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Record W2128400350 · doi:10.1177/070674370505001304

I Have the Answer, Now What's the Question?: Why Metaanalyses Do Not Provide Definitive Solutions

2005· editorial· en· W2128400350 on OpenAlexvenueno aff
David L. Streiner

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2005
Typeeditorial
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsnot available
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

(Can J Psychiatry 2005;50:829-831) It ain't so much the things we don't know that get us in trouble. It's the things we know that just ain't so. -Artemus Ward In a recent issue of the British Medical Journal, Moncrieff and Kirsch (1 ) concluded that Recent meta-analyses show selective serotonin reuptake inhibitors [SSRIs] have no clinically meaningful advantage over placebo and that Methodological artefacts may account for the small degree of superiority shown over placebo. Needless to say, this article generated a large number of letters to the editor, citing everything from despair about the lack of available alternatives to charges that the authors overlooked or ignored evidence about the positive effects of SSRIs, that they misinterpreted the findings and recommendations of the National Institute for Health and Clinical Excellence (NICE), that both the authors and NICE used inappropriate criteria to evaluate improvement, that the authors made erroneous assumptions about the distribution of depression, and so on. This editorial does not aim to critique the article by Moncrieff and Kirsch. Rather, it tries to explain why different people with honourable intentions can come to different conclusions regarding metaanalyses. Suffice it to say for now that their summary and recommendations are by no means accepted by all. Other metaanalyses (for example, 2-4), including one coauthored by Moncrieff (5), have supported the use of SSRIs; this article has merely brought the controversy to a head. The fact is that Moncrieff and Kirsch' s conclusions should not come as a surprise. Fourteen years ago, Greenberg and others (6) came to similar conclusions regarding the effectiveness (or rather, the lack thereof) of the older class of tricyclic antidepressants (TCAs). What some may find strange is why this debate (and similar ones regarding the effectiveness of interventions ranging from screening for breast cancer to the use of cholinesterase inhibitors in Alzheimer's disease) is still going on. After all, weren't we promised that metaanalyses would provide definitive answers to questions such as these? Metaanalysis is predicated on the assumption (or it may be more a belief and hope) that objectivity regarding the criteria used for conducting literature searches, selecting the articles to include or exclude, and abstracting and summarizing the findings would result in unbiased and unequivocal answers. In some hierarchies of evidence, metaanalyses are at the top, trumping even very large randomized controlled trials (7). Since Smith and Glass's pioneering 1977 metaanalysis of psychotherapy (8), there has been an exponential explosion in the number published in the medical and psychological literature. Doing a simple Medline and PsycLit search, using just the keyword metaanalysis, I found that there were 3 published in 1981, 422 in 1991, and 1712 in 2003. Indeed, there are international organizations, such as the Cochrane Collaboration in medicine and the Campbell Collaboration in the social sciences, devoted exclusively to conducting and publishing metaanalyses. Further, there are regularly published compendia of treatment recommendations based on their results (9). The fact is, though, that disagreements among metaanalyses of the same topic are quite common. Oxman and Guyatt found that 5 reviews about the need to treat mild hypertension all resulted in different recommendations (10), and Munsinger (11) and Kamin (12), reviewing the same articles about environmental effects on intelligence, came to diametrically opposite conclusions. Indeed, our review of the effectiveness of TCAs (13) disagreed with Greenberg and others' findings (6). The reality is that, despite the claims of true believers, metaanalysis is neither a purely objective, mechanical process nor a panacea for answering all questions. There are 2 major reasons why metaanalyses may differ with regard to the conclusions they draw: methodological considerations and interpretation. …

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 categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.662
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.003
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 head0.025
GPT teacher head0.307
Teacher spread0.282 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations19
Published2005
Admission routes1
Has abstractyes

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