Effects of exposure duration on emotional reactivity were investigated in two experiments that parametrically varied the duration of exposure to affective pictures from 25-6000 ms in the presence or absence of a visual mask. Evaluative, facial, autonomic, and cortical responses were measured. Results demonstrated that, in the absence of a visual mask (Experiment 1), emotional content modulated evaluative ratings, cortical, autonomic, and facial changes even with very brief exposures, and there was little evidence that emotional engagement increased with longer exposure. When information persistence was reduced by a visual mask (Experiment 2), differences as a function of hedonic content were absent for all measures when exposure duration was 25 ms but statistically reliable when exposure duration was 80 ms. Between 25-80 ms, individual differences in discriminability were critical in observing affective reactions to masked pictures.
Five experiments explored the role of the syllable in the processing of spoken Italian. According to the syllabic hypothesis, the sublexical unit used by speakers of Romance languages to segment speech and access the lexicon is the syllable. However, languages with different degrees of acoustic-phonetic transparency give rise to syllabic effects that vary in robustness. It follows from this account that speakers of phonologically similar languages should behave in a similar way. By exploiting the similarities between Spanish and Italian, the authors tested this prediction in Experiments 1-4. Indeed, Italian listeners were found to produce syllabic effects similar to those observed in Spanish listeners. In Experiment 5, the predictions of the syllabic hypothesis with respect to lexical access were tested. The results corroborated these predictions. The findings are discussed in relation to current models of speech processing.
Background Illness impact on HrQoL has been widely studied in hair loss‐affected patients, yet no study has addressed whether individual differences modulate HrQoL in patients with alopecia areata (AA), androgenetic alopecia (AGA) and telogen effluvium (TE). Objective To identify the personality dimensions most predictive of the impact of disease on HrQoL. Method A single‐site cross‐sectional study was carried out in the Dermatology Unit of Sant'Orsola‐Malpighi Hospital, Bologna between September 2016 and September 2017. The study included 143 patients (105 females, ages 18–60 years) diagnosed with AA (n = 27), AGA (n = 80) and TE (n = 36). Illness severity, alopecia type, age, gender, education and civil status were documented. Health‐related quality of life (HrQoL), personality traits, trait anxiety, emotional intelligence, social anxiety and social phobia were also measured. Results AA, AGA and TE groups differed significantly for illness severity with most severe patients falling in AA type. For HrQoL, Gender × Group interaction resulted significant with AGA females reporting a higher impact of hair loss on quality of life than males, while TE males were more impacted by hair loss than AA and AGA males. Lower scores were obtained by AGA females than males on emotional intelligence while no significant differences were evidenced on other groups. A significant Gender × Group interaction was also found for trait anxiety, social phobia and social anxiety: consistently, AGA females reported higher scores than AGA males in all three measures. Finally, discriminant analysis evidenced that anxiety‐related traits can contribute to reliably predict hair loss impact on HrQoL, regardless of illness severity and alopecia type. Conclusions We recommend that gender and individual differences in anxiety‐related dimensions be considered as key factors in gaining a deeper understanding of hair loss impact on quality of life as well as in reducing the burden of illness in alopecia‐affected patients.
Smartphone applications are considered as the prime candidate for the purposes of large-scale, low-cost and long-term sleep monitoring. How reliable and scientifically grounded is smartphone-based assessment of healthy and disturbed sleep remains a key issue in this direction. Here we offer a review of validation studies of sleep applications to the aim of providing some guidance in terms of their reliability to assess sleep in healthy and clinical populations, and stimulating further examination of their potential for clinical use and improved sleep hygiene. Electronic literature review was conducted on Pubmed. Eleven validation studies published since 2012 were identified, evaluating smartphone applications' performance compared to standard methods of sleep assessment in healthy and clinical samples. Studies with healthy populations show that most sleep applications meet or exceed accuracy levels of wrist-based actigraphy in sleep-wake cycle discrimination, whereas performance levels drop in individuals with low sleep efficiency (SE) and in clinical populations, mirroring actigraphy results. Poor correlation with polysomnography (PSG) sleep sub-stages is reported by most accelerometer-based apps. However, multiple parameter-based applications (i.e., EarlySense, SleepAp) showed good capability in detection of sleep-wake stages and sleep-related breathing disorders (SRBD) like obstructive sleep apnea (OSA) respectively with values similar to PSG. While the reviewed evidence suggests a potential role of smartphone sleep applications in pre-screening of SRBD, more experimental studies are warranted to assess their reliability in sleep-wake detection particularly. Apps' utility in post treatment follow-up at home or as an adjunct to the sleep diary in clinical setting is also stressed.
The no-visitor policies endorsed by healthcare organizations to limit COVID-19 virus risk exposure have unfortunately contributed to the isolation of patients further exacerbating distress in relatives and frontline healthcare workers. To contrast such effects, many healthcare institutions have adopted technology-based solutions helping patients and families communicate online through the aid of virtual devices. To date, no study has investigated whether facilitating patient-family videocalls would mitigate distress levels in frontline healthcare professionals. Caring for emotional needs of patients by re-establishing affiliative connections interrupted by the pandemic through patient-family videocalls is expected to mitigate distress in engaged healthcare workers as an example of a tend-and-befriend response to stress caused by the pandemic. We tested this hypothesis in a cross-sectional study conducted during 1-30 June 2020, involving 209 healthcare workers (nurses = 146; physicians = 63) engaged in the COVID-19 frontline in Italy. Half of participants in our sample (n = 107) had assisted efforts aimed at connecting patients remotely with families through videocalls. Psychological distress measures included symptoms of burnout, post-traumatic stress, anxiety, depression, and difficulty in sleep and wakefulness. Partially in line with our expectations we found a modulation effect specific for professional category: nurses assisting patient-family videocalls reported significantly lower levels of distress and a better quality of wakefulness compared to those who did not, whereas physicians reported higher levels of distress during such virtual communications. We interpret these findings from the perspective of patient-family communication and differences in skills and training between nurses and physicians. These findings highlight that technology-based solutions aimed at reducing barriers and alleviating distress in healthcare settings should be promoted in concert with skill enhancement training for healthcare professionals especially in terms of communicating online and communicating difficult topics with patients and families.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.