Can written disclosure reduce psychological distress and increase objectively measured injury mobility of student-athletes? A randomized controlled trial

Injured students-athletes took part in a randomized controlled trial to test whether written disclosure could reduce psychological distress and improve injury mobility. Writing took place alongside prescribed physical rehabilitation and consisted of three 20- minute writing sessions, once a week for three consecutive weeks. Participants in the experimental injury-writing group (푛 = 25) followed a structured form of written disclosure, called the guided disclosure protocol (GDP). They firstly, wrote about the onset of their injury in a chronological manner, secondly, they explicitly labelled their emotions and described the impact of the injury, finally they wrote about future coping and psychological growth. Controls(푛 = 21)wrote about nonemotional and noninjury related topics. In addition to self-report measures, a physiotherapist, blind to experimental condition, assessed mobility at the injury site. Although self-report indices remained unchanged, the GDP group evidenced a significant improvement in injury mobility compared to controls

Big data and smart cities: a public sector organizational learning perspective

Public sector organizations (city authorities) have begun to explore ways to exploit big data to provide smarter solutions for cities. The way organizations learn to use new forms of technology has been widely researched. However, many public sector organisations have found themselves in new territory in trying to deploy and integrate this new form of technology (big data) to another fast moving and relatively new concept (smart city). This paper is a cross-sectional scoping study—from two UK smart city initiatives—on the learning processes experienced by elite (top management) stakeholders in the advent and adoption of these two novel concepts. The findings are an experiential narrative account on learning to exploit big data to address issues by developing solutions through smart city initiatives. The findings revealed a set of moves in relation to the exploration and exploitation of big data through smart city initiatives: (a) knowledge finding; (b) knowledge reframing; (c) inter-organization collaborations and (d) ex-post evaluations. Even though this is a time-sensitive scoping study it gives an account on a current state-of-play on the use of big data in public sector organizations for creating smarter cities. This study has implications for practitioners in the smart city domain and contributes to academia by operationalizing and adapting Crossan et al’s (Acad Manag Rev 24(3): 522–537, 1999) 4I model on organizational learning

The impact of the Saudization policy on recruitment and retention: a case study of the banking sector in Saudi Arabia

&lt;p&gt;To reduce unemployment and reliance on expatriate workers, the Saudi Arabian government has been implementing a Saudization programme to replace expatriates with Saudis. This has succeeded in the public sector, but not in the private sector, except in banking, which is perceived as a white-collar occupation and acceptable in Saudi society. As such, this study investigates the impact of Saudization on recruitment and retention in the banking sector to see what lessons have been learned and what action is required. A systematic literature review was conducted, followed by questionnaires with 48 branch managers, and interviews with 12 Human Resource managers of key banks.&lt;/p&gt;&lt;p&gt;The findings show that Saudization has an impact on several aspects of recruitment and retention in the banking sector, in particular, banks must provide specific training to Saudi recruits, revise working hours and promote the attractiveness of the post. Adopting such practices can benefit Saudi banking and contribute to the fulfillment of Saudization.  &lt;/p&gt;</jats:p