Common factors theory

Summary

Common factors theory, a theory guiding some research in clinical psychology and counseling psychology, proposes that different approaches and evidence-based practices in psychotherapy and counseling share common factors that account for much of the effectiveness of a psychological treatment. This is in contrast to the view that the effectiveness of psychotherapy and counseling is best explained by specific or unique factors (notably, particular methods or procedures) that are suited to treatment of particular problems. However, according to one review, "it is widely recognized that the debate between common and unique factors in psychotherapy represents a false dichotomy, and these factors must be integrated to maximize effectiveness." In other words, "therapists must engage in specific forms of therapy for common factors to have a medium through which to operate." Common factors is one route by which psychotherapy researchers have attempted to integrate psychotherapies. Histor

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Common factors are omnipresent in everyday life, e.g., people who do well in one cognitive test are likely to perform well in other cognitive tests as well, and vice versa. In vision, however, there seems to be a multitude of specific factors rather than a strong and unique common factor. For example, only weak correlations were observed between the susceptibility to different visual illusions, suggesting that the structure underlying visual illusions is multifactorial. In this thesis, I first examined the multidimensionality of the structure underlying visual illusions. To this aim, the susceptibility to various visual illusions was measured. In addition, subjects were tested with variants of the same illusion, which differed in spatial features, luminance, orientation, or contextual conditions. In line with previous work, only weak correlations were observed between the susceptibility to different visual illusions (i.e., between-illusion). An individual showing a strong susceptibility to one visual illusion does not necessarily show a strong susceptibility to other visual illusions. In contrast, there were strong correlations between the susceptibility to variants of the same illusion (i.e., within-illusion). Hence, factors seem to be illusion-specific but not feature-specific. In addition, the susceptibility to combinations of two illusions, which I call merged illusions, was measured to investigate how factors for illusions interact. The susceptibility to a merged illusion was strongly predicted from the susceptibility to the two illusions of which it was made, suggesting that factors for illusions combine independently to form complex illusory percepts. Second, I showed that individual differences in the perception of visual illusions are robust across the eye(s) to which the stimulus is presented, over a month, and when measured with an adjustment procedure or a method of constant stimuli. Last, I investigated whether a strong visual factor emerges in healthy elderly and patients with schizophrenia, which may be expected from the general decline in perceptual abilities usually reported in these two populations compared to healthy young adults. Similarly, a strong visual factor may emerge in action video gamers, who, contrary to healthy elderly and patients with schizophrenia, often show enhanced perceptual performance compared to non-video gamers. Hence, healthy elderly, patients with schizophrenia, and action video gamers were tested with a battery of visual tasks, such as a contrast detection and orientation discrimination task. As in control groups, between-task correlations were weak in general, which argues against the emergence of a strong common factor for vision in these populations. While similar tasks are usually assumed to rely on similar neural mechanisms, the performances in different visual tasks were only weakly related to each other, i.e., performance does not generalize across visual tasks. The results presented in this thesis highlight the relevance of an individual differences approach to unravel the multidimensionality of the visual structure.

EPFL2021

About common factors in vision

Aline Françoise Cretenoud, Ophélie Gladys Favrod, Simona Adele Garobbio, Dario Alejandro Gordillo Lopez, Lukasz Grzeczkowski, Michael Herzog, Janir Nuno Ramos Antunes Da Cruz, Maya Roinishvili

Often, we intuitively assume that there are common factors in life. For example, we test people with a visual acuity test to determine whether they are allowed to drive a car or not- with the implicit assumption that the acuity test is representative of vision. Likewise, we make considerable efforts to exactly understand certain visual paradigms because we assume that they measure core functions of the human visual system. Contrary to many fields of psychology, researchers have paid very little attention to common factors in vision. In a series of studies, we tested batteries of standard visual paradigms in a variety of populations including the “normal” healthy population, video gamers, the older population, and schizophrenia patients. Even though test-retest reliability was generally good, all our studies indicate that most visual tests only weakly correlate with each other. Factor analysis supported this conclusion. Hence, we need to rethink to what extent common visual paradigms test what we implicitly assume they do. [Swiss National Science Foundation, NCCR Synapsy, Velux Foundation.]

SAGE Publishing2021

How many factors are there in vision?

Aline Françoise Cretenoud, Gregory Francis, Lukasz Grzeczkowski, Michael Herzog

Common factors are ubiquitous in cognition, audition, and somato-sensation. Surprisingly, there seems to be no common factor in vision, i.e., visual tasks correlate very weakly with each other. Here, we show that there are likely many very specific factors in vision. First, we have previously shown that the Ebbinghaus illusion correlates very little with other spatial illusions (except the Ponzo illusion). Here, we measured illusion strength in the classic Ebbinghaus illusion with disks and compared it with the illusion magnitude of 18 versions of the Ebbinghaus illusion, for example, having squares rather than disks or moving rather than static disks. In addition, we asked observers to compare the size of two single disks. All versions of the Ebbinghaus illusion strongly correlated with each other but not with the single disks comparison task, even though the tasks are the same. Second, we previously presented 10 illusions, each with 4 different luminance conditions, including 2 iso-luminant ones. For all 10 illusions, the luminance conditions correlated highly with each other. Here, we re-analyzed the data and found that there were almost no correlations between the 10 illusions, except for the vertical and horizontal bisection illusion, which correlated strongly with each other for all 4 luminance conditions. In both bisection illusions, there are likely different neurons, sensitive to vertical and horizontal orientations, involved. Hence, variations of an illusion correlate highly with each other, however, it seems that each illusion makes up its own factor.

2017