Evolutionary Concepts of Mental Disorders—A Unifying Framework?

2017 ◽  
Author(s):  
Andreas Heinz
Keyword(s):  
Mental Disorders ◽  
Mental Disorder ◽  
Human Behavior ◽  
Learning Mechanisms ◽  
Evolutionary Theories ◽  
Evolutionary Concepts ◽  
Basic Learning

Dysfunction of basic learning mechanisms my best be understood within an evolutionary framework of human behavior. In this chapter, traditional evolutionary accounts of mental disorders are described and criticized, because they often have been based on a rather prejudiced view of non-European cultures and their supposed “primitiveness”. Such existing evolutionary theories and their pitfalls have to be kept in mind when developing a new understanding of mental disorder.

Basic Learning Mechanisms: Pavlovian Conditioning in Mental Disorders

2017 ◽  
Author(s):  
Andreas Heinz
Keyword(s):  
Mental Disorders ◽  
Mental Disorder ◽  
Pavlovian Conditioning ◽  
Instrumental Behavior ◽  
Psychotic Experiences ◽  
Learning Mechanisms ◽  
Addictive Disorders ◽  
Clinical Consequences ◽  
Basic Learning

The second chapter focuses on basic learning mechanisms and specifically on Pavlovian conditioning and its relevance for mental disorder. Pavlovian conditioning has been implicated in addictive disorders, but may also play a role in affective and psychotic experiences. Influences of Pavlovian cues on instrumental behavior are explained with respect to their clinical consequences.

How a Focus on Learning Mechanisms Can Change Our Understanding of Mental Disorders

2017 ◽  
Author(s):  
Andreas Heinz
Keyword(s):  
Decision Making ◽  
Mental Disorders ◽  
Human Behavior ◽  
Human Learning ◽  
Learning Mechanisms ◽  
Computational Approaches ◽  
Human Creativity

The last chapter summarizes the previous findings and suggests that focusing on learning mechanisms can help to appreciate the malleability and diversity of human behavior. It is suggested that dimensional and computational approaches can foster a new understanding of mental disorders and create classifications based on basic dimensions of human learning and decision making. This chapter emphasizes that a focus on learning mechanisms should help to reduce the stigma of mental disorders, as it emphasized human creativity and resilience when dealing with stressful situations.

Resolving the paradox of common, harmful, heritable mental disorders: Which evolutionary genetic models work best?

2006 ◽  
Vol 29 (4) ◽  
pp. 385-404 ◽  
Author(s):  
Matthew C. Keller ◽  
Geoffrey Miller
Keyword(s):  
Mental Disorders ◽  
Mental Disorder ◽  
Human Behavior ◽  
Behavior Genetics ◽  
Balancing Selection ◽  
Paternal Age ◽  
Heterozygote Advantage ◽  
Psychiatric Genetics ◽  
Apparent Paradox ◽  
Evolutionary Genetic

Given that natural selection is so powerful at optimizing complex adaptations, why does it seem unable to eliminate genes (susceptibility alleles) that predispose to common, harmful, heritable mental disorders, such as schizophrenia or bipolar disorder? We assess three leading explanations for this apparent paradox from evolutionary genetic theory: (1) ancestral neutrality (susceptibility alleles were not harmful among ancestors), (2) balancing selection (susceptibility alleles sometimes increased fitness), and (3) polygenic mutation-selection balance (mental disorders reflect the inevitable mutational load on the thousands of genes underlying human behavior). The first two explanations are commonly assumed in psychiatric genetics and Darwinian psychiatry, while mutation-selection has often been discounted. All three models can explain persistent genetic variance in some traits under some conditions, but the first two have serious problems in explaining human mental disorders. Ancestral neutrality fails to explain low mental disorder frequencies and requires implausibly small selection coefficients against mental disorders given the data on the reproductive costs and impairment of mental disorders. Balancing selection (including spatio-temporal variation in selection, heterozygote advantage, antagonistic pleiotropy, and frequency-dependent selection) tends to favor environmentally contingent adaptations (which would show no heritability) or high-frequency alleles (which psychiatric genetics would have already found). Only polygenic mutation-selection balance seems consistent with the data on mental disorder prevalence rates, fitness costs, the likely rarity of susceptibility alleles, and the increased risks of mental disorders with brain trauma, inbreeding, and paternal age. This evolutionary genetic framework for mental disorders has wide-ranging implications for psychology, psychiatry, behavior genetics, molecular genetics, and evolutionary approaches to studying human behavior.

Dimensional psychiatry: mental disorders as dysfunctions of basic learning mechanisms

2016 ◽  
Vol 123 (8) ◽  
pp. 809-821 ◽  
Author(s):  
Andreas Heinz ◽  
Florian Schlagenhauf ◽  
Anne Beck ◽  
Carolin Wackerhagen
Keyword(s):  
Mental Disorders ◽  
Learning Mechanisms ◽  
Basic Learning

It Is Time to Rename the DSM

2006 ◽  
Vol 8 (1) ◽  
pp. 61-67 ◽  
Author(s):  
Bruce A. Thyer
Keyword(s):  
Mental Disorders ◽  
Conduct Disorder ◽  
Mental Disorder ◽  
Psychosocial Factors ◽  
Human Behavior ◽  
Natural Science ◽  
A Priori ◽  
Dysfunctional Behavior ◽  
Mental Disturbance ◽  
Dsm Iv

Although the DSM purports to be a theoretical with respect to the etiology of mental disorders, its fundamental assumption that aberrant patterns of thought, emotion or behavior reflect mental disturbance is itself an unjustifiable a priori position. Within the DSM-IV-TR, the existence of compelling dysfunctional psychosocial etiological influences precludes the diagnosis of conduct disorder. Consistent with this precedent, the following principle needs to be expanded to virtually all the conditions found in the DSM: “Conditions reasonably attributable to psychosocial factors or medical conditions should not be considered mental disorders.” Following this principle could cause the very concept of mental disorder to evaporate, in favor of a nondualist perspective on explaining human behavior in favor of a consistently physicalistic one. This would promote the study of dysfunctional behavior as a legitimate field of natural science and not one of metaphysical enquiry.

A New Understanding of Mental Disorders

2017 ◽  
Author(s):  
Andreas Heinz
Keyword(s):  
Mental Disorders ◽  
Computational Models ◽  
Dimensional Approach ◽  
Learning Mechanisms ◽  
Ethical Considerations ◽  
Addictive Disorders ◽  
Human Decision ◽  
Computational Aspects ◽  
Definition Of ◽  
Basic Learning

For many psychiatric disorders, neurobiological findings do not help to diagnose a specific disease or to predict its outcome. This book suggests to take a new look at mental disorders by using computational models to better understand human decision making. It shows how such models can be applied to basic learning mechanisms that cut across established nosological boundaries of mental disorders. Such a computational and dimensional approach focuses on the malleability of human behavior and its biological underpinnings. The book argues that this computational and dimensional approach can help to promote and focus neurobiological research, however, it does not replace an anthropological understanding of clinical questions including the definition of mental disorders and ethical considerations. This is illustrated by describing the new understanding of mental disorders with respect to clinical and neuro-computational aspects of psychosis, affective and addictive disorders.

scholarly journals Impact of arthritis on the perceived need and use of mental healthcare among Canadians with mental disorders: nationally representative cross-sectional study

BMJ Open ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. e041371
Author(s):  
Alyssa Howren ◽  
J Antonio Aviña-Zubieta ◽  
Deborah Da Costa ◽  
Joseph H Puyat ◽  
Hui Xie ◽  
...  
Keyword(s):  
Mental Health ◽  
Mental Disorders ◽  
Mental Disorder ◽  
Clinical Care ◽  
Mental Healthcare ◽  
Cluster Sampling ◽  
Cross Sectional ◽  
Perceived Need ◽  
Mental Health Support ◽  
Health Support

ObjectiveTo evaluate the association between having arthritis and the perceived need for mental healthcare and use of mental health support among individuals with mental disorders.DesignA cross-sectional analysis using data from Canadian Community Health Survey—Mental Health (2012).SettingThe survey was administered across Canada’s 10 provinces using multistage cluster sampling.ParticipantsThe study sample consisted of individuals reporting depression, anxiety or bipolar disorder.Study variables and analysisThe explanatory variable was self-reported doctor-diagnosed arthritis, and outcomes were perceived need for mental healthcare and use of mental health support. We computed overall and gender-stratified multivariable binomial logistic regression models adjusted for age, gender, race/ethnicity, income and geographical region.ResultsAmong 1774 individuals with a mental disorder in the study sample, 436 (20.4%) reported having arthritis. Arthritis was associated with increased odds of having a perceived need for mental healthcare (adjusted OR (aOR) 1.71, 95% CI 1.06 to 2.77). In the gender-stratified models, this association was increased among men (aOR 2.69, 95% CI 1.32 to 5.49) but not women (aOR 1.48, 95% CI 0.78 to 2.82). Evaluation of the association between arthritis and use of mental health support resulted in an aOR of 1.50 (95% CI 0.89 to 2.51). Individuals with arthritis tended to use medications and professional services as opposed to non-professional support.ConclusionComorbid arthritis among individuals with a mental disorder was associated with an increased perceived need for mental healthcare, especially in men, underscoring the importance of understanding the role of masculinity in health seeking. Assessing the mental health of patients with arthritis continues to be essential for clinical care.

scholarly journals A computational reward learning account of social media engagement

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Björn Lindström ◽  
Martin Bellander ◽  
David T. Schultner ◽  
Allen Chang ◽  
Philippe N. Tobler ◽  
...  
Keyword(s):  
Social Media ◽  
Human Behavior ◽  
Computational Models ◽  
Average Rate ◽  
Human Life ◽  
Modern Human ◽  
Reward Learning ◽  
Learning Mechanisms ◽  
Social Media Engagement ◽  
Social Rewards

AbstractSocial media has become a modern arena for human life, with billions of daily users worldwide. The intense popularity of social media is often attributed to a psychological need for social rewards (likes), portraying the online world as a Skinner Box for the modern human. Yet despite such portrayals, empirical evidence for social media engagement as reward-based behavior remains scant. Here, we apply a computational approach to directly test whether reward learning mechanisms contribute to social media behavior. We analyze over one million posts from over 4000 individuals on multiple social media platforms, using computational models based on reinforcement learning theory. Our results consistently show that human behavior on social media conforms qualitatively and quantitatively to the principles of reward learning. Specifically, social media users spaced their posts to maximize the average rate of accrued social rewards, in a manner subject to both the effort cost of posting and the opportunity cost of inaction. Results further reveal meaningful individual difference profiles in social reward learning on social media. Finally, an online experiment (n = 176), mimicking key aspects of social media, verifies that social rewards causally influence behavior as posited by our computational account. Together, these findings support a reward learning account of social media engagement and offer new insights into this emergent mode of modern human behavior.

Tobacco smoking and mental disorders in Australian adolescents

2021 ◽  
pp. 000486742110096
Author(s):  
David Lawrence ◽  
Sarah E Johnson ◽  
Francis Mitrou ◽  
Sharon Lawn ◽  
Michael Sawyer
Keyword(s):  
Mental Health ◽  
Mental Disorders ◽  
Mental Disorder ◽  
Tobacco Smoking ◽  
Mental Health Problems ◽  
Health Problems ◽  
Major Depressive ◽  
Current Smoking ◽  
Self Harm ◽  
Current Tobacco

Objectives: This study aimed to (1) examine the strength of the association between mental disorders/mental health problems, risk behaviours and tobacco smoking among Australian adolescents, (2) compare rates of tobacco smoking among Australian adolescents with major depressive disorder, attention-deficit/hyperactivity disorder and/or conduct disorder in 2013/14 vs 1998, and (3) identify the extent to which an association between tobacco smoking and mental health problems among adolescents can be attributed to non-mental health risk factors. Methods: The study utilised data from the first (1998) and second (2013/14) child and adolescent components of the National Surveys of Mental Health and Wellbeing. Both surveys identified nationally representative samples of Australian young people aged 4–17 years, living in private dwellings. Information was collected from parents and 13- to 17-year-olds about mental disorders, mental health problems, risk behaviours and tobacco smoking. Results: In the 2013/14 survey, the rate of current tobacco smoking among those with a mental disorder was 20% compared to 5% in those without a mental disorder. Rates were highest for young people with conduct disorder (50%), major depressive disorder (24%) and anxiety disorders (19%). In 2013/14, 38% of current tobacco smokers had a mental disorder and 32% reported self-harm and/or suicidal ideation vs 10% and 5%, respectively, among adolescents who had never smoked. Females with mental disorders or reporting self-harm or suicidal ideation had higher rates of current smoking than males. Other significant factors associated with current smoking included school-related problems, binge eating and having had more than one sexual partner. Conclusion: While smoking rates in 13- to 17-year-olds with mental disorders had declined since 1998, the strength of the association between mental disorders and smoking had increased, especially among females. Our findings highlight the need to address the tobacco smoking among adolescents with mental disorders, particularly females.

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