Evidence map›Paper›PMID 28572780›Full record

ArticleFrontiers in psychology2017

Modeling Psychological Attributes in Psychology - An Epistemological Discussion: Network Analysis vs. Latent Variables.

Hervé Guyon, Bruno Falissard, Jean-Luc Kop

Abstract read
In one paragraph

Article in Frontiers in psychology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

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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

3 authors.

Hervé GuyonINSERM U1018, CESP, APHP, Université Paris-Sud, UVSQ, Université Paris-SaclayVillejuif, France.
Bruno FalissardINSERM U1018, CESP, APHP, Université Paris-Sud, UVSQ, Université Paris-SaclayVillejuif, France.
Jean-Luc KopLaboratoire Interpsy - 2LPN (CEMA), Université de LorraineNancy, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Network Analysis is considered as a new method that challenges Latent Variable models in inferring psychological attributes. With Network Analysis, psychological attributes are derived from a complex system of components without the need to call on any latent variables. But the ontological status of psychological attributes is not adequately defined with Network Analysis, because a psychological attribute is both a complex system and a property emerging from this complex system. The aim of this article is to reappraise the legitimacy of latent variable models by engaging in an ontological and epistemological discussion on psychological attributes. Psychological attributes relate to the mental equilibrium of individuals embedded in their social interactions, as robust attractors within complex dynamic processes with emergent properties, distinct from physical entities located in precise areas of the brain. Latent variables thus possess legitimacy, because the emergent properties can be conceptualized and analyzed on the sole basis of their manifestations, without exploring the upstream complex system. However, in opposition with the usual Latent Variable models, this article is in favor of the integration of a dynamic system of manifestations. Latent Variables models and Network Analysis thus appear as complementary approaches. New approaches combining

Indexed as

complex systemsepistemology in psychologyLatent Network modelsLatent VariablesNetwork Analysispragmatism-realismpsychological attributes

Identifiers

PMID28572780
PMCPMC5435770

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.