Modern healthcare research has only in recent years investigated the impact of health care workers’ religious and other moral values on medical practice, interaction with patients, and ethically complex decision-making. Thus far, no international data exist on the way such values vary across different countries. We therefore established the NERSH International Collaboration on Values in Medicine with datasets on physician religious characteristics and values based on the same survey instrument. The present article provides (a) an overview of the development of the original and optimized survey instruments, (b) an overview of the content of the NERSH data pool at this stage and (c) a brief review of insights gained from articles published with the questionnaire. The questionnaire was developed in 2002, after extensive pretesting in the United States and subsequently translated from English into other languages using forward-backward translations with Face Validations. In 2013, representatives of several national research groups came together and worked at optimizing the survey instrument for future use on the basis of the existing datasets. Research groups were identified through personal contacts with researchers requesting to use the instrument, as well as through two literature searches. Data were assembled in Stata and synchronized for their comparability using a matched intersection design based on the items in the original questionnaire. With a few optimizations and added modules appropriate for cultures more secular than that of the United States, the survey instrument holds promise as a tool for future comparative analyses. The pool at this stage consists of data from eleven studies conducted by research teams in nine different countries over six continents with responses from more than 6000 health professionals. Inspection of data between groups suggests large differences in religious and other moral values across nations and cultures, and that these values account for differences in health professional’s clinical practices.

Nas duas últimas décadas, os estudos sobre a relação entre espiritualidade e saúde tem crescido significativamente no cenário internacional. No Brasil, as pesquisas nesse campo ganharam maior visibilidade a partir de 2009, sobretudo nas Ciências da Saúde, onde começou a aparecer o termo “cuidado espiritual”. Na Teologia, estudos sobre cuidado espiritual dentro do contexto da saúde são escassos. Este artigo pretende contribuir com a ampliação desta reflexão. Primeiramente, o cuidado espiritual é abordado a partir da produção científica em língua portuguesa. Em seguida, o modelo interdisciplinar de cuidado espiritual é apresentado como uma abordagem holística de cuidado ao paciente e também são delineadas as consequências da aplicação de um modelo de cuidado espiritual. Discute-se ainda, o papel novo e recém definido dos capelães hospitalares, conselheiros pastorais e cuidadores espirituais. O texto conclui mencionando os principais desafios que acompanham o cuidado espiritual interdisciplinar, especialmente aqueles que dizem respeito ao treinamento dos profissionais do cuidado em saúde.

Aims: Most prediction models for coronary artery disease (CAD) compile biomedical and behavioural risk factors using linear multivariate models. This study explores the potential of integrating positive psychosocial factors (PPFs), including happiness, satisfaction with life, and social support, into conventional and machine learning–based CAD-prediction models. Methods and results: We included UK Biobank (UKB) participants without CAD at baseline. First, we estimated associations of individual PPFs with subsequent acute myocardial infarction (AMI) and chronic ischaemic heart disease (CIHD) using logistic regression. Then, we compared the performances of logistic regression and eXtreme Gradient Boosting (XGBoost) prediction models when adding PPFs as predictors to the Framingham Risk Score (FRS). Based on a sample size between 160 226 and 441 419 of UKB participants, happiness, satisfaction with health and life, and participation in social activities were linked to lower AMI and CIHD risk (all P-for-trend ≤ 0.04), while social support was not. In a validation sample, adding PPFs to the FRS using logistic regression and XGBoost prediction models improved neither AMI [area under the receiver operating characteristic curve (AUC) change: 0.02 and 0.90%, respectively] nor CIHD (AUC change: −1.10 and −0.88%, respectively) prediction. Conclusion: Positive psychosocial factors were individually linked to CAD risk, in line with previous studies, and as reflected by the new European Society of Cardiology guidelines on cardiovascular disease prevention. However, including available PPFs in CAD-prediction models did not improve prediction compared with the FRS alone. Future studies should explore whether PPFs may act as CAD-risk modifiers, especially if the individual’s risk is close to a decision threshold.