2022
DOI: 10.1037/xge0001096
|View full text |Cite
|
Sign up to set email alerts
|

The conceptual building blocks of everyday thought: Tracking the emergence and dynamics of ruminative and nonruminative thinking.

Abstract: How do thoughts arise, unfold, and change over time? Are the contents and dynamics of everyday thought rooted in conceptual associations within one’s semantic networks? To address these questions, we developed the Free Association Semantic task (FAST), whereby participants generate dynamic chains of conceptual associations in response to seed words that vary in valence. Ninety-four adults from a community sample completed the FAST task and additionally described and rated six of their most frequently occurring… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
14
0
1

Year Published

2022
2022
2023
2023

Publication Types

Select...
7

Relationship

2
5

Authors

Journals

citations
Cited by 20 publications
(23 citation statements)
references
References 80 publications
(113 reference statements)
0
14
0
1
Order By: Relevance
“…For example, as shown in the current study, the dynamic modeling combined with machine learning has the potential to be used as an assessment tool for depression and anxiety in adjunct to self-report. Even in the absence of participant’s own self-report ratings, we previously showed in a behavioral FAST study that the affective dynamics of thought predicted individual differences in trait rumination ( 12 ), a common symptom of mood and anxiety disorders. Thus, if we can implement an automated sentiment analyzer into the analysis pipeline, we can shorten the task time markedly, providing a possibility to use the FAST as a web- or mobile-based monitoring tool for depression and anxiety.…”
Section: Discussionmentioning
confidence: 98%
See 3 more Smart Citations
“…For example, as shown in the current study, the dynamic modeling combined with machine learning has the potential to be used as an assessment tool for depression and anxiety in adjunct to self-report. Even in the absence of participant’s own self-report ratings, we previously showed in a behavioral FAST study that the affective dynamics of thought predicted individual differences in trait rumination ( 12 ), a common symptom of mood and anxiety disorders. Thus, if we can implement an automated sentiment analyzer into the analysis pipeline, we can shorten the task time markedly, providing a possibility to use the FAST as a web- or mobile-based monitoring tool for depression and anxiety.…”
Section: Discussionmentioning
confidence: 98%
“…Participants were asked to generate a total of 40 consecutive concepts for each seed word, and we used four seed words for four runs total. We made the number of associations for each seed word much longer than our previous study ( 12 ), in which we collected only 10 consecutive concepts to obtain a larger number of personal concepts. The four seed words were “family,” “tear,” “mirror,” and “abuse” for the first session and “love,” “fantasy,” “heart,” and “pain” for the retest session.…”
Section: Methodsmentioning
confidence: 99%
See 2 more Smart Citations
“…To simplify the problem, we focus here on thought control in the specific case of associative memory retrieval. Tasks probing associative memory are a useful tool for investigating thought processes, as evidenced by the relationship between people’s responses in a free association task and their everyday thoughts [ 20 ]. Numerous studies have demonstrated people’s ability to intentionally forget memories learned in the lab.…”
Section: Introductionmentioning
confidence: 99%