ABSTRACT Background Psychological well‐being is a critical component of disease management and recovery in patients with cardiovascular disorders. Cognitive flexibility, as a key psychological determinant, significantly influences adaptive functioning and health‐related outcomes. Self‐regulation skills training has recently gained attention as an effective approach to enhancing mental health in individuals with chronic illnesses. This study aimed to assess the effect of a self‐regulation skills training program on improving cognitive flexibility among patients with heart failure. Materials and Methods This randomized controlled trial included 69 hospitalized patients with heart failure who were randomly assigned to an intervention group (n = 35) or a control group (n = 34). Cognitive flexibility was assessed at baseline, immediately after the intervention, and 1 month later using the Cognitive Flexibility Inventory. The intervention group received six sessions of self‐regulation skills training over 3 weeks. The data were analyzed using SPSS software with independent t‐tests, chi‐square tests, Mann–Whitney tests, and repeated‐measures ANOVA. This trial was registered in the Iranian Registry of Clinical Trials (IRCT20160927030002N4). Results The findings demonstrated a significant time × group interaction for total cognitive flexibility scores (F [2,66] = 16.66, p < 0.001, partial η2 = 0.34). Immediately afterward, the intervention group showed significantly higher cognitive flexibility compared with those of the control group (mean difference = 8.78 points; 95% CI: 3.64–13.92; Cohen's d = 0.80). At 1‐month follow‐up, the cognitive flexibility scores in the intervention group showed a slight decline compared with post‐intervention levels but remained modestly higher than baseline, whereas no meaningful change was observed in the control group. Conclusions The findings suggest that self‐regulation skills training may serve as an effective intervention for enhancing cognitive flexibility and supporting the psychological well‐being of patients with heart failure.
This publication proposes a definition and a classification of agile software development approaches and analyses ten software development methods that can be characterized as being "agile" against the defined criterion.
P. Abrahamsson, O. Salo, Jussi Ronkainen et al.· arXiv.org· 727 citations· ⚡54
The study shows that agile practices improve both informal and formal communication, but indicates that, in larger development situations involving multiple external stakeholders, a mismatch of adequate communication mechanisms can sometimes even hinder the communication.
M. Pikkarainen, Jukka Haikara, O. Salo et al.· Empirical Software Engineeri...· 401 citations· ⚡48
The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.
Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al.· Information and Software Tec...· 394 citations· ⚡54
The results show that the embedded industry has been able to apply agile methods in its development processes and that the appreciation of the agile methods and their individual practices appears to increase once adopted and applied in practice.
O. Salo, P. Abrahamsson· IET Software· 238 citations· ⚡9
Consequences of happiness and unhappiness that are beneficial and detrimental for developers' mental well-being, the software development process, and the produced artifacts are found.
D. Graziotin, Fabian Fagerholm, Xiaofeng Wang et al.· Journal of Systems and Softw...· 236 citations· ⚡13
The Mobile-D approach is briefly outlined here and the experiences gained from four case studies are discussed, which helped develop an agile development approach for mobile application development.
P. Abrahamsson, Antti Hanhineva, H. Hulkko et al.· Conference on Object-Oriente...· 225 citations· ⚡18
Related blog posts
MIT News · Artificial Intelligence· news.mit.eduOct 22, 2026
“X-Hinges” helps design and 3D print items like lamps and gloves with an interactive twist: automatically embedded sensors that perceive and adaptively respond to human contact.
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 6, 2026