Treatment consideration and manifest complexity in comorbid neuropsychiatric disorders

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.

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.

The affective profiles in the USA: happiness, depression, life satisfaction, and happiness-increasing strategies

Background. The affective profiles model categorizes individuals as self-fulfilling (high positive affect, low negative affect), high affective (high positive affect, high negative affect), low affective (low positive affect, low negative affect), and self-destructive (low positive affect, high negative affect). The model has been used extensively among Swedes to discern differences between profiles regarding happiness, depression, and also life satisfaction. The aim of the present study was to investigate such differences in a sample of residents of the USA. The study also investigated differences between profiles with regard to happiness-increasing strategies.

Methods. In Study I, 900 participants reported affect (Positive Affect Negative Affect Schedule; PANAS) and happiness (Happiness-Depression Scale). In Study II, 500 participants self-reported affect (PANAS), life satisfaction (Satisfaction With Life Scale), and how often they used specific strategies to increase their own happiness (Happiness-Increasing Strategies Scales).

Results. The results showed that, compared to the other profiles, self-fulfilling individuals were less depressed, happier, and more satisfied with their lives. Nevertheless, self-destructive individuals were more depressed, unhappier, and less satisfied than all other profiles. The self-fulfilling individuals tended to use strategies related to agentic (e.g., instrumental goal-pursuit), communal (e.g., social affiliation), and spiritual (e.g., religion) values when pursuing happiness.

Conclusion. These differences suggest that promoting positive emotions can positively influence a depressive-to-happy state as well as increasing life satisfaction. Moreover, the present study shows that pursuing happiness through strategies guided by agency, communion, and spirituality is related to a self-fulfilling experience described as high positive affect and low negative affect.

Epigenetic Modulation of Mood Disorders

BACKGROUND

Mood disorders are expressed in many heterogeneous forms, varying from anxiety to severe major clinical depression. The disorders are expressed in individual variety through manifestations governed by co-morbidities, symptom frequency, severity, and duration, and the effects of genes on phenotypes. The underlying etiologies of mood disorders consist of complex interactive operations of genetic and environmental factors. The notion of endophenotypes, which encompasses the markers of several underlying liabilities to the disorders, may facilitate efforts to detect and define, through staging, the genetic risks inherent to the extreme complexity of disease state.

AIMS

This review evaluates the role of genetic biomarkers in assisting clinical diagnosis, identification of risk factors, and treatment of mood disorders.

METHODS

Through a systematic assessment of studies investigating the epigenetic basis for mood disorders, the present review examines the interaction of genes and environment underlying the pathophysiology of these disorders.

RESULTS

The majority of research findings suggest that the notion of endophenotypes, which encompasses the markers of several underlying liabilities to the disorders, may facilitate efforts to detect and define, through staging, the genetic risks inherent to the extreme complexity of the disease states. Several strategies under development and refinement show the propensity for derivation of essential elements in the etiopathogenesis of the disorders affecting drug-efficacy, drug metabolism, and drug adverse effects, e.g., with regard to selective serotonin reuptake inhibitors. These include: transporter gene expression and genes encoding receptor systems, hypothalamic-pituitary-adrenal axis factors, neurotrophic factors, and inflammatory factors affecting neuroimmune function. Nevertheless, procedural considerations of pharmacogenetics presume the parallel investment of policies and regulations to withstand eventual attempts at misuse, thereby ensuring patient integrity.

CONCLUSIONS

Identification of genetic biomarkers facilitates choice of treatment, prediction of response, and prognosis of outcome over a wide spectrum of symptoms associated with affective states, thereby optimizing clinical practice procedures. Epigenetic regulation of primary brain signaling, e.g., serotonin and hypothalamic-pituitary-adrenal function, and factors governing their metabolism are necessary considerations. The participation of neurotrophic factors remains indispensable for neurogenesis, survival, and functional maintenance of brain systems.

Neurogenetics and Epigenetics in Impulsive Behaviour: Impact on Reward Circuitry

Adverse, unfavourable life conditions, particularly during early life stages and infancy, can lead to epigenetic regulation of genes involved in stress-response, behavioral disinhibition, and cognitive-emotional systems. Over time, the ultimate final outcome can be expressed through behaviors bedeviled by problems with impulse control, such as eating disorders, alcoholism, and indiscriminate social behavior. While many reward gene polymorphisms are involved in impulsive behaviors, a polymorphism by itself may not translate to the development of a particular behavioral disorder unless it is impacted by epigenetic effects. Brain-derived neurotrophic factor (BDNF) affects the development and integrity of the noradrenergic, dopaminergic, serotonergic, glutamatergic, and cholinergic neurotransmitter systems, and plasma levels of the neurotrophin are associated with both cognitive and aggressive impulsiveness. Epigenetic mechanisms associated with a multitude of environmental factors, including premature birth, low birth weight, prenatal tobacco exposure, non-intact family, young maternal age at birth of the target child, paternal history of antisocial behavior, and maternal depression, alter the developmental trajectories for several neuropsychiatric disorders. These mechanisms affect brain development and integrity at several levels that determine structure and function in resolving the final behavioral expressions.

Coexisting disorders and academic achievement among children with ADHD

OBJECTIVE

ADHD is a commonly diagnosed neuropsychological disorder among school-aged children with reported high rates of coexisting or comorbid disorders. As ADHD has been associated with academic underachievement, the current study examines this association in view of the presence of coexisting disorders. The purpose of the current study is to examine the relationship between the presence of coexisting disorders and academic achievement among children with ADHD using a large, nationally representative, and community-based sample.

METHOD

To achieve this purpose, the presence of coexisting disorders with ADHD and academic achievement are examined across time utilizing latent growth models.

RESULTS

Our results indicate an inverse relationship between the presence of coexisting disorders and academic achievement across time among children diagnosed with ADHD.

CONCLUSION

The authors conclude that practitioners must be concerned with the presence of coexisting disorders for children with ADHD with respect to academic achievement as well as other behavioral and psychological outcomes.

Affective status in relation to impulsive, motor and motivational symptoms: personality, development and physical exercise

The contributions of impulsive and risk-taking behaviour in depressive and bipolar disorders, motivational and motor behaviours in anhedonic and substance addictive states, and the factors, particularly distress and trauma, underlying the development of neuropathology in affective status are described from clinical, epidemiological and laboratory perspectives. In order to distinguish one case factor for biopsychological substrates of health, an array of self-reported characteristics, e.g., positive or negative affect, stress or energy, optimism, etc., that may be predictive or counterpredictive for the propensity for physical exercise and activity were analysed using a linear regression in twelve different studies. Several individual characteristics were found to be markedly and significantly predictive of the exercise propensity, i.e., positive affect, energy, health-seeking behaviour and character, while optimism was of lesser, though significant, importance. Several individual characteristics were found to be significantly counterpredictive: expression of BDI- and HAD-depression, major sleep problems and lack/negligence of health-seeking behaviour. The consequences of physical activity and exercise for both affective well-being, cognitive mobility and neurogenesis is noted, particularly with regard to developmental assets for younger individuals. Affective disorder states may be studied through analyses of personal characteristics that unfold predispositions for symptoms-profiles and biomarkers derived from properties of dysfunction, such as impulsiveness, temperament dimensions, anhedonia and 'over-sensitivity', whether interpersonal or to reward.

Affective personality as cognitive-emotional presymptom profiles regulatory for self-reported health predispositions

Three studies that examined the links between affective personality, as constructed from responses to the Positive Affect (PA) and Negative Affect (NA) Scale (PANAS), and individuals' self-report of self-esteem, intrinsic motivation and Beck's Depression Inventory (BDI) depression in high school students and persons in working occupations are described. Self-report estimations of several other neuropsychiatric and psychosocial variables including, the Uppsala Sleep Inventory (USI), the Hospital Anxiety and Depression (HAD) test, Dispositional optimism, Locus of control, the Subjective Stress Experience test (SSE) and the Stress-Energy (SE) test, were also derived. Marked effects due to affective personality type upon somatic and psychological stress, anxiety and depression, self-esteem, internal and external locus of control, optimism, stress and energy, intrinsic motivation, external regulation, identified regulation, major sleep problems, problems falling asleep, and psychophysiological problems were observed; levels of self-esteem, self-motivation and BDI-depression all produced substantial effects on health and well-being. Regression analyses indicated PA was predicted by dispositional optimism (thrice), energy (thrice), and intrinsic motivation, and counter predicted by depression (twice) and stress (twice); and NA by anxiety (twice), stress (twice), psychological stress, identified regulation, BDI depression and psychophysiological problems, and counter predicted by internal locus of control and self-esteem. BDI-depression was predicted by negative affect, major sleep problems and psychophysiological problems (Study III), self-esteem by dispositional optimism and energy, and counter predicted by anxiety, depression and stress (Study I), and intrinsic motivation by dispositional optimism, energy, PA and self-esteem (Study II). These convergent findings are interpreted from a perspective of the cognitive-emotional expressions underlying behavioural or presymptomatic profiles presenting predispositions for health or ill health.