The need for preparing for digital transformation is a recurrent theme in the recent public and academic debate. Artificial Intelligence (AI) has the potential to reduce operational costs, increase efficiency, and improve customer experience. Thus, it is crucial to forming project teams in an organization, in such a way that they will welcome AI in the decision-making process. The current technological revolution is demanding a rapid pace of change to companies and has increased the attention to the role of teams in fostering innovation adoption. We propose an innovative multicriteria model based on the goal programming approach for solving the optimal allocation of individuals to different groups. The model copes with human resources’ cost and human–machine trust. Indeed, we propose an aggregated measure of the attitude towards AI tools to be employed to support tasks in an organization: more precisely our index is based on three dimensions: technology acceptance, technology self-efficacy, and source credibility. By incorporating this index in a team formation model, each team can be guaranteed to have less resistance to change in adopting machine-based decisions, a scenario that will characterize the years to come. The proposed index can also be integrated into more complex and comprehensive models to support business transformation.

In the near future, Artificial Intelligence (AI) is expected to participate more and more in decision making processes, in contexts ranging from healthcare to politics. For example, in the healthcare context, doctors will increasingly use AI and machine learning devices to improve precision in diagnosis and to identify therapy regimens. One hot topic regards the necessity for health professionals to adapt shared decision making with patients to include the contribution of AI into clinical practice, such as acting as mediators between the patient with his or her healthcare needs and the recommendations coming from artificial entities. In this scenario, a “third wheel” effect may intervene, potentially affecting the effectiveness of shared decision making in three different ways: first, clinical decisions could be delayed or paralyzed when AI recommendations are difficult to understand or to explain to patients; second, patients' symptomatology and medical diagnosis could be misinterpreted when adapting them to AI classifications; third, there may be confusion about the roles and responsibilities of the protagonists in the healthcare process (e.g., Who really has authority?). This contribution delineates such effects and tries to identify the impact of AI technology on the healthcare process, with a focus on future medical practice.

Breast cancer survivors have to deal with notable challenges even after successful treatment, such as body image issues, depression and anxiety, the stress related to changes in lifestyle, and the continual challenges inherent to health management. The literature suggests that emotional abilities, such as emotional intelligence, emotion management, mood repair, and coping play a fundamental role in such challenges. We performed a systematic review to systematize the evidence available on the role of emotional abilities in quality of life and health management in breast cancer survivors. The search was performed on three scientific databases (Pubmed, Scopus, and PsycINFO) and, after applying exclusion criteria, yielded 33 studies, mainly of a cross-sectional nature. The results clearly support the hypothesis that emotional abilities play multiple important roles in breast cancer survivors’ quality of life. Specifically, the review highlighted that coping/emotional management plays multiple roles in breast cancer survivors’ well-being and health management, affecting vitality and general adjustment to cancer positivity and promoting benefit findings related to the cancer experience; however, rare negative results exist in the literature. This review highlights the relevance of emotional abilities to promoting quality of life in breast cancer survivors. Future review efforts may explore other breast cancer survivors’ emotional abilities, aiming at assessing available instruments and proposing tailored psychological interventions.

Therapeutic Assessment is a brief semistructured and collaborative psychological intervention developed by Stephen E. Finn (1996, 2007). In Therapeutic Assessment, the assessor and clients are collaboratively involved in all the phases of the process and psychological tests are used as "empathy magnifiers" in order to promote positive change throughout an assessment. Over the years, many authors have tested the efficacy of Therapeutic Assessment procedures in different contexts and have concluded that Therapeutic Assessment is well-suited for use with a broad array of clients. Despite some studies documenting the benefits of Therapeutic Assessment, results of individual studies have not been meta-analytically analyzed. Therefore, we performed a series of three-level meta-analyses to examine the efficacy of Therapeutic Assessment with adult clients. We included nine studies with 42 dependent variables, grouped into three types of outcomes: treatment process (6 studies, 18 nonindependent variables), clients' symptoms (6 studies, 17 nonindependent variables), and clients' self-enhancement (5 studies, 7 nonindependent variables). The results revealed statistically significant effects for each outcome, treatment process: g = .46, 95% CI [.33; .59]; p < .001; clients' symptoms: g = .34, 95% CI [.06; .63]; p = .021; clients' self-enhancement: g = .37, 95% CI [.05; .69]; p = .029. Moderator analyses also suggested that Therapeutic Assessment is resilient, since supervision, the inclusion of more Therapeutic Assessment elements, and additional hours of intervention do not impact substantially its outcomes. These results suggest that the most important aspect of Therapeutic Assessment may be its underlying philosophy and values, and not so much the exact way in which it is implemented. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Avatar creation is an interesting topic for both video game and social network studies. Research has shown that the creation of avatars is influenced by individual, contextual, and cultural features. Avatars are used to represent aspects of users' personality, but multiple avatars are used in different virtual contexts, as self-presentation strategies may vary according to the different “audiences” to be met online (say: friends, or strangers). Moreover, avatar creation is also influenced by cultural variables, such as gender, as avatars embody stereotypical aspects of being a woman or a man. This research tested whether avatars, as digital self-representations, may change depending on the above-mentioned variables. Ninety-four participants created two avatars to be used in different contexts (video game and job-themed social network). Moreover, two groups of participants were told that they would have met friends or total strangers within the two virtual contexts. Results showed that avatars changed from the game to the job context. Changes involved avatars' transient features ( Clothes ) more than physical ( Body ) and symbolic ( Accessories ) ones, and females changed accessories more than males. Moreover, females who expected to meet friends changed their avatars' bodies significantly more than males in both virtual contexts. The findings are discussed based on literature about computer-mediated communication and online self-disclosure. In conclusion, possible implications of the results for avatar-based interventions and the field of video games and social network design are reviewed.