What do Syrian managers know about self-directed learning?

Although managerial Self-directed Learning (SDL) has been extensively researched, this research has largely been conducted within Western context. Thus, there is relatively little understanding of the influence of socio-cultural factors on managerial SDL in non-Western contexts. The significance of this research comes from being the first research that investigates the influence of factors that affect the form and extent of Syrian managers’ engagement with SDL. Four subsidiary aims branched from this main aim; these concerned the reasons for Syrian mangers’ engagement with SDL, the influences of organisational culture, the development in technology and the Syrian context on the Syrian managers’ SDL. Drawing on literature from the fields of SDL, self-directed learners, learning, management learning, culture and organisational factors, this research investigated the influence of these topics on the Syrian managers’ SDL. The research applied a qualitative interpretive approach involving twenty interviews with Syrian managers to collect the required data within a qualitative approach to examine their SDL, and the interview transcripts were analysed to understand how, why and what they learn. The main methods which were used to analyse the data are: observation, coding the interviews, deriving categories and conclusions, displaying the data and examining the relationships between all the findings. The analysis revealed their motivation for SDL, the difficulties and support that they have when they practice it, their aims of practicing it and the influence of the Syrian environment on their SDL. Four principal conclusions emerged from the data analysis. First, the participants were classified into three types according to their level of engagement in SDL (i.e. some participates had a high level of engagement in SDL, some of them had a low level and the rest showed a ‘moderate’ level of engagement in SDL). Second, the participants’ organisations were also classified into four categories according to three factors which are considered important forms of support and encouragement for learning. These factors are: (a) financial support, (b) different forms of support (resources, days off to study etc), (c) rewards for learning. Third, the factor which comes from the Syrian context and has influence on the Syrian managers’ SDL is the political factor (i.e. the Syrian government’s decisions). Finally, the two factors that come from outside Syria and have influence on the Syrian managers’ SDL are English and IT. Having concluded and explained these four factors, a model was developed based on them to explain how they practically interact in order to understand how the Syrian managers’ SDL happens. The principal contribution of this study is that it is the first research that examines the influence of the Syrian context on the Syrian managers’ SDL. The research specifically highlights the role of the Syrian government in influencing the Syrian managers’ SDL was highlighted within the model in addition to two factors that come from outside the Syrian context: English and IT. Therefore, the roles of the sociocultural, international, organisational and learners’ characteristics factors and their interactions were all prominent in the model, and this fulfils the aims of the research as it gives a wider and deeper insight into the Syrian managers’ SDL. The thesis concludes by making a number of suggestions and recommendations for more research arising from these findings. They include more research on the influence of civil war on managerial SDL, the differences between female and male managers regarding SDL and the influence of the reforms which the Syrian government implemented on the Syrian managers’ SDL. The thesis is structured as follows: Chapter 1 introduces the background and field of the research, Chapter Two presents the Literature Review, Chapter Three explains the qualitative methodology which I applied to implement the research to achieve the objectives of the research, Chapter Four explains how I coded the data and analysed it to obtain useful findings and results, Chapter Five presents the discussion and analysis of the findings from the collected data, Chapter Six explains how I used the four conclusions which I reached after examining and analysing the previous findings of the research to construct a model that explains the Syrian managers’ SDL in addition to my recommendations and the limitations of the research

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population

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)