Evidence map›Paper›PMID 38773706›Full record

ArticleNeuropsychopharmacology reports2024

Cluster analysis of patients with alcohol use disorder featuring alexithymia, depression, and diverse drinking behavior.

Kazuhiro Kurihara, Hiroyuki Enoki, Hotaka Shinzato, Yoshikazu Takaesu, Tsuyoshi Kondo

Abstract read
In one paragraph

Article in Neuropsychopharmacology reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Kazuhiro KuriharaDepartment of Neuropsychiatry, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan.ORCID 0000-0002-2032-3873
Hiroyuki EnokiMajor in Clinical Psychology, Graduate School of Psychological Sciences, Hiroshima International University, Hiroshima, Japan.
Hotaka ShinzatoDepartment of Neuropsychiatry, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan.ORCID 0000-0002-0354-1801
Yoshikazu TakaesuDepartment of Neuropsychiatry, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan.ORCID 0000-0002-9169-3249
Tsuyoshi KondoDepartment of Neuropsychiatry, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan.ORCID 0000-0002-8592-6288

Funding

Japan Society for the Promotion of Science JP17K10311Japan Society for the Promotion of Science JP21K07504
6 · The paper itself

Abstract

aimThis study aimed to identify subgroups of alcohol use disorder (AUD) based on a multidimensional combination of alexithymia, depression, and diverse drinking behavior.

methodWe recruited 176 patients with AUD, which were initially divided into non-alexithymic (n = 130) and alexithymic (n = 46) groups using a cutoff score of 61 on the Toronto Alexithymia Scale (TAS-20). Subsequently, the profiles of the two groups were compared. Thereafter, a two-stage cluster analysis using hierarchical and K-means methods was performed with the Z-scores from the TAS-20, the Quick Inventory of Depressive Symptomatology Self-Report Japanese Version, the 12-item questionnaire for quantitative assessment of depressive mixed state, and the 20-item questionnaire for drinking behavior pattern.

resultsIn the first analysis, Alexithymic patients with AUD showed greater depressive symptoms and more pathological drinking behavior patterns than those without alexithymia. Cluster analysis featuring alexithymia, depression, and drinking behavior identified three subtypes: Cluster 1 (core AUD type) manifesting pathological drinking behavior highlighting automaticity; Cluster 2 (late-onset type) showing relatively late-onset alcohol use and fewer depressive symptoms or pathological drinking behavior; and Cluster 3 (alexithymic type) characterized by alexithymia, depression, and pathological drinking behavior featuring greater coping with negative affect.

conclusionThe multidimensional model with alexithymia, depression, and diverse drinking behavior provided possible practical classification of AUD. The alexithymic subtype may require more caution, and additional support for negative affect may be necessary due to accompanying mood problems and various maladaptive drinking behaviors.

Indexed as

Affective SymptomsAlcoholismDepressionAdultAgedAlcohol DrinkingCluster AnalysisDrinking BehaviorFemaleHumansMaleMiddle Agedalcohol drinking habitsalcohol use disorderalexithymiacluster analysisdepression

Identifiers

PMID38773706
PMCPMC11544455

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.