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Record W7019185734

FEATURES OF DREAMS OF PATIENTS WITH ANXIETY-DEPRESSIVE DISORDER IN THE CONDITIONS OF INPATIENT TREATMENT IN THE PSYCHONEUROLOGICAL DEPARTMENT

2024· article· en· W7019185734 on OpenAlexaboutno aff

Bibliographic record

VenueThe Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy · 2024
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsnot available
Fundersnot available
KeywordsDreamAnxietyQualitative researchContent analysisAlexithymiaContent (measure theory)Intervention (counseling)Scale (ratio)
DOInot available

Abstract

fetched live from OpenAlex

The article analyzes the use of a qualitative approach to the study of dreams of patients in a psychoneurological hospital with anxiety-depressive disorder through a semi-structured interview in order to formulate a strategy for psychotherapeutic treatment. Purpose of the article.The purpose of the article is to analyze the feasibility of using qualitative methods of content analysis and semi-structured interview to identify key motives and content patterns of dream features of patients with symptoms of mixed anxiety-depressive disorder for a better understanding of the selection of a psychotherapeutic intervention strategy. To achieve this goal, the article analyzes such a key aspect as the limitations of the qualitative approach as a scientific method of dream analysis. Methods. Theoretical analysis of scientific literature and semi-structured qualitative method of dream content analysis were used to compare the results of the two groups. The control group consisted of 50 people who agreed to regularly provide a series of dreams (each provided 5 dreams) recorded using a semi-structured interview questionnaire: "The W. Phillips Dream Processing Plan (modified by M. Kompanowicz). The subjects also filled out the Hospital Anxiety and Depression Scale (HADS) and the Toronto Alexithymia Scale (TAS-26) questionnaires - a significant factor in the formation of the control group was the low level of anxiety and depression, as well as the absence of a pronounced level of alexithymia. Results. The general pattern of the predominance of the descending process as the ego's tendency to disintegrate, as well as the predominance of frustration, was noted. The elements in the experience of anxiety and depression that are found in the context of frustration and disintegration are also classic, in particular, the tendency for the emotional state of patients to worsen after dreams is significant; according to the subjects, dreams only increase the feeling of fatality, the depth of the experience of the wasteland, and increase anxiety, and dreams about the death of relatives or the death of the dreamer's Ego are often interpreted as a "bad omen" and a tendency to catastrophize the future. Originality. The possibility of conducting a content analysis of dreams as a qualitative research method is proved, and the key trends and characteristics of dreams of patients with anxiety-depressive disorder are identified, which is useful in formulating a treatment strategy Conclusions and prospects for further scientific research. The findings have identified recurring trends, motives, and patterns in the limited sample studied; the results are not sufficient to establish clear patterns, as the results cannot be generalized due to the high level of contextual subjectivity. Prospects for further research are to compare the dream material of patients with other disorder nosologies

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.347
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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