A qualitative study of enablers and barriers influencing the incorporation of social accountability values into organisational culture: a perspective from two medical schools

Background: Definitions of social accountability describe the obligation of medical schools to direct education, research and service activities towards addressing the priority health concerns of the population they serve. While such statements give some direction as to how the goal might be reached, it does not identify what factors might facilitate or hinder its achievement. This study set out to identify and explore enablers and barriers influencing the incorporation of social accountability values into medical schools. Methods: Semi structured interviews of fourteen senior staff in Bar Ilan and Leeds medical schools were undertaken following a literature review. Participants were recruited by purposive sampling in order to identify factors perceived to play a part in the workings of each institution. Results: Academic prestige was seen as a key barrier that was dependent on research priorities and student selection. The role of champions was considered to be vital to tackle staff perceptions and facilitate progress. Including practical community experience for students was felt to be a relevant way in which the curriculum could be designed through engagement with local partners. Conclusions: Successful adoption of social accountability values requires addressing concerns around potential negative impacts on academic prestige and standards. Identifying and supporting credible social accountability champions to disseminate the values throughout research and education departments in medical and other faculties is also necessary, including mapping onto existing work streams and research agendas. Demonstrating the contribution the institution can make to local health improvement and regional development by a consideration of its economic footprint may also be valuable

Factors that promote or inhibit the implementation of e-health systems: an explanatory systematic review

OBJECTIVE: To systematically review the literature on the implementation of e-health to identify: (i) barriers and facilitators to e-health implementation, and (ii) outstanding gaps in research on the subject.METHODS: MEDLINE, EMBASE, CINAHL, PSYCINFO and the Cochrane Library were searched for reviews published between 1 January 1995 and 17 March 2009. Studies had to be systematic reviews, narrative reviews, qualitative metasyntheses or meta-ethnographies of e-health implementation. Abstracts and papers were double screened and data were extracted on country of origin; e-health domain; publication date; aims and methods; databases searched; inclusion and exclusion criteria and number of papers included. Data were analysed qualitatively using normalization process theory as an explanatory coding framework.FINDINGS: Inclusion criteria were met by 37 papers; 20 had been published between 1995 and 2007 and 17 between 2008 and 2009. Methodological quality was poor: 19 papers did not specify the inclusion and exclusion criteria and 13 did not indicate the precise number of articles screened. The use of normalization process theory as a conceptual framework revealed that relatively little attention was paid to: (i) work directed at making sense of e-health systems, specifying their purposes and benefits, establishing their value to users and planning their implementation; (ii) factors promoting or inhibiting engagement and participation; (iii) effects on roles and responsibilities; (iv) risk management, and (v) ways in which implementation processes might be reconfigured by user-produced knowledge.CONCLUSION: The published literature focused on organizational issues, neglecting the wider social framework that must be considered when introducing new technologies.<br/

Machine Learning Approach for the Early Prediction of the Risk of Overweight and Obesity in Young People

Obesity is a major global concern with more than 2.1 billion people overweight or obese worldwide which amounts to almost 30% of the global population. If the current trend continues, the overweight and obese population is likely to increase to 41% by 2030. Individuals developing signs of weight gain or obesity are also at a risk of developing serious illnesses such as type 2 diabetes, respiratory problems, heart disease and stroke. Some intervention measures such as physical activity and healthy eating can be a fundamental component to maintain a healthy lifestyle. Therefore, it is absolutely essential to detect childhood obesity as early as possible. This paper utilises the vast amount of data available via UK’s millennium cohort study in order to construct a machine learning driven model to predict young people at the risk of becoming overweight or obese. The childhood BMI values from the ages 3, 5, 7 and 11 are used to predict adolescents of age 14 at the risk of becoming overweight or obese. There is an inherent imbalance in the dataset of individuals with normal BMI and the ones at risk. The results obtained are encouraging and a prediction accuracy of over 90% for the target class has been achieved. Various issues relating to data preprocessing and prediction accuracy are addressed and discussed

A model of professional self-identity formation in student doctors and dentists: a mixed method study.

BACKGROUND: Professional self-identity [PSI] can be defined as the degree to which an individual identifies with his or her professional group. Several authors have called for a better understanding of the processes by which healthcare students develop their professional identities, and suggested helpful theoretical frameworks borrowed from the social science and psychology literature. However to our knowledge, there has been little empirical work examining these processes in actual healthcare students, and we are aware of no data driven description of PSI development in healthcare students. Here, we report a data driven model of PSI formation in healthcare students. METHODS: We interviewed 17 student doctors and dentists who had indicated, on a tracking questionnaire, the most substantial changes in their PSI. We analysed their perceptions of the experiences that had influenced their PSI, to develop a descriptive model. Both the primary coder and the secondary coder considered the data without reference to the existing literature; i.e. we used a bottom up approach rather than a top down approach. RESULTS: The results indicate that two overlapping frames of reference affect PSI formation: the students' self-perception and their perception of the professional role. They are 'learning' both; neither is static. Underpinning those two learning processes, the following key mechanisms operated: [1] When students are allowed to participate in the professional role they learn by trying out their knowledge and skill in the real world and finding out to what extent they work, and by trying to visualise themselves in the role. [2] When others acknowledge students as quasi-professionals they experience transference and may respond with counter-transference by changing to meet expectations or fulfil a prototype. [3] Students may also dry-run their professional role (i.e., independent practice of professional activities) in a safe setting when invited. CONCLUSIONS: Students' experiences, and their perceptions of those experiences, can be evaluated through a simple model that describes and organises the influences and mechanisms affecting PSI. This empirical model is discussed in the light of prevalent frameworks from the social science and psychology literature