Background: Treatment of temporomandibular disorder (TMD) currently consists of a combination of noninvasive therapies and may be supported by e-Health. It is, however, unclear if physical therapists and patients are positive towards the use of e-Health. Purpose: To assess the needs, facilitators and barriers of the use of an e-Health application from the perspective of both orofacial physical therapists and patients with TMD. Methods: A descriptive qualitative study was performed. Eleven physical therapists and nine patients with TMD were interviewed using a topic guide. Thematic analysis was applied, and findings were ordered according to four themes: acceptance of e-Health, expected utility, usability and convenience. Results: Physical therapists identified the need for e-Health as a supporting application to send questionnaires, animated exercises and evaluation tools. Key facilitators for both physical therapists and patients for implementing e-Health included the increase in self-efficacy, support of data collection and personalization of the application. Key barriers are the increase of screen time, the loss of personal contact, not up-to-date information and poor design of the application. Conclusions: Physical therapists and patients with TMD are positive towards the use of e-Health, in a blended form with the usual rehabilitation care process for TMD complaints.Implications for rehabilitation The rehabilitation process of temporomandibular complaints may be supported by the use of e-Health applications. Physical therapists and patients with temporomandibular disorders are positive towards the use of e-Health as an addition to the usual care. Especially during the treatment process, there is a need for clear animated videos and reminders for the patients.
This longitudinal, quantitative study contributes to the debate on technology-based professional development by examining the extent to which a learning (LinkedIn) intervention in a university setting affects an individual’s social media use for professional development, and the extent to which this relates to self-reported employability. In addition, we investigated how this relationship is moderated by an individual’s motivation to communicate through social media (LinkedIn). Based on social capital theory and the conservation of resources theory, we developed a set of hypotheses that were tested based on longitudinal data collected from university employees (N = 101) in middle- and high-level jobs. First, in line with our expectations, social media use for professional development was significantly higher after the learning intervention than before. Second, partially in line with our expectations, social media use for professional development was positively related with the employability dimension anticipation and optimization. Third, contrary to our expectations, motivation to communicate through social media (LinkedIn) did not have a moderating role in this relationship. We concluded that the learning intervention has the potential to foster social media use for professional development, and in turn, can contribute to individuals’ human capital in terms of their employability. Hence, the intervention that forms the core of this empirical research can be a sustainable and promising human resource management (HRM) practice that fits the human capital agenda.
The value of a decision can be increased through analyzing the decision logic, and the outcomes. The more often a decision is taken, the more data becomes available about the results. More available data results into smarter decisions and increases the value the decision has for an organization. The research field addressing this problem is Decision mining. By conducting a literature study on the current state of Decision mining, we aim to discover the research gaps and where Decision mining can be improved upon. Our findings show that the concepts used in the Decision mining field and related fields are ambiguous and show overlap. Future research directions are discovered to increase the quality and maturity of Decision mining research. This could be achieved by focusing more on Decision mining research, a change is needed from a business process Decision mining approach to a decision focused approach.
