Causal discovery and the problem of psychological interventions

Eronen, Markus I.

doi:10.1016/j.newideapsych.2020.100785

Cited by 67 publications

(71 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Variables such as symptoms are often intertwined, and even though therapists try to intervene on, for example, mood, it is likely that other things (e.g., going out more) will change at the same time. This phenomenon is also known as the fat-handed intervention, as things (thoughts and mood) are so interconnected that it is dubious whether interventions on a single variable, for example, worrying, are possible without changing the rest of the system (for more on this, see Eronen, 2018). Instead, the network approach can be seen as an incentive to move more towards more complex theories and models, belonging to the field of complex system theory (van de Leemput et al, 2014;Van Der Maas et al, 2006;Van der Maas & Molenaar, 1992;Wichers, Groot, & Psychosystems, 2016).…”

Section: Ways Forwardmentioning

confidence: 99%

What do centrality measures measure in psychological networks?

Bringmann¹,

Elmer²,

Epskamp

et al. 2019

Journal of Abnormal Psychology

742

506

View full text Add to dashboard Cite

Centrality indices are a popular tool to analyze structural aspects of psychological networks. As centrality indices were originally developed in the context of social networks, it is unclear to what extent these indices are suitable in a psychological network context. In this paper we critically examine several issues with the use of the most popular centrality indices in psychological networks: degree, betweenness, and closeness centrality. We show that problems with centrality indices discussed in the social network literature also apply to the psychological networks. Assumptions underlying centrality indices, such as presence of a flow and shortest paths, may not correspond with a general theory of how psychological variables relate to one another. Furthermore, the assumptions of node distinctiveness and node exchangeability may not hold in psychological networks. We conclude that, for psychological networks, betweenness and closeness centrality seem especially unsuitable as measures of node importance. We therefore suggest three ways forward: (1) using centrality measures that are tailored to the psychological network context, (2) reconsidering existing measures of importance used in statistical models underlying psychological networks, and (3) discarding the concept of node centrality entirely. Foremost, we argue that one has to make explicit what one means when one states that a node is central, and what assumptions the centrality measure of choice entails, to make sure that there is a match between the process under study and the centrality measure that is used.

show abstract

Section: Ways Forwardmentioning

confidence: 99%

What do centrality measures measure in psychological networks?

Bringmann¹,

Elmer²,

Epskamp

et al. 2019

Journal of Abnormal Psychology

742

506

View full text Add to dashboard Cite

show abstract

“…The problem, however, is that discovering causal relationships between psychological variables is often extremely difficult or impossible, as extensively argued in Eronen (2020). To explain why, we rely on the framework of the interventionist theory of causation (Woodward, 2003(Woodward, , 2015; see also Pearl, 2000Pearl, , 2009, which lays out the conditions for inferring causal relationships in a clear and general way.…”

Section: Psychological Theories and The Problem Of Finding Causesmentioning

confidence: 99%

The Theory Crisis in Psychology: How to Move Forward

Eronen¹,

Bringmann

2021

Perspect Psychol Sci

Self Cite

298

199

View full text Add to dashboard Cite

Meehl argued in 1978 that theories in psychology come and go, with little cumulative progress. We believe that this assessment still holds, as also evidenced by increasingly common claims that psychology is facing a “theory crisis” and that psychologists should invest more in theory building. In this article, we argue that the root cause of the theory crisis is that developing good psychological theories is extremely difficult and that understanding the reasons why it is so difficult is crucial for moving forward in the theory crisis. We discuss three key reasons based on philosophy of science for why developing good psychological theories is so hard: the relative lack of robust phenomena that impose constraints on possible theories, problems of validity of psychological constructs, and obstacles to discovering causal relationships between psychological variables. We conclude with recommendations on how to move past the theory crisis.

show abstract

“…It is worthwhile noting, however, that between-subjects designs suffer a logical problem with respect to inferring experimental effects. For instance, the gold-standard of research design, the Randomized Control Trial (RCT) is always missing half of the necessary data to fully observe an effect (Eronen, 2020). That is, such experiments possess the implicit assumption that we can infer effects that occur within people by comparing people in one condition with people in another condition.…”

Section: The Benefits Of Observing Effects Within Subjectsmentioning

confidence: 99%

Statements About the Pervasiveness of Behavior Require Data About the Pervasiveness of Behavior

Speelman

McGann

2020

Front. Psychol.

View full text Add to dashboard Cite

Despite recent close attention to issues related to the reliability of psychological research (e.g., the replication crisis), issues of the validity of this research have not been considered to the same extent. This paper highlights an issue that calls into question the validity of the common research practice of studying samples of individuals, and using sample-based statistics to infer generalizations that are applied not only to the parent population, but to individuals. The lack of ergodicity in human data means that such generalizations are not justified. This problem is illustrated with respect to two common scenarios in psychological research that raise questions for the sorts of theories that are typically proposed to explain human behavior and cognition. The paper presents a method of data analysis that requires closer attention to the range of behaviors exhibited by individuals in our research to determine the pervasiveness of effects observed in sample data. Such an approach to data analysis will produce results that are more in tune with the types of generalizations typical in reports of psychological research than mainstream analysis methods.

show abstract

Causal discovery and the problem of psychological interventions

Abstract: Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

Cited by 67 publications

References 63 publications

What do centrality measures measure in psychological networks?

What do centrality measures measure in psychological networks?

The Theory Crisis in Psychology: How to Move Forward

Statements About the Pervasiveness of Behavior Require Data About the Pervasiveness of Behavior

Contact Info

Product

Resources

About