Suchergebnisse

This open access volume focuses on the development of a P5 eHealth, or better, a methodological resource for developing the health technologies of the future, based on patients' personal characteristics and needs as the fundamental guidelines for design. It provides practical guidelines and evidence based examples on how to design, implement, use and elevate new technologies for healthcare to support the management of incurable, chronic conditions. The volume further discusses the criticalities of eHealth, why it is difficult to employ eHealth from an organizational point of view or why patients do not always accept the technology, and how eHealth interventions can be improved in the future. By dealing with the state-of-the-art in eHealth technologies, this volume is of great interest to researchers in the field of physical and mental healthcare, psychologists, stakeholders and policymakers as well as technology developers working in the healthcare sector.

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.

Luca Bailo,1,* Laura Vergani,1,2,* Gabriella Pravettoni1,2 1Applied Research Division for Cognitive and Psychological Science, European Institute of Oncology, IRCCS, Milan 20141, Italy; 2Department of Oncology and Hemato-Oncology, University of Milan, Milan 20122, Italy*These authors contributed equally to this workCorrespondence: Luca BailoApplied Research Division for Cognitive and Psychological Science, European Institute of Oncology, IRCCS, via Ripamonti 435, Milan 20141, ItalyTel +39 0257489207Email luca.bailo@ieo.itAbstract: Guidelines and policies support the decision process to make sure that patients can benefit from the best treatment for their condition. The implementation of guidelines and policies is evolving, allowing decision makers to be able to choose between alternatives while considering the effect of biases and fallacies that may hinder their choice. Patient preferences play a precious role in those decisions in which is not possible to recognize an objective "best" alternative and it's not possible to nudge them toward one alternative based on scientific evidence and clinical experience. Having patient input as part of the decision process itself would allow the recognition of the attributes related to what is relevant for patients, which can be considered as important as clinical data. The authors advocate that the integration of preference-sensitive attributes with decision policies could provide a benefit against fallacies in the decision process when there is not a "best" alternative, and a shared decision-making paradigm allows both patient and clinician to recognize and pursue the option that best fits the individual case.Keywords: nudge, shared decision-making, health policies, patient preferences

Due to the lack of other treatment options, patient candidates for participation in phase I clinical trials are considered the most vulnerable, and many ethical concerns have emerged regarding the informed consent process used in the experimental design of such trials. Starting with these considerations, this nonsystematic review is aimed at analyzing the decision-making processes underlying patients' decision about whether to participate (or not) in phase I trials in order to clarify the cognitive and emotional aspects most strongly implicated in this decision. Considering that there is no uniform decision calculus and that many different variables other than the patient-physician relationship (including demographic, clinical, and personal characteristics) may influence patients' preferences for and processing of information, we conclude that patients' informed decision-making can be facilitated by creating a rigorously developed, calibrated, and validated computer tool modeled on each single patient's knowledge, values, and emotional and cognitive decisional skills. Such a tool will also help oncologists to provide tailored medical information that is useful to improve the shared decision-making process, thereby possibly increasing patient participation in clinical trials.

Gabriella Pravettoni,1,2 Ilaria Cutica,1,2 Simona Righetti,1 Ketti Mazzocco1,2 1Department of Oncology and Hematology, University of Milan, 2Applied Research Division for Cognitive and Psychological Science, European Institute of Oncology, Milan, Italy Purpose: The aim of this study was to review the experiences of direct involvement in patient survivorship for treatment and research. Methods: This is a narrative-focused review of the following two recent experiences of patient involvement: the Chordoma Foundation and the Triple Negative Breast Cancer Foundation. Results: These two examples represent concrete experiences that patients have built to favor a real involvement in the care and treatment of tumors. These experiences are profoundly modifying how cancer research is conducted and draw attention to the psychosocial dimensions of health care. Conclusion: These examples represent the new scenario in which modern medicine faces completely new challenges, copes with new needs, and cooperates with new health care professionals. Implications: Involving patients in a new perspective raises practical and ethical challenges for organizations to work together, for health providers to be professionally skilled and for the government to promote safeguarding policies. Keywords: patient empowerment, patients' association, empowerment, skills, codesign ­techniques, cancer

Health-care systems as well as legislators and society seem largely unprepared to face and manage the massive production of genetic risk information. Ethics committees and professional bodies usually do not involve the individuals directly concerned in defining guidelines for genetic risk communication. Therefore, they do not always reflect people's needs and preferences. We argue in this article that we currently experience a cultural shift in medicine where individuals' concerns and preferences regarding genetic risk information are playing a more significant role than before, and that this should have some normative implications. We are going toward a situation where individual citizens are approached as consumers by personal genomics companies [Prainsack: Account Res 2011;18:132-147]. In clinical and research contexts, individuals are also increasingly informed about their own responsibilities for counterbalancing their genetic risk by making individual health care and lifestyle choices. In this situation, communication of genetic risk information may rather be regulated like traffic and markets in which consumers' decision-making power has a fundamental role in the management and regulation of how a service should be provided, as well as in the creation of policy and legislation. We acknowledge that markets may be different depending on different genetic conditions. For example, genetic risk communication for rare diseases, where a close relationship with clinicians is of paramount significance, should be differently regulated than personal genetic profiles of complex diseases, where contributing risk factors related to lifestyle are modifiable by the individual.

Abstract. Cancer is a deadly disease that can lead to psychological suffering and decreased quality of life (QoL). Personality has been proven to have an effect on QoL and, in particular, Dispositional Optimism (DO) has been studied in relation to overcoming health crisis. The aim of this systematic review is to deepen the state of art of the relationship between QoL and DO in cancer patients. PubMed and Embase databases were systematically searched. Fifteen studies were included with a total of 5,249 cancer patients. All of the studies consider the relationship between DO and QoL, some studies analyze the correlation between the two variables and found a positive association. The majority of the studies investigate the predictive power of DO over QoL and most of them found DO to be predictive of a higher QoL. Results confirmed the association between DO and QoL in a sample of cancer patients. These results could influence the clinical practice as DO has been proven to have a beneficial effect on mental and physical health.

BACKGROUND: Psychological health has been one of the aspects affected by the recent COVID-19 pandemic. We aim to evaluate the patterns of Google search for mental distress symptoms of Italian citizens during the various phases of the COVID-19 pandemic. METHODS: We assessed Google searches for psychological-health related words. We gathered and analyzed data on daily search queries on depression, anxiety, and insomnia from Google Trends, in a time ranging from the Pre-COVID phase (beginning 25th January 2020) up to the second wave phase (ending 17th October 2020). We performed three general linear models on search trends of the three words and tested whether and to what extent official data about new cases of COVID-19, information searching on new cases, and the government health measures impacted on these trends. RESULTS: Average daily search queries were higher for anxiety, followed by depression and insomnia. General linear models performed to assess differences in daily search queries for anxiety, depression and insomnia were significant, respectively [F(13, 253) = 6.80, P < .001]; [F(13, 253) = 10.25, P < .001]; [F(13, 253) = 6.61, P < .001]. Specifically, daily search queries differed among different phases of managing the COVID-19 outbreak: anxiety [F(5, 253) = 10.35, P < .001, [Formula: see text] = .17]; depression [F(5, 253) = 13.59, P < .001, [Formula: see text] = .21]; insomnia [F(5, 253) = 3.52, P = .004, [Formula: see text] = .07]. CONCLUSIONS: Our study contributed to the investigation of online information-seeking behaviors of Italians regarding mental health throughout the entire phase of the pandemic and provides insights on the possible future trends of mental distress during upcoming pandemic phases. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-11887-2.

Cancer clinical trials and, in general, cancer clinical research by definition need a multi-modality approach. It is not enough to discover and register new drugs. To get cancer under control requires us to perform complex clinical studies that integrate drugs, companion diagnostics, new or improved surgical procedures and new radiotherapy approaches as well as, most importantly, to integrate all available information. This includes biological material and, of increasing importance, large amounts of data using big data technologies. To personalise treatment, genetic data are more and more frequently used. Therefore, the general approach is holistic. Legislators, on the other hand, work in a silo mentality; the needs of clinical research are poorly understood, and legislation focuses on either health care or the commercialisation of a product, and not on clinical research. In the last 2 years the EU has drafted several major regulations touching on clinical trials, in vitro diagnostics, medical devices and data protection, all of which will impact clinical research, although the silo mentality makes the overall framework inconsistent and potentially highly damaging to the EU's capacity to make rapid progress in the field of personalised medicine.