Why is heartache associated with sadness? Sadness is represented by specific physical pain through verbal knowledge

Does sadness bring myopia: an intertemporal choice experiment with college students

Introduction

While economics often interprets individual intertemporal choice preferences through the rationality assumption of utility maximization, the reality is that as emotional beings, individuals' preferences for intertemporal behavior are much more diverse and inconsistent. Prior research has predominantly focused on positive or negative emotions based on prospect theory, such as anxiety, anger, disgust, and depression. However, there has been relatively little research on how sadness affects individuals' preferences for immediate and future rewards.

Methods

In this study, 170 college students are recruited as participants, and their emotions are primed with a video before engaging in an intertemporal task. Covariance analysis and logit regression model are established to examine the main and interactive effects of sadness on individuals' immediate reward preferences.

Results

The findings reveal that sadness led individuals to prefer smaller immediate rewards, demonstrating a more myopic behavioral pattern, but didn't affect time discount rate. As the reward baseline increases, sadness's impact on immediate reward preferences is more pronounced, exacerbating individuals' myopic behavior.

Discussion

In conclusion, these findings underscore the importance of considering emotional states in economic decision-making models and suggest avenues for future research to explore the complex dynamics of emotions and intertemporal choices.

Experimental Pain Picture System (EPPS): Development and Validation

Pain-related pictures are useful for studying how individuals respond to pain-related stimulation. Such pictures can occasionally be found in databases for affective pictures. However, a validated database specifically for pain-related pictures is not available yet. In 2 experiments (N = 185 and 103, respectively), we developed and validated the Experimental Pain Pictures System (EPPS). In both experiments, negative valence, arousal, and painfulness ratings were compared between neutral-, sad-, and pain-related pictures. The pain-related pictures represented both deep and superficial somatic pain. Across the 2 experiments, pain-related pictures were judged as more negative, arousing, and painful than neutral pictures and more painful than sad pictures. The final EPPS contains 50 pictures of different painful events considered moderately to highly painful by participants. The EPPS is a valuable tool for studying pain-related responses, as it gives researchers a choice among many validated pictures depicting different types of pain, increasing the comparability between studies. PERSPECTIVE: This article presents the validation of the experimental pain pictures system, which consists of a set of pain-related pictures. The experimental pain pictures system is composed of pictures depicting different types of pain. Participants rated all the pictures as being negative, arousing, and painful.

Color features continuously represent negative and positive aspects of sadness

Emotion is assumed to be stored in long-term memory as a concept by a feature (e.g., "tears" for "sadness") that is a memory unit of a concept. Memory activation of emotion concepts via features is supposed to enable recognition of emotional states. Emotion concepts are associated with various perceptual features oriented toward the interior and exterior of the body. Although previous studies have revealed that internal perceptual features need to recognize emotional experiences, how external perceptual features contribute to memory representation of emotions is unclear. This study focused on sadness and aimed to identify how color, which is an external perceptual feature, represents sadness in long-term memory. We hypothesized that colors continuously represent positive and negative aspects of sadness. Participants rated the congruency between each of 99 color visual stimuli and five major emotions, six sadness-related situations, and five psychological properties. Consistent with the prediction, two bluish color groups appeared to represent sadness based on emotional congruency ratings. Colors with the highest sadness ratings were related to dark and dull bluish ones. On the other hand, lighter bluish colors mixed with green appearance were similarly congruent with both sadness and happiness. The lightness properties of these sadness-related bluish colors continuously represent sadness dominancy (sadness rating minus happiness rating). Additionally, sadness dominancy of each sadness-related color group was differently associated with sadness-related situations. These findings indicate that color features contribute to memory representation of sadness in association with situations and that color features continuously instantiate negative and positive aspects of sadness.

EXPLORING SENTIMENT AND CARE MANAGEMENT OF HOSPITALIZED PATIENTS DURING FIRST WAVE OF COVID-19 PANDEMIC USING ELECTRONIC NURSING HEALTH RECORDS: DESCRIPTIVE STUDY

BACKGROUND

The COVID-19 pandemic has changed the usual work in many hospitalization units (or wards). Few studies use electronic nursing clinical notes (ENCN) and their unstructured text to identify alterations in patients' feelings and therapeutic procedures of interest.

OBJECTIVE

Analysis of positive/negative sentiments through inspection of the free text of the ENCN; comparison of sentiments of ENCN with/without hospitalized COVID-19 patients; temporal analysis of the sentiments of the patients during the start of the first wave of the COVID-19 pandemic; and identification of the topics in ENCN.

METHODS

This is a descriptive study with analysis of the text content of ENCN. All ENCNs between January and June 2020 at Guadarrama Hospital (Madrid, Spain) extracted from the CGM Selene Electronic Health Records System were included. Two groups of ENCNs were analyzed: one from hospitalized patients in post intensive care units COVID-19, and a second group from hospitalized patients with non COVID-19. A sentiment analysis was performed on the lemmatized text, using the dictionaries NRC, Affin and Bing. A polarity analysis of the sentences was performed using the Bing dictionary, the SO Dictionaries V1.11Spa dictionary as amplifiers and decrementators. Machine learning techniques were applied in order to evaluate the presence of significant differences in the ENCN in groups of COVID-19 or non COVID-19 patients. Finally, a structural analysis of thematic models was performed to study the abstract topics that occur in the ENCN, using Latent Dirichlet Allocation topic modeling.

RESULTS

A total of 37,564 electronic health records were analyzed. Sentiment analysis in ENCN showed that patients with subacute COVID-19 have a higher proportion of positive sentiments compared to non COVID-19. Also, there are significant differences in polarity between both groups (Z=5.532, P<.001) with a polarity in COVID-19 patients of 0.108±0.299 versus a polarity in non COVID-19 patients of 0.09±0.301. Machine learning modeling reported that despite all models presenting high values, it is the neural network that presents the best indicators, over 0.8, and with significant P values between both groups. From Structural Topic Modeling analysis, the final model containing 10 topics was selected. It is noted a high correlation between topics 2, 5 and 8 (pressure ulcer and pharmacotherapy treatment), topics 1, 4, 7 and 9 (incidences related to fever and well-being state, and baseline oxygen saturation) and topics 3, 10 (blood glucose level and pain).

CONCLUSIONS

The ENCN may help in the development and implementation of more effective programs which allows to the COVID-19 pandemic patients a faster come back to a pre-pandemic way of life. Topic modeling could help identify specific clinical problems in patients and better target the care they receive.

CLINICALTRIAL

Impact of untreated dental caries and dental pain on sadness related to oral health of Brazilian children

PURPOSE

Children should feel sad when they believe that a negative outcome is permanent. The sadness that an oral problem might bring tends to contribute to children's loneliness and increase the social stress levels. The aim of this study was to evaluate the impact of untreated dental caries, dental pain, malocclusion, and traumatic dental injury on prevalence of sadness related to oral health among Brazilian children.

METHODS

This cross-sectional study was carried out with 397 children aged 8-10 years randomly selected from public and private schools in Diamantina, Brazil. The Brazilian version of the CPQ_8-10 was applied. Sadness was collected through the question, "In the last month how often did you feel sad because of your teeth or mouth?" and dental pain through the question, "In the last month, how many times have you had pain in your teeth?" One calibrated examiner (Kappa value intra examiner: 0.77-0.91; Kappa value inter examiner: 0.80-1.00) performed the exam for dental caries (DMFT), malocclusion (DAI), and dental trauma (O'Brien). Parents answered questions addressing socioeconomic issues. Descriptive analyses, Chi-square test, and hierarchical Poisson regression models were performed (IC 95%; p < 0.05)."

RESULTS

The prevalence of sadness related to oral health was 30.5% (n = 121). Sadness related to oral health was associated with untreated dental caries (PR: 1.46; 95% CI 1.32-2.46; p = 0.001 ) and dental pain (PR: 2.91; 95% CI 2.00-4.22; p < 0.001). Other clinical variables analyzed (traumatic dental injury and malocclusion) were not significantly associated with sadness related to oral health.

CONCLUSIONS

Children with untreated dental caries and dental pain presented a higher report of sadness related to oral health.

The burden of depressive disorders in musculoskeletal diseases: is there an association between mood and inflammation?

IMPORTANCE

Evidence emerged concerning how inflammatory arthritis and mood disorders can often occur in the same patient and show a similar clinical pattern. An overview of the rheumatological and psychiatric aspects of these diseases can certainly be useful for the improvement of patients' clinical and therapeutic management.

OBJECTIVE

The aim of this narrative review was to summarize existing literature about common pathogenetic and clinical aspects as a means of improving management and therapeutic approach in patients affected by rheumatoid arthritis, psoriatic arthritis and spondyloarthritis. Outcomes such as disease activity indexes and patient reported outcomes (PROs) were considered.

FINDINGS

Common pathogenetic pathways emerged between inflammatory arthritis and mood disorders. Pro-inflammatory mechanisms, such as TNFα, IL-6, IL-17 and oxidative stress factors as well as neurotransmitter alterations at the level of CNS and blood-brain barrier (BBB) cells are involved. The activation of these common pathogenetic pathways is, also, affected by the same triggers, such as smoking, stress, lifestyle, and evidence has emerged concerning the possibility of the clinical efficacy of using the same therapeutic approaches.

CONCLUSIONS

The main causes of the variability in clinical studies outcomes are the rheumatological diseases considered, the prevalence of depression in the general population and in patients with rheumatological diseases and the type of depressive symptom examined. Patients affected by inflammatory arthritis can present symptoms and signs in common with mood disorders, leading to possible clinical overlap. There are still few studies analyzing this concept: they are extremely heterogeneous, both in the characteristics of the population taken into consideration and in the methods used for the definition of depressive disorder, but the suggestions of the data obtained so far are promising and deserve to be pursued.

Preliminary development of a deep learning-based automated primary headache diagnosis model using Japanese natural language processing of medical questionnaire

BACKGROUND

Primary headaches are widespread and costly public health problems. However, there are insufficient medical resources for their treatment in Japan due to two reasons. First, the numbers of headache specialists and clinics remain insufficient. Second, neurologists and neurosurgeons mainly treat headaches in Japan. However, they mainly work as general stroke neurologists, so they cannot focus on primary headache treatment. To solve these problems, we preliminarily developed a deep learning (DL)-based automated diagnosis model from patients' Japanese unstructured sentences in the medical questionnaire using a DL framework. We hypothesized that the model would reduce the time and burden on both doctors and patients and improve their quality of life.

METHODS

We retrospectively investigated our primary headache database and developed a diagnosis model using the DL framework (Prediction One, Sony Network Communications Inc., Japan). We used age, sex, date, and embedding layer made by the medical questionnaire's natural language processing (NLP).

RESULTS

Eight hundred and forty-eight primary headache patients (495 women and 353 men) are included. The median (interquartile range) age was 59 (40-74). Migraine accounted for 46%, tension-type headache for 47%, trigeminal autonomic cephalalgias for 5%, and other primary headache disorders for 2%. The accuracy, mean precision, mean recall, and mean F value of the developed diagnosis model were 0.7759, 0.8537, 0.6086, and 0.6353, which were satisfactory.

CONCLUSION

The DL-based diagnosis model for primary headaches using the raw medical questionnaire's Japanese NLP would be useful in performing efficient medical practice after ruling out the secondary headaches.

Identifying Positive Features of the Sadness Prototype

Sadness, an emotional experience of daily life, is typically associated with negative experiences such as the loss of a loved one. However, sadness also has an adaptive function, as it can help us respond appropriately to environmental demands. While previous research has revealed positive functions of sadness, it is unclear whether laypeople recognize any positive aspects of sadness. In the present three-part study, we aimed to identify whether laypeople conceptualize any positive features of sadness. In Part 1, we asked Japanese participants (n = 122) to describe the features of "sadness," and their responses revealed 37 different sadness features, some of which were assumed to be positive aspects (e.g., meaning making). In Part 2, we asked a second group of Japanese participants (n = 140) to rate the centrality of each previously named feature, and we then classified the features into either central or peripheral sadness features. At this point, participants reported positive aspects of sadness (e.g., co-occurrence of positive emotion). To confirm the differences between central and peripheral features, in Part 3 we examined automatic responses toward these features from a third group of Japanese participants (n = 91) and demonstrated the relationship between the concept of sadness and its characteristic features. We presented these participants with a subset of the features of sadness and then asked them to complete a recall and recognition task. As expected, they recalled central features more often than peripheral features of sadness, and they generated false recognitions to central features. In conclusion, this three-part study indicated that there are positive features related to the function of sadness that laypeople can identify in their mental lexicon.