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Cited by 338

The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.

Dimensions of Alexithymia and Their Relationships to Anxiety and Depression

Hendryx, Michael S., Haviland, Mark G., Shaw, Dale G.·1991·Journal of Personality Assessment

Abstract

Investigators have suggested that alexithymia is a multidimensional construct and that it is responsive to situational stressors. We tested these hypotheses in a sample of 110 freshman medical students. We conducted factor analyses on the Toronto Alexithymia Scale (TAS), the Beck Depression Inventory (BDI), and the state portion of the State-Trait Anxiety Inventory (STAI) and then used LISREL to examine the relationships among the various factors. The results indicated that the TAS consists of several independent dimensions and that the dimensions associated with difficulties identifying and communicating feelings are positively related to depression and anxiety. Thus, the evidence now affirms that alexithymia (as measured by the TAS) is multidimensional and that certain dimensions are state dependent.

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Metadata

Authors
Hendryx, M. S., Haviland, M. G., & Shaw, D. G.
Venue
Journal of Personality Assessment
Published
1991-04
Volume
56
Issue
2
Pages
227-237
ISSN
  • 0022-3891 (ISSN-L)
  • 1532-7752
OpenAlex
W1965222967
Cited by
338
References
27
FWCI
4.01
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Dimensions of Alexithymia and Their Relationships to Anxiety and Depression. https://app.cochat.ai/papers/10.1207/s15327752jpa5602_4
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Hendryx, M. S., Haviland, M. G., & Shaw, D. G. (1991). Dimensions of Alexithymia and Their Relationships to Anxiety and Depression. Journal of Personality Assessment. https://doi.org/10.1207/s15327752jpa5602_4

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.