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Executive function (EF) helps navigate most daily activities and constitutes a set of cognitive processes allowing self-regulation/self-directed behaviour toward a goal. ER impairments are associated with most forms of psychopathology. Poor EF predicts rumination, and poor use of emotion regulation – risk factors for psychopathologies.
There’s a lot of parallel play between clinical and cognitive approaches to EF, potentially leading to failures to apply theoretical and methodological advances in one field to the other, hindering progress.
Three main goals:
EF is best described consisting of separable but related cognitive processes including unique and shared individual differences, genetic influences, and neural substrates. Aspects of EF that have been heavily studied in clinical psychology include shifting, inhibition, updating, working memory manipulation, verbal fluency, and planning – many of these can be further subdivided.
Previous research on EF impairments associated with psychopathology reviewed in this section has mainly used cross-sectional designs in adult samples, and assessed EF with traditional neuropsychological tasks. But there are limitations in the literature – imposing constraints on the state of knowledge and what can be determined through meta-analysis:
Despite these limitations, meta-analytic evidence indicates that EF deficits are pervasive across disorders and EF tasks.
Definitions:
Impairments across disorders:
Complex tasks may tap multiple aspects of EF – problematic if goal is to understand which specific processes are impaired. Nonetheless, these tasks still used in clinical studies of EF.
Deficits in verbal fluency are widespread across disorders. Meta-analyses show largest deficit for adults with schizophrenia and depression to be semantic verbal fluency. Semantic verbal fluency also impaired in people with BD, OCD, and ADHD, but inconsistent evidence for verbal fluency in PTSD patients. Little research on verbal fluency in anxiety disorder, mixed results.
Verbal fluency tasks impose multiple EF demands. One possibility of why semantic verbal fluency is more impaired in schizophrenic, BD, and depression patients is that it may place heavier demands on shifting. Another possibility is that semantic memory retrieval deficits could contribute to semantic verbal fluency impairment, especially in schizophrenia. Conversely, larger effect for phonemic verbal fluency in ADHD patients could be due to deficits in phonological processing, since ADHD and reading disabilities frequently co-occur. Deficits in verbal fluency could come from various sources – difficult to interpret results from complex tasks.
Planning is less studied. Depression and BD patients have significant impairments in planning. Meta-analyses found mixed results for planning tasks in people with ADHD and OCD. There’s inconsistent evidence for planning deficits in PTSD. In theory, planning tasks tap multiple EF aspects, but standard measures of planning may be less sensitive than other tasks in detecting subtler deficits in some disorders.
EF is hard to study, define, and measure. Now will be outlined the limitations of how EF has been defined, conceptualized, and measured in previous research, and concrete suggestions will be presented to address these limitations.
Many previous clinical studies of EF have treated it as either unitary, or a list of separate, specific abilities. Seeing it as unitary over-lumps diverse tasks into a single construct, seeing it as diverse over-splits, treating a list of tasks as if they were assessing separate abilities rather than a common set of component processes supporting completion of more complex tasks.
The best evidence indicates individual difference in EF to show unity and diversity. Different components of EF correlate with each other, tapping some common underlying ability (unity), while showing separability (diversity). General structure of common and specific elements is shared by different models of EF, focusing on different components and levels of analysis.
Though these models differ, they have points of convergence, often agreeing on core cognitive and neural mechanisms involved in EF.
Unity/diversity model – captures several features of what’s believed to be the key components of EF, practical to use for understanding EF at the behavioural level, and has potential to shed light on commonalities and differences in impairments across populations by differentiating common and specific components of EF. Focuses on three aspects of EF: updating WM, shifting, and inhibition. This unity/diversity pattern has been consistently found over other samples. Each EF ability can be decomposed into what is common across all three (unity (common EF)), and what’s unique to each ability (diversity).
The unity/diversity model suggests decomposing task performance into common and specific abilities that could better map the underlying cognitive processes. New approach that has produced significant findings:
Biggest problem in measuring EF -> task-impurity problem. All tasks necessarily include systematic variance attributable to non-EF processes associated with that task context, making it difficult to cleanly measure the variance of interest. Since most clinical EF studies have used a single task to assess EF processes of interest, results are nearly always a mixture of non-, common-, and specific-EF component effects, making interpretation difficult.
This problem can be alleviated by using multiple measures of each component under investigation. If the chosen tasks share little systematic non-EF variance, one can see what’s common across tasks and use the resulting ‘purer’ variable as a measure of EF. E.g. measures of each EF component should be used then aggregated to measure common EF.
Simplest way to combine data from measures is to calculate a z-mean across tasks. Advantage – z-mean across tasks instead of individual tasks, variance in the scores not related to the constructs of interest no longer drive the effects. Disadvantage – merely combines scores, error variance is still there and can be a source of reduced power. So, if the sample is large enough, it’s preferred to use latent variable approaches for extracting the variance shared across tasks while removing error variance, - e.g. factor analysis, structural equation modeling.
It’s also important to carefully pick tasks. Many clinical studies now use traditional neuropsychological measures tapping multiple aspects of (non-)EF abilities. Useful for screening for severe deficits but too broad to answer questions about specific aspects of EF that may be implicated in psychopathology. Complex neuropsychological tests tap a variety of cognitive processes, making interpretation difficult. This can be addressed by using tasks designed to specifically place demands on individual aspects. Important to include specific tasks to identify what processes account for impairment on broad neuropsychological tasks.
Many studies also use questionnaires or self-report measures. These correlate poorly with task-based measures of EF, and shouldn’t be assumed to be measuring the same constructs. Questionnaire-based measures have ecological validity as they as about real-world situations. But they pose interpretational problems because of the multiple executive and non-executive functions involved in real world settings/contextual influence. Specific questions about EF are best addressed using targeted tasks.
Sensitivity and reliability of tasks are important. Tasks should be sensitive to the magnitude of deficits expected form the sample being tested. Tasks with low reliability have poor correlations with other measures. Reliability is sample specific. Unfortunately, complex EF tasks tend to have low internal/test-retest reliability due to different strategies used when completing them.
Problems with sensitivity and reliability are problematic because they could lead to false negatives resulting in not being published, or being published with the conclusion that EF isn’t impaired in the clinical group.
There are a number of commercially available task batteries including tasks assessing EF.
How the data is collected and analyzed is also important. When the total individual variance in EF task performance in broken into EF, task-specific and error components, the ‘noise’ of non-EF task-specific variance and error variance can be large, while the ‘signal’ of EF-specific variance may be small. So to detect the most important signal for the inquiry, it’s important to minimize error variance and maximize power. First, strong need to increase sample size to improve power (underpowered studies lead to file drawer problem and lack of replicability). Second, once data’s collected, reliability and validity of the measures depend on how they are screened and analyzed. Also important to screen for and address the presence of outliers.
Given the discussed limitations to previous research and the goal of understanding links between EF and psychopathology at a level of specificity that can support translational research, we propose two broad directions for future research.
First direction suggested is that the problem of understanding the undifferentiated nature of EF impairments across disorders may be made more tractable by testing models that include both unity and diversity in psychopathology and EF.
What gives rise to broad patterns of impairment in EF across disorders? These deficits can’t easily be explained by non-specific factors. In most cases effect sizes are similar across core EF domains. This pattern of broad impairment is consistent with the theory that people with multiple forms of psychopathology have impairments in the unitary component of EF, posited to be the ability to actively maintain task goals.
Latent variable models of psychopathology find that there’s a common factor spanning all aspects of common psychopathologies in addition to more specific aspects (the ‘p factor’). Transdiagnostic impairments in EF might be explained by a link between the p Factor and common EF. But, cognitive factors that appear as transdiagnostic at one level of analysis may not be when more detailed measures at multiple levels of analysis are considered.
Second direction suggested is that research needs to move beyond cross-sectional case-control designs to test different possible causal links between EF and psychopathology.
A general shortcoming of the broad field of cognitive risks in psychopathology across the lifespan is the frequent lack of consideration of possible models of how cognitive impairments and psychopathology may be causally related. It’s unknown if EF deficits (a) precede and are a potential causal risk factor for developing psychopathology, (b) follow, and are a consequence of psychopathology, or (c) are a correlate of psychopathology without playing a causal role.
Many studies assume a particular causal model, but there have been fewer attempts to try to rule out/in particular models based on evidence. Cross-sectional case-control studies aren’t able to differentiate between these possible models.
Current evidence suggests that approaches aimed at teaching compensatory strategies may be the most promising direction for future translational research. There’s little evidence supporting direct training of EF (targeting the weakness instead of compensatory strategies), little evidence that it generalizes to real world functions or improves clinical symptoms. There’s still the possibility that types of training that better target areas of weakness might provide better transfer.
Treatment and prevention programs involving compensatory strategies may therefore be a more promising direction for translational research e.g. goal management techniques, - shown to improve functional outcomes in schizophrenic individuals.
In addition to this there may be a need to adapt and personalize current treatment approaches to match client’s EF abilities – tailoring treatment approaches through better understanding of their profile.
Executive function deficits also have important implications for psychopharmacological treatments. For behavioural therapies, pre-treatment EF has been shown to predict drug treatment response. Better understanding of EF deficits can enhance targeting of medications that affect the neurotransmitter systems known to be involved in those EF processes.
Cognitive and clinical psychology have followed largely independent paths. It’s argued that it’s necessary to move past the ‘parallel play’ of these fields to push clinical psychological science toward a better understanding of how/why EF is broadly compromised across disorders.
It’s recommended to apply validated models of EF to clinical research using multiple tasks to obtain purer measures, and also select/analyze tasks that minimize noisiness of EF data.
To address the task impurity problem/improve reliability, we recommend carefully choosing EF components to focus on and using multiple measures of each component of interest and combining them to composite scores or latent variable analysis.
We advise using more specific EF measures rather than traditional, broad neuropsychological tests. It’s the hope that combining current theoretical and methodological advances of clinical and cognitive science can advance the field towards understanding underlying processes involved in EF impairments at a level that enables translational research to improve treatment.
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Summaries on Psychopathology, it gives an insight in research that tries to unravel the mechanisms behind Psychopathology. This set of articles is based on the 2020-2021 course 'Understanding Psychopathology' at Groningen university.
Topics that will be discussed: mental illness, mental disorders, anxiety, depression, panic (disorder), psychotherapy, mental cognition, social psychology, phobias, addiction
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