Assessment of motivation levels and associated factors among the nursing staff of tertiary‐level government hospitals

Abstract

The present study assessed the motivation level of nurses working in 3 highly decorated tertiary-level government hospitals of India and also underpins the factors attributing to motivation levels. A sequential mixed-method design was used in this study wherein 400 nurses working in 5 units of nursing care in the hospitals were enrolled based upon proportionate random stratified sampling techniques. A self-administered questionnaire with Likert scale was developed based upon scale used by Mbindyo et al. The attributes of motivation were then categorized into external and internal attributes. For the qualitative component, participants with varied responses in quantitative data were selected and interviewed. Overall mean motivation score of the nursing staff was found 3.57 ± 0.93, which was higher for extrinsic motivational attributes (3.67 ± 0.88) as compared with intrinsic attributes (3.47 ± 0.98). The intrinsic motivational attribute of organizational commitment was rated highest followed by general motivation, conscientiousness, and self-efficacy. Personal issues, timeliness, and burnout were prime discouraging attributes among study participants. Sociodemographic characteristics and work profile characteristics showed significant relationship with the attributes of motivation. This study underscores the significance of different attributes of motivation which needs to be considered while framing administrative strategies and policy guidelines by authorities.

Stimulating Intrinsic Motivation in Millennial Students: A New Generation, a New Approach

“…Client safety and communication skills are issues that are constantly scrutinized in the training of health care professionals (Marks, ; Edwards, ; Archer, ). Training through simulation exercises offers pragmatic opportunities to build competence (Khalaila, ; Gillispie, ) and confidence (Barrett et al, ) in an interactive manner (Desy et al, ; Pandey et al, ) and within a risk‐free environment. The modalities that can be employed include, but are not limited to, screen‐based computer simulators (Abdel Meguid and Khalil, ; Havyer et al, ), standardized patients (Marks, ), complex task trainers (Rogers and Tutty, ; Christensen et al, ), and realistic patient simulators (Alcamo et al, ; Hill et al, ).…”

“…Educators have long recognized the importance of enhancing IM in students toward improving their educational experience (Everly et al, 1994;Deci and Ryan, 2012;Ramirez et al, 2018), since it has been demonstrated to be associated with deep learning (Sinclair et al, 2015) and improved academic performance (Desy et al, 2018). Reports have also indicated that students who were intrinsically motivated had higher self-esteem (Yilmaz et al, 2016), greater personal control of their lives (Pandey et al, 2018), and exhibited psychological well-being (Cook and Artino, 2016;Raza et al, 2018). It is universally acknowledged that the non-fulfillment of these needs is one of the major reasons for dropouts (Tai et al, 2016;Rothmaler et al, 2017;Mabel and Britton, 2018), or considerations of discontinuation of training among health care students (Jacobs et al, 2015;Brass et al, 2017).…”

“…However, it is a daunting task considering the generational nonconformities between educators and students (Bronson, 2016;Ma et al, 2018). While these generational disparities are at times underplayed (Agius et al, 2018;Pandey et al, 2018), people of the same age tend to share more behavioral similarities than differences (Smith and Shoffner, 1991;Miller, 2013;Si, 2018). These misgivings (Orsini et al, 2015) and skepticism (Haro et al, 2014;Manzi et al, 2018) between educators and students with naturally divergent perspectives (Harpe, 2017), orientations (Evans and Cuffe, 2009;Barry et al, 2016), and approaches (Budden et al, 2017;Luthar, 2017) pose significant challenges in working toward the common goal of effective health care education.…”

“…The Honey and Mumford's learning style model (Honey and Mumford, 1992) relies more on the identification of the attitudes (Burgess et al, 2018) and general behavioral tendencies of the student population to determine their preference for learning styles (Kipp et al, 2007). The Canfield style model (Canfield, 1988) adopts a more direct approach and asks students to rank their learning preferences (Eide et al, 2001;Pandey et al, 2018), and assesses the organizational skills of students (Andreou et al, 2014), and the capacity to work independently (Cerasoli and Ford, 2014). The Felder and Silverman style (Felder and Silverman, 1988) model identifies personality traits such as the capacity for reflection and deduction (Felder and Spurlin, 2005) to determine the learning style of a student (Felder and Silverman, 1988;Graf et al, 2007;Sockalingam et al, 2016).…”

“…Most significantly, it is limited by knowledge acquired in the classroom (Strombach et al, 2016;Ciliberto et al, 2018), and therefore cannot entirely allay the apprehensions of students in their transition to reality (Abrishami, 2018;Englander and Carraccio, 2018). Another caveat often advanced in the incorporation of simulation-based training is that it entails excessive expenditure in its setup (Yan et al, 2017;Manzi et al, 2018) and maintenance (Gliddon and Cridge, 2015;Pandey et al, 2018;Pape et al, 2018). It has therefore been suggested that these resources could be more efficiently utilized in training students through actual clinical settings (Buetow, 2007;Boyce et al, 2009;Rogers and Tutty, 2016).…”