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Record W2118568573 · doi:10.1017/s0033291701005086

Functional effects of agents differentially selective to noradrenergic or serotonergic systems

2002· article· en· W2118568573 on OpenAlexaff
Richard Tranter, Helen Healy, Dinah Cattell, D. HEALY

Bibliographic record

VenuePsychological Medicine · 2002
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsUniversity College of the North
Fundersnot available
KeywordsReboxetineSertralineMoodPsychologyPersonalityClinical psychologyHarm avoidanceFluoxetineSerotonergicSassPsychiatryMedicineBig Five personality traitsReuptake inhibitorSerotoninAnxietyInternal medicineSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: The diversity of pharmacological actions of antidepressants suggests that they may bring about their clinical effects by different functional means. METHODS: Twenty healthy volunteers were randomized in a cross-over design to receive 2 weeks of a clinical dose of both reboxetine and sertraline. Baseline assessments of personality were made using the Cloninger Tridimensional Personality Questionnaire and the Karolinska Scales of Personality. Daily and weekly ratings of mood (POMS and PANAS) and quality of life (SASS) were undertaken. RESULTS: Reboxetine and sertraline differed in their effects on the SASS as well as on measures of mood. Reboxetine appeared more likely to be energy enhancing; the effects of sertraline were more difficult to quantify. Personality factors, such as harm avoidance predicted the preference of subjects for these effects and the effect of being on a preferred drug had a significant impact on SASS, and ratings of moods as well as on self-assessments of personality. CONCLUSIONS: The differences reported here are consistent with the original thinking that led to the development of the SSRIs. The findings point to the need for further research on possible differential functional effects of psychotropic agents selective to different brain systems. The findings also have implications for clinical practice, in particular for maintenance treatment with antidepressants.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.900
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.077
GPT teacher head0.339
Teacher spread0.262 · 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.

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

Citations20
Published2002
Admission routes1
Has abstractyes

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