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BackgroundIntegrative oncology (IO) appears to be beneficial to patients with cancer, but its implementation remains a challenge. Guided by the Theoretical Domains Framework (TDF) and the Capability-Opportunity-Motivation-Behaviour (COM-B) model, this systematic review identified the barriers to and facilitators of IO implementation in conventional cancer care settings. MethodsWe searched eight electronic databases from their inception until February 2022 for qualitative, quantitative or mixed-methods empirical studies reporting the implementation outcomes for IO services. Critical appraisal approach was tailored according to study types. The identified implementation barriers and facilitators were mapped onto TDF domains and the COM-B model, and subsequently onto the behavioural change wheel (BCW) for formulating behavioural change interventions. ResultsWe included 28 studies (11 qualitative, 6 quantitative, 9 mixed-methods and 2 Delphi studies) of satisfied methodological quality. The main implementation barriers were the lack of IO knowledge, the absence of funding and healthcare professionals low level of IO receptiveness. The key implementation facilitators were the dissemination of evidence on IO clinical benefits, the equipping of professionals with IO service delivery skills and the provision of a supportive organisational climate. ConclusionMultifaceted implementation strategies are needed to address the determinants influencing IO service delivery. Based on our BCW-based analysis of the included studies, the key behavioural change techniques are: (1) educating healthcare professionals about the value and application of traditional and complementary medicine; (2) ensuring access to actionable clinical evidence on IO effectiveness and safety and (3) designing guidelines on communicating traditional and complementary medicine interventions with patients and caregivers for biomedically trained doctors and nurses., Funding Agencies|Chinese Medicine Development Fund of the Hong Kong Special Administrative Region Government [20B2/031A]

Background: A supplementary chapter on the diagnostic patterns of Traditional Medicine, including Traditional Chinese Medicine (TCM), was introduced into the latest edition of the International Classification of Diseases (ICD-11). However, evidence-based rules are yet to be developed for pattern differentiation in patients with specific conventional medicine diagnoses. Without such standardised rules, the level of diagnostic agreement amongst practitioners is unsatisfactory. This may reduce the reliability of practice and the generalisability of clinical research. Purpose: Using cross-sectional study data from patients with functional dyspepsia, we reviewed and illustrated a quantitative approach that combines TCM expertise and computer algorithmic capacity, namely latent tree analysis (LTA), to establish score-based pattern differentiation rules. Review of methods: LTA consists of six major steps: (i) the development of a TCM clinical feature questionnaire; (ii) statistical pattern discovery; (iii) statistical pattern interpretation; (iv) TCM diagnostic pattern identification; (v) TCM diagnostic pattern quantification; and (vi) TCM diagnostic pattern differentiation. Step (i) involves the development of a comprehensive questionnaire covering all essential TCM clinical features of the disease of interest via a systematic review. Step (ii) to (iv) required input from TCM experts, with the algorithmic capacity provided by Lantern, a dedicated software for TCM LTA. Motivational example to illustrate the methods: LTA is used to quantify the diagnostic importance of various clinical features in each TCM diagnostic pattern in terms of mutual information and cumulative information coverage. LTA is also capable of deriving score-based differentiation rules for each TCM diagnostic pattern, with each clinical feature being provided with a numerical score for its presence. Subsequently, a summative threshold is generated to allow pattern differentiation. If the total score of