Search results
1 – 3 of 3Helen Frances Harrison, Elizabeth Anne Kinsella, Stephen Loftus, Sandra DeLuca, Gregory McGovern, Isabelle Belanger and Tristan Eugenio
This study aims to investigate student mentors' perceptions of peer mentor relationships in a health professions education program.
Abstract
Purpose
This study aims to investigate student mentors' perceptions of peer mentor relationships in a health professions education program.
Design/methodology/approach
The design uses embodied hermeneutic phenomenology. The data comprise 10 participant interviews and visual “body maps” produced in response to guided questions.
Findings
The findings about student mentors' perceptions of peer mentor relationships include a core theme of nurturing a trusting learning community and five related themes of attunement to mentees, commonality of experiences, friends with boundaries, reciprocity in learning and varied learning spaces.
Originality/value
The study contributes original insights by highlighting complexity, shifting boundaries, liminality, embodied social understanding and trusting intersubjective relations as key considerations in student peer mentor relationships.
Details
Keywords
Andrew Pressey, David Houghton and Dogá Istanbulluoglu
We have witnessed an evolution in the use of smartphones in recent years. We have been aware for some time of the potentially deleterious impact of smartphones on users' lives and…
Abstract
Purpose
We have witnessed an evolution in the use of smartphones in recent years. We have been aware for some time of the potentially deleterious impact of smartphones on users' lives and their propensity for user addiction, as reflected in the large and growing body of work on this topic. One modern phenomenon – the distracted mobile phone user in public, or “smartphone zombie” – has received limited research attention. The purpose of the present study is to develop a robust measure of smartphone zombie behaviour.
Design/methodology/approach
The research deign comprises three studies: A round of focus groups (n = 5) and two online surveys (survey one n = 373, survey two n = 386), in order to develop and validate a three-factor, 15-item measure named the Smartphone Zombie Scale (SZS).
Findings
Following the round of focus groups conducted, Exploratory Factor Analysis and a Confirmatory Factor Analysis, the SZS measure (Cronbach's α = .932) is demonstrated to be robust and comprises three factors: Attention Deficit (Cronbach's α = .922), Jeopardy (Cronbach's α = .817) and Preoccupation (Cronbach's α = .835), that is shown to be distinct to existing closely related measures (Smartphone Addiction scale and Obsessive Compulsive Use).
Originality/value
The present study represents the first extant attempt to produce a measure of smartphone zombie behaviour, and provides us with a reliable and valid measure with which we can study this growing phenomenon.
Details
Keywords
Kusum Lata and Naval Garg
This study aims to develop a model to predict non-violent work behaviour (NVWB) among employees using machine learning techniques.
Abstract
Purpose
This study aims to develop a model to predict non-violent work behaviour (NVWB) among employees using machine learning techniques.
Design/methodology/approach
Four machine learning techniques (Naïve Bayes, decision tree, logistic regression and ensemble learning) were used to develop a prediction model for NVWB of employees. Also, 10-fold cross-validation method was used to validate the NVWB prediction models. The confusion matrix is used to derive various performance matrices to express the predictive capability of NVWB models quantitatively.
Findings
The model developed using random forest technique was identified as best NVWB prediction model, as it resulted in highest true positive rate and true negative rate, thereby resulting in the highest geometric mean, balance and area under receiver operator characteristics curve.
Originality/value
To the best of the authors’ knowledge, this is one of the pioneer studies that used machine learning techniques to develop a predictive model of NVBW.
Details