Prevalence of complex post-traumatic stress disorder in survivors of human trafficking and modern slavery: a systematic review

Background and objectives. The human rights violation of human trafficking and modern slavery could be described as multiple and prolonged traumatisation. This corresponds to the type of trauma identified as most likely to be associated with ‘complex post-traumatic stress disorder’ (CPTSD) as identified in the new 11th edition of the International Classification of Diseases (ICD-11). This review aims to collate the evidence of complex post-traumatic stress disorder in populations that have been trafficked, with the intention to highlight important considerations to be made in terms of managing survivor's health care needs and minimising further traumatisation. Methods Five databases were searched using key terms related to human trafficking, modern slavery, and complex post-traumatic stress disorder. Results Five studies reporting on a total of 342 participants were included in the review. These studies indicated that an average of 41% of survivors of modern slavery and human trafficking had CPTSD. This was higher than the 14% diagnosed with PTSD. Post-trafficking stress, endured whilst living in refugee camps, was higher in individuals with CPTSD than in those living with PTSD. Healthcare was more difficult to access by populations with PTSD and CPTSD compared to those with no diagnosis. Conclusion There is a high prevalence of CPTSD in modern slavery and trafficking survivors therefore a need for identification and specialised treatment. Consideration should be given to consequent biopsychosocial needs, particularly access to healthcare and minimisation of post-trafficking stress.

Prevention of dementia using mobile phone applications (PRODEMOS): protocol for an international randomised controlled trial.

INTRODUCTION: Profiles of high risk for future dementia are well understood and are likely to concern mostly those in low-income and middle-income countries and people at greater disadvantage in high-income countries. Approximately 30%-40% of dementia cases have been estimated to be attributed to modifiable risk factors, including hypertension, smoking and sedentary lifestyle. Tailored interventions targeting these risk factors can potentially prevent or delay the onset of dementia. Mobile health (mHealth) improves accessibility of such prevention strategies in hard-to-reach populations while at the same time tailoring such approaches. In the current study, we will investigate the effectiveness and implementation of a coach-supported mHealth intervention, targeting dementia risk factors, to reduce dementia risk. METHODS AND ANALYSIS: The prevention of dementia using mobile phone applications (PRODEMOS) randomised controlled trial will follow an effectiveness-implementation hybrid design, taking place in the UK and China. People are eligible if they are 55-75 years old, of low socioeconomic status (UK) or from the general population (China); have ≥2 dementia risk factors; and own a smartphone. 2400 participants will be randomised to either a coach-supported, interactive mHealth platform, facilitating self-management of dementia risk factors, or a static control platform. The intervention and follow-up period will be 18 months. The primary effectiveness outcome is change in the previously validated Cardiovascular Risk Factors, Ageing and Incidence of Dementia dementia risk score. The main secondary outcomes include improvement of individual risk factors and cost-effectiveness. Implementation outcomes include acceptability, adoption, feasibility and sustainability of the intervention. ETHICS AND DISSEMINATION: The PRODEMOS trial is sponsored in the UK by the University of Cambridge and is granted ethical approval by the London-Brighton and Sussex Research Ethics Committee (reference: 20/LO/01440). In China, the trial is approved by the medical ethics committees of Capital Medical University, Beijing Tiantan Hospital, Beijing Geriatric Hospital, Chinese People's Liberation Army General Hospital, Taishan Medical University and Xuanwu Hospital. Results will be published in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: ISRCTN15986016.

Predicting dementia from primary care records: A systematic review and meta-analysis.

INTRODUCTION: Possible dementia is usually identified in primary care by general practitioners (GPs) who refer to specialists for diagnosis. Only two-thirds of dementia cases are currently recorded in primary care, so increasing the proportion of cases diagnosed is a strategic priority for the UK and internationally. Variables in the primary care record may indicate risk of developing dementia, and could be combined in a predictive model to help find patients who are missing a diagnosis. We conducted a meta-analysis to identify clinical entities with potential for use in such a predictive model for dementia in primary care. METHODS AND FINDINGS: We conducted a systematic search in PubMed, Web of Science and primary care database bibliographies. We included cohort or case-control studies which used routinely collected primary care data, to measure the association between any clinical entity and dementia. Meta-analyses were performed to pool odds ratios. A sensitivity analysis assessed the impact of non-independence of cases between studies. From a sift of 3836 papers, 20 studies, all European, were eligible for inclusion, comprising >1 million patients. 75 clinical entities were assessed as risk factors for all cause dementia, Alzheimer's (AD) and Vascular dementia (VaD). Data included were unexpectedly heterogeneous, and assumptions were made about definitions of clinical entities and timing as these were not all well described. Meta-analysis showed that neuropsychiatric symptoms including depression, anxiety, and seizures, cognitive symptoms, and history of stroke, were positively associated with dementia. Cardiovascular risk factors such as hypertension, heart disease, dyslipidaemia and diabetes were positively associated with VaD and negatively with AD. Sensitivity analyses showed similar results. CONCLUSIONS: These findings are of potential value in guiding feature selection for a risk prediction tool for dementia in primary care. Limitations include findings being UK-focussed. Further predictive entities ascertainable from primary care data, such as changes in consulting patterns, were absent from the literature and should also be explored in future studies.