Background: In the past decade, marketing studies have greatly benefited from the adoption of neuroscience techniques to explore conscious and unconscious drivers of consumer behavior. Electroencephalography (EEG) is one of the most frequently applied neuroscientific techniques for marketing studies, thanks to its low cost and high temporal resolution.Objective: We present an overview of EEG applications in consumer neuroscience. The aim of this review is to facilitate future research and to highlight reliable approaches for deriving research and managerial implications.Method: We conducted a systematic review by querying five databases for the titles of articles published up to June 2020 with the terms [EEG] AND [neuromarketing] OR [consumer neuroscience].Results: We screened 264 abstracts and analyzed 113 articles, classified based on research topics (e.g., product characteristics, pricing, advertising attention and memorization, rational, and emotional messages) and characteristics of the experimental design (tasks, stimuli, participants, additional techniques).Conclusions: This review highlights the main applications of EEG to consumer neuroscience research and suggests several ways EEG technique can complement traditional experimental paradigms. Further research areas, including consumer profiling and social consumer neuroscience, have not been sufficiently explored yet and would benefit from EEG techniques to address unanswered questions.

This study addresses the crucial need for resilient healthcare systems, highlighted by recent global health emergencies such as the Ebola and COVID-19 crises. It identifies a significant gap in the current literature: a lack of practical, actionable frameworks for healthcare resilience. To bridge this gap, the research introduces an innovative framework that blends theoretical resilience concepts with heuristic approaches. This framework, rooted in the principles of monitoring, anticipation, recognition, and learning, is designed to enhance the crisis management capabilities of healthcare systems. The methodology involves a comprehensive literature review, combined with heuristic methods, culminating in a framework that is both academically sound and practically applicable. This framework guides healthcare systems through various stages of crisis management, including data collection, situation analysis, risk anticipation, and response evaluation. It provides a holistic approach to enhancing resilience in healthcare settings. Overall, this paper makes a significant contribution to the field of healthcare system resilience, offering a strategic blueprint for improved crisis response and recovery. It marks an important advancement in aligning theoretical resilience concepts with practical implementation strategies, essential for tackling current and future healthcare challenges.

Background: Balance impairment is a common disability in post-stroke survivors, leading to reduced mobility and increased fall risk. Robotic gait training (RAGT) is largely used, along with traditional training. There is, however, no strong evidence about RAGT superiority, especially on balance. This study aims to determine RAGT efficacy on balance of post-stroke survivors. Methods: PubMed, Cochrane Library, and PeDRO databases were investigated. Randomized clinical trials evaluating RAGT efficacy on post-stroke survivor balance with Berg Balance Scale (BBS) or Timed Up and Go test (TUG) were searched. Meta-regression analyses were performed, considering weekly sessions, single-session duration, and robotic device used. Results: A total of 18 trials have been included. BBS pre-post treatment mean difference is higher in RAGT-treated patients, with a pMD of 2.17 (95% CI 0.79; 3.55). TUG pre-post mean difference is in favor of RAGT, but not statistically, with a pMD of −0.62 (95%CI − 3.66; 2.43). Meta-regression analyses showed no relevant association, except for TUG and treatment duration (β = −1.019, 95% CI − 1.827; −0.210, p-value = 0.0135). Conclusions: RAGT efficacy is equal to traditional therapy, while the combination of the two seems to lead to better outcomes than each individually performed. Robot-assisted balance training should be the focus of experimentation in the following years, given the great results in the first available trials. Given the massive heterogeneity of included patients, trials with more strict inclusion criteria (especially time from stroke) must be performed to finally define if and when RAGT is superior to traditional therapy.

Background: Medication adherence has been studied in different settings, with different approaches, and applying different methodologies. Nevertheless, our knowledge and efficacy are quite limited in terms of measuring and evaluating all the variables and components that affect the management of medication adherence regimes as a complex phenomenon. The study aim is mapping the state-of-the-art of medication adherence measurement and assessment methods applied in chronic conditions. Specifically, we are interested in what methods and assessment procedures are currently used to tackle medication adherence. We explore whether Big Data techniques are adopted to improve decision-making procedures regarding patients’ adherence, and the possible role of digital technologies in supporting interventions for improving patient adherence and avoiding waste or harm. Methods: A scoping literature review and bibliometric analysis were used. Arksey and O’Malley’s framework was adopted to scope the review process, and a bibliometric analysis was applied to observe the evolution of the scientific literature and identify specific characteristics of the related knowledge domain. Results: A total of 533 articles were retrieved from the Scopus academic database and selected for the bibliometric analysis. Sixty-one studies were identified and included in the final analysis. The Morisky medication adherence scale (36%) was the most frequently adopted baseline measurement tool, and cardiovascular/hypertension disease, the most investigated illness (38%). Heterogeneous findings emerged from the types of study design and the statistical methodologies used to assess and compare the results. Conclusions: Our findings reveal a lack of Big Data applications currently deployed to address or measure medication adherence in chronic conditions. Our study proposes a general framework to select the methods, measurements and the corpus of variables in which the treatment regime can be analyzed.

Rare diseases imply clinical and economic burden as well as a significant challenge for health systems. One relevant objective of the activities planned within the European Reference Network on Rare and Complex Connective Tissue and Musculoskeletal Diseases (ERN ReCONNET) is to address the economic dimensions of rare diseases to identify, develop and suggest strategies to improve research and patients’ access to orphan drugs (ODs) and highly specialised health technologies. This paper presents a preliminary review of the existing policies on rare diseases in the countries of the Network members. It also introduces and discusses the theme of how to perform health economic evaluations of rare diseases and of existing or new treatments for rare diseases. To obtain a preliminary overview aiming at defining the state of the art of rare diseases policies and initiatives in ERN ReCONNET countries, we collected and analysed the rare diseases national plans of all the eight countries of the ERN ReCONNET participants. The preliminary overview that has been performed showed that in all the ERN ReCONNET countries are in place national plans for rare diseases; however, heterogeneity exists in the reimbursement of ODs, direct provision by the healthcare system, involvement of patients’ associations in decision making and implementation of clinical practice guidelines.

Purpose: The purpose of this paper is to explore the associations between food literacy, consumer profiling and purchasing behaviour in a sample of Italian consumers.Design/methodology/approach: Participants (N = 194) completed an online survey including personal data, two questionnaires on purchase behaviour and food consumption, the General Trust Scale (GTS), a questionnaire assessing individual chronotype and two scales about food literacy: one investigating nutritional knowledge (short food literacy questionnaire, SFLQ) and the other focussing on procedural skills (self-perceived food literacy scale, SPFL). Associations between food literacy, consumer profiling and purchase behaviour were analysed with linear regression models.Findings: Participants with specific education in nutrition reported higher scores in food literacy. The final score of food literacy was predicted by a greater attention to nutritional content and nutritional properties of products. Women paid more attention to nutritional properties than men, and they obtained higher scores in SFLQ. Evening types obtained lower scores in SFPL compared to intermediate and morning chronotypes. Body mass index (BMI) was negatively correlated to SPFL score, while it was associated with the easy availability of a product, so that obese (BMI ≥ 30) subjects considered the easy availability of a product more important compared to non-obese ones (BMI < 30).Originality/value: This study investigates the influence of personal and psychometric variables of consumer profiling on food literacy and consequently on purchase behaviour, paving the way for implementing healthier food consumption policies. These findings reinforce the primacy of specific education in building healthy eating habits.