Trevor Archer

We used the affective profiles model to investigate individual differences in motivation, stress and energy. The aim was to replicate past findings, but we also focused on matched comparisons within individuals with affective profiles that are similar in one affective dimension and differ in the other in order to predict changes when individuals increase/decrease their experience of positive or negative affect. Methods: <span class="fontstyle2">A total of 567 participants answered the Positive Affect and Negative Affect Schedule, which was used for affective profiling; the Situational Motivation Scale, which measures intrinsic motivation, identified regulation, external regulation, and amotivation; and the Stress-Energy questionnaire. Results: <span class="fontstyle2">Comparisons between the four different profiles, replicating the past findings, showed that individuals with high affective and self-fulfilling profile scored highest in intrinsic motivation, identified regulation, and energy, while they scored lowest in external motivation, amotivation, and the self-fulfilling profile, also lowest in stress. Additionally, the matched comparisons showed, for example, that levels of intrinsic motivation increase when negative affect levels decrease, and positive affect is kept high when positive affect decreases and negative affect is kept low. Conclusions: One important feature of the affective profiles model is the possibility to compare individuals that are similar in one affect dimension but differ in the other (Garcia, 2011, 2017). This way of discussing individual differences helps to predict what changes could be expected when individuals increase or decrease their experience of positive or negative affect. Importantly, the direction of these changes cannot be addressed from cross-sectional data

Background: The affectivity system is a complex dynamic system, thus, it needs to be seen as a whole-system unit that is best studied by analyzing four profiles: self-destructive (low positive affect, high negative affect), low affective (low positive affect, low negative affect), high affective (high positive affect, high negative affect), and self-fulfilling (high positive affect, low negative affect). Our purpose was to examine individual differences in psychological well-being and self-regulatory strategies (assessment/locomotion). Additionally, we investigated if the effect of psychological well-being on self-regulatory strategies was moderated by the individual’s type of profile. Method: Participants (N = 567) answered the Positive Affect Negative Affect Schedule, Ryff’s Scales of Psychological Well-being, and the Regulatory Mode Questionnaire. We conducted a Multivariate Analysis of Variance using age as covariate and Structural Equation Modeling in a multi-group for moderation analysis. Result: Individuals with a self-fulfilling profile scored highest in all psychological well-being constructs and locomotion and lowest in assessment. Nevertheless, matched comparisons showed that increases in certain psychological resources might lead to profile changes. Moreover, while some psychological well-being constructs (e.g., self-acceptance) had an effect of self-regulatory mode independently of the individual’s profile, other constructs’ (e.g., personal growth) effect on self-regulation was moderated by the person’s unique type of profile. Conclusions: Although only theoretical, these results give an idea of how leaps/changes might be extreme (i.e., from one profile at the extreme of the model to the other extreme), while other might be serial (i.e., from one profile to another depending on matching affective dimensions).

Aims: We investigated gender differences among adolescents in quality of sleep, psychophysiological problems, dream frequency, emotional states, and personality traits and also if the effect of quality of sleep on psychophysiological problems, dream frequency, emotional states, and personality traits was moderated by gender. Method: High school pupils (n1 = 155, n2 = 142, and n3 = 325) responded to the Uppsala Sleep Inventory, the Positive Affect Negative Affect Schedule, Beck’s Depression Inventory, the Type A-Personality Scale, and the Temperament and Character Inventory. Gender differences were investigated using Multivariate Analyses of Variance and moderation using multi-group Structural Equation Modeling. Results: Girls scored higher in major sleep problems, difficulties falling asleep, night awakenings, psychophysiological problems, dream frequency, negative affect, depression, stress, and Type A-personality. Boys scored higher in novelty seeking, harm avoidance, and persistence. Girls’ quality of sleep was related to their psychophysiological problems, dream frequency, positive affect, negative affect, stress, novelty seeking, reward dependence, persistence, and self-directedness. Boys’ quality of sleep was related to their psychophysiological problems, negative affect, stress, Type A-personality, novelty seeking, harm avoidance, reward dependence, and self-directedness. Conclusion: Girls showed the unhealthiest sleep-psychophysiological-emotional-personality profile. For both genders, good quality of sleep or “beauty sleep” might result in less psychophysiological problems, less negative affect, less stress, less novelty seeking, and less self-directedness. However, for boys, “sleeping beauty” comprises less Type A-behaviour, ss harm avoidance, and more reward dependence; while for girls “sleeping beauty” comprises less frequency of vivid dreams, more positive affect, less reward dependence, and more persistent behaviour.