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- Garcia, Danilo, 1973, et al.
(författare)
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Questions of Self-regulation and Affect: Affectivity, Locomotion, Assessment, and Psychological Well-Being
- 2018
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Ingår i: Biquarterly Iranian Journal of Health Psychology. - 2588-4204. ; 1:1, s. 37-50
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Tidskriftsartikel (refereegranskat)abstract
- Objective: 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).
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| 2. |
- Garcia, Danilo, 1973, et al.
(författare)
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Two different approaches to the affective profiles model : median splits (variable-oriented) and cluster analysis (person-oriented)
- 2015
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Ingår i: PeerJ. - : PeerJ Inc.. - 2167-8359. ; 3
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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