With this Festschrift, we want to celebrate your 60 th birthday, to show our appreciation for you as colleague and friend, as well as mentor and teacher. We are many that have you to thank for a lot of what we are doing nowadays, something that is reflected not only in us wanting to present you with this volume, but also through the impact evident in the articles analyzing your work here.Happy 60 th Birthday!

Nowadays, measure the quality and quantity of the scientific production is an important necessity since almost every research assessment decision depends, to a great extent, upon the scientific merits of the involved researchers. To do that, many different indicators have been proposed in the literature. In addition, the highly cited papers of a discipline could be discovered by means of citation classics analysis. On the other hand, the extraction of knowledge from the intellectual, social or conceptual structure of a research field could be done by means of science mapping analysis based on bibliographic networks. In this paper, we introduce some of the most important techniques and software tools to analyze the impact of a research field and its scientific structures. Particularly, four bibliometric indices (h, g, hg and q2), the h-classics approach to identify the classics papers of a research field and three science free science mapping software tools (CitNetExplorer, SciMAT and VOSViewer) are shown.

BackgroundChronic pain is a major health issue requiring an approach that not only considers medication, but also many other factors included in the biopsychosocial model of pain. New technologies, such as mobile apps, are tools to address these factors, although in many cases they lack proven quality or are not based on scientific evidence, so it is necessary to review and measure their quality.ObjectiveThe aim is to evaluate and measure the quality of mobile apps for the management of pain using the Mobile App Rating Scale (MARS).MethodsThis study included 18 pain-related mobile apps from the App Store and Play Store. The MARS was administered to measure their quality. We list the scores (of each section and the final score) of every app and we report the mean score (and standard deviation) for an overall vision of the quality of the pain-related apps. We compare the section scores between the groups defined according to the tertiles via analysis of variance (ANOVA) or Kruskal-Wallis test, depending on the normality of the distribution (Shapiro-Wilk test).ResultsThe global quality ranged from 1.74 (worst app) to 4.35 (best app). Overall, the 18 apps obtained a mean score of 3.17 (SD 0.75). The best-rated sections were functionality (mean 3.92, SD 0.72), esthetics (mean 3.29, SD 1.05), and engagement (mean 2.87, SD 1.14), whereas the worst rated were app specific (mean 2.48, SD 1.00), information (mean 2.52, SD 0.82), and app subjective quality (mean 2.68, SD 1.22). The main differences between tertiles were found on app subjective quality, engagement, esthetics, and app specific.ConclusionsCurrent pain-related apps are of a certain quality mainly regarding their technical aspects, although they fail to offer information and have an impact on the user. Most apps are not based on scientific evidence, have not been rigorously tested, and the confidentiality of the information collected is not guaranteed. Future apps would need to improve these aspects and exploit the capabilities of current devices.

Stroke is the main cause of disability in adulthood. Recent advances in virtual reality (VR) technologies have led to its increased use in the rehabilitation of stroke patients. A systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted to determine the effectiveness of game-based reality on upper limb (UL) motor function and quality of life after stroke. In March 2018, a search of the following databases was performed: PubMed, PEDro, Web of Science, Scopus, The Cochrane Library, and Medline at EBSCO. The selection criteria were all RCTs published in English or Spanish during the past 10 years. The PEDro scale was used to evaluate the methodological quality of the studies. A total of 20 clinical trials were included in the systemic review, of which 15 contributed information to the meta-analysis. Favorable results were found for VR interventions on UL motor function (Fugl-Meyer Assessment for upper extremity, standardized mean difference [SMD] = 1.53, 95% CI [0.51-2.54]) and quality of life (functional independence measure, SMD = 0.77, 95% CI [0.05-1.49]). The results demonstrate the potential benefits of VR interventions on the recovery of UL motor function and on quality of life after stroke.