“I Do Not Like Being Me”: the Impact of Self-hate on Increased Risky Sexual Behavior in Sexual Minority People

Background: Increased risky sexual behaviors (RSB) in sexual minority people relative to heterosexual individuals are well documented. However, the role of trans-diagnostic factors that are not sexual orientation-specific, such as self-criticism, in predicting RSB was understudied. The present study aimed to test participants’ gender and sexual orientation as moderators between self-criticism and RSB. Methods: Data were collected during 2019. The total sample included 986 sexual minority people (Nwomen = 51%) and 853 heterosexual people (Nwomen = 46%), ranging from 18 to 35 years of age. Self-criticism dimensions (self-hate, self-inadequacy, self-reassurance), types of positive affect (relaxed, safe/content, and activated affect), and RSB were assessed. Bivariate, multivariate analyses, and moderated regression analyses were conducted. Results: Sexual minority participants showed higher levels of RSB, self-hate, and self-inadequacy than heterosexual people. Only in sexual minority men, RSB correlated positively with self-hate and negatively with safe/content positive affect. Moderated regressions showed that only for sexual minority participants, higher RSB were predicted by higher levels of self-hate. At the same time, this association was not significant for heterosexual people controlling the effects of age, presence of a stable relationship, other self-criticism dimensions, and activation safe/content affect scale. The two-way interaction between sexual orientation and gender was significant, showing that regardless of self-hate, the strength of the association between sexual orientation and RSB is stronger for sexual minority men than sexual minority women and heterosexual participants. Conclusions: Findings highlight the distinctive role of self-hate in the occurrence of RSB in sexual minority people and support the usefulness of developing a compassion-focused intervention to target self-hate in sexual minority people

The interplay between risk and protective factors during the initial height of the COVID-19 crisis in Italy: The role of risk aversion and intolerance of ambiguity on distress

The present study aimed to test a model of relations to ascertain the determinants of distress caused by lockdown for COVID- 19. It was hypothesized that the exposure to the COVID-19 increased distress directly and through the mediation of worry, health-related information seeking, and perception of the utility of the lockdown. It was also expected that higher levels of ambiguity intolerance corresponded to higher distress directly and through the mediation of worry, health information seeking behaviors, and perceived utility of the lockdown. Finally, it was expected that risk aversion positively influenced distress directly and through the increasing of worry, health-related information seeking behavior, and more positive perception of the utility of the lockdown The study was conducted in Italy during the mandatory lockdown for COVID-19 pandemic on 240 individuals (age range 18\u201376). Data recruitment was conducted via snowball sampling. COVID-19 exposure was positively associated with worry and health-related information seeking. Risk-aversion was positively associated with health-related information seeking and perceived utility of the lockdown to contain the spread of the virus. Worry and health-related information seeking were positively associated with distress, whereas the perceived utility of the lockdown was negatively associated with distress. Intolerance for the ambiguity was directly linked to distress with a positive sign. Findings suggest that risk aversion represents both a risk factor and a protective factor, based on what kind of variable mediates the relationship with distress, and that the intolerance to the ambiguity is a risk factor that busters distress

An ultra-wideband sensing board for IoT

In this paper, we present an ultra-wideband impedance sensing board for the radio-frequency front-ends used in wireless units for the Internet of Things and the fifth-generation wireless communication systems. We adopt as an impedance sensing board a six-port junction which was designed, fabricated, and tested experimentally in the frequency range from 5 GHz to 6 GHz. Moreover, the sensing board functionality was fully validated with load-pull measurements carried out in the same frequency range

A study on text-score disagreement in online reviews

In this paper, we focus on online reviews and employ artificial intelligence tools, taken from the cognitive computing field, to help understanding the relationships between the textual part of the review and the assigned numerical score. We move from the intuitions that 1) a set of textual reviews expressing different sentiments may feature the same score (and vice-versa); and 2) detecting and analyzing the mismatches between the review content and the actual score may benefit both service providers and consumers, by highlighting specific factors of satisfaction (and dissatisfaction) in texts. To prove the intuitions, we adopt sentiment analysis techniques and we concentrate on hotel reviews, to find polarity mismatches therein. In particular, we first train a text classifier with a set of annotated hotel reviews, taken from the Booking website. Then, we analyze a large dataset, with around 160k hotel reviews collected from Tripadvisor, with the aim of detecting a polarity mismatch, indicating if the textual content of the review is in line, or not, with the associated score. Using well established artificial intelligence techniques and analyzing in depth the reviews featuring a mismatch between the text polarity and the score, we find that -on a scale of five stars- those reviews ranked with middle scores include a mixture of positive and negative aspects. The approach proposed here, beside acting as a polarity detector, provides an effective selection of reviews -on an initial very large dataset- that may allow both consumers and providers to focus directly on the review subset featuring a text/score disagreement, which conveniently convey to the user a summary of positive and negative features of the review target.Comment: This is the accepted version of the paper. The final version will be published in the Journal of Cognitive Computation, available at Springer via http://dx.doi.org/10.1007/s12559-017-9496-

Comparing Discrete Choice Experiment with Swing Weighting to Estimate Attribute Relative Importance:A Case Study in Lung Cancer Patient Preferences

Introduction: Discrete choice experiments (DCE) are commonly used to elicit patient preferences and to determine the relative importance of attributes but can be complex and costly to administer. Simpler methods that measure relative importance exist, such as swing weighting with direct rating (SW-DR), but there is little empirical evidence comparing the two. This study aimed to directly compare attribute relative importance rankings and weights elicited using a DCE and SW-DR. Methods: A total of 307 patients with non–small-cell lung cancer in Italy and Belgium completed an online survey assessing preferences for cancer treatment using DCE and SW-DR. The relative importance of the attributes was determined using a random parameter logit model for the DCE and rank order centroid method (ROC) for SW-DR. Differences in relative importance ranking and weights between the methods were assessed using Cohen’s weighted kappa and Dirichlet regression. Feedback on ease of understanding and answering the 2 tasks was also collected. Results: Most respondents (&gt;65%) found both tasks (very) easy to understand and answer. The same attribute, survival, was ranked most important irrespective of the methods applied. The overall ranking of the attributes on an aggregate level differed significantly between DCE and SW-ROC (P &lt; 0.01). Greater differences in attribute weights between attributes were reported in DCE compared with SW-DR (P &lt; 0.01). Agreement between the individual-level attribute ranking across methods was moderate (weighted Kappa 0.53–0.55). Conclusion: Significant differences in attribute importance between DCE and SW-DR were found. Respondents reported both methods being relatively easy to understand and answer. Further studies confirming these findings are warranted. Such studies will help to provide accurate guidance for methods selection when studying relative attribute importance across a wide array of preference-relevant decisions. Both DCEs and SW tasks can be used to determine attribute relative importance rankings and weights; however, little evidence exists empirically comparing these methods in terms of outcomes or respondent usability. Most respondents found the DCE and SW tasks very easy or easy to understand and answer. A direct comparison of DCE and SW found significant differences in attribute importance rankings and weights as well as a greater spread in the DCE-derived attribute relative importance weights.</p

Comparing Discrete Choice Experiment with Swing Weighting to Estimate Attribute Relative Importance:A Case Study in Lung Cancer Patient Preferences

Introduction: Discrete choice experiments (DCE) are commonly used to elicit patient preferences and to determine the relative importance of attributes but can be complex and costly to administer. Simpler methods that measure relative importance exist, such as swing weighting with direct rating (SW-DR), but there is little empirical evidence comparing the two. This study aimed to directly compare attribute relative importance rankings and weights elicited using a DCE and SW-DR. Methods: A total of 307 patients with non–small-cell lung cancer in Italy and Belgium completed an online survey assessing preferences for cancer treatment using DCE and SW-DR. The relative importance of the attributes was determined using a random parameter logit model for the DCE and rank order centroid method (ROC) for SW-DR. Differences in relative importance ranking and weights between the methods were assessed using Cohen’s weighted kappa and Dirichlet regression. Feedback on ease of understanding and answering the 2 tasks was also collected. Results: Most respondents (&gt;65%) found both tasks (very) easy to understand and answer. The same attribute, survival, was ranked most important irrespective of the methods applied. The overall ranking of the attributes on an aggregate level differed significantly between DCE and SW-ROC (P &lt; 0.01). Greater differences in attribute weights between attributes were reported in DCE compared with SW-DR (P &lt; 0.01). Agreement between the individual-level attribute ranking across methods was moderate (weighted Kappa 0.53–0.55). Conclusion: Significant differences in attribute importance between DCE and SW-DR were found. Respondents reported both methods being relatively easy to understand and answer. Further studies confirming these findings are warranted. Such studies will help to provide accurate guidance for methods selection when studying relative attribute importance across a wide array of preference-relevant decisions. Both DCEs and SW tasks can be used to determine attribute relative importance rankings and weights; however, little evidence exists empirically comparing these methods in terms of outcomes or respondent usability. Most respondents found the DCE and SW tasks very easy or easy to understand and answer. A direct comparison of DCE and SW found significant differences in attribute importance rankings and weights as well as a greater spread in the DCE-derived attribute relative importance weights.</p

Comparing Discrete Choice Experiment with Swing Weighting to Estimate Attribute Relative Importance:A Case Study in Lung Cancer Patient Preferences

Introduction: Discrete choice experiments (DCE) are commonly used to elicit patient preferences and to determine the relative importance of attributes but can be complex and costly to administer. Simpler methods that measure relative importance exist, such as swing weighting with direct rating (SW-DR), but there is little empirical evidence comparing the two. This study aimed to directly compare attribute relative importance rankings and weights elicited using a DCE and SW-DR. Methods: A total of 307 patients with non–small-cell lung cancer in Italy and Belgium completed an online survey assessing preferences for cancer treatment using DCE and SW-DR. The relative importance of the attributes was determined using a random parameter logit model for the DCE and rank order centroid method (ROC) for SW-DR. Differences in relative importance ranking and weights between the methods were assessed using Cohen’s weighted kappa and Dirichlet regression. Feedback on ease of understanding and answering the 2 tasks was also collected. Results: Most respondents (&gt;65%) found both tasks (very) easy to understand and answer. The same attribute, survival, was ranked most important irrespective of the methods applied. The overall ranking of the attributes on an aggregate level differed significantly between DCE and SW-ROC (P &lt; 0.01). Greater differences in attribute weights between attributes were reported in DCE compared with SW-DR (P &lt; 0.01). Agreement between the individual-level attribute ranking across methods was moderate (weighted Kappa 0.53–0.55). Conclusion: Significant differences in attribute importance between DCE and SW-DR were found. Respondents reported both methods being relatively easy to understand and answer. Further studies confirming these findings are warranted. Such studies will help to provide accurate guidance for methods selection when studying relative attribute importance across a wide array of preference-relevant decisions. Both DCEs and SW tasks can be used to determine attribute relative importance rankings and weights; however, little evidence exists empirically comparing these methods in terms of outcomes or respondent usability. Most respondents found the DCE and SW tasks very easy or easy to understand and answer. A direct comparison of DCE and SW found significant differences in attribute importance rankings and weights as well as a greater spread in the DCE-derived attribute relative importance weights.</p

A tailored compassion-focused therapy program for sexual minority young adults with depressive symotomatology: study protocol for a randomized controlled trial.

Background: Lesbian, gay, and bisexual (LGB) men and women represent one of the highest-risk populations for depressive symptomatology and disorders, with young LGB adults being at greatest risk. To date, there have been no randomized controlled trials (RCT) to specifically target depressive symptoms in young LGB adults. This is despite research highlighting unique predictors of depressive symptomatology in this population. Here we outline a protocol for an RCT that will test the preliminary efficacy of a tailored compassion-focused therapy (CFT) intervention for young LGB adults compared with a self-directed cognitive behavioral therapy (CBT) program with no specific tailoring for LGB individuals.N/