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Record W2115493774 · doi:10.1016/j.janxdis.2011.06.012

Prospective mental imagery in patients with major depressive disorder or anxiety disorders

2011· article· en· W2115493774 on OpenAlexfundno aff
Nexhmedin Morina, Catherine Deeprose, Christina Pusowski, Marina Schmid, Emily A. Holmes

Bibliographic record

VenueJournal of Anxiety Disorders · 2011
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsnot available
FundersLupina FoundationWellcome Trust
KeywordsAnxietyProspective cohort studyPsychologyMajor depressive disorderAnxiety disorderMental imagePsychiatryDepression (economics)Clinical psychologyCognitionMedicineInternal medicine

Abstract

fetched live from OpenAlex

Prospective negative cognitions are suggested to play an important role in maintaining anxiety disorders and major depressive disorder (MDD). However, little is known about positive prospective mental imagery. This study investigated differences in prospective mental imagery among 27 patients with anxiety disorders, 24 patients with MDD, and 32 control participants. Measures of both deliberately generated and intrusive imagery were completed. Results indicated that both patients with anxiety disorders and those with MDD provided poorer vividness ratings for deliberately generated prospective positive scenarios compared to the control group. Patients with anxiety disorders showed a greater ability to vividly generate imagery for prospective negative scenarios than both patients with MDD and control participants. Finally, both clinical groups reported greater levels of intrusive prospective imagery of personally-relevant events as compared to the control group. The current findings underline the necessity to target prospective positive mental imagery in treating MDD and anxiety disorders.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.271
Teacher spread0.260 · 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

Citations234
Published2011
Admission routes1
Has abstractyes

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