Biological basis of personality

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The biological basis of personality is the collection of brain systems and mechanisms that underlie human personality. Human neurobiology, especially as it relates to complex traits and behaviors, is not well understood, but research into the neuroanatomical and functional underpinnings of personality are an active field of research. Animal models of behavior, molecular biology, and brain imaging techniques have provided some insight into human personality, especially trait theories.

Much of the current understanding of personality from a neurobiological perspective places an emphasis on the biochemistry of the behavioral systems of reward, motivation, and punishment. This has led to a few biologically based personality theories such as Eysenck's three factor model of personality, Grey's reinforcement sensitivity theory (RST), and Cloninger's model of personality. The Big Five model of personality is not biologically based; yet some research in the differences in brain structures provided biological support also for this model.

Defining personality in a biological context

Personality can be defined as a set of characteristics or traits that drive individual differences in human behavior. From a biological perspective, these traits can be traced back to brain structures and neural mechanisms. However, this definition and theory of biological basis is not universally accepted. There are many conflicting theories of personality in the fields of psychology, psychiatry, philosophy, and neuroscience. A few examples of this are the nature vs. nurture debate and how the idea of a 'soul' fits into biological theories of personality.

History of biology-based personality research

Hans Eysenck

Since the time of the ancient Greeks, humankind has attempted to explain personality through spiritual beliefs, philosophy, and psychology. Historically, studies of personality have traditionally come from the social sciences and humanities, but in the past two decades neuroscience has begun to be more influential in the understanding of human personality.

However, the most cited and influential figures in publishing the first biology-based personality theories are Hans Eysenck and Jeffrey Alan Gray. Eysenck used both behavioral and psychophysiological methodologies to test and develop his theories. He published a book in 1947 called Dimensions of Personality, describing the personality dimensions of extraversion and neuroticism. Gray, a student of Eysenck, studied personality traits as individual differences in sensitivity to rewarding and punishing stimuli. The significance of Gray's work and theories was his use of biology to define behavior, which stimulated a lot of subsequent research.

In 1951, Hans Eysenck and Donald Prell published an experiment in which identical (monozygotic) and fraternal (dizygotic) twins, ages 11 and 12, were tested for neuroticism. It is described in detail in an article published in the Journal of Mental Science in which Eysenck and Prell concluded that "The factor of neuroticism is not a statistical artifact, but constitutes a biological unit which is inherited as a whole ... neurotic predisposition is to a large extent hereditarily determined." The study concluded that the neuroticism trait was a result of up to eighty percent of genetics. There was a stronger correlation among identical twins rather than fraternal twins.

The idea of biology-based personality research is relatively new, but growing in interest and number of publications. In August 2004, there was a conference specifically on the topic, called The Biological Basis of Personality and Individual Differences. This allowed for presenting and sharing of ideas between psychologists, psychiatrists, molecular geneticists, and neuroscientists, and eventually gave birth to the book under the same title. The book is a collection of current research (as of 2006) in the field contributed by many authors and edited by Turhan Canli. Recently, psychology professor Colin G. DeYoung has even named the idea as the field of "Personality Neuroscience." Furthermore, a journal devoted to cultivating research investigating the neurobiological basis of personality has recently been established and is called "Personality Neuroscience."

Personality theories with biological basis

There are many theories of personality that centre on the identification of a set of traits that encompass human personality. Few however, are biologically based. This section will describe some theories of personality that have a biological basis.

Eysenck's three-factor model of personality

Eysenck's three-factor model of personality was a causal theory of personality based on activation of reticular formation and limbic system. The reticular formation is a region in the brainstem that is involved in mediating arousal and consciousness. The limbic system is involved in mediating emotion, behavior, motivation, and long-term memory.

1. Extraversion (E) – degree to which people are outgoing and are interactive with people, which is mediated by the activation of the reticular formation.
2. Neuroticism (N) – degree of emotional instability, which is associated with the limbic system.
3. Psychoticism (P) – degree of aggression and interpersonal hostility.

Gray's reinforcement sensitivity theory

Gray's reinforcement sensitivity theory (RST) is based on the idea that there are three brain systems that all differently respond to rewarding and punishing stimuli.

1. Fight-flight-freeze system (FFFS) – mediates the emotion of fear (not anxiety) and active avoidance of dangerous situations. The personality traits associated with this system is fear-proneness and avoidance.
2. Behavioral inhibition system (BIS) – mediates the emotion of anxiety and cautious risk-assessment behavior when entering dangerous situations due to conflicting goals. The personality traits associated with this system is worry-proneness and anxiety.
3. Behavioral approach system (BAS) – mediates the emotion of 'anticipatory pleasure,' resulting from reactions to desirable stimuli. The personality traits associated with this system are optimism, reward-orientation, and impulsivity.

Cloninger's biological dimensions of personality

Cloninger model of personality

This model of personality is based on the idea that different responses to punishing, rewarding, and novel stimuli the main characteristics of the human mind is caused by an interaction of the three dimensions below:

1. Novelty Seeking (NS) – degree to which people are impulsive, correlated with low dopamine activity.
2. Harm Avoidance (HA) – degree to which people are anxious, correlated with high serotonin activity.
3. Reward Dependence (RD) – degree to which people are approval seeking, correlated with low norepinephrine activity.

Five factor model of personality

The five factor model (also known as the Big Five) is a widely used personality assessment that describes five core traits that a person possesses:

1. Openness – degree to which people enjoy experiencing new stimuli
2. Conscientiousness – degree to which people are dutiful and goal-oriented
3. Extraversion – degree to which people seek stimuli outside of themselves
4. Agreeableness – degree to which people aim to cooperate and please others
5. Neuroticism – degree to which people are emotionally unstable

There is large body of research relating the Big Five traits to individual differences in the brain's structure and function, as measured by MRI-based techniques. A selection of these findings are outlined in the "Brain imaging basis of personality" section below.

Two factor model of personality

A higher-order factor structure can be derived from the Big Five traits, as these traits have often been found to be correlated. Agreeableness, Conscientiousness, and Neuroticism (reversed) can be distilled into a single factor α, or the Stability factor. On the other hand, Extraversion and Openness can be distilled into a single factor β, or the Plasticity factor. These two meta-traits have been shown to be significantly heritable using behavior genetic analysis, which suggests a neurobiological basis that is unique and specific to these meta-traits. Indeed, a growing body of evidence demonstrates that serotonin is associated with Stability and dopamine is associated with Plasticity.

Experimental techniques

There are many experimental techniques for measuring the biology of the brain, but there are five main methods used to investigate the biological basis of personality. The biological data from these methods are commonly correlated with personality traits. These personality traits are often determined by personality questionnaires. However, personality questionnaires may be biased because they are self-reported. As a result, scientists emphasize using several different measures of personality, rather than solely self-reported measures of personality. For example, another measure of personality traits is observation of behavior. Both humans and animals have been observed to measure personality traits, but animals are particularly useful for studying the long-term behavioral-biological relationship of personality.

Another interesting method that has become more sophisticated and affordable to researchers is the method of whole genome expression analysis. This method involves collecting data for a large number of genes simultaneously which provides many advantages in studying personality. In an article written by Alison M. Bell and Nadia Aubin-Horth, they describe the advantages very clearly by stating, "For one, it is probable that the genetic basis of personality is polygenic, so it makes sense to simultaneously study many genes. In addition, gene products rarely act alone. Instead, they perform their function by interacting together in pathways and networks. As a result, the molecular changes that characterize a phenotype are frequently not based on a single marker or gene, but rather on an entire pathway. Whole genome expression profiling therefore has the potential to reveal new candidates genes and pathways."

Method	Function	Significance
Electroencephalography (EEG)	This method measures electrical activity on the surface of the brain through the scalp, and has the high temporal resolution.	Before the advent of brain imaging technology, the only method to measure brain activity was electroencephalography (EEG).
Brain Imaging	Brain imaging can refer to either structural or functional imaging. Structural imaging allows for analysis using structural characteristics of the brain, whereas functional imaging involves measuring brain activity. Structural imaging of the brain can be accomplished by using Magnetic Resonance Imaging (MRI). Examples of functional imaging methods include Positron Emission Tomography (PET) and functional MRI (fMRI). PET scans measure the metabolism associated with brain activity, and fMRI measures the flow of blood in the brain, which reflects local brain activity. MRI has particularly high spatial resolution and is entirely non-invasive, whereas PET scans require the injection of radioactive tracers.	Brain imaging has catalyzed research of the neurobiological correlates of personality.
Molecular genetics	This method is used to analyze a gene-trait link, by measuring the structure and function of genes in the brain.	The use of molecular genetics in biology-based personality research is expected to grow.
Molecular assays	This method is used to analyze the amount of psychoactive substances, such as hormones and neurotransmitters.	Together, these two methods can specifically quantify, define, and manipulate the effects of brain molecules on behavior and personality traits. This has great clinical significance for treatment of personality disorders.
Pharmacological Manipulation	This method is used to alter the levels of biochemicals, and observe the effects on behavior.

Genetic and molecular correlations to personality

Neurotransmitters

Dopamine and Serotonin pathways

The biology-based personality theories (discussed below) are based on correlating personality traits with behavioral systems related to motivation, reward, and punishment. On a broad level, this involves the autonomic nervous system, fear-processing circuits in the amygdala, the reward pathway from the ventral tegmental area (VTA) to the nucleus accumbens and prefrontal cortex. All of these circuits heavily rely on neurotransmitters and their precursors, but there has been the most research support for dopamine and serotonin pathways:

• Dopamine: Dopamine is a monoamine neurotransmitter that has been found to promote exploratory behavior. Dopaminergic pathways have been specifically correlated with the extraversion trait of the Five Factor Model of Personality. The monoamine oxidase (MAO) enzyme has a preferential affinity for dopamine, and its levels are inversely correlated with sensation seeking.
• Serotonin: Serotonin is a monoamine neurotransmitter, and has been found to promote avoidance behavior through inhibitory pathways. Specifically, serotonin has been associated with Neuroticism, Agreeableness, and Conscientiousness (traits defined by the Five Factor Model of Personality).

Genes

Previous studies show that genes account for at most 50 percent of a given trait. However, it is widely accepted that variance in gene sequence affect behavior, and genes are a significant risk factor for personality disorders. With the growing interest in using molecular genetics in tracing the biological basis of personality, there may be more gene-trait links found in the future.

Varying polymorphisms and sequence repeats in the gene for dopamine receptor D4 and serotonin transporter gene 5-HTTLPR, have both been found to influence the extraversion trait in adults. Specifically, study participants with at least one copy of the 7-repeat variant of the dopamine receptor D4 gene had higher scores of self-reported extraversion. This suggests that dopamine and serotonin interact to regulate the conflicting behavioral traits of careless exploration vs. cautious inhibition.

Synaptic plasticity

Synaptic plasticity refers to the ability of neurons to strengthen or weaken the connections between them. According to Hebbian theory, these connections are strengthened and maintained through repeated stimulation between neurons. Specifically, there is an emphasis on long-term potentiation (LTP), which is the prolonged strengthening of synaptic connections that facilitate learning from experience.

On a larger scale, there are many pathways and brain regions that are interdependent and contribute to a cohesive, stable personality. For example, the amygdala and hippocampus of the limbic system mediate emotional intensity and consolidate memory of these experiences. But the basic mechanism by which these pathways and brain regions perform these functions, is synaptic plasticity. Ultimately, it boils down to this feature of neurons that allows the brain to learn from repeated experiences, retain memories, and ultimately maintain personality. Joseph LeDoux, an award-winning neuroscientist, asserts that although humans share the same brain systems, it is the unique wiring of neurons that is different in each person and makes their personality.

Brain imaging basis of personality

Over the past two decades, structural magnetic resonance imaging (sMRI) and functional magnetic resonance imaging (fMRI) techniques have been used to study associations between neural activations in the brain and personality traits and other cognitive, social, and emotional processes that characterize personality. Using MRI-based methods for such studies has become increasingly popular due to the non-invasive nature of MRI and the high resolution of MRI.

Structural magnetic resonance imaging

The use of structural magnetic resonance imaging (sMRI) to understand the neurobiological basis of personality and sociocognitive functioning involves assessing the relationship between individual differences in these factors and individual differences in measures of brain structure, such as gray matter volume, cortical thickness, or structural integrity of white matter tracts.

Studies have shown that brain volume is meaningfully correlated with four of the Big Five personality measures. Extraversion was associated with increased volume of medial orbitofrontal cortex, a region associated with processing reward-related stimuli. Conscientiousness was associated with increased volume in the lateral prefrontal cortex, a region involved in planning and the voluntary control of behavior. Agreeableness was associated with increased volume in regions involved in mentalizing, which is the ability to infer the intentions and mental states of other individuals. Neuroticism was associated with increased volume of brain regions associated with threat, punishment, and negative emotions. Openness/Intellect was not significantly correlated with the volume of any brain structures. In another study, neuroticism was negatively correlated with the gray matter volume of the right amygdala, whereas extraversion was positively correlated with gray matter volume of the left amygdala. A separate study also reported a significant association between neuroticism scores and gray matter volume of the left amygdala. In one MRI study, Novelty Seeking correlated with increased grey matter volume in regions of the cingulate cortex, Harm Avoidance correlated with decreased grey matter volume in the orbitofrontal, occipital, and parietal cortex. Reward Dependence correlated with decreased grey matter volume in the caudate nucleus.

A separate but similar line of research has used diffusion tensor imaging to measure the structural integrity of white matter in the brain. One study has shown that neuroticism is negatively correlated with the structural integrity of white matter tracts that connect various brain regions, such as the prefrontal cortex, parietal cortex, amygdala, and other regions in the subcortex. On the other hand, Openness and Agreeableness are positively associated with the structural integrity of these white matter tracts. Openness was also positively associated with the structural integrity of white matter interconnecting dorsolateral prefrontal cortex in both hemispheres.

Functional magnetic resonance imaging

Functional magnetic resonance imaging (fMRI) involves the indirect measurement of neural activity by measuring disturbances in local magnetic fields in the brain. These local disturbances are linked to differential amounts of blood flow to the brain, which is linked to neural activity. Early work using fMRI has studied whether individual differences in personality traits and sociocognitive functioning are associated with individual differences in neural activations in certain brain regions during certain tasks. Such studies have demonstrated associations between single brain regions’ neural responses to certain tasks and individual differences in a wide range of sociocognitive functioning, such as approach/avoidance behavior, sensitivity to rejection, conceptions of the self, and susceptibility to persuasive messages. A small collection of fMRI studies have also demonstrated a significant relationship between brain responses to certain tasks and personality survey measures, such as extraversion and neuroticism.

Over time, neuroscience researchers have recognized that brain regions do not operate in isolation. In fact, the synchronization of firing rates of neurons across different brain regions helps mediate the integration and processing of information across the brain. Thus, studies relating neural activation in single regions to personality measures and associated sociocognitive functioning ignore information about how personality and sociocognitive functioning relate to neural activations across multiple regions in the brain. For example, it is unlikely that neural activation in a single brain region is unilaterally associated with individual differences in personality measures, such as the tendency to down-regulate negative emotions. However, the functional connectivity, or the synchronization of neural activity, between two brain regions can be related to individual differences in personality and sociocognitive functioning. For example, one study found that in an emotion regulation task, coupling of neural responses in the amygdala and the prefrontal cortex was significantly associated with more successful regulation of negative emotions. Other studies shown that neuroticism is associated with relatively low functional connectivity between amygdala and anterior cingulate cortex during a variety of tasks, such as viewing negative emotional stimuli and during a classical conditioning reward task.

Resting-state functional connectivity

Functional connectivity can also be measured at rest, during which individuals are not explicitly engaged in any task. These resting-state functional connectivities can also be related to personality measures and other sociocognitive functioning. For instance, one study found that functional connectivity patterns originating from the amygdala are predictive of neuroticism and extraversion scores. However, personality measures and sociocognitive functioning are not subserved solely by the functional connectivity between two given brain regions. Indeed, examining functional connectivity across the brain may shed more light on the neurobiological basis of personality and sociocognitive functioning. For example, a recent line of research has demonstrated that individual differences in functional connectomes, which are characterized by patterns of spontaneous synchronization of neural activations across the entire brain, are predictive of individual differences in personality and sociocognitive functioning, such as openness to experience, fluid intelligence, and trait levels of paranoia. The use of functional connectomes to predict individual differences is known as “functional connectome fingerprinting” and allows researcher to construct models of personality and sociocognitive functioning based on neural activity across the whole brain rather than within single regions (if using neural activations) or single pairs of regions (if using functional connectivity).

Graph theory-based analysis

Functional connectomes can be distilled into constituent intrinsic brain networks that are present during sleep, at rest, and during tasks. These brain networks can also reliably be mapped onto cognitive systems. The default mode network, for example, is composed of regions such as the medial prefrontal cortex, angular gyrus, temporoparietal junction, and the hippocampus, to name a few. One study has shown that Extraversion and Agreeableness are positively correlated with overall neural activity in the default mode network. Assessing the relationship between neural activity in brain networks and personality traits is an important first step for identifying where the neurobiological basis of personality traits may be localized. However, this approach does not offer a complete mechanistic explanation of how and why individual differences in these brain networks are related to individual differences in personality. To address this gap, neuroscience researchers have begun to leverage graph theoretical approaches to better understand characteristics of these brain networks, such as their assortativity, efficiency, and modularity. For example, one study has demonstrated that individual differences in anxiety-related harm avoidance behavior was associated with relatively low efficiency (i.e., high path length) in the insular-opercular brain network at rest. This finding suggests that trait anxiety may be associated with relatively slow and inefficient transfer of information within the insular-opercular brain network. Another study used a graph theoretical approach to demonstrate that high trait impulsivity was associated with relatively high modularity of resting-state brain networks, such that brain networks exhibited relatively high within-system density of functional connectivity but relatively low between-system density of functional connectivity. A separate study has also demonstrated that high Conscientiousness is associated with high local clustering and high betweenness centrality within the default mode network and the fronto-parietal network (FPN). Given the role of the FPN in cognitive control, these findings suggest that people high on Conscientiousness may exhibit higher cognitive control. Furthermore, heightened interconnectivity within the DMN also provides convergent evidence that highly conscientious individuals may be adept at high-level cognitive tasks, such as complex planning, given that the DMN is strongly associated with high-level executive function and working memory.

Reinforcement sensitivity theory

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https://en.wikipedia.org/wiki/Reinforcement_sensitivity_theory

Reinforcement sensitivity theory (RST) proposes three brain-behavioral systems that underlie individual differences in sensitivity to reward, punishment, and motivation. While not originally defined as a theory of personality, the RST has been used to study and predict anxiety, impulsivity, and extraversion. The theory evolved from Gray's biopsychological theory of personality to incorporate findings from a number of areas in psychology and neuroscience, culminating in a major revision in 2000. The revised theory distinguishes between fear and anxiety and proposes functionally related subsystems. Measures of RST have not been widely adapted to reflect the revised theory due to disagreement over related versus independent subsystems. Despite this controversy, RST informed the study of anxiety disorders in clinical settings and continues to be used today to study and predict work performance. RST, a continuously evolving paradigm, is the subject of multiple areas of contemporary psychological enquiry.

Origins and evolution of the theory

Gray's biopsychological theory of personality was informed by his earlier studies with Mowrer on reward, punishment, and motivation and Hans Eysenck’s study of the biology of personality traits. Eysenck linked Extraversion to activation of the Ascending Reticular Activation System (ARAS), an area of the brain which regulates sleep and arousal transitions.

Eysenck's two original personality factors, Neuroticism and Extraversion, were derived from the same lexical paradigm used by other researchers (e.g., Gordon Allport, Raymond Cattell) to delineate the structure of personality. Eysenck’s Extraversion-Arousal Hypothesis states that under low stimulation conditions, introverts (defined as low in Extraversion) will be more highly aroused than extraverts; however, under high stimulation, introverts may become over-aroused, which will feedback within the ARAS and result in decreases in arousal. Alternatively, extraverts tend to show greater increases in arousal under high stimulation. Eysenck also studied the relationship between neuroticism and activation of the limbic system using classical emotional conditioning models. His theory focused more on anxiety as a disorder than a personality trait. Eysenck’s theory predicts that introverts are more likely to develop anxiety disorders because they show higher neuroticism and stronger emotional conditioning responses under high arousal. His theory was criticized because introverts often show the opposite pattern, weaker classical conditioning under high arousal, and some supporting data confounded personality traits with time of day.

Gray's biopsychological theory: behavioral activation and inhibition systems

Unlike Eysenck, Gray believed that personality traits and disorders could not be explained by classical conditioning alone. Gray proposed the Biopsychological Theory of personality in 1970 based on extensive animal research. His theory emphasized the relationship between personality and sensitivity to reinforcement (i.e. reward and punishment). Eysenck’s theory emphasized Extraversion, Neuroticism, and arousal, while Gray’s theory emphasized Impulsivity, Anxiety, approach motivation, and avoidance motivation.

Gray's model of personality was based on three hypothesized brain systems:

Behavioral activation system (BAS)

• The BAS includes brain regions involved in regulating arousal: cerebral cortex, thalamus, and striatum. The system is responsive to conditioned and unconditioned reward cues. BAS regulates approach behaviors and is referred to as the reward system. In general, individuals with a more active BAS tend to be more impulsive and may have difficulty inhibiting their behavior when approaching a goal.

Behavioral inhibition system (BIS)

• The BIS also includes brain regions involved in regulating arousal: the brain stem, and neocortical projections to the frontal lobe. BIS is responsive to punishment, novelty, uncertainty, and non-rewarding stimuli. BIS regulates avoidance behaviors and is often referred to as the punishment system. Individuals with more active BIS may be vulnerable to negative emotions, including frustration, anxiety, fear, and sadness.

Fight/flight system (FFS)

• The FFS mediates reactions of rage and panic, flight versus fight, and is sensitive to unconditioned aversive stimuli. FFS is often referred to as the threat system.

According to Gray, personality traits are associated with individual differences in the strengths of BAS (approach motivation) and BIS (avoidance motivation) systems. As it is defined for the remainder of the article, higher BAS/BIS refers to greater activation of that system.

Measures

High BAS is generally associated with high extraversion, low neuroticism, and trait impulsivity, while high BIS is associated with low extraversion, high neuroticism, and trait anxiety. In addition to predicting trait standings, high BAS is associated with higher positive affect in response to reward, while high BIS is associated with higher negative affect in response to punishment. Studies in Gray’s laboratory supported his prediction that extraverts, higher in BAS and lower in BIS than introverts, are more sensitive to rewards, experience higher levels of positive affect, and learn faster under rewarding conditions.

The most widely used measures of the approach (BAS) and avoidance (BIS) systems are the BIS/BAS scales developed by Carver and White in 1994. The Generalized Reward and Punishment Expectancies Scales (GRAPES) were also used to operationalize BIS and BAS. Both self-report measures (listed above) and behavioral measures (such as affective modulation of the eyeblink startle response) have been used to test predictions and provide mixed support for Gray’s theory.

Critique

These measures were constructed under the assumption that BIS, BAS and associated traits Anxiety and Impulsivity are independent. In contrast, Gray first described BIS and BAS as opposing systems with bidirectional inhibitory links in animal models. Thus, empirical results that claimed to falsify the theory may have relied on faulty predictions for independent, non-interacting systems. Gray’s theory was also criticized because the boundary between FFS (threat response system) and BIS (punishment system) was difficult to define empirically, akin to differentiating between fear and anxiety. Matthews and Gilliland proposed separate cognitive systems underlying fear and anxiety and emphasized the need to study these systems outside of animal models. These critiques led to a major revision and renaming of the theory in 2000. The Reinforcement Sensitivity Theory (RST) redefined the three systems underlying anxiety, impulsivity, motivation, and reinforcement learning.

Reinforcement sensitivity theory

Reinforcement sensitivity theory is one of the major biological models of individual differences in emotion, motivation, and learning. The theory distinguishes between fear and anxiety, and links reinforcement processes to personality.

Behavioral activation system (BAS)

• Proposed to facilitate reactions to all appetitive/rewarding stimuli and regulates approach behavior.

Behavioral inhibition system (BIS)

• Proposed to mediate conflict both within and between FFFS and BAS: FFFS (avoidance) and BAS (approach) (or BAS-BAS, FFFS-FFFS). These conflicts underlie anxiety.

Fight-flight-freeze system (FFFS)

• Proposed to mediate reactions to all aversive/ punishing stimuli (conditioned and unconditioned), regulates avoidance behavior, and underlies fear.

Improved measures

The fight-flight-freeze system (FFFS) was expanded to include all aversive/punishment stimuli, conditioned and unconditioned. Similarly, the Behavioral Activation System (BAS) was expanded to include all appetitive/reward stimuli. The Behavioral Inhibition System (BIS) was defined as a conflict system activated whenever both BAS and FFFS are activated together or multiple inputs compete within the systems, thereby producing anxiety. If the systems are assumed to be functionally related, the effect of a given stimulus is dependent upon the strength of that stimulus, reactivity in the activated system, and strength of the competing system. Thus, for a reward, the behavior output from BAS is dependent on the strength of the reward, activation of the BAS, and inhibition strength of BIS. For example, if a reward outweighs a threat, the BIS should excite the BAS and inhibit the FFFS, which will likely result in approach behavior.

The new RST distinguishes the subsystems underlying anxiety and fear. The FFFS is associated with fear and the BIS is associated with anxiety. This distinction is still debated, especially in clinical settings wherein BIS scores are sensitive to fear/panic-reducing, not anxiety-reducing treatments. Furthermore, the possibility of anxiety's triggering panic and vice versa supports a model of the BIS and the FFFS in which the two are not causally independent. Conflicting results regarding the relationship between fear and anxiety may reflect measures which were not updated to reflect the functionally dependent systems of the new RST. A review by Perkins and Corr (2006) found that the BIS as measured in Carver, 1994 scales and similar constructs tap into the FFFS (which fear responses) and not the true BIS (which underlies anxiety). These definitions were not updated to reflect the revised RST model. D.C. Blanchard and colleagues (2001) created vignettes with response options that modeled rodent reactions to anxiety (the BIS, used ambiguous/partially threatening stimuli) and fear (the FFFS, used pure threat situations) to study these constructs in humans. These behavioroid scales ask: "What would you do if (insert scenario inducing fear or anxiety)?" Response options accurately reflect the revised RST, but have not been widely tested or applied.

Separable and joint subsystems hypotheses

The revised RST reflects functional dependence of the systems; however, there are two competing hypotheses developed for testing RST predictions. The separable systems hypothesis (SSH) is defined by two independent systems, reward and punishment. Independence implies that reactivity to rewards should be approximately equal across all levels of punishment, and reactivity to punishment should be equal across all levels of reward. Thus, rewarding stimuli may activate the BAS, without exerting effects on the BIS or the FFFS. The SSH is proposed to operate in extreme circumstances, within individuals with highly reactive systems and/or experimental conditions that only present rewarding or punishing stimuli. The separable subsystems hypothesis has been applied successfully to study reinforcement learning and motivation in clinical populations. Alternatively, the joint subsystems hypothesis (JSH), in accordance with Gray’s original animal models and the revised RST, states that reward and punishment exert combined effects in the BAS and the FFFS, while the BIS resolves conflict within and between the systems. The reward and punishment systems are defined as dependent, such that reward activation (the BAS) both increases responses to appetitive stimuli and decreases responses to aversive stimuli. The joint subsystems hypothesis is most applicable in real-world contexts that contain mixed stimuli: strong, weak, punishment, and reward.

In a recent review on RST measurement, authors distinguished between dependent system inputs and dependent behavioral outputs. The BAS, FFFS, and BIS are dependent systems (and current research attempts to define under what task situations and to what degree they interact). A rewarding stimulus may activate all three systems to some extent such that high scores on a BAS-related behavioral trait, for example, may include high BAS, low FFFS, and low BIS activations. Corr and colleagues tested separate and joint subsystems predictions against each other. Their results support the joint subsystems hypothesis: high anxiety individuals reacted more strongly to punishment cues, and this effect was stronger in jointly low impulsive, high anxiety individuals. Pickering used regression and neural network models to show that patterns of inputs from the BAS and the BIS/FFFS generate a large range of outcomes that support the JSH (all three system activations were needed to determine best fit for behavioral output). There is now pharmacological evidence to support dependence of these systems, notably serotonergic (5-HT) modulation of the dopamine pathway.

As mentioned previously, these complex, dependent systems are not reflected in questionnaires, such as Carver’s BIS/BAS, that are oftentimes used to test RST predictions. A variety of disparate experimental findings, originally viewed as inconsistent with Gray’s Biopsychological theory, are more consistent with RST joint systems hypothesis.

Renaming impulsivity

Smillie, Pickering, and Jackson (2006) advocated for renaming trait Impulsivity, which is associated with BAS in the revised RST, Extraversion. Empirical tests find that Extraversion is a better predictor than Impulsivity of reward learning. Some components of the BAS and reward learning are better explained by association with Extraversion, especially high positive affect, while the cortical arousal loop originally proposed to underlie BAS in Gray's theory is still tied most closely with Impulsivity.  Regardless of the trait label, the authors point out that the RST did not develop as a theory to explain the personality constructs, Anxiety and Impulsivity. Rather, the RST predicts associations between reinforcement sensitivity, motivation, and behavior.

Applications

Workplace performance

Carver and White's 1994 BIS/BAS scales were used to support the finding that employees high in BIS (avoidance motivation) show lower work performance and engagement, while employees high in BAS (approach motivation) show higher performance in rewarding situations only. These measures are not based on the revised RST, and may confound fear and anxiety. Alternatively, the Jackson 5 has recently been validated as a measure of the revised RST and shows convergent validity with measures of fear and anxiety. The proposed fear (FFFS) subscale is associated with avoidance behaviors (example item: 'If approached by a suspicious stranger, I run away') while the anxiety (BIS) subscale includes social situations wherein reward and punishment stimuli result in conflict between approach and avoidance motivations (example item: 'I prefer to work on projects where I can prove my abilities to others'). Clark and Loxton (2011) used the Jackson 5 to investigate mediators between fear, psychological acceptance, and work engagement. Self-reported fear, not anxiety, best predicted psychological acceptance, and lower work performance in turn. Thus, current research aims to apply measures based on the revised RST to more accurately clarify relations between fear, anxiety, and job performance.

Clinical research

The BIS and BAS sensitivities are associated with individual differences in positive and negative affect. This association has been largely explored in clinical populations exhibiting extreme scores on BIS/BAS measures. In their 2009 review, Bijttebier and colleagues summarized studies showing that high BIS sensitivity is present in individuals with anxiety, depression, and anorexia nervosa, whereas low BIS sensitivity is associated with psychopathy. Extremely high BAS sensitivity is characteristic of individuals with bipolar disorder, ADHD, and bulimia, while extremely low BAS often characterizes individuals with anhedonic depression. BIS and BAS may differentiate, as illustrated above, between sub-types of eating disorders and depression. These findings are correlational, and causal mechanisms were not directly tested. Researchers in fields ranging from cognitive science to self-regulation and attention are using the RST to investigate causal mechanisms that underlie the relationship between personality traits and psychopathology.

Learned industriousness

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Learned_industriousness

Learned industriousness is a behaviorally rooted theory developed by Robert Eisenberger to explain the differences in general work effort among people of equivalent ability. According to Eisenberger, individuals who are reinforced for exerting high effort on a task are also secondarily reinforced by the sensation of high effort. Individuals with a history of reinforcement for effort are predicted to generalize this effort to new behaviors.

Operationalization of industriousness

An individual is considered industrious if he or she demonstrates perseverance and determination in performing a task. This term has also been used interchangeably with work ethic, which is generally regarded as the attitude that hard work and effort is virtuous. Learned industriousness theory asserts that industriousness is developed over time through a history of reinforcement.

Possible relationship to learned helplessness

Learned helplessness is a term to explain a specific pattern of behavior that occurs in both animals and humans. When an animal or human is consistently exposed to an aversive condition (pain, unpleasant noise, etc.) and is unable to escape this condition, that animal or human will become helpless and stop attempting escape. The animal or human may develop motivational deficits, as demonstrated in learned helplessness experiments. In contrast, learned industriousness theory attempts to explain why some individuals are more motivated than others. In an attempt to merge these two phenomena, Eisenberger, Park, & Frank invoked learned industriousness in children by providing task-contingent verbal approval for a small group of behaviors, contrasting outcomes between a group of children conditioned to exhibit learned helplessness and a control group. On a subsequent approval-contingent task, children conditioned by task-contingent verbal approval outperformed controls. However, the learned-helplessness group performed no differently from controls.

Antecedents of industriousness

Effort

Effort is the subjective experience of fatigue felt by the body when it is in motion or meets resistance. This fatigue can refer to both physical and mental fatigue depending on the task at hand. Until the theory of learned industriousness, effort was generally considered an aversive sensation. Hull summed up this concept with the Law of Least Effort, which asserts that individuals will choose a solution that minimizes effort for any given problem. Learned industriousness theory is considered an addendum to the Law of Least Effort.

Relationship between effort and goal-setting strategies

Individuals with high levels of industriousness have a history of applying great effort towards tasks. It has been demonstrated in many studies that different uses of goals result in more effort and task persistence. Thus, specific goal-setting strategies are antecedents to effort and subsequently increase the likelihood of an individual 'learning' industriousness. Below is an overview of the findings.

A goal is defined as the "object or aim of an action". As motivational tools, goals have been shown to improve performance in a wide variety of settings. For example, one study looked at the effects of high goals versus low goals on performance. To investigate this effect, students were given goals for a brainstorming activity; those with higher goals were able to brainstorm more ideas than those with lower goals. Therefore, the investigator concluded that goal setting not only increases performance, but more ambitious goals evoke better performance than lower-set goals.

In addition to improving performance, setting goals also increases task effort and persistence. In one study, participants were assigned to three groups: short-term goals, long-term goals, and a control group with no goals. The participants were then asked to attempt a complicated mirror maze as many times as they would like. Both groups with goals persisted on the maze task significantly longer than the control group, providing evidence that goals promote higher effort and persistence.

Another facet of goals that has been studied in relation to task persistence is whether the goal is a cooperative or competitive goal structure. A cooperative goal structure is one in which an individual must work alongside a group to reach a common goal, whereas a competitive goal structure is one in which an individual competes with others to reach a goal. The investigators tested whether participants' social values (cooperativeness, competitiveness, and individualism) moderate the relationship between goal structure and task persistence. In accordance with their hypotheses, individuals who were classified as "cooperators" persisted longer on the cooperative goal-structured task than the competitive goal-structured task. Similarly, individuals who were classified as "individualists" persisted longer on a competitive goal-structured task than a cooperative one. Therefore, the investigators conclude that the effect of "cooperative versus competitive goal structures on task persistence are influenced by individuals' social values and history of rewarded effort".

Relationship between effort and task interest/difficulty

There are certain aspects of tasks that induce greater effort and persistence: a performer's interest in the task and the level of difficulty of the task. These factors are relevant in creating an environment where an individual is likely to exert more effort and, in turn, become more industrious. Therefore, task interest and task difficulty may both act as moderators in the relationship between effort and industriousness.

Task interest, or an individual's engagement in an activity, is claimed to be an antecedent to the exertion of effort on a task. In a study by Fisher & Noble, the hypothesis that task interest is important for self-regulation during performance and task effort was empirically tested. The findings suggest that task interest positively predicted effort with a significant correlation. While a significant correlation cannot prove causation, there is evidence that higher effort is linked to higher intrinsic motivation. Other studies have supported this finding as well.

Task difficulty is also suggested to precede high effort. The reasoning behind this claim is that high difficulty tasks evoke high effort exertion if the individual is motivated to succeed on the task. The study conducted by Fisher and Noble also supports this hypothesis, as a significant positive relationship between task difficulty and effort was found.

Reinforcement

According to Daniels & Daniels, reinforcement is any stimulus, event, or situation that fulfills the following two requirements:

1. Follows a behavior
2. Increases the frequency of that behavior

A stimulus, event, or situation is considered a reinforcer if it follows a targeted behavior and causes the increased occurrence of that behavior. Many confuse the terms "reward" and "reinforcer" because they often mean the same thing; a reward is given as a consequence of a desired behavior and often motivates an individual to perform that behavior again in order to receive another reward. However, individuals can receive rewards and not increase the behavior in question (e.g., receiving a prize for completing a marathon may not motivate an individual to run more marathons). In that case, the reward is not a reinforcer because it does not increase the frequency of the behavior. Positive reinforcement is any stimulus that is presented after a behavior and increases the frequency of that behavior. Negative reinforcement is the removal of an aversive stimulus after a behavior that increases the frequency of that behavior. Both positive and negative reinforcement are effective in the development of industriousness.

Reinforcing high effort

Learned industriousness theory asserts that reinforcing an individual for achieving a performance standard increases the likelihood of that individual's performing those behaviors again. If the individual exerted high levels of effort during the completion of the task, the effort takes on its own reinforcing value. This is because the individual enjoys the sensation of working hard because it is associated with reinforcement. Therefore, this individual is more likely to generalize this high level of effort to other tasks because it is less aversive and is associated with positive results. On the other hand, the theory also claims that if an individual has a history of being reinforced for completing tasks with very low levels of effort, that individual will eventually generalize this low level of effort to other tasks. This facet of the theory is termed "learned laziness." Evidence for these claims is provided below.

Eisenberger's theory claims an essentially dichotomous relationship between effort and reinforcement: the exertion of low effort on a simple tasked paired with high levels of reinforcement will result in low levels of effort on future tasks; on the other hand, the exertion of high effort on a difficult task paired with low levels of reinforcement (intermittent reinforcement) will result in high levels of effort on future tasks. A study conducted by Drucker et al. showed support for this claim. In this study, participants were randomly assigned to computer tasks that ranged in level of difficulty and then given either high or low levels of reinforcement for performance on the task. Participants then were given an anagram task on which their persistence time was measured. In accordance with Eisenberger's theory, individuals who were highly reinforced for performance on the low-difficulty computer task spent less time persisting on the subsequent anagram task, demonstrating that the low level of effort generalized to another activity. Additionally, individuals who were given low levels of reinforcement for performance on the moderately high-difficulty computer task spent more time persisting on the anagram task. This demonstrated that the effort exerted on the first task, paired with low levels of reinforcement, generalized to the following task. However, participants who were given the highest-difficulty computer tasks did not generalize this effort. According to the researchers, this version of the task was so difficult that the participants could not succeed and thus demonstrated a pattern of behaviors similar to learned helplessness.

Consequences

Increased effort

In addition to being an antecedent to industriousness, effort is the foremost consequence of learned industriousness theory. As predicted by the theory, multiple experimental studies have demonstrated increased effort when paired with reinforcement.

Pierce, Cameron, Banko, and So conducted two studies in directly testing Eisenberger's theory. Mimicking Drucker's methodology, the authors placed participants in a task that was of either constant or progressively higher difficulty and then either rewarded for completing the task or not rewarded (a 2x2 experiment). Afterwards the participants were presented with a difficult free-choice task. Participants who were in the progressive difficulty-reward condition spent more time on the free-choice task, especially compared to the constant difficulty-reward condition (who spent the least amount of time). A year later, Cameron, Pierce, and So repeated the experiment, this time with an easy/difficult task condition split instead of a constant/progressive difficulty condition split. Not only did participants in the difficult-reward condition put forth more effort in the free-choice phase, the authors found that participants who were rewarded for completing the difficult task performed better on the free choice task than those who were not rewarded. Additionally, participants who were rewarded for completing the easy task performed worse on the free choice task than those who were not rewarded.

Another similar study found that the secondary effort reinforcement, both positive and negative, is equally transferable to tasks other than the one originally used in the conditioning.

Applications

Creativity

There have been many studies looking at the links between creativity and rewards. Many argue that if students are rewarded for a task such as creativity, they will be less interested, perform worse, and enjoy the task less once the reward is removed. Eisenberger applied his learned industriousness theory to studies of creativity to show that extrinsic rewards do not always negatively affect intrinsic motivation or creativity.

Using a similar training, Eisenberger and Selbst performed a series of experiments looking at whether creativity and divergent thought could be conditioned in the same manner as effort. Participants performed a task where they pulled letters out of a long word to create different words and were either given a performance standard (high difficulty condition) or no performance standard (low difficulty condition). After completing five rounds of words, the participants were instructed to make as many unique drawings from a circle as they could. The pictures were judged for uniqueness and general creativity.

The authors found similar results to previous learned industriousness studies: participants in the high difficulty-low reward condition showed more creativity in the circle drawing task than those without a reward while participants in the low difficulty-low reward showed even less creativity. Although most creativity research up until that point suggested that any reward for creative thoughts reduced generalized creativity, this study showed that increases or decreases in generalized creativity depend on whether or not high or low divergent thought is rewarded.

Smoking/drug habits

Currently the area of study that learned industriousness has been cited in the applied world is smoking and drug cessation research. An example of such research is Quinn et al.'s correlational study which examined the levels of persistence of smokers vs. non-smokers using the Anagram Persistence Task (APT) and the Mirror-Tracing Persistence Task (MTPT). As predicted, non-smokers had higher levels of persistence than smokers. The authors suggested that people who have been reinforced with high effort throughout their lives would be more persistent in their use of strategies for coping with stress than smokers and that people reinforced with low effort would be more likely to use low effort strategies when coping with stress (such as smoking). In addition, people with low persistence are less likely to produce the high effort behaviors required to quit smoking. Adding support to Brandon et al.'s hypotheses is a study by Brown, Lejuez, Kahler, & Strong. The authors found that smokers who have never been able to quit for more than a day had lower levels of persistence than those who were able to quit for at least 3 months at a time.

Another study by Brandon, Herzog, Juliano, Irvin, Lazev, & Simmons continued the work of the previous two by using a longitudinal perspective. After testing for persistence using the APT and the MTPT, the participants went through eleven days of smoking cessation therapy that included cognitive-behavioral therapy, training on coping strategies, and nicotine replacement therapy. Participants were then contacted on a monthly basis for 6 months and then at 9 and 12 months for updates on their smoking habits. In addition to supporting previous findings that smokers perform worse on persistence tasks, participants who scored higher on the persistence tasks were less likely to relapse during the 12-month period of the study. Although the study was again limited because of its correlational design, the authors suggest that their results fit within the theoretical framework of learned industriousness.

An additional study by Steinberg et al. looking at adolescents and smoking found much of the same results as Brandon et al. Non-smoking adolescents scored higher on a self-reported persistence measure than smokers and smokers who planned on quitting scored higher than those who did not plan on quitting.

Future research

There are several areas in which the literature on learned industriousness can be expanded. Due to the unclear results of Eisenberger's study of a Learned Industriousness-Learned Helplessness Continuum, further research should be done to provide evidence for or against its existence. This research could be useful for personnel selection purposes and understanding performance in the workplace. Also, the most current smoking-related learned industriousness research has been correlational; experimental studies could not only be powerful evidence for the theory but also generate important practical contributions for smoking cessation therapy.

Learned helplessness

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Learned_helplessness 

Learned helplessness is the behavior exhibited by a subject after enduring repeated aversive stimuli beyond their control. It was initially thought to be caused by the subject's acceptance of their powerlessness, by way of their discontinuing attempts to escape or avoid the aversive stimulus, even when such alternatives are unambiguously presented. Upon exhibiting such behavior, the subject was said to have acquired learned helplessness. Over the past few decades, neuroscience has provided insight into learned helplessness and shown that the original theory had it backward: the brain's default state is to assume that control is not present, and the presence of "helpfulness" is what is learned first. However, it is unlearned when a subject is faced with prolonged aversive stimulation.

In humans, learned helplessness is related to the concept of self-efficacy; the individual's belief in their innate ability to achieve goals. Learned helplessness theory is the view that clinical depression and related mental illnesses may result from a real or perceived absence of control over the outcome of a situation.

Foundation of research and theory

Early experiments

Inescapable shock training in the shuttle box

American psychologist Martin Seligman initiated research on learned helplessness in 1967 at the University of Pennsylvania as an extension of his interest in depression. This research was later expanded through experiments by Seligman and others. One of the first was an experiment by Seligman & Overmier: In Part 1 of this study, three groups of dogs were placed in harnesses. Group 1 dogs were simply put in a harness for a period of time and were later released. Groups 2 and 3 consisted of "yoked pairs". Dogs in Group 2 were given electric shocks at random times, which the dog could end by pressing a lever. Each dog in Group 3 was paired with a Group 2 dog; whenever a Group 2 dog got a shock, its paired dog in Group 3 got a shock of the same intensity and duration, but its lever did not stop the shock. To a dog in Group 3, it seemed that the shock ended at random because it was their paired dog in Group 2 that was causing it to stop. Thus, for Group 3 dogs, the shock was "inescapable".

In Part 2 of the experiment, the same three groups of dogs were tested in a shuttle-box apparatus (a chamber containing two rectangular compartments divided by a barrier a few inches high). All of the dogs could escape shocks on one side of the box by jumping over a low partition to the other side. The dogs in Groups 1 and 2 quickly learned this task and escaped the shock. Most of the Group 3 dogs – which had previously learned that nothing they did had any effect on shocks – simply lay down passively and whined when they were shocked.

In a second experiment later that year with new groups of dogs, Maier and Seligman ruled out the possibility that, instead of learned helplessness, the Group 3 dogs failed to avert in the second part of the test because they had learned some behavior that interfered with "escape". To prevent such interfering behavior, Group 3 dogs were immobilized with a paralyzing drug (curare) and underwent a procedure similar to that in Part 1 of the Seligman and Overmier experiment. When tested as before in Part 2, these Group 3 dogs exhibited helplessness as before. This result serves as an indicator for the ruling out of the interference hypothesis.

From these experiments, it was thought that there was to be only one cure for helplessness. In Seligman's hypothesis, the dogs do not try to escape because they expect that nothing they do will stop the shock. To change this expectation, experimenters physically picked up the dogs and moved their legs, replicating the actions the dogs would need to take in order to escape from the electrified grid. This had to be done at least twice before the dogs would start willfully jumping over the barrier on their own. In contrast, threats, rewards, and observed demonstrations had no effect on the "helpless" Group 3 dogs.

Later experiments

Later experiments have served to confirm the depressive effect of feeling a lack of control over an aversive stimulus. For example, in one experiment, humans performed mental tasks in the presence of distracting noise. Those who could use a switch to turn off the noise rarely bothered to do so, yet they performed better than those who could not turn off the noise. Simply being aware of this option was enough to substantially counteract the noise effect. In 2011, an animal study found that animals with control over stressful stimuli exhibited changes in the excitability of certain neurons in the prefrontal cortex. Animals that lacked control failed to exhibit this neural effect and showed signs consistent with learned helplessness and social anxiety.

Expanded theories

Research has found that a human's reaction to feeling a lack of control differs both between individuals and between situations, i.e. learned helplessness sometimes remains specific to one situation but at other times generalizes across situations. Such variations are not explained by the original theory of learned helplessness, and an influential view is that such variations depend on an individual's attributional or explanatory style. According to this view, how someone interprets or explains adverse events affects their likelihood of acquiring learned helplessness and subsequent depression. For example, people with pessimistic explanatory style tend to see negative events as permanent ("it will never change"), personal ("it's my fault"), and pervasive ("I can't do anything correctly"), and are likely to suffer from learned helplessness and depression.

In 1978, Lyn Yvonne Abramson, Seligman and John D. Teasdale reformulated Seligman's work, using attribution theory. They proposed that people differed in how they classified negative experiences on three scales, from internal to external, stable to unstable, and from global to specific. They believed that people who were more likely to attribute negative events to internal, stable, and global causes were more likely to become depressed than those attributed things to causes at the other ends of the scales.

Bernard Weiner proposed a detailed account of the attributional approach to learned helplessness in 1986. His attribution theory includes the dimensions of globality/specificity, stability/instability, and internality/externality:

• A global attribution occurs when the individual believes that the cause of negative events is consistent across different contexts.
  • A specific attribution occurs when the individual believes that the cause of a negative event is unique to a particular situation.
• A stable attribution occurs when the individual believes the cause to be consistent across time.
  • An unstable attribution occurs when the individual thinks that the cause is specific to one point in time.
• An external attribution assigns causality to situational or external factors,
  • while an internal attribution assigns causality to factors within the person.

Research has shown that those with an internal, stable, and global attributional style for negative events can be more at risk for a depressive reaction to failure experiences.

Neurobiological perspective

Research has shown that increased 5-HT (serotonin) activity in the dorsal raphe nucleus plays a critical role in learned helplessness. Other key brain regions that are involved with the expression of helpless behavior include the basolateral amygdala, central nucleus of the amygdala and bed nucleus of the stria terminalis. Activity in medial prefrontal cortex, dorsal hippocampus, septum and hypothalamus has also been observed during states of helplessness.

In the article, "Exercise, Learned Helplessness, and the Stress-Resistant Brain", Benjamin N. Greenwood and Monika Fleshner discuss how exercise might prevent stress-related disorders such as anxiety and depression. They show evidence that running wheel exercise prevents learned helplessness behaviors in rats. They suggest that the amount of exercise may not be as important as simply exercising at all. The article also discusses the neurocircuitry of learned helplessness, the role of serotonin (or 5-HT), and the exercise-associated neural adaptations that may contribute to the stress-resistant brain. However, the authors finally conclude that "The underlying neurobiological mechanisms of this effect, however, remain unknown. Identifying the mechanisms by which exercise prevents learned helplessness could shed light on the complex neurobiology of depression and anxiety and potentially lead to novel strategies for the prevention of stress-related mood disorders".

Health implications

People who perceive events as uncontrollable show a variety of symptoms that threaten their mental and physical well-being. They experience stress, they often show disruption of emotions demonstrating passivity or aggressivity, and they can also have difficulty performing cognitive tasks such as problem-solving. They are less likely to change unhealthy patterns of behavior, causing them, for example, to neglect diet, exercise, and medical treatment.

Depression

Abnormal and cognitive psychologists have found a strong correlation between depression-like symptoms and learned helplessness in laboratory animals. Steven Maier, a professor from the University of Colorado, states that a model of depression could be caused by "impaired medial prefrontal cortical inhibitory control over stress-responsive limbic and brainstem structures." Comorbidity between psychological disorders and learned helplessness may be due to stressful events. Maier also mentions depression may not be the only mental illness that this involves, which could link to other mental illnesses. Similarly, the National Institute of Health, in 2021, looked at a wide range of depressive models. It highlights the Learned helplessness model. The model allows one to predict depressive symptoms because of its high rates of overlap with post-traumatic stress disorder and major depressive disorder, which is the leading research in the article, "Overlapping neurobiology of learned helplessness and conditioned defeat: Implications for PTSD and mood disorders."

(See Neurobiological perspective section above for further information on this article)

Young adults and middle-aged parents with a pessimistic explanatory style often suffer from depression. They tend to be poor at problem-solving and cognitive restructuring and demonstrate poor job satisfaction and interpersonal relationships in the workplace. Those with a pessimistic style can have weakened immune systems. It includes increased vulnerability to minor ailments (e.g., cold, fever) and major illnesses (e.g., heart attack, cancers). It can also cause poorer recovery from health problems.

Social impact

Learned helplessness can be a factor in a wide range of social situations.

• In emotionally abusive relationships, the victim often develops learned helplessness. This occurs when the victim confronts or tries to leave the abuser only to have the abuser dismiss or trivialize the victim's feelings, pretend to care but not change, or impede the victim from leaving. As the situation continues and the abuse gets worse, the victim will begin to give up and show signs of this learned helplessness. This often results in a traumatic bonding with ones victimizer, as in Stockholm syndrome or Battered woman syndrome.
• Complex post-traumatic stress disorder.
• According to Gregory Bateson's theory of schizophrenia, the disorder is a pattern of learned helplessness in people habitually caught in double binds in childhood. In such cases, the double bind is presented continually and habitually within the family context from infancy on. By the time the child is old enough to have identified the double bind situation, it has already been internalized, and the child is unable to confront it. The solution then is to create an escape from the conflicting logical demands of the double bind, in the world of the delusional system (see in Towards a Theory of Schizophrenia – Illustrations from Clinical Data).
• The motivational effect of learned helplessness is often seen in the classroom. Students who repeatedly fail may conclude that they are incapable of improving their performance, and this attribution keeps them from trying to succeed, which results in increased helplessness, continued failure, loss of self-esteem and other social consequences. This becomes a pattern that will spiral downward if it continues to go untreated.
• Child abuse by neglect can be a manifestation of learned helplessness. For example, when parents believe they are incapable of stopping an infant's crying, they may simply give up trying to do anything for the child. This learned helplessness will negatively impact both the parent and child.
• Those who are extremely shy or anxious in social situations may become passive due to feelings of helplessness. Gotlib and Beatty (1985) found that people who cite helplessness in social settings may be viewed poorly by others, which tends to reinforce passivity.
• Aging individuals may respond with helplessness to the deaths of friends and family members, the loss of jobs and income, and the development of age-related health problems. This may cause them to neglect their medical care, financial affairs, and other important needs.
• According to Cox et al., Abramson, Devine, and Hollon (2012), learned helplessness is a key factor in depression that is caused by inescapable prejudice (i.e., "deprejudice"). Thus: "Helplessness born in the face of inescapable prejudice matches the helplessness born in the face of inescapable shocks."
• According to Ruby K. Payne's book A Framework for Understanding Poverty, treatment of the poor can lead to a cycle of poverty, a culture of poverty, and generational poverty. This type of learned helplessness is passed from parents to children. People who embrace this mentality feel there is no way to escape poverty and so one must live in the moment and not plan for the future, trapping families in poverty.

Social problems resulting from learned helplessness may seem unavoidable to those entrenched. However, there are various ways to reduce or prevent it. When induced in experimental settings, learned helplessness has been shown to resolve itself with the passage of time. People can be immunized against the perception that events are uncontrollable by increasing their awareness of previous experiences, when they were able to affect the desired outcome. Cognitive therapy can be used to show people that their actions do make a difference and bolster their self-esteem. Seeking out these types of treatment options can be extremely helpful for people stuck in a rut when it comes to learned helplessness. While it may initially feel hard to escape, with the proper time and help it can get better.

Extensions

Cognitive scientist and usability engineer Donald Norman used learned helplessness to explain why people blame themselves when they have a difficult time using simple objects in their environment.

The UK educationalist Phil Bagge describes it as a learning avoidance strategy caused by prior failure and the positive reinforcement of avoidance such as asking teachers or peers to explain and consequently do the work. It shows itself as sweet helplessness or aggressive helplessness often seen in challenging problem solving contexts, such as learning to use a new computer programming language.

The US sociologist Harrison White has suggested in his book Identity and Control that the notion of learned helplessness can be extended beyond psychology into the realm of social action. When a culture or political identity fails to achieve desired goals, perceptions of collective ability suffer.

Emergence in the political atmosphere

In a political setting, learned helplessness is involved when a voter votes for a candidate and that candidate does not win. If this happens over time, it can lead to learned helplessness. When this does occur, it can often lead to having fewer voters in the future. However, Wollman & Stouder (1991) found that there was not a significant finding between situation-specific efficacy and predictive behavior of voting.

Emergence under torture

Studies on learned helplessness served as the basis for developing enhanced interrogation techniques, otherwise known as torture. In CIA interrogation manuals, learned helplessness is characterized as "apathy" which may result from prolonged use of coercive techniques which result in a "debility-dependency-dread" state in the subject, "If the debility-dependency-dread state is unduly prolonged, however, the arrestee may sink into a defensive apathy from which it is hard to arouse him."