PhD Scientific Days 2024

Poster Session G - Mental Health Sciences 2.

The cognitive processing of social functioning dependent on mental problems in a linguistic approach

Előadó neve

Ms. Kovács, Zsanett

Neptun code

NMHEHL

Előadó munkahelye

Semmelweis University

Előadó telefonszáma

06302072022

Előadó e-mail címe

ling.zsana@gmail.com

Az előadás címe

The cognitive processing of social functioning dependent on mental problems in a linguistic approach

Szerző(k) neve és munkahelye

Zsanett Kovács¹

1: Semmelweis University

Bemutatás módja

Poszter

Szekció

Poster Session G - Mental Health Sciences 2.

Language of the presentation

Hungarian

Preferred session

Mental Health Sciences

Összefoglaló szövege

Introduction:
Our social functioning is affected by the cognitive processing of our social relationships. Self-reported questionnaires are accepted methods to measure consciously available social representations. Our implicit cognitive processing of social information could be detected by measuring the reaction time differences between socially relevant, potentially relevant, and irrelevant words.

Aims:
In our study, we tested the hypothesis of whether certain socially relevant words have longer reaction times and are made to be mistaken more often than the irrelevant words in the Emotional Stroop Task (EST) and the Lexical Decision Task (LDT). Our other aim is also to highlight actual words that can trigger people, which is to be seen through reaction times.

Method:
An online test package was advertised primarily on Facebook. This pilot study includes 30 anonymous participants. The test package was made by PsychoPy-2024.1.1, and contains questions about demographic data, mental health data, three tasks (EST, LDT, and Words Emotional Value and Intrusiveness Scale), and five types of questionnaires (Beck Depression Questionnaire, Borderline Personality Disorder Screening questionnaire, Early Trauma Questionnaire, certain parts of Young Schema Questionnaire, and Adult Attachment Questionnaire). The tasks were based on selected words, which were separated in threee groups as socially relevant, potentially relevant (certain pronoms), and irrelevant (neutral) words.

Results:
At this stage of the data processing our analysis showed not to have significantly relevant differences between socially relevant (t=0.66; p=0.52), potentially relevant (t=0.27; p=0.79), and irrelevant words (t=-0.39; p=0.7) when it is related to whether participants have mental problems or not. On the other hand, we found the reactiontime of "billentyűzettel" (F=4.12; p=0.05) and "megbocsátok" (F=4.19; p=0.05) showed significant relation with mental problems.

Conclusion:
In the further stage of the study more participants and Machine learning specifically Cluster analysis is needed to classify wordforms by other aspects.

Funding:
No funding.

University

Semmelweis University

Supervisor

Dr. Zsolt Unoka, Dr. Anna Babarczy

Publication of my abstract

I give consent to the publication of my abstract on the website of the congress.

Kind

Szabad

Status

elfogadva

Accepted presentation method

poszter

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

8107

Start

14:55

End

14:58