Enhancing inferences and conclusions in body image focused non-experimental research via a causal modelling approach: A tutorial.
Causal diagram
Causal inference
Non-experimental data
Target trial
Journal
Body image
ISSN: 1873-6807
Titre abrégé: Body Image
Pays: Netherlands
ID NLM: 101222431
Informations de publication
Date de publication:
04 Apr 2024
04 Apr 2024
Historique:
received:
20
09
2023
revised:
29
02
2024
accepted:
06
03
2024
medline:
6
4
2024
pubmed:
6
4
2024
entrez:
5
4
2024
Statut:
aheadofprint
Résumé
Causal inference is often the goal of psychological research. However, most researchers refrain from drawing causal conclusions based on non-experimental evidence. Despite the challenges associated with producing causal evidence from non-experimental data, it is crucial to address causal questions directly rather than avoiding them. Here we provide a clear, non-technical overview of the fundamental concepts (including the counterfactual framework and related assumptions) and tools that permit causal inference in non-experimental data, intended as a starting point for readers unfamiliar with the literature. Certain tools, such as the target trial framework and causal diagrams, have been developed to assist with the identification and reduction of potential biases in study design and analysis and the interpretation of findings. We apply these concepts and tools to a motivating example from the body image field. We assert that more precise and detailed elucidation of the barriers to causal inference within one's study is arguably a key first step in the enhancement of non-experimental research and future intervention development and evaluation.
Identifiants
pubmed: 38579514
pii: S1740-1445(24)00026-3
doi: 10.1016/j.bodyim.2024.101704
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
101704Informations de copyright
Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest None.