Is Interoception Deficit Linking Alexithymia and Eating Spectrum Symptoms? Study on a Non-Clinical Sample of Young Adults.

We investigated if interoceptive deficits could be the link between alexithymic traits and eating spectrum manifestations in a non-clinical sample. One-hundred sixty-one young adults (mean age: 23.2 ± 2.4 years) were evaluated with the Toronto Alexithymia Scale-20 (TAS-20), the Interoceptive Accuracy Scale (IAS), the Interoceptive Confusion Questionnaire (ICQ), and the Eating Attitudes Test-26 (EAT-26). Questionnaires were administered with an online procedure (Microsoft Form, Office 365 A1, Pisa, Italy) (Study Protocol #0012005/2023). We compared ICQ, IAS, and TAS-20 scores in subjects who met the threshold for a potential eating spectrum disorder according to EAT-26 scores ≥ 20 (n = 27) vs. subjects who scored <20 (n = 134), with an ANCOVA corrected for 'age' and 'gender'. Subjects with EAT-26 ≥ 20, scored significantly higher at ICQ (54.4 ± 13.2 vs. 50.2 ± 6.8; p = 0.011), TAS-20 'Total Score' (60.8 ± 11.9 vs. 58.1 ± 9.2; p = 0.006), and TAS-20 'Identifying Feelings' (21.5 ± 7.6 vs. 17.3 ± 5.8; p = 0.0001). A binary logistic regression analysis, with EAT-26 scores < 20 vs. ≥20 as the dependent variable, and ICQ, IAS, TAS-20 total scores and dimensions, age, and gender (categorical) as covariates, showed that the only variable predicting eating spectrum symptomatology was 'ICQ Total Score' (OR = 1.075, 95% CI: 1.016-1.139; p = 0.013). Interoceptive confusion was the dimension linking the occurrence of alexithymic traits and eating spectrum manifestations.

Patients with Chronic Pain: Are Mindfulness Traits Protective Against Distress, Anxiety and Depression?

Objective: To investigate mindfulness traits/attitudes as protective factors against chronic pain related distress, depression and anxiety. Method: Fifty patients (25 with chronic non-oncologic pain-NOP; 25 with chronic oncologic pain-COP) were administered with the following scales: Visual Analogue Scale (VAS), Pain Disability Index (PDI), Italian Questionnaire for Pain (QUID), Perceived Stress Scale (PSS), State and Trait Anxiety Scale (STAY-y1 module), Beck Depression Inventory II (BDI-II), Pittsburgh Sleep Quality Index (PSQI), Psychological General Well Being Index (PGWBI), Mindful Attention Awareness Scale (MAAS). Results: MAAS value ≥ 4.38 was adopted as cut-off to compare 'high level of mindfulness' (HM) vs. 'normal level of mindfulness' (NM) attitudes. Twenty-six patients (52%) scored ≥4.38, with no different distribution between NOP and COP. HM patients scored significantly lower than NM patients on PDI 'family/home responsibilities' domain (4.5±3.2 vs. 6.4±2.8; p<.037), and on PSS (17.8±2.6 vs. 20.9±2.5; p<.0001), STAY-y1 (9.4±1.8 vs. 10.3±2.1; p<.0001), BDI-II (7.8±5.0 vs. 17.6±8.6; p<.0001) total scores. HM scored significantly higher than NM patients in all PGWBI domains. A multiple regression analysis was carried out to analyze the predictor variables of PGWB. The most complete model considered the variables MAAS, STAIy and VAS (F=42.21; p<.0001), that accounted for the 71.6% of PGWB variance. MAAS score was the only variable positively predicting for PGWB; STAIy and VAS scores predicted negatively. Conclusions: Chronic pain patients with high levels of mindfulness attitudes experienced less distress, anxiety, depressive symptoms, and more physical and general wellbeing than patients with low levels of mindfulness attitudes.

Language models and psychological sciences.

Large language models (LLMs) are demonstrating impressive performance on many reasoning and problem-solving tasks from cognitive psychology. When tested, their accuracy is often on par with average neurotypical adults, challenging long-standing critiques of associative models. Here we analyse recent findings at the intersection of LLMs and cognitive science. Here we discuss how modern LLMs resurrect associationist principles, with abilities like long-distance associations enabling complex reasoning. While limitations remain in areas like causal cognition and planning, phenomena like emergence suggest room for growth. Providing examples and increasing the dimensions of the network are methods that further improve LLM abilities, mirroring facilitation effects in human cognition. Analysis of LLMs errors provides insight into human cognitive biases. Overall, we argue LLMs represent a promising development for cognitive modelling, enabling new explorations of the mechanisms underlying intelligence and reasoning from an associationist point of view. Carefully evaluating LLMs with the tools of cognitive psychology will further understand the building blocks of the human mind.

A Machine Learning Approach Unveils the Relationships between Sickness Behavior and Interoception after Vaccination: Suggestions for Psychometric Indices of Higher Vulnerability.

OBJECTIVE: Prior research has suggested a possible connection between vaccination and manifestations of Sickness Behavior; however, a need remains to first delve deeper into this association and second examine how Interoceptive Awareness and emotional factors may modulate individuals' perceptions of their health status post vaccination. METHOD: An online retrospective cross-sectional survey of 647 individuals who received a COVID-19 vaccination was conducted. Together with vaccination side effects, socio-demographic characteristics, health status, level of concern about vaccination, and Interoceptive Awareness were collected at the baseline level. Mood, sleep, and Sickness Behavior were assessed at baseline and after vaccination. Data were analyzed using inferential statistics and machine learning techniques. RESULTS: After vaccination, there was a significant increase in Sickness Behavior levels (mean (±SD) SicknessQ T0 = 1.57 (±2.72), mean (±SD) SicknessQ T1 = 5.54 (±5.51); p-value = 0.001; ES = 0.77). A Machine Learning analysis revealed specific patterns of individual dispositions (sex and age), baseline emotional characteristics (levels of depression, anxiety, stress, and concern about adverse reactions), as well as some components of Interoceptive Awareness (Noticing, Body Listening, and Attention Regulation), as predictors of high levels of Sickness Behavior, both in terms of overall scores (JRIP: 72.65% accuracy, AUC = 0.692, d = 0.709; F1 = 0.726) and individual items (JRIP: 75.77% accuracy, AUC = 0.694; d = 0.717; F1 = 0.754). CONCLUSIONS: Our results provide new insight into post-immune reactions by highlighting the contribution of Interoceptive Awareness in modulating the severity of Sickness Behavior. This sheds light on the role of awareness of bodily sensations in modulating perceptions of health status, helping to identify the characteristics that make individuals more prone to feeling sick.

Alexithymia and Interoceptive Confusion in Covid-19 Pandemic Distress.

Objective: Alexithymic traits are associated with the difficulty of perceiving 'non-affective interoceptive signals', and are related to a problematic management of stressful life events (SLEs). The main purpose of this study was to quantify the psychological response of the general population to COVID-19 pandemic stress and to evaluate potential correlations with the presence of 'alexithymic traits' and 'interoceptive confusion' (study protocol # 0077794/2022). Method: 175 subjects from general population were assessed with the Toronto-Alexithymia Scale (TAS-20), the Event-Revised Impact Scale (IES-R), the Interoceptive Accuracy Scale (IAS), and the Interoceptive Confusion Questionnaire (ICQ). Results: a significant relationship emerged between alexithymic traits (assessed with the TAS-20), the ICQ 'interoceptive confusion', and the domain of 'hyper-arousal' as assessed with IES-R. Logistic regression model showed that ICQ-Total Score and IES-R 'hyper-arousal' domain were significantly correlated with TAS-20 total score, with DR value (R2 corrected) explaining the 36.8% of the variability (standard error: 10.7). Conclusions: This study, albeit with the limitations of a cross-sectional experimental design with self-evaluation tools in a general population sample, showed a vulnerability to COVID-19 pandemic stress due to high levels of hyper-arousal in subjects with alexithymic traits and interoceptive confusion.

COVID-19 Pandemic and Internet Addiction in Young Adults: A Pilot Study on Positive and Negative Psychosocial Correlates.

Objective: During and after the lockdowns of the COVID-19 pandemic period, a strain was put on young adults who have taken refuge in the problematic use of internet, social media, gaming, and gambling. This paper aims to investigate possible correlates of Internet Addiction Disorder (IAD), hypothesizing anxiety, depression and perceived stress would promote addiction, while mindfulness skills, resilience and socialization would, conversely, hamper IAD, and promote, consequently, a more functional internet use. Method: A pilot study was carried out with a sample of 31 young adults, recruited through a snowball sampling using social networks. Participants filled out an online questionnaire including the following measures: Internet Use, Abuse and Addiction (UADI), Beck Depression Inventory (BDI-II); State-Trait Anxiety Inventory (STAI-Y); Perceived Stress Scale (PSS); Five Facet Mindfulness Questionnaire (FFMQ); Mindfulness Attention and Awareness Scale (MAAS); Resilience Scale (RS-14). It was also administered an ad hoc questionnaire for the assessment of socialization behaviour (6 items) and gambling (2 items). Results: All the measures, but socialization, showed adequate reliability. Our sample showed high levels of anxiety, stress, IA and gambling, while presenting low levels of resilience, the mindful skill of no-reactivity and socialization. The first hypothesis was confirmed, finding positive and significant correlations between Internet Addiction on one side and PSS, STAI-Y1, STAY-2, and BDI II on the other side. We also partially confirmed the second hypothesis about UADI negatively correlated with both RS-14 and Mindful Acting. Finally, no correlations were found between Gambling and IA. Conclusions: In conclusion, the more one perceives an emotional overload with less stress-control, high anxiety, and depression, and the less one can leverage on the skills of mindful acting and resilience, the more one uses the internet as a strategy to escape from a threatening reality.

Anti-Vaccination Attitude and Vaccination Intentions Against Covid-19: A Retrospective Cross-Sectional Study Investigating the Role of Media Consumption.

Objective: The present study explores, retrospectively, the link between anti-vaccination attitude and vaccination intentions and extends this relationship to the effect of media consumption style on attitude. Method: Generalized linear mixed-models were used to estimate vaccination intentions (related to each of the four available vaccines at the time of the survey) relying on anti-vaccination attitude measured using the Italian translation of the Vaccination Attitude Examination (VAX) scale. Multiple linear regression was used to estimate which media type and which consumption frequency were responsible for variation in the anti-vaccination attitude. Results: Greater anti-vaccination attitude led to lower vaccination intention (b=-8.33, p<.0001) confirming the attitude-intention link. Crucially, consuming vaccination related information via printed press weekly (b=-0.74, p=.0001) or daily (b=-0.96, p<.0001) were the only protective factors against developing anti-vaccination attitudes. On the other hand, discussing vaccination with the family physician weekly (b=0.66, p=.002) or even daily (b=0.52, p=.026), and actively looking for vaccination related information on specialized websites and blogs every day (b=0.64, t=2.78, p=.006) were risk factors related to increased anti-vaccination attitude. No effects of social media on anti-vaccination attitude were found. Conclusions: The results confirm that vaccination intentions can be linked to the underlying anti-vaccination attitude. Moreover, our results suggest that the web and the blog sphere, but not social media, are the most anti-vaccination fuelling media and that health practitioners engage with the most vaccination-hesitant individuals. Further interventions could leverage these insights to tackle the vaccination hesitancy issue.

Reconstructing individual responses to direct questions: a new method for reconstructing malingered responses.

Introduction: The false consensus effect consists of an overestimation of how common a subject opinion is among other people. This research demonstrates that individual endorsement of questions may be predicted by estimating peers' responses to the same question. Moreover, we aim to demonstrate how this prediction can be used to reconstruct the individual's response to a single item as well as the overall response to all of the items, making the technique suitable and effective for malingering detection. Method: We have validated the procedure of reconstructing individual responses from peers' estimation in two separate studies, one addressing anxiety-related questions and the other to the Dark Triad. The questionnaires, adapted to our scopes, were submitted to the groups of participants for a total of 187 subjects across both studies. Machine learning models were used to estimate the results. Results: According to the results, individual responses to a single question requiring a "yes" or "no" response are predicted with 70-80% accuracy. The overall participant-predicted score on all questions (total test score) is predicted with a correlation of 0.7-0.77 with actual results. Discussion: The application of the false consensus effect format is a promising procedure for reconstructing truthful responses in forensic settings when the respondent is highly likely to alter his true (genuine) response and true responses to the tests are missing.

Human-like problem-solving abilities in large language models using ChatGPT.

Backgrounds: The field of Artificial Intelligence (AI) has seen a major shift in recent years due to the development of new Machine Learning (ML) models such as Generative Pre-trained Transformer (GPT). GPT has achieved previously unheard-of levels of accuracy in most computerized language processing tasks and their chat-based variations. Aim: The aim of this study was to investigate the problem-solving abilities of ChatGPT using two sets of verbal insight problems, with a known performance level established by a sample of human participants. Materials and methods: A total of 30 problems labeled as "practice problems" and "transfer problems" were administered to ChatGPT. ChatGPT's answers received a score of "0" for each incorrectly answered problem and a score of "1" for each correct response. The highest possible score for both the practice and transfer problems was 15 out of 15. The solution rate for each problem (based on a sample of 20 subjects) was used to assess and compare the performance of ChatGPT with that of human subjects. Results: The study highlighted that ChatGPT can be trained in out-of-the-box thinking and demonstrated potential in solving verbal insight problems. The global performance of ChatGPT equalled the most probable outcome for the human sample in both practice problems and transfer problems as well as upon their combination. Additionally, ChatGPT answer combinations were among the 5% of most probable outcomes for the human sample both when considering practice problems and pooled problem sets. These findings demonstrate that ChatGPT performance on both set of problems was in line with the mean rate of success of human subjects, indicating that it performed reasonably well. Conclusions: The use of transformer architecture and self-attention in ChatGPT may have helped to prioritize inputs while predicting, contributing to its potential in verbal insight problem-solving. ChatGPT has shown potential in solving insight problems, thus highlighting the importance of incorporating AI into psychological research. However, it is acknowledged that there are still open challenges. Indeed, further research is required to fully understand AI's capabilities and limitations in verbal problem-solving.

Cognitive Fusion, Ruminative Response Style and Depressive Spectrum Symptoms in a Sample of University Students.

Psychological inflexibility is related to depressive symptoms through the 'ruminative response style' (RR) and 'cognitive fusion' (CF). We aimed at exploring whether university students were more exposed to CF, RR and depressive symptoms because of their intellectual performance than non-university students of the same age. We compared university students (US) (n = 105) vs. non-university students (NUS) (n = 76) through online administration of the 'Cognitive Fusion Questionnaire' (CFQ-7), the 'Depression-Zung Self-Assessment Scale' (ZSDS) and the 'Perseverative Thinking Questionnaire' (PTQ) (study protocol #0077818/2022, approved by the Ethical Committee of the University of Pisa, Italy). University students scored significantly higher than non-university students in the CFQ-7 Total Score (27.5 ± 9.4 vs. 24.4 ± 9.5; p = 0.040), ZSDS Total Score (41.1 ± 7.7 vs. 39.0 ± 7.3; p = 0.031), PTQ Total Score (26.1 ± 13.1 vs. 21.8 ± 13.9; p = 0.029), PTQ 'Repetitiveness' (5.3 ± 2.8 vs. 4.5 ± 2.9; p = 0.034), 'Intrusiveness' (5.8 ± 3.0 vs. 4.8 ± 3.1; p = 0.046) and 'Repetitive Negative Thinking capturing mental resources' (5.0 ± 3.1 vs. 4.0 ± 3.0; p = 0.013) (MANOVA analysis). In a binary logistic regression analysis of US (with ZSDS scores < 44 vs. ≥44 as the dependent variable, and PTQ Total Score and dimensions, CFQ-7 Total Score, age and gender as the covariates), PTQ Total Score predicted the more severe depressive symptomatology (OR = 1.44, 95% CI: 1.017-2.039; p = 0.040). We believe that RR and CF should be specifically targeted through psychoeducational/psychotherapeutic interventions in university students.

Social Media in Adolescents: A Retrospective Correlational Study on Addiction.

Considering the growing interest in the possible effects of internet's addiction on adoles-cent's mental health, this study aimed at exploring the psychological correlates of social media and internet problematic use during the first year of the covid-19 pandemic. A cross-sectional study was conducted in a sample of secondary school students (N = 258); participants were asked to complete an online survey, investigating social media addiction (BSMAS), self-esteem (RSES), feelings of isolation (CSIQ-A) and anxiety (STAI-Y). Data analysis (descriptive statistics, correlational and regression analyses) was conducted through XLSTAT software ©. An additional ad hoc questionnaire was administrated. Findings showed that the 11% of the participants were significantly addicted to social media, mostly females (59%). Gender represented an exposure factor for the hours spent on social media and the checking activity while performing other daily activities. Significant correlations emerged between the self-report measure of social media addiction and self-esteem and anxiety. Low scores at RSES corresponded to higher checking activity, hours spent on social networks, and playing videogames that were investigated as supplementary indicators of addiction with ad hoc questionnaire. The regression analysis showed just two predictors of social media addiction, gender (female) and trait anxiety. Limitations and implications of the study were argued in order to give some indications for future programs.

Machine learning item selection for short scale construction: A proof-of-concept using the SIMS.

ObjectiveThis proof-of-concept paper provides evidence to support machine learning (ML) as a valid alternative to traditional psychometric techniques in the development of short forms of longer parent psychological tests. ML comprises a variety of feature selection techniques that can be efficiently applied to identify the set of items that best replicates the characteristics of the original test. MethodsIn the present study, we integrated a dataset of 329 participants from published and unpublished datasets used in previous research on the Structured Inventory of Malingered Symptomatology (SIMS) to develop a short version of the scale. The SIMS is a multi-axial self-report questionnaire and a highly efficient psychometric measure of symptom validity, which is frequently applied in forensic settings. Results State-of-the-art ML item selection techniques achieved a 72% reduction in length while capturing 92% of the variance of the original SIMS. The new SIMS short form now consists of 21 items. ConclusionsThe results suggest that the proposed ML-based item selection technique represents a promising alternative to standard psychometric correlation-based methods (i.e. item selection, item response theory), especially when selection techniques (e.g. wrapper) are employed that evaluate global, rather than local, item value.

The Hidden Impact of Covid-19 on Memory: Disclosing Subjective Complaints.

Objective: A significant body of research has suggested that the contraction of SARS-CoV-2 may cause memory impairment, even in the months following recovery. In this regard, studies suggest that COVID-19 predominantly targets structures and cortices within the temporal lobe, and the hippocampus, a critical brain structure for memory and spatial navigation.The purpose of this study was to investigate the potential impact of the COVID-19 pandemic on subjective memory complaints, which represent an individual's perception of subtle changes in memory in the absence of an objective memory impairment. Method: to explore how the COVID-19 pandemic may affect subjective memory complaints, we incorporated ad hoc self-reported measures of subjective memory complaints, the "Subjective Memory Complaints Questionnaire" (SMCQ) and the "Prospective and Retrospective Memory Questionnaire" (PRMQ), in our cross-sectional study. Both measures referred to two periods: the pre-pandemic period (T0) and the moment of survey administration (T1) (December 28th, 2021, to February 6th, 2022). Results: 207 Italian participants accessed the survey, out of which 189 participants were included in the final sample. The majority of the participants were females, and their age ranged from 55 to 65 years. The study revealed a significant increase in the total PRMQ score at T1 compared to T0 (p = 0.02). However, no significant differences were found between PRMQ and SMCQ scores of COVID-19-negative individuals and those who tested positive for COVID-19 in the last 12 months from the date of completing the survey. McNemar's test showed a statistically significant increase in the score of item 1 ("Do you think that you have a memory problem?" (p = 0.016) and item 10 ("Do you lose objects more often than you did previously") (0.019) of the SMCQ, while for the PRMQ, significant increases were found in several individual items. Conclusions: our study suggests that subjective memory complaints increased during the pandemic, potentially due to the compound effects of stress and social isolation, rather than solely due to COVID-19 infection. Although a marginal association between COVID-19 and reported prospective memory issues was detected, further investigation is warranted to understand its persistent effects.

Neurobiological outcomes of cognitive behavioral therapy for obsessive-compulsive disorder: A systematic review.

Introduction: Obsessive-compulsive disorder (OCD) is characterized by recurrent distressing thoughts and repetitive behaviors, or mental rituals performed to reduce anxiety. Recent neurobiological techniques have been particularly convincing in suggesting that cortico-striatal-thalamic-cortico (CSTC) circuits, including orbitofrontal cortex (OFC) and striatum regions (caudate nucleus and putamen), are responsible for mediation of OCD symptoms. However, it is still unclear how these regions are affected by OCD treatments in adult patients. To address this yet open question, we conducted a systematic review of all studies examining neurobiological changes before and after first-line psychological OCD treatment, i.e., cognitive-behavioral therapy (CBT). Methods: Studies were included if they were conducted in adults with OCD and they assessed the neurobiological effects of CBT before and after treatment. Two databases were searched: PsycINFO and PubMed for the time frame up to May 2022. Results: We obtained 26 pre-post CBT treatment studies performed using different neurobiological techniques, namely functional magnetic resonance imaging (fMRI), Positron emission tomography (PET), regional cerebral blood flow (rCBF), 5-HT concentration, magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), Electroencephalography (EEG). Neurobiological data show the following after CBT intervention: (i) reduced activations in OFC across fMRI, EEG, and rCBF; (ii) decreased activity in striatum regions across fMRI, rCBF, PET, and MRI; (iii) increased activations in cerebellum (CER) across fMRI and MRI; (iv) enhanced neurochemical concentrations in MRS studies in OFC, anterior cingulate cortex (ACC) and striatum regions. Most of these neurobiological changes are also accompanied by an improvement in symptom severity as assessed by a reduction in the Y-BOCS scores. Conclusion: Cognitive-behavioral therapy seems to be able to restructure, modify, and transform the neurobiological component of OCD, in addition to the clinical symptoms. Nevertheless, further studies are necessary to frame the OCD spectrum in a dimensional way.

The effects of Transcranial Direct Current Stimulation on food craving and food intake in individuals affected by obesity and overweight: a mini review of the magnitude of the effects.

Obesity represents one of the wellness diseases concurring to increase the incidence of diabetes, cardiovascular diseases, and cancer. One of the main perpetuating factors of obesity is food craving, which is characterized by an urgent desire to eat a large and various amount of food, regardless of calories requirement or satiety signals, and it might be addressed to the alteration of the dorsolateral prefrontal cortex (DLPFC) activity. Despite most of the gold-standard therapies focus on symptom treatment only, non-invasive brain stimulation techniques such as transcranial direct current stimulation (tDCS) could help treat overeating by modulating specific neural pathways. The current systematic review was conducted to identify whether convergent evidence supporting the usefulness of tDCS to deal with food craving are present in the literature. The review was conducted by searching articles published up to January 1st 2022 on MEDLINE, Scopus and PsycInfo databases. We included studies investigating the effects of tDCS on food craving in subjects affected by overweight and obesity. According to eligibility criteria, 5 articles were included. Results showed that tDCS targeting left DLPFC with unipolar montage induced ameliorating effects on food craving. Controversial results were shown for the other studies, that might be ascribable to the use of bipolar montage, and the choice of other target areas. Further investigations including expectancy effect control, larger sample sizes and follow-up are needed to support more robust conclusions. To conclude, tDCS combined with the use of psychoeducative intervention, diet and physical activity, might represents a potential to manage food craving in individuals with overweight and obesity.

Mindfulness and Defense Mechanisms as Explicit and Implicit Emotion Regulation Strategies against Psychological Distress during Massive Catastrophic Events.

Emotion regulation is an important aspect of psychological functioning that influences subjective experience and moderates emotional responses throughout the lifetime. Adaptive responses to stressful life events depend on the positive interaction between explicit and implicit emotion regulation strategies, such as mindfulness and defense mechanisms. This study demonstrates how these emotion regulation strategies predict psychological health during the early phase of the COVID-19 pandemic. A convenience sample of 6385 subjects, recruited via snowball sampling on various social media platforms, responded to an online survey assessing psychological reaction to social restrictions imposed to limit the spread of COVID-19 in Italy. Psychological distress, post-traumatic stress symptoms, mindfulness, and defense mechanisms were assessed using SCL-90, IES-R, MAAS, and DMRS-30-SR, respectively. Higher mindfulness was significantly associated with higher overall defensive maturity and a greater use of high-adaptive defenses (p < 0.0001). Both mindfulness and defense mechanisms acted as good predictors of psychological health (R2 = 0.541) and posttraumatic symptoms (R2 = 0.332), confirming the role of emotion regulation in protecting against maladaptive responses to stressful situations.

Identifying single-item faked responses in personality tests: A new TF-IDF-based method.

Faking in a psychological test is often observed whenever an examinee may gain an advantage from it. Although techniques are available to identify a faker, they cannot identify the specific questions distorted by faking. This work evaluates the effectiveness of term frequency-inverse document frequency (TF-IDF)-an information retrieval mathematical tool used in search engines and language representations-in identifying single-item faked responses. We validated the technique on three datasets containing responses to the 10-item Big Five questionnaire (total of 694 participants, respectively 221, 243, and 230) in three faking situations. Each participant responded twice, once faking to achieve an objective in one of three contexts (one to obtain child custody and two to land a job) and once honestly. The proposed TF-IDF model has proven very effective in separating honest from dishonest responses-with the honest ones having low TF-IDF values and the dishonest ones having higher values-and in identifying which of the 10 responses to the questionnaire were distorted in the dishonest condition. We also provide examples of the technique in a single-case evaluation.

Alternate fluency in Parkinson's disease: A machine learning analysis.

OBJECTIVE: The aim of the present study was to investigate whether patients with Parkinson's Disease (PD) had changes in their level of performance in extra-dimensional shifting by implementing a novel analysis method, utilizing the new alternate phonemic/semantic fluency test. METHOD: We used machine learning (ML) in order to develop high accuracy classification between PD patients with high and low scores in the alternate fluency test. RESULTS: The models developed resulted to be accurate in such classification in a range between 80% and 90%. The predictor which demonstrated maximum efficiency in classifying the participants as low or high performers was the semantic fluency test. The optimal cut-off of a decision rule based on this test yielded an accuracy of 86.96%. Following the removal of the semantic fluency test from the system, the parameter which best contributed to the classification was the phonemic fluency test. The best cut-offs were identified and the decision rule yielded an overall accuracy of 80.43%. Lastly, in order to evaluate the classification accuracy based on the shifting index, the best cut-offs based on an optimal single rule yielded an overall accuracy of 83.69%. CONCLUSION: We found that ML analysis of semantic and phonemic verbal fluency may be used to identify simple rules with high accuracy and good out of sample generalization, allowing the detection of executive deficits in patients with PD.

Interpersonal Problematic Areas in Liaison Psychiatry: A Feasibility Study.

OBJECTIVE: Interpersonal Psychotherapy (IPT) model, with its four problematic areas of grief, deficit, role transition and role dispute, provides a useful frame of reference for a quick case formulation. We aimed at applying the IPT problematic areas assessment in a sample of patients from a liaison psychiatry setting. METHODS: One-hundred and twenty-nine hospitalized patients of both sexes, aged between 18 and 80 years were interviewed. The 'Interpersonal Problem Areas Rating Scale' (IPARS) was used to detect the interpersonal focuses. RESULTS: IPARS problematic areas were identified in the 76% of the sample (n=98). Grief and role transition, interpersonal deficits and role disputes were, respectively, the most frequently (43.4 and 42.6%, respectively) and the less frequently described focuses (14 and 11.6%). Moreover, 31 patients (24%) showed no problem areas related to current symptomatology. CONCLUSIONS: The IPT model has proved to be an easy-to-use tool, able to guide the psychological interview and allowing the collection of information from an interpersonal perspective in a short time, although no specific focuses were detected as related to current psychological distress in around 25% of the sample.

Eating Disorders Spectrum During the COVID Pandemic: A Systematic Review.

Background: Several data suggest that coronavirus disease 2019 (COVID-19) pandemic may exacerbate or trigger eating disorders (EDs). The aim of this paper was to summarize current literature studies on COVID pandemic and EDs. Methods: Literature search, study selection, methods, and quality evaluation were performed according to the preferred reporting items for systematic review and meta-analyses (PRISMA) guidelines. Results: A systematic search allowed the initial selection of 172 papers; 21 (12.2%) papers were eligible and included in the review. In selected studies, a total number of 29,108 subjects were enrolled (range: 10-11,391; mean/SD: 1,386 ± 2,800), 6,216 were men (21.4%), 22,703 were women (77.9%), and 189 (0.7%) were gender fluid or not declared. The mean age/SD of subjects was 30.2 ± 7.7. About 12 studies (57.1%) were online surveys, 4 (19.0%) were retrospective studies, 2 (9.5%) were qualitative studies, 2 (9.5%) were longitudinal cohort studies, and 1 was a social media survey (4.8%). Their analysis revealed five main findings: (1) changes in the routines of physical activities were related to the worsening of preoccupation on weight/body shape; (2) food access limitation during pandemic represented the risk factors for both triggering and exacerbating EDs; (3) restriction in healthcare facilities contributed to increase anxiety levels and to modify treatment compliance; (4) social isolation was related to the exacerbation of symptoms in patients with EDs who are home-confined with family members; and (5) conflicts and difficulties in relationships with "no way out" were the maintenance factors for ED symptoms, especially in adolescents and young adults. Conclusion: The COVID-19 pandemic had a negative impact on EDs that might be triggered by the exceptional conditions derived from COVID-19-related stress in predisposed subjects. Patients who were already affected by EDs experienced the worsening of their clinical conditions and related quality of life (QoL).