Dataset Information

Autism traits outweigh alexithymia traits in the explanation of mentalising performance in adults with autism but not in adults with rejected autism diagnosis.

ABSTRACT:

Background

Pronounced alexithymia traits have been found in autism spectrum disorder (ASD) and recent research has been carving out the impact alexithymia traits might have on mentalising deficits associated with ASD.

Method

In this cross-sectional study, a large representative referral population for diagnostic examination for possible ASD (n = 400) was screened for clinical alexithymia with a German version of the Reading the Mind in the Eyes test (RME). In contrast to previous attempts to carve out the impact of alexithymia traits on mentalising deficits though, we employed dominance analysis to account for the correlation between predictors. The relative relationship between alexithymia traits and autism traits with RME performance was investigated in the group of individuals with confirmed ASD diagnosis (N = 281) and compared to the clinical referral sample in which ASD was ruled out (N = 119).

Results

Dominance analysis revealed autism traits to be the strongest predictor for reduced mentalising skills in the ASD sample, whereas alexithymia contributed significantly less. In the sample of individuals with ruled out diagnosis, autism traits were the strongest predictor, but alexithymia traits were in sum equally associated to mentalising, with the External-Oriented Thinking subscale as an important predictor of this association.

Limitations

It needs to be considered that the cross-sectional study design does not allow for causal inference. Furthermore, mentalising is a highly facetted capacity and measurements need to reduce this complexity into simple quantities which limits the generalizability of results.

Discussion

While alexithymia traits should be considered for their mental health importance, they do not dominate the explanation of reduced mentalising skills in individuals with ASD, but they might do to a larger degree in individuals with ruled out ASD.

SUBMITTER: Falter-Wagner CM

PROVIDER: S-EPMC9264711 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundSelf-explanation without feedback has been shown to improve medical students' diagnostic reasoning. While feedback is generally seen as beneficial for learning, available evidence of the value of its combination with self-explanation is conflicting. This study investigated the effect on medical students' diagnostic performance of adding immediate or delayed content-feedback to self-explanation while solving cases.MethodsNinety-four 3rd-year students from a Canadian medical school were randomly assigned to three experimental conditions (immediate-feedback, delayed-feedback, control). In the learning phase, all students solved four clinical cases by giving i) the most likely diagnosis, ii) two main arguments supporting this diagnosis, and iii) two plausible alternative diagnoses, while using self-explanation. The immediate-feedback group was given the correct diagnosis after each case; delayed-feedback group received the correct diagnoses only after the four cases; control group received no feedback. One week later, all students solved four near-transfer (i.e., same final diagnosis as the learning cases but different scenarios) and four far-transfer cases (i.e., different final diagnosis from the learning cases and different scenarios) by answering the same three questions. Students' diagnostic accuracy (score for the response to the first question only) and diagnostic performance (combined score of responses to the three questions) scores were assessed in each phase. Four one-way ANOVAs were performed on each of the two scores for near and far-transfer cases.ResultsThere was a significant effect of experimental condition on diagnostic accuracy on near-transfer cases (p < .05). The immediate-feedback and delayed-feedback groups performed equally well, both better than control (respectively, mean = 90.73, standard deviation =10.69; mean = 89.92, standard deviation = 13.85; mean = 82.03, standard deviation = 17.66). The experimental conditions did not significantly differ on far-transfer cases.ConclusionsProviding feedback to students in the form of the correct diagnosis after using self-explanation with clinical cases is potentially beneficial to improve their diagnostic accuracy but this effect is limited to similar cases. Further studies should explore how more elaborated feedback combined with self-explanation may impact students' diagnostic performance on different cases.