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Record W7054562238

Acceptance and Commitment Therapy for Depression after Psychosis: autobiographical memory specificity and rumination as candidate mechanisms of change:
\n and Clinical research portfolio

2019· dissertation· en· W7054562238 on OpenAlexaboutno aff

Bibliographic record

VenueEnlighten: Theses (The University of Glasgow) · 2019
Typedissertation
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsRuminationAutobiographical memoryContext (archaeology)Schizophrenia (object-oriented programming)MindfulnessBeck Depression InventoryRecallDepression (economics)
DOInot available

Abstract

fetched live from OpenAlex

Background: Understanding how interventions work is a key step in the development and evaluation of complex interventions. Based on previous research, autobiographical memory specificity and rumination are candidate mechanisms of change. Our aim was to explore mechanisms of therapeutic change in the context of a pilot trial of Acceptance and Commitment Therapy (ACT) for people with a diagnosis of schizophrenia and major depression. 
\nMethod: The ACT for Depression After Psychosis Trial (ADAPT; Gumley et al., 2017) provided repeated measures data that allowed exploration of the change process in ACT for depression after psychosis. Participants who met criteria for schizophrenia and major depression were randomly allocated to standard care or standard care plus up to 5-months of individual ACT for depression after psychosis (ACTdp). Primary outcomes administered on entry to the study (pre-randomisation), at 5-months (posttreatment), and at 10-months (follow up) included the Beck Depression Inventory (BDI), Calgary Depression Scale for Schizophrenia (CDSS), the Kentucky Inventory of Mindfulness Skills (KIMS), and the Acceptance and Action Questionnaire (AAQ). Candidate mechanisms of change were assessed using Ruminative Response Scale (RRS) and the Autobiographical Memory Test (AMT). 
\nResults: Significant correlations between change scores were found for BDI and proposed mechanisms of change at 5-months (Rumination: r = 0.60, p< .05; Overgeneral memory responses: r = 0.67, p < .05; memory recall latency: r = -0.84, p< .01) and 10-months (Rumination: r = 0.80, p < .01; Overgeneral memory responses: r = 0.61, p < .01). Changes in CDSS depression and rumination scores were significantly correlated at 10-months (Rumination: r = 0.76, p < .01). In order to examine hypotheses that aspects of autobiographical memory specificity would vary by treatment group, cue word valence, and time of assessment, three-way mixed ANOVAs were performed for percentage of overgeneral memories recalled, and emotional tone of events recalled. Significantly more overgeneral responses were recalled for negative cue words (F (1, 22) = 17.817, p < .001, partial eta squared = .447). Additionally, significantly more negative feeling was evoked for memories recalled in response to negative cue words (F (1, 17) = 83.232, p < .001, partial eta squared = .839). A threeway interaction was found for cue word x time point x treatment group’s effect on feeling evoked by memories recalled (F (2, 15) = 6.251, p < .013, partial eta squared = .455). Post-hoc analysis found the negative feeling evoked by memories recalled in response to negative cue words was significantly reduced in the ACT group posttreatment. For the ACT group, the difference between mean feeling evoked to negative cue words at baseline and 5-months was 2.72, (95% CI [-5.115, -0.318], p < .013). 
\nApplication: This study provides insight into the change mechanisms through which interventions like ACTdp may produce beneficial effects. Preliminary findings suggest ACT may facilitate positive change for those experiencing depression after psychosis by reducing cognitive avoidance and enhancing ability to tolerate recollection and discussion of emotionally challenging events.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.775
Threshold uncertainty score0.628

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.042
GPT teacher head0.307
Teacher spread0.265 · 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 teacher head, 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
Published2019
Admission routes1
Has abstractyes

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