ArticleHealth psychology review2020
Semi-Automated evidence synthesis in health psychology: current methods and future prospects.
Article in Health psychology review, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Understanding and predicting health behaviour change: a contemporary view through the lenses of meta-reviews.Health psychology review · 2020Pooled it
- Artificial Intelligence Software to Accelerate Screening for Living Systematic Reviews.Clinical child and family psychology review · 2026Article
- The landscape of artificial intelligence tools and platforms for evidence synthesis: a scoping review.Systematic reviews · 2026Article
- StudyTypeTeller-Large language models to automatically classify research study types for systematic reviews.Research synthesis methods · 2025Article
- Article
- Applying the Non-adoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) framework to evaluate automated evidence synthesis in health behaviour change.Journal of health psychology · 2024Review
- STEED: A data mining tool for automated extraction of experimental parameters and risk of bias items from in vivo publications.PloS one · 2024Article
- Ensuring Prevention Science Research is Synthesis-Ready for Immediate and Lasting Scientific Impact.Prevention science : the official journal of the Society for Prevention Research · 2022Article
- Artificial Intelligence and Behavioral Science Through the Looking Glass: Challenges for Real-World Application.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2020Review
- Perspective: Towards Automated Tracking of Content and Evidence Appraisal of Nutrition Research.Advances in nutrition (Bethesda, Md.) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The evidence base in health psychology is vast and growing rapidly. These factors make it difficult (and sometimes practically impossible) to consider all available evidence when making decisions about the state of knowledge on a given phenomenon (e.g., associations of variables, effects of interventions on particular outcomes). Systematic reviews, meta-analyses, and other rigorous syntheses of the research mitigate this problem by providing concise, actionable summaries of knowledge in a given area of study. Yet, conducting these syntheses has grown increasingly laborious owing to the fast accumulation of new evidence; existing, manual methods for synthesis do not scale well. In this article, we discuss how semi-automation via machine learning and natural language processing methods may help researchers and practitioners to review evidence more efficiently. We outline concrete examples in health psychology, highlighting practical, open-source technologies available now. We indicate the potential of more advanced methods and discuss how to avoid the pitfalls of automated reviews.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.