Background: Learning styles are inherent personal attributes that determine the preferred teaching and learning method(s) for individual while an intelligence type is an individual's levels of aptitude in various content areas as there is no one individual who is universally intelligent. An understanding of the two concepts is essential for designing suitable teaching approaches. Methods: This was a descriptive correlation study which explored the relationship between two variables; learning styles and intelligence types and academic performance of nursing students enrolled in the conventional nursing program at the University of Zambia. Data on learning styles was collected using the Visual, Auditory, Reading/Writing and Kinesthetic (VARK) questionnaire version 7.8 as proposed by Neil Fleming while Gardner's questionnaire for assessing multiple intelligences was used to collect data on the students' intelligence types. Results for the end of 2015/2016 academic year were used to determine academic performance. Results: Almost two thirds 64 (65.4%) of the participants' academic performance was at credit level, 32 (32.7%) were at pass while only 2 (2%) were meritorious students. Participants had wide-ranging learning styles from unimodal, to bimodal and tri modal styles, although the majority were unimodal learners 81 (82.6%). Among the unimodal learners, majority 35 (35.5%) were kinaesthetic. On the other hand, 37 (37.8%) had logical mathematical intelligence, followed by bodily-Kinaesthetic 27 (27.6%). Both learning styles and intelligence types showed negative correlation and no significant association with academic performance. The Pearson r correlation and level of significance between learning styles and academic performance was -.092 and 0.372 respectively, while that for intelligence types and academic performance were -.027 and 0.790. Of the three demographic variables of age, gender and year of study, only age showed a positive correlation and significant association with academic performance (p = .002, and r = .144). Conclusions: The negative correlation between learning styles and intelligence types and academic performance may be an indication that the teaching methods utilized for nursing students are varied and therefore capable of promoting learning across different styles and intelligence types without necessarily favouring a specific style or type or that there is simply no association between learning styles and intelligence types and academic performance.

Background: Management of stroke patients requires a multidisciplinary approach. Literature presents unequivocal evidence of improved outcomes when patients are treated in a stroke unit by multi-disciplinary teams made up of medical doctors, nurses, physiotherapists and occupational therapists. Among the multidisciplinary team members, physiotherapists and nurses are the largest professional workforce working with both stroke patients and survivors. This study, therefore, aims at investigating the role of nurses and physiotherapists in the management of stroke patients at the Adult University Teaching Hospital. Methodology: This study shall utilize a convergent parallel mixed method design where both quantitative and qualitative data will be collected at the same time resulting in two data sets which will eventually be merged at the point of discussion. The quantitative component shall utilize an analytical cross-sectional approach while the qualitative component shall use a qualitative case study approach. The study will be conducted at the Adult University Teaching Hospital in Lusaka. Data will be collected from all the 287 nurses and 37 physiotherapists working in the Emergency Department, Medical Wards, Adult Intensive Care Unit and the Department of Physiotherapy. Quantitative data will be analyzed using Statistical Package for social sciences. Descriptive statistics shall be computed on the role of nurses and physiotherapists in stroke care. In addition, chi-square and fisher's exact tests will be used in the test for associations between variables while binary logistic regression will be used in identifying predictors of the various roles played by nurses and physiotherapists in the management of stroke patients. Qualitative data will be analyzed using thematic analysis in order to generate new concepts