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Record W4399118153 · doi:10.1016/j.jpain.2024.104582

Treatment Expectations—You Get What You Expect—and Depression Plays a Role

2024· article· en· W4399118153 on OpenAlexfundno aff
Claudia Levenig, Monika Hasenbring, Lea Günnewig, Christina Titze, Sigrid Elsenbruch, Tobias L. Schulte

Bibliographic record

VenueJournal of Pain · 2024
Typearticle
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsnot available
FundersRuhr-Universität BochumDeutsche ForschungsgemeinschaftFORUM PharmaceuticalsFaculty of Medicine, University of British Columbia
KeywordsDepression (economics)PsychologyEconomicsKeynesian economics

Abstract

fetched live from OpenAlex

Positive treatment expectations demonstrably shape treatment outcomes regarding pain and disability in patients with chronic low back pain. However, knowledge about positive and negative treatment expectations as putative predictors of interindividual variability in treatment outcomes is sparse, and the role of other psychological variables of interest, especially of depression as a known predictor of long-term disability, is lacking. We present results of the first prospective study considering expectations in concert with depression in a sample of 200 patients with chronic low back pain undergoing an inpatient interdisciplinary multimodal pain therapy. We analyzed the characteristics of pain and disability, treatment expectation, and depression assessed at the beginning (T0), at the end of (T1), and at 3-month follow-up (T2) of interdisciplinary multimodal pain therapy. Treatment expectations did emerge as a significant predictor of changes in pain intensity and disability, respectively, showing that positive expectations were associated with better treatment outcomes. Mediation analyses revealed a partially mediating effect of treatment expectations on the relation between depression and pain outcomes. PERSPECTIVE: These results expand knowledge regarding the role of treatment expectations in individual treatment outcome trajectories in chronic pain patients, paving the way for much-needed efforts toward optimizing patient expectations and personalized approaches in clinical settings.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.691
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.019
GPT teacher head0.280
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations15
Published2024
Admission routes1
Has abstractyes

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