Evidence map›Paper›PMID 28695475›Full record

ArticleTheoretical medicine and bioethics2017

Symptom modelling can be influenced by psychiatric categories: choices for research domain criteria (RDoC).

Sam Fellowes

Open access · hybridAbstract read
In one paragraph

Article in Theoretical medicine and bioethics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
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  5. Understanding disease and illness.Theoretical medicine and bioethics · 2017
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Sam FellowesDepartment of Politics, Philosophy and Religion, Lancaster University, Lancaster, LA1 4YL, UK. m.fellowes1@lancaster.ac.uk.
Lancaster University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Psychiatric researchers typically assume that the modelling of psychiatric symptoms is not influenced by psychiatric categories; symptoms are modelled and then grouped into a psychiatric category. I highlight this primarily through analysing research domain criteria (RDoC). RDoC's importance makes it worth scrutinizing, and this assessment also serves as a case study with relevance for other areas of psychiatry. RDoC takes inadequacies of existing psychiatric categories as holding back causal investigation. Consequently, RDoC aims to circumnavigate existing psychiatric categories by directly investigating the causal basis of symptoms. The unique methodological approach of RDoC exploits the supposed lack of influence of psychiatric categories on symptom modelling, taking psychiatric symptoms as the same regardless of which psychiatric category is employed or if no psychiatric category is employed. But this supposition is not always true. I will show how psychiatric categories can influence symptom modelling, whereby identical behaviours can be considered as different symptoms based on an individual's psychiatric diagnosis. If the modelling of symptoms is influenced by psychiatric categories, then psychiatric categories will still play a role, a situation which RDoC researchers explicitly aim to avoid. I discuss four ways RDoC could address this issue. This issue also has important implications for factor analysis, cluster analysis, modifying psychiatric categories, and symptom based approaches.

Indexed as

Biomedical ResearchMental DisordersChoice BehaviorHumansPsychiatryDSMFactor analysisPsychiatric categoriesRDoCSymptom-based approachesSymptoms

Identifiers

PMID28695475
PMCPMC5522519
OpenAlexW2736107958

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.