as well as to a more structured future.

The affective profiles, psychological well-being, and harmony: environmental mastery and self-acceptance predict the sense of a harmonious life

Background. An important outcome from the debate on whether wellness equals happiness, is the need of research focusing on how psychological well-being might influence humans’ ability to adapt to the changing environment and live in harmony. To get a detailed picture of the influence of positive and negative affect, the current study employed the affective profiles model in which individuals are categorised into groups based on either high positive and low negative affect (self-fulfilling); high positive and high negative affect (high affective); low positive and low negative affect (low affective); and high negative and low positive affect (self-destructive). The aims were to (1) investigate differences between affective profiles in psychological well-being and harmony and (2) how psychological well-being and its dimensions relate to harmony within the four affective profiles.

Method. 500 participants (mean age = 34.14 years, SD. = ±12.75 years; 187 males and 313 females) were recruited online and required to answer three self-report measures: The Positive Affect and Negative Affect Schedule; The Scales of Psychological Well-Being (short version) and The Harmony in Life Scale. We conducted a Multivariate Analysis of Variance where the affective profiles and gender were the independent factors and psychological well-being composite score, its six dimensions as well as the harmony in life score were the dependent factors. In addition, we conducted four multi-group (i.e., the four affective profiles) moderation analyses with the psychological well-being dimensions as predictors and harmony in life as the dependent variables.

Results. Individuals categorised as self-fulfilling, as compared to the other profiles, tended to score higher on the psychological well-being dimensions: positive relations, environmental mastery, self-acceptance, autonomy, personal growth, and purpose in life. In addition, 47% to 66% of the variance of the harmony in life was explained by the dimensions of psychological well-being within the four affective profiles. Specifically, harmony in life was significantly predicted by environmental mastery and self-acceptance across all affective profiles. However, for the low affective group high purpose in life predicted low levels of harmony in life.

Conclusions. The results demonstrated that affective profiles systematically relate to psychological well-being and harmony in life. Notably, individuals categorised as self-fulfilling tended to report higher levels of both psychological well-being and harmony in life when compared with the other profiles. Meanwhile individuals in the self-destructive group reported the lowest levels of psychological well-being and harmony when compared with the three other profiles. It is proposed that self-acceptance and environmental acceptance might enable individuals to go from self-destructive to a self-fulfilling state that also involves harmony in life.