Evidence map›Paper›PMID 30940225›Full record

ArticleThe Behavioral and brain sciences2019

Families of network structures - we need both phenomenal and explanatory models.

Tony Ward, Ronald Fischer

Abstract readComment
PubMed Publisher
In one paragraph

Article in The Behavioral and brain sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Tony WardSchool of Psychology,Victoria University of Wellington,PO Box 600,Wellington,New Zealand.Tony.Ward@vuw.ac.nzRonald.Fischer@vuw.ac.nzhttps://mindcultureevolution.com/.
Ronald FischerSchool of Psychology,Victoria University of Wellington,PO Box 600,Wellington,New Zealand.Tony.Ward@vuw.ac.nzRonald.Fischer@vuw.ac.nzhttps://mindcultureevolution.com/.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Symptom network models (SNWMs) play an important role in identifying but not explaining patterns of symptoms. We discuss underlying assumptions of SNWMs and argue that they represent phenomenal models, best suited to detecting patterns among symptoms. SNWMs need to be supplemented with mechanistic models that provide constitutive and etiological explanations of each symptom (network nodes) once relevant patterns have been identified.

Indexed as

Brain DiseasesPsychopathologyHumansResearch

Identifiers

PMID30940225

What OpenQuestion holds

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Registered trials

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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.