Introduction Chronic pain (CP) is a complex multidimensional experience severely affecting individuals’ quality of life. Multiple cognitive, affective, emotional, and interpersonal factors play a major role in CP. Furthermore, the psychological, social, and physical circumstances leading to CP show high inter-individual variability, thus making it difficult to identify core syndrome characteristics. In a biopsychosocial perspective, we aim at identifying a pattern of psycho-physical impairments that can reliably discriminate between CP individuals and healthy controls (HC) with high accuracy and estimated generalizability using machine learning. Methods A total of 118 CP and 86 HC were recruited. All individuals were administered several scales assessing quality of life, physical and mental health, personal functioning, anxiety, depression, beliefs about medical treatments, and cognitive ability. These features were trained to separate CP from HC using support vector classification and repeated nested cross-validation. Results Our psycho-physical classifier was able to discriminate CP from HC with 86.5% balanced accuracy and significance ( p = 0.0001). The most reliable features characterizing CP were anxiety and depression scores, and belief of harm from prolonged pharmacological treatments; for HP, the most reliable features were physical and occupational functioning, and vitality levels. Conclusion Our findings suggest that, using psychological and physical assessments, it is possible to classify CP from HC with high reliability and estimated generalizability via (i) a pattern of psychological symptoms and cognitive beliefs characteristic of CP, and (ii) a pattern of intact physical functioning characteristic of HC. We think that our algorithm enables novel insights into potential individualized targets for CP-related early intervention programs.

Background Psycho-oncology literature pointed out that individual health outcomes may depend on patients’ propensity to adopt approach or, conversely, avoidant coping strategies. Nevertheless, coping factors associated with postoperative distress remain unclear, unfolding the lack of tailored procedures to help breast cancer patients manage the psychological burden of scheduled surgery. In view of this, the present study aimed at investigating: 1. pre-/post-surgery distress variations occurring among women diagnosed with breast cancer; 2. the predictivity of approach and avoidant coping strategies and factors in affecting post-surgery perceived distress. Methods N = 150 patients (mean age = 59.37; SD =  ± 13.23) scheduled for breast cancer surgery were administered a screening protocol consisting of the Distress Thermometer (DT) and the Brief-COPE. The DT was used to monitor patients’ distress levels before and after surgery (± 7 days), whereas the Brief-COPE was adopted only preoperatively to evaluate patients’ coping responses to the forthcoming surgical intervention. Non-parametric tests allowed for the detection of pre-/post-surgery variations in patients’ perceived distress. Factor analysis involved the extraction and rotation of principal components derived from the Brief-COPE strategies. The predictivity of such coping factors was investigated through multiple regression (Backward Elimination). Results The Wilcoxon Signed-Rank Test yielded a significant variation in DT mean scores (TW = -5,68 < -zα/2 = -1,96; p < .001) indicative of lower perceived distress following surgery. The four coping factors extracted and Varimax-rotated were, respectively: 1. cognitive processing (i.e., planning + acceptance + active coping + positive reframing); 2. support provision (i.e., instrumental + emotional support); 3. emotion-oriented detachment (i.e., self-blame + behavioral disengagement + humor + denial); 4. goal-oriented detachment (i.e., self-distraction). Among these factors, support provision (B = .458; β = − .174; t = − 2.03; p = .045), encompassing two approach coping strategies, and goal-oriented detachment (B = .446; β = − .176; t = − 2.06; p = .042), consisting of one avoidant strategy, were strongly related to post-surgery distress reduction. Conclusion The present investigation revealed that the pre-surgery adoption of supportive and goal-oriented strategies led to postoperative distress reduction among breast cancer patients. These findings highlight the importance of timely psychosocial screening and proactive interventions in order to improve patients’ recovery and prognosis.

Objectives The study assessed a smartphone-based technology system, which was designed to enable six participants with intellectual disability and sensory impairment to start and carry out functional activities through the use of reminders and verbal or pictorial instructions. Methods The technology system involved a Samsung Galaxy A22 with Android 11 operating system and four Philips Hue indoor motion sensors. Three to five activities were scheduled per day. At the time at which an activity was due, the system provided the participant with a reminder followed by the verbal or pictorial instruction for the initial part of the first response (e.g., “Go to the bathroom and take the dirty towels”). The instruction would be available (repeated) until the participant responded to it and, in so doing, activated a sensor. Sensor activation caused the presentation of the instruction for the second part of the same (first) response (e.g., “Put the towels in the laundry machine”). The same process occurred for each of the responses involved in the activity. The system was introduced according to nonconcurrent multiple baseline designs across participants. Results During baseline, the mean percentage of activities the participants started independently was below 7; the mean frequency of correct responses per activity was below 0.5 (out of a maximum possible of 8). During the intervention (i.e., with the support of the technology system), the mean percentage and mean frequency values increased to nearly 100 and 8, respectively. Conclusions The data suggest that the aforementioned technology system may enable people with intellectual disability and sensory impairment to start and carry out functional activities independent of staff.

The COVID-19 pandemic is an unprecedented event entailing long-term consequences on population health and welfare. Those who contracted the coronavirus may have suffered from both physical and mental health issues that unfold the need for tailored intervention strategies. Hence, our study aims to investigate the psychological and social consequences of COVID-19 on a sample of 86 participants, encompassing 43 patients (clinical group; 25 women; mean age = 50.4 ± 10.1 years) recruited from Bari University Hospital, 19 of whom were hospitalized due to the disease. The remaining 43 were individuals not fallen ill with COVID-19 to date (control group; 25 women; mean age = 50.4 ± 10.1 years). The investigation yielded significant gender differences in post-traumatic stress symptoms, depression, and representation of interpersonal distance (IPD), evaluated through the IES-R, the BDI-II, and the IVAS task, respectively. This pattern of results was not replicated in the control group. In general, participants who reported having experienced the most intense post-traumatic symptoms also presented a greater mood deflection and, more specifically, within the clinical group women obtained the highest scores on both scales. Women reported higher IES-R and BDI-II scores compared to men, that could indicate that women who have contracted COVID-19 are more exposed to post-traumatic and depressive symptoms. Our results also showed a significant effect of COVID-19 on IPD with a tendency of disease-experienced individuals to increase their preferred IPD from adults, children, and elderly people. Regarding gender differences in mood and proxemic behavior, a correlation between depressive symptoms and probable PTSD and a further correlation between probable PTSD and greater IPD were found in women from both clinical and control group. Overall, these findings might contribute to a better understanding of gender-based implications of the current pandemic on mental health, also leading to the development of integrated yet personalized intervention strategies.

Background Information processing speed is commonly impaired in people with multiple sclerosis (PwMS). However, depression and fatigue can affect the cognitive profile of patients: fatigue has a negative impact from the disease’s earliest stage and a reduced information processing speed is often associated with higher levels of depression. Therefore, the aim of this study was to investigate the correlations between information processing speed and physical fatigue in a cohort of Italian PwMS from a single center, considering the effect of depression. Methods Two hundred (W = 128; mean age = 39.83 years; SD = 11.86) PwMS, from the Bari University Hospital, underwent testing for processing speed (Symbol Digit Modalities Test [SDMT]), fatigue level (Fatigue Severity Scale [FSS]), and depression (Beck’s Depression Inventory [BDI]). Results Statistically significant correlations emerged between SDMT and FSS, SDMT and BDI, FSS and BDI. Mediation analyses revealed that while physical fatigue had no significant direct negative effect on information processing speed (z=-0.891; p > 0.05), depression predicted the relationship between fatigue and information processing speed (z=-2.181; p < 0.05). Conclusion Our findings showed that cognitive performance at SDMT was not affected by patients’ perceived level of physical fatigue, but by depression. The presence of a high BDI score mediates the physical fatigue on cognitive performance impact.