Physiotherapists’ ethical behavior in professional practice: a qualitative study

BackgroundIn health professions, ethics is considered a fundamental competence. The increase in clinical autonomy in the field of physiotherapy is associated with an increase in ethical situations in their clinical practice.ObjectiveTo explore the ethics of the clinical relationship between physiotherapists and patients, the ethics training received by physiotherapists, and if in the clinical context, physiotherapists identify the necessary attitudes and apply the ethical recommendations of the profession for the ethical situations they experience.MethodsA qualitative exploratory and descriptive study was performed with physiotherapists. Data were collected through semi-structured interviews. The data were analyzed using content analysis, as proposed by Krippendorf. The study protocol was approved by the University of Valencia Ethics Committee of Human Research.ResultsThis study included 15 physiotherapists (66.66% women, average age = 42.2 years), which was sufficient to reach data saturation. We identified four categories: (i) Ethics of the clinical relationship (ethical values, principles, and norms; type of clinical relationship), (ii) Ethics training received (during the physiotherapy studies; current training of students; low importance of ethics in the curriculum), (iii) Necessary attitudes for professional ethical practice (main attitudes were identified: personal attitudes and professional attitudes); (iv) Experiences from professional practice (general; public sector vs. private sector).ConclusionThe ethics of the clinical relationship between physiotherapists and patients is determined by the attitudes of the practitioner, which are the result of his or her values and previous experiences; and are very centered on ethics of indication (founded mainly on the principles of Beneficence and Non-Maleficence). It is necessary to improve the ethical training received by physiotherapists, which is poorly focused on professional attitudes

Discovering HIV related information by means of association rules and machine learning

Acquired immunodeficiency syndrome (AIDS) is still one of the main health problems worldwide. It is therefore essential to keep making progress in improving the prognosis and quality of life of affected patients. One way to advance along this pathway is to uncover connections between other disorders associated with HIV/AIDS-so that they can be anticipated and possibly mitigated. We propose to achieve this by using Association Rules (ARs). They allow us to represent the dependencies between a number of diseases and other specific diseases. However, classical techniques systematically generate every AR meeting some minimal conditions on data frequency, hence generating a vast amount of uninteresting ARs, which need to be filtered out. The lack of manually annotated ARs has favored unsupervised filtering, even though they produce limited results. In this paper, we propose a semi-supervised system, able to identify relevant ARs among HIV-related diseases with a minimal amount of annotated training data. Our system has been able to extract a good number of relationships between HIV-related diseases that have been previously detected in the literature but are scattered and are often little known. Furthermore, a number of plausible new relationships have shown up which deserve further investigation by qualified medical experts

Evaluation of a quality improvement intervention to reduce anastomotic leak following right colectomy (EAGLE): pragmatic, batched stepped-wedge, cluster-randomized trial in 64 countries

Background Anastomotic leak affects 8 per cent of patients after right colectomy with a 10-fold increased risk of postoperative death. The EAGLE study aimed to develop and test whether an international, standardized quality improvement intervention could reduce anastomotic leaks. Methods The internationally intended protocol, iteratively co-developed by a multistage Delphi process, comprised an online educational module introducing risk stratification, an intraoperative checklist, and harmonized surgical techniques. Clusters (hospital teams) were randomized to one of three arms with varied sequences of intervention/data collection by a derived stepped-wedge batch design (at least 18 hospital teams per batch). Patients were blinded to the study allocation. Low- and middle-income country enrolment was encouraged. The primary outcome (assessed by intention to treat) was anastomotic leak rate, and subgroup analyses by module completion (at least 80 per cent of surgeons, high engagement; less than 50 per cent, low engagement) were preplanned. Results A total 355 hospital teams registered, with 332 from 64 countries (39.2 per cent low and middle income) included in the final analysis. The online modules were completed by half of the surgeons (2143 of 4411). The primary analysis included 3039 of the 3268 patients recruited (206 patients had no anastomosis and 23 were lost to follow-up), with anastomotic leaks arising before and after the intervention in 10.1 and 9.6 per cent respectively (adjusted OR 0.87, 95 per cent c.i. 0.59 to 1.30; P = 0.498). The proportion of surgeons completing the educational modules was an influence: the leak rate decreased from 12.2 per cent (61 of 500) before intervention to 5.1 per cent (24 of 473) after intervention in high-engagement centres (adjusted OR 0.36, 0.20 to 0.64; P < 0.001), but this was not observed in low-engagement hospitals (8.3 per cent (59 of 714) and 13.8 per cent (61 of 443) respectively; adjusted OR 2.09, 1.31 to 3.31). Conclusion Completion of globally available digital training by engaged teams can alter anastomotic leak rates. Registration number: NCT04270721 (http://www.clinicaltrials.gov)