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Table 2 Challenges facing evidence synthesis and interpretation in behaviour change

From: The Human Behaviour-Change Project: harnessing the power of artificial intelligence and machine learning for evidence synthesis and interpretation

Challenge Solution
Research methods: Diversity of research methods and topics, and inconsistency and incompleteness in reporting of study methods and findings Development and application of an ontology of behaviour change interventions
Human limitations: Insufficient human resources to undertake reviews and syntheses in a timely manner given the volume of findings and increasing rate of evidence accumulation Use of automated literature searching and study feature extraction
Research findings: Equivocal or contradictory findings, sparseness of findings relative to the number and variety of behaviours, interventions, populations and settings about which information is required, complexity of interactions between intervention components, populations, settings and behavioural outcomes Use of machine learning and reasoning algorithms for evidence synthesis and interpretation. Focus will be on methods providing a confidence level associated with the prediction so as to be able to rigorously incorporate conflicting and missing information