Marsh, J. K., De Los Reyes, A., & Wallerstein, A. (in press). The influence of contextual information on lay judgments of childhood mental health concerns. Psychological Assessment. abstract
Marsh, J. K., & Hick, D. H. (in press). Beliefs about experiencing and destroying art. Proceedings of the 36th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. abstract
Marsh, J. K., & Shanks, L. L. (in press). Thinking you can catch mental illness: How beliefs about membership attainment and category structure influence interactions with mental health category members. Memory & Cognition. abstract
Marsh, J. K., & Kulkofsky, S. (2014). The selective power of causality on memory errors. Memory. Advance online publication. doi: 10.1080/09658211.2014.884139. abstract
Marsh, J. K. & Rothman, N. B. (2013). The ambivalence of expert categorizers. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society (pp. 984-989). Austin, TX: Cognitive Science Society. [PDF] abstract
Ahn, W., Taylor, E. G., Kato, D., Marsh, J. K., & Bloom, P. (2013). Causal essentialism in kinds. Quarterly Journal of Experimental Psychology, 66, 1113-1130. [doi] abstract
Marsh, J. K., & Ahn, W. (2012). Memory for patient information as a function of experience in mental health. Applied Cognitive Psychology, 26, 462-474. [doi] abstract
De Los Reyes, A., & Marsh, J. K. (2011). Patients' contexts and their effects on clinicians' impressions of conduct disorder symptoms. Journal of Clinical Child and Adolescent Psychology, 40, 479-485. [doi] abstract
Marsh, J. K., & Ahn, W. (2009). Spontaneous assimilation of continuous values and temporal information in causal induction. Journal of Experimental Psychology: Learning, Memory, & Cognition, 25, 334-352. [doi] abstract
Ahn, W., Marsh, J. K., & Luhmann, C. C. (2007). Dynamic interpretations of covariation data. In A. Gopnik & L. Schulz (Eds.) Causal Learning: Psychology, Philosophy, and Computation (Oxford Series in Cognitive Development) New York: Oxford University Press. [PDF] abstract
Ahn, W., Flanagan, E., Marsh, J. K., & Sanislow, C. (2006). Beliefs about essences and the reality of mental disorders. Psychological Science, 17, 759-766. [doi] abstract
Marsh, J. K., & Ahn, W. (2006). Order effects in contingency learning: The role of task complexity. Memory & Cognition, 34, 568-576. [doi] abstract
Marsh, J. K., & Ahn, W. (2006). The role of causal status versus inter-feature links in feature weighting. In R. Sun & N. Miyake (Eds.), Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 561-566). Mahwah, New Jersey: Lawrence Erlbaum Associates. [PDF] abstract
Ahn, W., Levin, S., & Marsh, J. K. (2005). Determinants of Feature Centrality in Clinicians' Concepts of Mental Disorders, Proceedings of the 27th Annual Conference of the Cognitive Science Society. Mahwah, New Jersey: Lawrence Erlbaum Associates. [PDF] abstract
Marsh, J. K., & Ahn, W. (2003). Interpretation of ambiguous information in causal induction. In R. Alterman & D. Kirsh (Eds.), Proceedings of the 25th Annual Conference of the Cognitive Science Society. (pp. 775-780). Mahwah, New Jersey: Lawrence Erlbaum Associates, Inc. [PDF] abstract
Ahn, W.,Marsh, J., Luhmann, C., & Lee, K (2002). Effect of theory-based feature correlations on typicality judgments. Memory & Cognition, 30, 107-118. [doi] abstract
Abstracts
Marsh, De Los Reyes, & Wallerstein (in press): Decisions about whether a person is in need of mental health care are often made by laypeople with no training in the identification of mental health concerns. For example, the parent of a child displaying problematic behavior has to decide whether this behavior is likely related to mental health concerns and necessitates professional care. The process of identifying mental health concerns is made more complicated by the rich background of real-world environmental factors or contexts in which concerns can present; contexts that might or might not relate to the presence of mental health concerns. We investigated whether laypeople use contextual information to make judgments regarding childhood mental health disorder symptoms. In Experiment 1 we demonstrated that laypeople's judgments of the likelihood of a mental disorder are influenced by non-diagnostic contextual information that surrounds symptoms of the disorder. In Experiment 2 we demonstrated that providing a causal origin for such disorder symptoms accentuates the use of context, regardless of the nature of the causal process (i.e., environmental vs. biological). These findings indicate that contextual influences on judgments about mental health concerns may reflect a more general set of mental reasoning processes than indicated by previous work focused on clinicians' judgments. Consequently, these findings have important implications for how we think about the influence of contextual information on decision-making more generally, as well as improving our ability to both reliably identify children in need of mental health care and increase children's access to such care.
Marsh & Hick (in press): Based in current debates in aesthetics, we examined whether people's beliefs match philosophers' arguments that an original painting or carved sculpture possesses a privileged nature when compared with originals in other types of art. We tested whether participants believe the destruction of an original art piece has different consequences on the ability to experience that piece if the art is visual, literary, or musical (Experiment 1). In Experiment 2 we explored how different forms of destruction varied whether people believe an art piece still exists and the perceived quality of an experience with the piece. In summary, we demonstrated that people have a more lax view of how art can be experienced than is assumed by most philosophers, but share an intuition that the original form of a work of visual art has a unique nature.
Marsh & Shanks (in press): We explored beliefs about mental disorder categories that influence potential interactions with category members. Specifically, we investigated beliefs related to how membership in a mental disorder category is obtained (communicability and causal origin) as well as beliefs related to the underlying reality of disorder categories (essentialism and controllability). In Experiment 1 participants' interaction willingness decisions were predicted by believing a mental disorder category was communicable, psychologically or environmentally caused, and possessed all-or-none membership. In fictitious mental disorders, people were less willing to interact with others described as having a communicable mental disorder than people described as possessing any of the other factors of interest, highlighting the independent influence of these contagion beliefs (Experiment 2). We further explored beliefs in the communicability of mental disorders in Experiment 3 by asking participants to generate descriptions of how mental disorders are transferred between people. Our findings suggest the importance of understanding contagion beliefs in discovering why people distance themselves from people diagnosed with mental disorders. More generally, our findings help in understanding how our basic category knowledge is used to guide interactions with category members, illustrating how knowledge is translated into action.
Marsh & Kulkofsky (2014): We tested the influence of causal links on the production of memory errors in a misinformation paradigm. Participants studied a set of statements about a person, which were presented as either individual statements or pairs of causally linked statements. Participants were then provided with causally plausible and causally implausible misinformation. We hypothesised that studying information connected with causal links would promote representing information in a more abstract manner. As such, we predicted that causal information would not provide an overall protection against memory errors, but rather would preferentially help in the rejection of misinformation that was causally implausible, given the learned causal links. In two experiments, we measured whether the causal linkage of information would be generally protective against all memory errors or only selectively protective against certain types of memory errors. Causal links helped participants reject implausible memory lures, but did not protect against plausible lures. Our results suggest that causal information may promote an abstract storage of information that helps prevent only specific types of memory errors.
Marsh & Rothman (2013): We explored people's reactions to expert categorizers who expressed difficulty in making a categorization decision. Specifically, we compared people's impressions of expert health professionals who either expressed certainty, uncertainty, or ambivalence about a categorization decision in the form of a diagnosis. We found that ambivalence resulted in the most negative impressions of these experts, including lower ratings of competence and decisiveness (Experiment 1). Impressions of ambivalence did not improve when the complexity of the decision was explicitly manipulated (Experiment 2). Implications for categorization are discussed.
Ahn, Taylor, Kato, Marsh, & Bloom (2013): The current study examines Causal Essentialism, derived from Psychological Essentialism of concepts (Medin & Ortony, 1989). We examine whether people believe that members of a category share some underlying essence that is both necessary and sufficient for category membership and that also causes surface features. The main claim is that Causal Essentialism is restricted to categories that correspond to our intuitive notions of existing kinds, and hence is more attenuated for categories that are based on arbitrary criteria. Experiments 1 and 3 found that people overtly endorse causal essences in non-arbitrary kinds but are less likely to do so for arbitrary categories. Experiments 2 and 4 found that people were more willing to generalize a member's known causal relations (or lack thereof) when dealing with a kind than when dealing with an arbitrary category. These differences between kinds and arbitrary categories were found across various domains - not only categories of living things, but also for artifacts. These findings have certain real-world implications, including how people make sense of mental disorders that are treated as real kinds.
Marsh & Ahn (2012): Mental health clinicians are tasked to diagnose and treat the millions of people worldwide seeking help for mental health issues. This paper investigates the memory clinicians have for patient information. We hypothesize that clinicians encapsulate mental health knowledge through experience into more abstract concepts, as in other domains changing what clinicians remember about patients compared with non-professionals. We tested memory for realistic patient–therapist interactions in experienced clinicians, intermediately trained graduate students, and laypeople. Clinicians recalled fewer facts than intermediate trainees and as many as laypeople. Furthermore, clinicians reported more abstracted information than all other participants, providing the first empirical demonstration of knowledge encapsulation in the memory of mental health clinicians. We discuss how our results fit into the existing literature on clinical expertise in mental health and the implications of our findings for future research relevant to mental health care.
De Los Reyes & Marsh (2011): The purpose of this study was to examine whether contextual information about patients' clinical presentations affected clinicians' judgments of conduct disorder symptoms. Forty-five clinicians read vignettes describing hypothetical patients who displayed one conduct disorder symptom alongside information about the patients' home, school, and peer contexts. Clinicians judged the likelihood of patients meeting conduct disorder criteria. Contextual information highly affected judgments and these effects varied across the 15 conduct disorder symptoms. Importantly, clinical judgments were not in agreement on the symptoms affected by context.
Marsh & Ahn (2009): Existing models of causal induction primarily rely on the contingency between the presence and the absence of a causal candidate and an effect. Yet, classification of observations into these four types of covariation data may not be straightforward because (a) most causal candidates, in real life, are continuous with ambiguous, intermediate values and because (b) effects may unfold after some temporal lag, providing ambiguous contingency information. Although past studies suggested various reasons why ambiguous information may not be used during causal induction, the authors examined whether learners spontaneously use ambiguous information through a process called causal assimilation. In particular, the authors examined whether learners willingly place ambiguous observations into one of the categories relevant to the causal hypothesis, in accordance with their current causal beliefs. In Experiment 1, people's frequency estimates of contingency data reflected that information ambiguous along a continuous quantity dimension was spontaneously categorized and assimilated in a causal induction task. This assimilation process was moderated by the strength of the upheld causal hypothesis (Experiment 2), could alter the overall perception of a causal relationship (Experiment 3), and could occur over temporal sequences (Experiment 4).
Ahn, Marsh, & Luhmann (2007): In discovering causes of events, people evidently use various types of evidence or cues (e.g., Einhorn & Hogarth, 1986). Virtually all models of causal learning (e.g., Cheng, 1997, Rescorla & Wagner, 1972) have focused on how causal relations are learned based on covariation information -- namely, information about whether the presence or absence of one event (C or ~C) co-occurs with the presence or absence of another event (E or ~E). Thus, in all of these models, relevant input data are classified as either CE, ~CE, C~E, or ~C~E, as summarized in Figure 1. Existing models of causal learning have stipulated different ways in which these four types of covariation evidence would or should be combined to evaluate the causal relationship among events. Yet, these models, in their current forms, share an underlying assumption that all events of a given type (e.g., CE) play an identical role in assessing causal strength.
Marsh & Ahn (2006): Dennis and Ahn (2001) found that during contingency learning initial evidence influences causal judgments more than later evidence (a primacy effect), whereas López, Shanks, Almaraz, and Fernández (1998) found the opposite (a recency effect). We propose that in contingency learning, people use initial evidence to develop an anchoring hypothesis that tends to be under-adjusted by later evidence, resulting in a primacy effect. Thus, factors interfering with initial hypothesis development, such as simultaneously learning too many contingencies as in López et al. (1998), would reduce the primacy effect. Experiment 1 found a primacy effect with learning contingencies involving only one outcome, but no primacy effect with two outcomes. Experiment 2 demonstrated that the magnitude of the primacy effect correlated with participants' verbal working memory capacity. It is concluded that a critical moderator for exhibition of the primacy effect is task complexity, presumably because it interferes with initial hypothesis development.
Ahn, Flanagan, Marsh, & Sanislow (2006): Do people believe mental disorders are real and possess underlying essences? The current study found that both novices and practicing clinicians held weaker essentialist beliefs about mental disorders than about medical disorders. They were also unwilling to endorse the idea that mental disorders are real and natural. Furthermore, compared with novices, mental health clinicians were less likely to endorse the view that there is a shared cause underlying a mental disorder and that one needs to remove the cause to get rid of the mental disorder. Clinicians were polarized on their views about whether mental disorders are categorical or dimensional. These findings reflect current controversies about mental disorders in the field at large.
Marsh & Ahn (2006): Studies have found that the causal status of features determines what exemplars are considered good members of a category (see Ahn & Kim, 2000). However, this causal status effect was questioned in recent studies (Rehder, 2003; Rehder & Hastie, 2001), because the preservation of causal links of a category's causal network was shown to play a significant role. We demonstrate in this study that these results are methodological artifacts arising from the use of unnatural wording of category attributes.
Ahn, Levin, & Marsh (2005): What determines which features are more central in concepts? Sloman, Love, and Ahn (1998) examined laypeople's concepts about everyday objects (e.g., chairs and apples) and found that lay theories of these concepts determined feature centrally as much as category validity judgments (i.e., how prevalent features are in a given category) did. The current study examined determinants of feature centrality in 35 clinical psychologists, psychiatrists, and clinical social workers' concepts of Major Depressive Disorder (MDD) and Dysthymic disorder (Dysthymia). Unlike previous findings, we found that category validities were by far the strongest predictor of conceptual centrality in clinicians' concepts of these mental disorders and their theories about these disorders were only a weak, albeit significant, predictor. We discuss possible reasons for this discrepancy.
Marsh & Ahn (2003): The current study investigates how people incorporate ambiguous information into judgments of causal relations. We presented participants with information that was not easily classified into the presence or absence of a candidate cause, breaking a traditional requirement of models of causal induction. We found that people were willing to incorporate this ambiguous information into their collected evidence, instead of ignoring the information as uninformative. Furthermore, people interpreted ambiguous stimuli as evidence most consistent with their prevailing causal hypothesis. These results give an idea of how people begin to determine what can function as a candidate cause in a causal induction problem.
Ahn, Marsh, Luhmann, & Lee (2002): The current study examined what types of feature correlations are salient in our conceptual representations. It was hypothesized that of all possible feature pairs, those that are explicitly recognized as correlated (i.e., explicit pairs) and affect typicality judgments are the ones that are more likely theory-based than those that are not explicitly recognized (i.e., implicit pairs). Real-world categories and their properties taken from Malt and Smith (1984) were examined. We found that explicit pairs had more asymmetric dependency relations (i.e., one feature depends on the other feature, but not vice versa) and stronger dependency relations than implicit pairs which statistically correlated in the environment but were not recognized as such. In addition, people more often provided specific relation labels for explicit pairs than for implicit pairs; these labels were most often causal relations. Finally, typicality judgments were more affected when explicit correlations were broken than when implicit correlations were broken. It is concluded that in natural categories, feature correlations that are explicitly represented and affect typicality judgments are the ones about which people have theories.