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PM2.5 was continuously collected in Ho Chi Minh City (HCMC), Vietnam, during the period from September 2019 to August 2020, which included the period of socioeconomic suppression caused by restrictions imposed in the face of the coronavirus disease of 2019. The concentrations of PM2.5 mass, water-soluble ions (WSIs), organic carbon (OC), elemental carbon (EC), and water-soluble organic carbon (WSOC) were determined to evaluate the seasonal variations in PM2.5, the effect of socioeconomic suppression on PM2.5, and potential PM2.5 sources in HCMC. The PM2.5 mass concentration during the sampling period was 28.44 +/- 11.55 mu g m(-3) (average +/- standard deviation). OC, EC, and total WSIs accounted for 30.7 +/- 6.6%, 9.7 +/- 2.9%, and 24.9 +/- 6.6% of the PM2.5 mass, respectively. WSOC contributed 46.4 +/- 10.1% to OC mass. NO3-, SO42-, and NH4+ were the dominant species in WSIs (72.7 +/- 17.7% of the total WSIs' mass). The concentrations of PM2.5 mass and total WSIs during the rainy season were lower than those during the dry season, whereas the concentrations of carbonaceous species during the rainy season were higher. The concentrations of PM2.5 mass and chemical species during the socioeconomic suppression period significantly decreased by 45%-61% compared to the values before this period. The OC/EC ratio (3.28 +/- 0.61) and char-EC/soot-EC (4.88 +/- 2.72) suggested that biomass burning, coal combustion, vehicle emissions, cooking activities are major PM2.5 sources in HCMC. Furthermore, the results of a concentration-weighted trajectory analysis suggested that the geological sources of PM2.5 were in the local areas of HCMC and the northeast provinces of Vietnam (where coal-fired power plants are located).
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Machine learning models can use information from gene expressions in patients to efficiently predict the severity of symptoms for several diseases. Medical experts, however, still need to understand the reasoning behind the predictions before trusting them. In their day-to-day practice, physicians prefer using gene expression profiles, consisting of a discretized subset of all data from gene expressions: in these profiles, genes are typically reported as either over-expressed or under-expressed, using discretization thresholds computed on data from a healthy control group. A discretized profile allows medical experts to quickly categorize patients at a glance. Building on previous works related to the automatic discretization of patient profiles, we present a novel approach that frames the problem as a multi-objective optimization task: on the one hand, after discretization, the medical expert would prefer to have as few different profiles as possible, to be able to classify patients in an intuitive way;on the other hand, the loss of information has to be minimized. Loss of information can be estimated using the performance of a classifier trained on the discretized gene expression levels. We apply one common state-of-the-art evolutionary multi-objective algorithm, NSGA-II, to the discretization of a dataset of COVID-19 patients that developed either mild or severe symptoms. The results show not only that the solutions found by the approach dominate traditional discretization based on statistical analysis and are more generally valid than those obtained through single-objective optimization, but that the candidate Pareto-optimal solutions preserve the sense-making that practitioners find necessary to trust the results. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Inapparent infection plays an important role in the disease spread, which is an infection by a pathogen that causes few or no signs or symptoms of infection in the host. Many pathogens, including HIV, typhoid fever, and coronaviruses such as COVID-19 spread in their host populations through inapparent infection. In this paper, we formulated a degenerated reaction-diffusion host-pathogen model with multiple infection period. We split the infectious individuals into two distinct classes: apparent infectious individuals and inapparent infectious individuals, coming from exposed individuals with a ratio of (1-p) and p, respectively. Some preliminary results and threshold-type results are achieved by detailed mathematical analysis. We also investigate the asymptotic profiles of the positive steady state (PSS) when the diffusion rate of susceptible individuals approaches zero or infinity. When all parameters are all constants, the global attractivity of the constant endemic equilibrium is established. It is verified by numerical simulations that spatial heterogeneity of the transmission rates can enhance the intensity of an epidemic. Especially, the transmission rate of inapparent infectious individuals significantly increases the risk of disease transmission, compared to that of apparent infectious individuals and pathogens in the environment, and we should pay special attentions to how to regulate the inapparent infectious individuals for disease control and prevention, which is consistent with the result on the sensitive analysis to the transmission rates through the normalized forward sensitivity index. We also find that disinfection of the infected environment is an important way to prevent and eliminate the risk of environmental transmission.
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Este caso objetiva promover uma reflexao sobre o processo de escrita de casos para ensino e direcionamentos para aplicação do método. Em 2020, João Luiz Marinho, doutorando em Administração na Universidade do Aprendizado (UNIAPRE), foi desafiado pelo professor Fernando a escrever o seu primeiro caso para ensino para aplicação na disciplina de Estratégias Organizacionais, da qual era estagiário em docencia. Porém, muitos questionamentos sobre a construção e aplicação de casos para ensino sondavam os pensamentos de João, uma vez que este nao tinha experiencias anteriores com o método, possuía pouca prática na docencia e a migração das aulas para a modalidade on-line era novidade. Assim, a proposta foi fazer com que os alunos se colocassem no lugar de João, a fim de propiciar um debate sobre a escrita e aplicação de um caso para ensino na modalidade on-line. Sugere-se sua aplicação nos cursos de pos-graduaçâo lato sensu e stricto sensu em Administração, nas disciplinas de Metodologia e Casos para Ensino.Alternate :This case aims to promote a reflection on the teaching case writing process and directions for applying the method. In 2020, João Luiz Marinho, a doctoral candidate in Administration at the University of Learning (UNIAPRE), was challenged by Professor Fernando to write his first teaching case for application in the Organizational Strategies discipline, of which he was an intern in teaching. However, many questions about the construction and application of teaching cases probed João's thoughts, since he had no previous experience with the method, he had little practice in teaching, and the migration of classes to the online mode was very new. Thus, the proposal is to make students put themselves in João's place, in order to provide a debate on the writing and application of a case for online teaching. It is suggested that it be applied in lato sensu and stricto sensu graduate courses in Administration in the disciplines of Methodology and Teaching Cases.
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This investigation presents results of Computational Fluid Dynamics (CFD) modelling of aerosol behaviour within an arbitrary 'realistic' 100m2 office environment, with dynamic and variable respiratory droplet release profile applied based on published findings (Morawska et al., 2009). A multitude of ventilation strategies and configurations have been applied to the base model to compare the effectiveness of reducing the concentration of suspended aerosols over time. A key finding of the investigation indicates a relatively low sensitivity to increasing outside air percentage, and that the benefit from this strategy is heavily dependent on the in-duct droplet decay factor. The application of local recirculating air filtration systems with MERV-13 filters mounted on occupant desks proved significantly more effectiveness than increasing outside air concentration from 25% to 100% in reducing the quantity of suspended aerosols. This highlights that the ventilation industry should perhaps focus on opportunities to integrate filtration systems into furniture, partitions, cabinetry etc., and that an appliance-based solution may be more beneficial for reducing COVID-19 transmission in buildings (and likely more straightforward) than modifications to central ventilation systems, particularly in the application of refurbishments and retrofits. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.
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Covid-19 has been one of the most disruptive pandemics to date. Among the other aspects of disruption, it also disrupted the way people work in organizations. Many of the organizations surrendered their offices for good. However, there are many ill effects of these unconventional work practices also. This research study aims to explore the perception of the employees towards the adoption of Virtual and flexible work practices. The study uses a conjoint analysis approach on different possible Work Practice Profiles, that specify the nature of work (Virtual, offline, or hybrid), nature of work schedule (flexible, or fixed), nature of ownership (individual, or team), and length of working hours (8.5 hours, or 9.5 hours or 10.5 hours). The study finds that the number of working hours is the most important criterion for the employees followed by mode of work, responsibility, and work schedule. © 2023 IEEE.
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BACKGROUND: It is unknown how the patterns of negative and positive attentional biases in children predict fear of COVID-19, anxiety symptoms, and depression symptoms during the COVID-19 pandemic. The study identified profiles of negative and positive attentional biases in children and examined their association with emotional symptoms during the COVID-19 pandemic. METHOD: 264 children (girls: 53.8% and boys: 46.2%) of 9-10 years born in Hong Kong or mainland China from a primary school in Shenzhen, People's Republic of China were involved in a two-wave longitudinal study. Children completed the COVID-19 Fear Scale, the Revised Child Anxiety and Depression Scale, and the Attention to Positive and Negative Information Scale to measure fear of COVID-19, anxiety and depression symptoms, and negative and positive attentional biases in classrooms. After six months, they completed the second assessment of fear of COVID-19, anxiety symptoms, and depression symptoms in classrooms. Latent profile analysis was conducted to reveal distinct profiles of attentional biases in children. A series of repeated MANOVA was performed to examine the association of profiles of attentional biases to fear of COVID-19, anxiety symptoms, and depression symptoms across 6 months. RESULTS: Three profiles of negative and positive attentional biases were revealed in children. Children with a "moderate positive and high negative attentional biases" profile had significantly higher fear of the COVID-19 pandemic, anxiety symptoms, and depression symptoms than children with a "high positive and moderate negative attentional biases" profile. Children with a "low positive and negative attentional biases" profile were not significantly different in fear of COVID-19, anxiety symptoms, and depression symptoms than those with the other two profiles. CONCLUSIONS: Patterns of negative and positive attentional biases were related to emotional symptoms during the COVID-19 pandemic. It might be important to consider children's overall patterns of negative and positive attentional biases to identify children at risk of higher emotional symptoms.
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Purpose: With the rapid development of sharing economy, travelers are facing choices between conventional hotels and the peer-to-peer sharing accommodation in urban tourism. The purpose of this study is to examine how travelers form their preferences in such choice situations and whether/how their preference formation mode would change with the COVID-19 pandemic. Design/methodology/approach: A relative preference model was constructed and estimated for both domestic and outbound tourists, based on two waves of survey data collected before and after the COVID-19. The results of this study were compared to derive the evolution of preference formation patterns. Findings: A set of 15 key value attributes and personal traits was identified, together with their differential effects with the pandemic. Their divergent effects between domestic and outbound trips were also delineated. Based on these findings, the competitive edges and advantageous market profiles were depicted for both hotel and sharing accommodation sectors. Originality/value: This study contributes to the knowledge of tourists' preference between accommodation types and adds empirical evidences to the impact of the pandemic on tourist behavior patterns. Both hotel and sharing accommodation practitioners can benefit from the findings to enhance their competitiveness.
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PurposeThe key concern nowadays is smartphone addiction and user profiles. Following the risk and protective factors framework, the authors aim to characterize smartphone users according to two levels: (1) individual: referred to the use (i.e. boredom proneness, compulsive app downloading smartphone addiction) and (2) microsystem: referred to family and peers (i.e. family harmony and phubbing). Besides, the authors will derive useful managerial implications and strategies.Design/methodology/approachFirst, an extensive literature revision and in-depth interviews with experts were employed to identify the addiction-related variables at the individual and microsystem level. Second, information was collected from a sample of 275 Spanish smartphone users, and a K-means clustering algorithm was employed to classify smartphone users.FindingsThe proposed traffic lights schema identifies three users' profiles (red, yellow and green) regarding their smartphone addiction and considering individual and microsystem critical variables.Originality/valueThis study proposes a practical and pioneer traffic lights schema to classify smartphone users and facilitate each cluster's strategies development.
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This study aimed to investigate the differences in mental health during COVID-19, specifically among second-, third-, and fourth-year Japanese university students (n = 2,157; n = 2,000; and n = 2,284; respectively). A one-way MANOVA was conducted to assess the association between year of enrollment (academic years 2020, 2021, and 2022) and each of the eight subscales of the counseling Center Assessment Psychological Symptoms-Japanese. For second-year students, depression and generalized anxiety mean scores were higher in 2021 than those in 2020 and 2022. Alcohol use mean scores got smaller each year. For third-year students, depression, generalized anxiety, social anxiety, hostility, and alcohol use were significantly higher in 2021 than those in 2020 and 2022. Among fourth-year students, means for all eight subscale categories were significantly higher in 2021 than those in 2020 and 2022. The findings found worsened mental health profiles during 2021, which recovered to approximate pre-pandemic levels in 2022. This study demonstrates that university students' mental health has been negatively impacted by the COVID-19 pandemic, an effect which is more salient among fourth-year students. Further, it offers insights into mental health trends among Japanese university students and a possible foundation for learning about changes among university students worldwide.
Subject(s)
COVID-19 , Mental Health , Students , Humans , Anxiety/epidemiology , Depression/epidemiology , East Asian People , Pandemics , Students/psychology , UniversitiesABSTRACT
Introduction: The COVID-19 has generated a series of problems such as that of the education sector that allowed the use of digital platforms in order not to lose the school year, this has produced in teachers and students the challenge of adapting to a new reality of teaching and learning, therefore, it is worth adapting instruments that assess the academic stress produced. The objective was to evaluate the psychometric properties of the academic stressors scale (ECEA) in the context of COVID-19. Method: The sample consisted of 300 participants in the first study and 566 students from public and private universities between 18 and 30 years of age (M_age=21.34;SD_ age=2.926) in the second study. In the first study, the internal structure of the construct was verified through exploratory factor analysis, while in the second study it was verified through confirmatory factor analysis. Results: The results of the first study indicated a factorial structure equivalent to the theoretical conceptualization;however, the empirical recommendation consisted of removing some items because their factorization was complex. With respect to the second study, four models were obtained, of which the seven-factor oblique model is the most significant (chi(2)=2393.181;gl=608;.2/gl=.121;CFI=.999;TLI=.999;SRMR=.022;RMSEA=.020). Likewise, the reliability of the scale and the scores were significant. Conclusions: Finally, the ECEA is an instrument that has adequate psychometric properties and is suitable for research purposes and for describing Peruvian university groups in the context produced by COVID-19.
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Severe acute respiratory syndrome, COVID-19, is a global pandemic and is facing unprecedented challenges. The introduction of several precautions during the pandemic, such as lockdown and long-term isolation, might result in the adoption of poor dietary habits, raising the medium-term risk of noncommunicable diseases. Determining the impact of nutrition is crucial since dietary habits may prevent both nutritional disorders and act as an immunostimulant, assisting in the prevention, treatment, and recovery of patients with viral infections, particularly those with COVID-19. Although there are various medications such as antiviral drugs, interferons, etc., and vaccines to combat COVID-19 but they all have many limitations. There is a high need to move towards a more promising approach to cure this illness. Nutrigenetics involves determining how nutrients and other food ingredients affect gene regulation and gene expression. Nutrigenetics help in identifying a person's unique nutritional needs based on their genetic makeup and the relationship between diet and chronic diseases, which will aid in understanding the etiology of chronic illnesses like cancer, type 2 diabetes, obesity, and cardiovascular disease. For the proper functioning of immune function, a healthy and balanced diet is very necessary. The consumption of macronutrients (proteins, fats, and carbohydrates) and micronutrients (vitamins;D, C, E, folate, B6, B12, and minerals;zinc, copper, iron, and selenium) are essential for the normal functioning of the immune function and increased resistance to viral infections such as COVID-19. Gut microbiota plays a very important role in the regulation of the immune system and hence in various viral infections. It has been observed that people suffering from intestinal dysbiosis are more linked to chronic diseases such as obesity and cardiovascular diseases and are at higher risks of COVID-19. The human microbiome is supported by dietary and host-derived nutrients, enabling its survival. Because changes in diet can impact the composition of bacteria in the gut, changes in the microbiota can be linked to changes in nutrition. A number of probiotics such as Lactobacillus and Bifidobacterium have been reported to significantly reduce the severity of viral infections as well as enhance intestinal health and general immunity. In conclusion, nutrigenetics is crucial for proper immune functioning and can be a vital tool for boosting the immune system and helping to fight against viral infections such as COVID-19. © 2023 Elsevier Inc. All rights reserved.
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Teaching staff are especially vulnerable to COVID-19-related stress, due to the significant demands they have experienced. Yet, many have shown resilience-good mental health despite stress exposure. The current study used a person-centered approach to identify distinct profiles according to individual differences in psychosocial risk and protective factors. Latent Profile Analysis and ANOVAs were employed among 350 Israeli teaching staff during the fourth wave of COVID-19. Two distinct profiles, "risk" (55%) and "resilience" (45%) were identified. While groups showed no differences in COVID-19-related stress outcomes, they consistently differed in their psychological reaction to COVID-19 (psychopathology, compassion fatigue, and compassion satisfaction).
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The quantity and quality of environmental stimuli and contexts are crucial for children's development. Following the outbreak of SARS-CoV-2 (COVID-19), restrictive measures have been implemented, constraining children's social lives and changing their daily routines. To date, there is a lack of research assessing the long-lasting impacts that these changes have had on children's language and emotional-behavioral development. In a large sample of preschoolers (N = 677), we investigated (a) the long-lasting effects of changes in family and social life and in daily activities over the first Italian nationwide COVID-19-pandemic-related lockdown upon children's linguistic and emotional-behavioral profiles and (b) how children's demographic variables and lifelong family characteristics moderated these associations within a multiple-moderator framework. Our findings showed a relationship between the time spent watching TV/playing video games and affective problems that was moderated by the number of siblings. Our findings showed that children who could be at high risk in more normal circumstances, such as only children, have been particularly harmed. Therefore, assessing the long-term effects of lockdown-related measures and how these could have been moderated by potential risk/protective factors added significant information to the existing literature.
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Identifying molecular targets of a drug is an essential process for drug discovery and development. The recent in-silico approaches are usually based on the structure information of chemicals and proteins. However, 3D structure information is hard to obtain and machine-learning methods using 2D structure suffer from data imbalance problem. Here, we present a reverse tracking method from genes to target proteins using drug-perturbed gene transcriptional profiles and multilayer molecular networks. We scored how well the protein explains gene expression changes perturbed by a drug. We validated the protein scores of our method in predicting known targets of drugs. Our method performs better than other methods using the gene transcriptional profiles and shows the ability to suggest the molecular mechanism of drugs. Furthermore, our method has the potential to predict targets for objects that do not have rigid structural information, such as coronavirus.
Subject(s)
Machine Learning , Transcriptome , Transcriptome/genetics , Drug Discovery/methods , Proteins/chemistry , Gene Regulatory NetworksABSTRACT
Given their occupational risk profile, HCWs were the first to receive anti-SARS-CoV-2 vaccination. However, breakthrough infections remained common, mainly sustained by new SARS-CoV-2 variants of concern (VOCs) that rapidly spread one after another in Italy. Evidence suggests that the measured level of anti-SARS-CoV-2 antibodies does not clearly predict the level of protection conferred by either natural infection or vaccine-induced immunization, highlighting the need for further study on the diversity in susceptibility to SARS-CoV-2 infection. The present study aimed to characterize different risk profiles for SARS-CoV-2 infection in HCWs who had recently received the booster dose, and who were classified according to their immunization profile. The very small number of workers infected during the 8 months following the primary-cycle administration represents proof of the vaccine's effectiveness against non-omicron strains. The comparison among different immunization profiles showed that hybrid immunization (vaccine plus natural infection) elicits higher antibody levels. However, hybrid immunization does not always provide better protection against reinfection, thus suggesting that the immunization profile plays a major role as a virus-host interaction modifier. Despite the high resistance to the reinfection, the peri-booster infection had a not-neglectable infection rate (5.6%), this further reinforcing the importance of preventive measures.
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To examine how and when stress affect individual (i.e., psychological health) and relationship well-being (i.e., marital satisfaction) during the COVID-19 pandemic, the present study used latent profile analysis to identify the typologies of communication and investigated whether the typologies would moderate the associations between stress and individual and relationship well-being in a sample of adults living in China (N = 3,354). Results revealed that (a) stress was negatively associated with psychological health and marital satisfaction during the COVID-19 pandemic and that its effect on psychological health was greater than that on marital satisfaction and (b) four profiles were identified: low communication (10%), moderate communication (43%), positive communication (43%), and contradictory communication (5%). Further, the typologies moderated the effects of stress on psychological health and marital satisfaction, but the patterns of moderation differed in psychological health and marital satisfaction. © 2022 Taylor & Francis Group, LLC.
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OBJECTIVE: The study is an explorative investigation aimed to assess the differences in acute stress response patterns of health workers facing coronavirus disease 2019 (COVID-19) during Italy's first lockdown. METHODS: A cross-sectional investigation using convenience sampling method was conducted in Italy during April 2020. Eight hundred fifty-eight health workers participated in the research filling out self-report measures including Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder (GAD-7), Insomnia Severity Index (ISI), and Impact of Event Scale-Revised (IES-R). RESULTS: Moderate/severe depression was found in 28.9% (95% CI, 25.8-32.04), moderate/severe anxiety in 55.4% (95% CI, 51.9-58.8), insomnia in 15% (95% CI, 12.5-17.5), and distress in 52.5% (95% CI, 48.5%-56.6) of participants. The 3% of health workers reported frequent suicidal thoughts. Female sex, working for >15 h/week in a COVID-19 unit, and living apart from family were associated with a significantly higher risk of distress, anxiety, insomnia, depression, and functional impairment. Four profiles were identified on the basis of psychopathological measures: Profile_0 included 44% (N = 270); Profile_1, 25.6% (N = 157); Profile_2, 19.1% (N = 117); and Profile_3, 11.3% (N = 69) of participants. Results showed a significant effect for Profiles X IES-R (η2 = 0.079; f = 0.29), indicating that in all profiles, except for Profile_0, avoidance scale is lower than hyperarousal and intrusion symptoms scales of the IES-R. This characteristic could be a probable index of the control exerted by the responders to not fly away from their job. CONCLUSION: The identification of specific profiles could help psychiatrists and emergency psychologists to build specific interventions in terms of both primary and secondary prevention to face future waves of the COVID-19 outbreak.
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With the COVID-19 outbreak, the population was suddenly forced to "stay at home". Although research suggests that social isolation affects health and wellbeing, reactions may vary depending on individuals. The current study assessed the relationships between personality variables (preference for solitude and Big Five personality), mental health (anxiety, stress, loneliness), and creativity, and tried to determine whether the identified personality profiles affect individuals' mental health and creativity. French respondents (N = 430) filled in an online questionnaire during the first lockdown in Spring 2020. The results showed that the preference for solitude and personality variables of the Big Five predicted individuals' mental health and creativity. Moreover, a cluster analysis revealed three profiles of individuals: "Affiliation", "Emotionally Stable Lonely" and "Emotionally Unstable Lonely". Results showed that individuals with "Affiliation" and "Emotionally Unstable Lonely" profiles expressed higher stress and anxiety, and the latter performed better on a divergent creative thinking task. By contrast, those with an "Emotionally Stable Lonely" profile expressed a lower level of loneliness, and performed better on a creative insight task. These findings reveal the importance of personality profiles in psychological reactions during lockdowns. With this knowledge, health professionals could develop appropriate interventions to accompany high-risk individuals in situations of social isolation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12144-021-01885-3.
ABSTRACT
Intuitive eating (IE) is a promising approach to improve eating behaviors that is primarily focused on eating in attunement with one's internal signals of hunger and satiety. Intuitive eating is related to an array of benefits including improved physical and mental health;however, many gaps exist in the IE literature. The current work utilized a novel approach in the IE context, a latent profile analysis (LPA) of 947 adults, to identify common patterns of responses to the four subscales of IE during the early COVID-19 pandemic, a time period currently understudied in the IE field. The study employed independent LPAs for two subsamples (n = 446 undergraduate students and n = 501 community members) to detect potential differences in model structure. The derived profiles were then used to test associations between COVID-19-related changes in dietary behaviors and weight concern, gender, weight loss attempts, physical activity, and mental health. LPAs of the combined sample resulted in a four-profile model. This model structure was not replicated in the undergraduate and community subsamples which showed notably different profile solutions. The two undergraduate profiles distinguished patterns of responses that were associated with lower overall (Low) and moderately high (Mod-high) levels of IE. Men were more likely to be in the Mod-High profile compared to women and the Low profile was associated with higher amounts depression, anxiety and weight loss attempts, increases in food eaten during the COVID-19 pandemic, and higher probabilities of increased weight concern during the pandemic. The community subsample showed a four-profile solution. 1: high levels of Unconditional Permission to Eat (UPE) and low levels of Eating for Physical Rather than Emotional Reasons (EPR), Reliance on Hunger and Satiety Cues (RHSC), and Body-Food Choice Congruence (B-FCC), which was related to increases in amount of food eaten, depression, and anxiety, and higher probabilities of increases in weight concern compared to the other profiles. 2: moderately high levels of UPE and very low levels of EPR, RHSC, and B-FCC, which showed the highest rates of weight loss attempts as well as high probabilities of increased weight concern. 3: moderate to high levels of all 4 IE subscales characterized by fewer weight loss attempts than profiles 1 and 2. 4: highest overall levels of IE which had the most stability in their weight concern compared to the other profiles. There were no gender differences between the four profiles of the community subsample and there were no associations with physical activity in either the undergraduate or community subsamples' profiles. These findings support the hypothesis that multiple, distinct profiles of IE exist and have unique relationships with health-related behaviors and outcomes. However, profile structures did vary between the undergraduate and community subsamples, suggesting limited generalizability between the two groups. Together, results suggest that IE levels both globally and in specific, naturally-occurring combinations of subscales are differentially related to eating and dieting behaviors, body image, and mental health. In application, findings suggest there may be benefits to recognizing varying patterns of IE to create tailored techniques for interventions seeking to increase these adaptive eating behaviors. Future research should continue to employ person-centered approaches alongside variable-centered ones to study more diverse populations and non-pandemic conditions. (PsycInfo Database Record (c) 2022 APA, all rights reserved)