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Record W3157577308 · doi:10.3389/fpsyt.2021.587122

Informing About the Nocebo Effect Affects Patients’ Need for Information About Antidepressants—An Experimental Online Study

2021· article· en· W3157577308 on OpenAlexaff
Yvonne Nestoriuc, Yiqi Pan, Timm Kinitz, Ella Weik, Meike Shedden‐Mora

Bibliographic record

VenueFrontiers in Psychiatry · 2021
Typearticle
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsBC Mental Health & Substance Use ServicesUniversity of British Columbia
FundersDeutsche Forschungsgemeinschaft
KeywordsNocebo EffectAlgorithmMedicineNoceboCategorical variableArtificial intelligenceMachine learningComputer sciencePsychologyPlaceboClinical psychologyAlternative medicine

Abstract

fetched live from OpenAlex

Relevance: Understanding patients’ informational needs and adapting drug-related information are the prerequisites for a contextualized informed consent. Current information practices might rather harm by inducing nocebo effects. Objective: To investigate whether informing about the nocebo effect using a short information sheet affects patients’ need for information about antidepressants. Methods: A total of 97 patients taking recently prescribed antidepressants (≤4 months intake) were recruited over the internet and randomized to receiving either a one-page written information about the nocebo effect or a control text about the history of antidepressants. After experimental manipulation, informational needs about the side effects and mechanisms of antidepressants were assessed with 3 and 7 items on categorical and 5-point Likert scales. Group differences in informational needs were calculated with Chi-square tests and ANOVAs. Results: Patients received antidepressants for depression (84.5%) and/or anxiety disorders (42.3%). Three participants (6.0%) of the nocebo group reported previous knowledge of the nocebo effect. After the experimental manipulation, participants in the nocebo group reported a reduced desire for receiving full side effect information [ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:msubsup><mml:mrow><mml:mi>X</mml:mi></mml:mrow><mml:mrow><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:mn>4</mml:mn><mml:mo>,</mml:mo><mml:mn>97</mml:mn></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msubsup></mml:math> = 12.714, Cramer’s V = 0.362, p = 0.013] and agreed more frequently to the usefulness of withholding information about possible side effects [ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:msubsup><mml:mrow><mml:mi>X</mml:mi></mml:mrow><mml:mrow><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:mn>4</mml:mn><mml:mo>,</mml:mo><mml:mn>97</mml:mn></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msubsup></mml:math> = 14.878, Cramer’s V = 0.392, p = 0.005]. Furthermore, they desired more information about the mechanisms of antidepressants ( F = 6.373, p = 0.013, partial η 2 = 0.063) and, specifically, non-pharmacological mechanisms, such as the role of positive expectations ( F = 16.857, p &amp;lt; 0.001, partial η 2 = 0.151). Conclusions: Learning about the nocebo effect can alter patients’ informational needs toward desiring less information about the potential side effects of antidepressants and more information about general mechanisms, such as expectations. The beneficial effects of including nocebo information into contextualized informed consent should be studied clinically concerning more functional information-seeking behavior, which may ultimately lead to improved treatment outcomes, such as better adherence and reduced side effect burden.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.163
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.280
Teacher spread0.268 · 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

Citations31
Published2021
Admission routes1
Has abstractyes

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