Two-stage Cluster Analysis Research Articles

Characterizing emotion profiles in non-clinical population: A cluster analytical study.

Emotion processing and beliefs about pleasure can influence the development and severity of depressive symptoms. This cluster analysis study aimed to profile a large sample of college students using pleasure experience, emotion expression and regulation as well as beliefs about pleasure. We also aimed to validate the resultant clusters in terms of depressive symptoms. A set of checklists capturing beliefs about pleasure and the three facets of emotion processing was administered to 1028 college students. A two-stage cluster analysis was used to analyze the profile of these emotional aspects in these college students. Our results showed that a three-cluster solution best fit the data. Cluster 1 (n=536) was characterized by moderate levels of beliefs about pleasure, pleasure experience, emotion expression, and regulation; Cluster 2 (n=402) was characterized by generally high levels of beliefs about pleasure, pleasure experience, emotion expression, and regulation; Cluster 3 (n=90) was characterized by relatively low levels of beliefs about pleasure, pleasure experience, emotion expression, and regulation. The three clusters differed significantly in the severity of depressive symptoms. Our findings suggest the existence of three emotional subtypes, which may be useful in early detection of youth at risk of developing depression.

The Job Performance of Fly-In-Fly-Out Workers in Industrial Enterprises (on the Example of Oil and Gas Production, Diamond Mining Production, and Construction)

With high health requirements for FIFO work at industry, workers may experience adverse changes in psychological well-being and health status. This makes it relevant when developing the job performance model to rely on considering not only the effectiveness by employees but also their psychophysiological “cost of activity”, which is not reflected in modern scientific research. This article theoretically substantiates and empirically develops a job performance typology of fly-in-fly-out workers at industrial enterprises by correlating three components: effectiveness, psychophysiological resources, and the way of accomplishing tasks. The study involved 359 fly-in-fly-out workers in oil and gas, diamond mining and construction industries with different duration of the fly-in period, operating in the South and the North of the Russian Federation. The research methods included questioning, psychophysiological instrumental testing, and psychological testing. Statistical processing was carried out using the methods of descriptive statistics, two-stage cluster analysis, and multivariate analysis of variance. As a result of the study, six types of job performance of fly-in-fly-out personnel of industrial enterprises were identified. The employees at industrial enterprises of all six types of job performance correspond to their position and perform the assigned tasks, the difference in them lies in the desire to show an average or the highest possible result, as well as how much internal resources the employee spends to achieve this result and how quickly he restores them, which is expressed in terms of his state and well-being. Based on the results of these connections, measures for personnel management for industrial enterprises were proposed.

Do alexithymia and negative affect predict poor sleep quality? The moderating role of interoceptive sensibility.

Emotion-related hyperarousal is an important core pathology of poor sleep. Studies investigating the interplay of alexithymia and affective experiences in determining sleep quality have yielded mixed results. To disentangle the inconsistency, this study examined the concurrent predictive power of alexithymia, and negative and positive affect, while incorporating interoceptive sensibility (IS) as a possible moderator. A sample of 224 (70.10% were female) participants completed the Toronto Alexithymia Scale, Positive and Negative Affect Schedule, Pittsburgh Sleep Quality Index, Multidimensional Assessment of Interoceptive Awareness (MAIA), and Marlowe-Crowne Social Desirability Scale (for controlling response bias) using paper and pencil. A two-stage cluster analysis of the MAIA was used to capture IS characteristics. Stepwise regression was conducted separately for each IS cluster. A three-group structure for IS characteristics was found. Higher alexithymia was predictive of poor sleep quality in the low IS group, while higher negative affect predicted poor sleep quality in the moderate and high IS groups. Additionally, alexithymia and positive affect were significantly different in the three IS groups, while negative affect and sleep quality were not. Emotion and cognitive arousal may impact sleep quality differently in individuals with different levels of internal focusing ability, depending on physiological versus emotional self-conceptualization. The implications on pathological research, clinical intervention, study limitations and future directions are discussed.

VERİ MADENCİLİĞİNDE İKİ AŞAMALI KÜMELEME İLE İNSANİ GELİŞME ENDEKSİ İNCELEMESİ

Bu çalışmada ulusal düzeyde sosyoekonomik gelişmeyi ölçen ve ekonomiler arasındaki farkları karşılaştıran göstergelerden olan İnsani Gelişme Endeksi ve Cinsiyet Gelişme Endeksi ile ülkelerin gelişim düzeyleri incelenmektedir. Ülkelerin gruplanmasında hangi değişkenlerin etkili olduğu veri madenciliği tekniklerinden biri olan iki aşamalı kümeleme analizi ile araştırılmaktadır. Çalışmada kullanılan verilerin tamamı Birleşmiş Milletler Gelişme Programı(UNDP)’ndan elde edilmektedir. Analizler UNDP tarafından yayımlanan rapordaki 2019 yılına ait 189 ülke için 2268 gözlem ile gerçekleştirilmiştir. İnsani Gelişme Endeksi sonuçlarına göre ülkeler yüksek, orta ve düşük gelişme endeksine sahip ülkeler olmak üzere üç grupta toplanmaktadır. Cinsiyet Gelişme Endeksi sonuçlarına göre ülkeler yüksek, yüksek-orta, orta, orta-düşük ve düşük gelişme endeksine sahip ülkeler olmak üzere beş grupta toplanmaktadır. İnsani Gelişme Endeksi için belirlenen grup sayısının UNDP raporunda açıklanan grup sayısından faklı olduğu, Cinsiyet Gelişme Endeksi’nin grup sayısının rapor ile aynı olduğu belirlenmiştir. Genel olarak sonuçlar, kadınların erkeklere nazaran daha uzun ömürlü olduğunu, kadın ve erkeklerin eğitim seviyelerinin hemen hemen aynı olduğunu, erkeklerin kadınlara göre daha yüksek milli gelire sahip olduğunu göstermektedir. Böylece cinsiyet faktörünün gelişme endeksi üzerindeki etkisi ortaya koyulmaktadır.

Detecting the research structure and topic trends of social media using static and dynamic probabilistic topic models

PurposeA huge volume of published research articles is available on social media which evolves because of the rapid scientific advances and this paper aims to investigate the research structure of social media.Design/methodology/approachThis study employs an integrated topic modeling and text mining-based approach on 30381 Scopus index titles, abstracts, and keywords published between 2006 and 2021. It combines analytical analysis of top-cited reviews with topic modeling as means of semantic validation. The output sequences of the dynamic model are further analyzed using the statistical techniques that facilitate the extraction of topic clusters, communities, and potential inter-topic research directions.FindingsThis paper brings into vision the research structure of social media in terms of topics, temporal topic evolutions, topic trends, emerging, fading, and consistent topics of this domain. It also traces various shifts in topic themes. The hot research topics are the application of the machine or deep learning towards social media in general, alcohol consumption in different regions and its impact, Social engagement and media platforms. Moreover, the consistent topics in both models include food management in disaster, health study of diverse age groups, and emerging topics include drug violence, analysis of social media news for misinformation, and problems of Internet addiction.Originality/valueThis study extends the existing topic modeling-based studies that analyze the social media literature from a specific disciplinary viewpoint. It focuses on semantic validations of topic-modeling output and correlations among the topics and also provides a two-stage cluster analysis of the topics.

The Influence of Taxation on Income Inequality: Analysis of the Practice in the EU Countries

The growing economic inequality around the world is recognized as a global problem of mankind. At the same time, the key tool for reducing inequality and ensuring the achievement of sustainable development goals is the taxation system given its distributive function. That is why this paper puts forward and proves a scientific hypothesis according to which direct taxation has a significant impact on economic inequality, with its scale and sphere depending on the level of economic development and the specific architecture of the tax system adopted in a particular country. The study relies on data from 28 European Union countries, including the United Kingdom, whose tax systems are not identical but harmonized in accordance with European Union directives, the same as the legislation in other economic sectors. Accordingly, it can be concluded that similar institutional characteristics are present. We have used the method of two-stage cluster analysis, which is meant for identifying the natural splitting of the mass of data into groups, then carried out regression analysis and built some models. The contribution of the study is revealing a number of important regularities that are significant for characterizing the dependence of income inequality on direct taxation as well as formulation recommendations for improving the tax policies of European Union countries, with the potential of policy implications. The results obtained can play a significant role in the development and further harmonization of tax systems and resolving the global problem of increased inequality within and between countries.

Face specific inversion effects provide evidence for two subtypes of developmental prosopagnosia

Many studies have attempted to identify the perceptual underpinnings of developmental prosopagnosia (DP). The majority have focused on whether holistic and configural processing mechanisms are impaired in DP. However, previous work suggests that there is substantial heterogeneity in holistic and configural processing within the DP population; further, there is disagreement as to whether any deficits are face-specific or reflect a broader perceptual deficit. This study used a data-driven approach to examine whether there are systematic patterns of variability in DP that reflect different underpinning perceptual deficits. A group of individuals with DP (N = 37) completed a cognitive battery measuring holistic/configural and featural processing in faces and non-face objects. A two-stage cluster analysis on data from the Cambridge Face Perception Test identified two subgroups of DPs. Across several tasks, the first subgroup (N = 21) showed typical patterns of holistic/configural processing (measured via inversion effects); the second (N = 16) was characterised by reduced or abolished inversion effects compared to age-matched control participants (N = 91). The subgroups did not differ on tasks measuring upright face matching, object matching, non-face holistic processing, or composite effects. These findings indicate two separable pathways to face recognition impairment, one characterised by impaired configural processing and the other potentially by impaired featural processing. Comparisons to control participants provide some preliminary evidence that the deficit in featural processing may extend to some non-face stimuli. Our results demonstrate the utility of examining both the variability between and consistency across individuals with DP as a means of illuminating our understanding of face recognition in typical and atypical populations.

The cluster analysis of patients with morbid obesity in bariatric and metabolic surgery

INTRODUCTION. Existing classifications of various forms of obesity are poorly adapted to the practical goals of bariatric surgery from the standpoint of personalizing the choice of method and volume of intervention.The OBJECTIVE was develop new approaches to stratification of patients with morbid obesity based on cluster analysis; to evaluate of the effectiveness and safety of metabolic surgical interventions, depending on the belonging of patients to a particular bariatric cluster.METHODS AND MATERIALS. The study included 745 bariatric patients. To form clinical and demographic groups, a two-stage cluster analysis procedure was used using the SPSS 16.0 package with 11 categorical and 2 quantitative variables. The efficacy and safety of metabolic surgical interventions depending on the patients' belonging to a particular bariatric cluster was evaluated.RESULTS. As a result of cluster analysis in the general population of patients with morbid obesity, 3 unique clinical and demographic groups (clusters) of patients were identified, characterized by an initial set of similar indicators that differed from that in patients of other groups (clusters): the1st cluster: «premorbid obesity»; the 2nd cluster: «morbid obesity without metabolic syndrome and complications»; the 3rd cluster: «morbid obesity with metabolic syndrome and/ or complications». The best long-term results on the BAROS scale were generally observed in patients of the 1st cluster (87.8 % of excellent and good results compared to 66.7 % in patients of the 2nd clusters and 65.5 % in patients of the 3rd cluster, p<0.001). The total risk of serious complications in patients of the 3rd cluster was 2.4 times higher than in patients of the 1st cluster (P<0.05) and 1.9 times higher than in patients of the 2nd cluster (P>0.05).CONCLUSION. The procedure of clustering patients with obesity allows individualizing the indications for conducting and choosing bariatric interventions.

Smartphone addiction and its associated behaviors among medical and dental students in Pakistan: A cross-sectional survey.

INTRODUCTION:Addiction refers to the irresistible urge to engage in certain actions or dependence on a particular substance despite knowing negative consequences. The current study evaluated the severity of Smartphone addiction and the factors associated with cell phone-like activity.MATERIALS AND METHODS:This cross-sectional study was conducted from July to August 2019 among medical and dental students in Karachi, Pakistan. A pretested self-administered questionnaire was used among 400 students. The mobile phone addiction was assessed using a 20-item, Mobile Phone Addiction Scale. A two-stage cluster analysis was used to assess mobile phone addiction-like behaviours. Chi-square test was used to find associations between categorical variables. Kolmogorov–Smirnov to test normality of data were also used. A P < 0.05 was considered to be statistically significant for all tests.RESULTS:Out of the total 400 students, the majority 316 (79%) comprise female students. The mean age was 20.54 ± 1.59 years. In 184 (48%) students, there was evidence of mobile phone addiction-like behavior. The prevalence was higher in female than male students and among older compared to adolescent students; the differences were statistically nonsignificant. A higher median score ≥ of 4 is found in questions related to components reflected intense desire, impaired control, and tolerance and harmful mobile use.CONCLUSION:This study highlights that a large number of students are addicted to their smartphones. Smartphone addiction continues to be the most problematic addiction aided by the presence of intense desire, impaired control tolerance, and harmful mobile use. The phenomenon must be fully understood to draw deeper and richer inferences about the origins of this addictive behavior, which is becoming more prevalent in our Pakistani society on a daily basis.

Collective Actions and Leadership Attributes: A Cluster Analysis of Water User Associations in Chile

Good leaders can greatly influence the effective governance of water resources, however, how their attributes relate to group cooperation in Water User Associations (WUAs) remains an open question. Using the case of Chile, we explore the factors of three non-cooperative behaviors in WUAs by performing a two-stage cluster analysis. The results describe four clusters that differ in structural and human characteristics, where highly cooperative WUAs are characterized by having presidents who dedicate more time to their duties, are more active in applying for governmental subsidies, are embedded in social organizations, have high levels of bridging social capital, and have a positive attitude toward the presidency. Our results add to the limited empirical knowledge about the role of leadership in fostering cooperation in the use of common-pool resources. This article sheds light on this matter as the results suggest that policy interventions should aim at strengthening social capital and providing incentives to increase the time dedication of presidents to the WUAs duties.

High School Students’ Accelerometer-Measured Physical Activity and Sedentary Behavior by Motivational Profiles Toward Physical Activity

ABSTRACT Purpose: Based on a Self-Determination Theory with a person-centered approach, the purposes were: (1) to identify motivational profiles toward physical activity (PA) among high school students, and (2) to compare students’ accelerometer-measured PA and sedentary behavior (SB) levels between the motivational profiles toward PA. Methods: The present study followed a cross-sectional design. A total of 394 high school students (173 females; final sample = 360 and 198 for the purposes 1 and 2, respectively) aged 12–16 years completed the study. Participants’ PA and SB levels were objectively measured by ActiGraph GT3X+ accelerometers (right hip) during seven consecutive days. Later, motivation toward PA was measured by the Behavioral Regulation in Exercise Questionnaire. Results: Based on a two-stage cluster analysis approach, the results identified three clusters: (1) “Self-determined motivational profile toward PA” (65.3%); (2) “Non-self-determined motivational profile toward PA” (23.9%), and (3) “Controlled motivational profile toward PA” (10.8%). The results of the chi-square test showed that a statistically significantly higher percentage of males were represented in cluster 1 (p < .001). The results of the one-way analysis of variance showed that students from cluster 1 had statistically significantly lower levels of SB, and higher levels of light PA, moderate-to-vigorous PA and total PA than those from cluster 2 (p < .05; |d| = 0.40–0.61). Conclusions: In line with the Self-Determination Theory, the students within the self-determined motivational profile had lower SB and higher PA. This preliminary evidence could inform and guide future policy regarding students’ PA promotion.

Análise de agrupamento (Clusters Analysis) em duas etapas no ensino à distância: Uma forma de reduzir as lacunas na literatura científica no ensino à distância

Background: Dropout rates are often very high in distance education. A plethora of research has been conducted to identify the contributing factors; however, the majority of the findings are inconclusive and point to the fact that it is difficult to isolate a single explanatory factor. While frequently examined factors are personal and environmental, there is less research on the relationship between course design and retention or dropout. Method: This paper presents a study involving two-stage cluster analysis of 623 variables from 19 university courses at one open and distance education (ODE) institution. To this end, the current study grouped the courses into five types based on 22 variables. Results: The results indicate that certain sociodemographic variables become a risk factor for course dropout depending on their distribution in the standard courses. Conclusions: This result highlights the importance of instructional design in the ODE retention and dropout equation and helps explain, in part, why previous studies have not reached a consensus on which variables should be considered to explain dropout rates.

Sustainable Purchasing of Fresh Food by Restaurants and Cafes in France

This paper explores the purchasing practices adopted by restaurants and cafés operating in France to observe how the owner/operator(s) attitudes towards sustainable business practice impact on the choice of fresh food suppliers. A two-stage cluster analysis revealed the presence of two clusters: conventional buyers and green buyers that showed significant differences in the adoption of sustainable purchasing practices, the perceived benefits derived from the adoption of sustainable business practices, and barriers to the adoption of green purchasing. In making the decision to operate as a green restaurant, the personal beliefs of the owner/operator(s) were paramount, guided in part by the belief that in order to prepare and present the best-tasting food to patrons, executive chefs needed to procure the very best ingredients. In procuring the best quality fresh food ingredients, executive chefs preferred to deal with many small suppliers with whom they had developed a long-term relationship based on their reputation for delivering premium quality products in season.

Exploration of the investment patterns of potential retail banking customers using two-stage cluster analysis

Identifying investment patterns as part of customer segmentation is one of the most important tasks in retail banking. Clustering customers effectively is an important element of improving marketing policy and strategic planning. There are several methods for identifying similar groups of customers and describing their characteristics to offer them appropriate products. However, using machine learning methods is rare, and the application is limited for certain types of data. The aim of this study is to investigate the benefits of using a two-stage clustering method using neural-network-based Kohonen self-organizing maps followed by hierarchical clustering for identifying the investment patterns of potential retail banking customers. The unique benefit of this method is the ability to use both categorical and numerical variables at the same time. This research examined 1,542 responses received for an online investment survey, focusing on the questions that are related to the respondents’ investment preferences and their current financial assets. The research utilizes descriptive statistics and multiple correspondence analysis (MCA) to understand the variables and Kohonen self-organizing maps (SOMs), in combination with hierarchical clustering, to identify customer groups and describe the characteristics of these clusters. The analysis was able to identify clusters of potential customers with similar preferences and gained insights into their investment patterns related to their investment portfolio and investment behavior, including their savings profile, attitude to risk-taking, and preferences for investment advice. These findings were supported by additional insights through the application of multiple correspondence analysis (MCA) describing patterns of financial instruments and portfolios. The main contribution of the research is the combined application of the machine learning methods Kohonen SOM, hierarchical clustering, and MCA for investment pattern analysis in the retail banking business.

Features of participatory interaction among people with disabilities

Introduction. The urgency of the problem of participatory interaction is due to the fact that the development of modern society cannot be imagined outside the concept of creating a space of equal opportunities. In this regard, the issues of participatory interaction in the system “people with disabilities – society” are in the focus of attention of specialists in various fields of knowledge. The research purpose was to identify the types of participatory interaction in society that are typical for people with disabilities. Materials and methods. The study was conducted in the Saratov Region of the Russian Federation (N=100). The sample included young people with disabilities aged 15-23. The author’s questionnaire “Degree of Participation Manifestation” was used as a diagnostic tool. The results were processed using the standard package of IBM SPSS Statistics 21 (two-stage cluster analysis). Research results. Four types of participatory interaction of people with disabilities were identified: actively cooperating (25%), moderately included (17%), non-initiating (29%), inertly accepting (29%) types. Features of participation are determined by the vector of participatory interaction, the modality of the life perspective and the activity of people with disabilities (the importance of predictors is equal to 1; 0.83 and 0.75, respectively). Discussion and conclusion. Research results showed that young people with disabilities are involved in participatory interaction to varying degrees. Moreover, the overwhelming majority of respondents consider participatory interaction as an important condition for the effective fulfillment of individual capacity and a full-quality life in society. In this regard, the author’s typology can be used in specialists’ practical activities when constructing a space of equal opportunities.

COVID-19(코로나) 발생 전후로 나타난 청년의 여가활동유형과 우울감 관계

The purpose of this study was to identify the types of leisure activities before and after COVID-19 by using Two-stage Cluster analysis for Youth and the association of demographic characteristics and depression. A total of 358 data were collected. Frequency analysis, Independent sample t-test, Exploratory factor analysis, Reliability analysis, One-way ANOVA analysis, Two-stage cluster analysis and Chi-squre analysis were used. A Two-stage clustering analysis resulted in seven significant clusters. According to the type of leisure activities before and after COVID-19, 1.Culture viewing-Culture viewing, 2.Culture viewing-Exercise, 3.Hobby-Hobby, 4.Exercise-Exercise, 5.Watching sports-Watching sports, 6.Exercise- Entertainment activities, 7.Entertainment activities-Entertainment activities. The results were as follow: First, in Demographic variables, Women have higher depression than men, workers have lower depression than unemployed, highest for college graduates, and the highest income group have the lowest depression. Second, The group with the highest level of depression was the group 6. Exercise- Entertainment activities group, while the group with the lowest level of depression was 7. Entertainment activities-Entertainment activities group. Third, when looking at the clusters according to demographic variables, it was analyzed that the differences in groups by final educational background, income level, and gender were significant except for employment.

Illness perceptions and illness behaviours in back pain: A cross-sectional cluster analysis.

Individuals' perceptions of back pain may shape what they do in response to manage their pain, for example, self-care, medication and seeking healthcare. Illness perceptions encompass a variety of beliefs such as how long pain is expected to last and whether treatments are perceived to control pain. Whether these beliefs meaningfully cluster and whether these clusters are associated with how people manage their back pain are currently unknown. 1,343 individuals with back pain from a general population sample completed the brief Illness Perceptions Questionnaire and measures about their pain and illness behaviours. Using a two-stage cluster analysis, we identified four distinct clusters of individuals. Logistic regression was used to investigate relationships between cluster membership and illness behaviours. After adjustment for socio-demographic characteristics, pain severity, interference and duration, relative to a low threat illness perception cluster, a high threat cluster was more likely to have contacted a general practitioner (OR: 3.03, 95% CI: 1.75, 5.23) and a moderate threat-high treatment control cluster was more likely to have consulted a physical therapist (OR: 2.21, 95% CI: 1.26, 3.87). Both the moderate threat-high treatment control cluster and high threat cluster were also less likely to have reported self-care (OR: 0.64, 95% CI: 0.43, 0.95; OR: 0.53, 95% CI: 0.34, 0.83, respectively). The cluster analysis provided a meaningful classification of individuals based on their cognitive illness perceptions of their back pain, as these clusters were associated with different illness behaviours. Interventions which modify clusters of illness perceptions may be effective in influencing how individuals respond to back pain. Within a general population setting, we identified four clearly distinct groups of people based on the perceptions they held about their back pain. These groupings seemed to reflect meaningful characterisations as they differed based on the characteristics of their pain (e.g., severity and duration) and, after adjustment for these characteristics, were associated with different ways of managing pain. Interventions which focus on targeting the sets of illness perceptions that people hold may be effective in influencing how individuals manage back pain.

INFLUENCE OF THE ECONOMIC CRISIS ON THE IDENTIFICATION OF COUNTRY PROFILES WITHIN THE EUROPEAN TOMATO MARKET

The objectives of this work are to determine the profiles of the countries that make up the European tomato consuming market and to observe if the economic-financial crisis (2007/2008) has influenced them. Both Lafay’s economic indicators were applied and country profiles and subprofiles were identified through a multilevel two-stage cluster analysis. The empirical analysis covers the period from 2005 to 2016, separated into two periods, pre-crisis (2005–2010) and post-crisis (2011–2016). Most countries obtained import and export profiles that coincide in both indices, Except in Italy. Only one post-crisis profile change was detected, this being for Greece, from an importer to an exporter. As a result of the initial two-stage clustering analysis (both in the pre-crisis and post-crisis period), three clusters were obtained. At the first level of clustering, Italy is identified with a producer profile and Spain and the Netherlands with an exporter profile. At the second level of clustering of the initial larger group, two clusters were identified, Germany and the United Kingdom with an importing sub-profile, and France and Belgium with an exporting sub-profile. In the transition from the pre-crisis to the post-crisis period, Portugal changed from a producer sub-profile to an exporter sub-profile.

Executives’ Knowledge Management and Emotional Intelligence Role: Dynamizing Factor towards Open Innovation

The main aim of this empirical research was to classify the profiles of executives of Spanish companies. We classified the executives’ profiles based on two key factors of innovation: knowledge management and emotional intelligence. The sample comprised study 241 executives of Spanish companies, a principal component analysis, a two-stage cluster analysis, and an ANOVA analysis conducted by taking innovation as a dependent variable. The theory of resources and capacities was the theoretical framework. We conclude that the differentiation of executives’ profiles is essential to avoid the loss of innovative potential and a consequent loss of competitive advantage in the Spanish business sector. This research contributes to identify a taxonomy of executives’ profiles—agile, laggard, soloist and cooperator. These groups present some different levels of knowledge management and emotional intelligence and differences in their ability to innovate.

Cluster analysis of risky behaviors among the youth in Western Iran: Determining correlates and comparing clusters based on severity of disability and attitude toward mental health help-seeking.

Background and Aims:The objectives of the study were (i) cluster analysis of risky behaviors; (ii) determining correlates; and (iii) comparing clusters with regard to the attitude toward mental health help seeking.Methods:The current cross-sectional study is a part of the first phase of the Persian Youth Cohort. From October 2014 to January 2017, 2990 individuals from Ravansar City in western Iran completed structured interviews and national and international standard questionnaires. The obtained data were analyzed using two-stage cluster analysis, multinomial logistic regression analysis, and Chi-square test.Results:This model provided three distinct clusters: (i) low-risk group with mild distress, (ii) high-risk group with high distress, and (iii) violent group with medium distress. Some sociodemographic and lifetime psychiatric disorders were the correlates of unhealthy clusters (P < 0.05). Compared to the reference cluster, a higher number of members in unhealthy clusters were suffering from medium to severe disability. Nevertheless, the participants in these clusters were less inclined to mental health help seeking.Conclusions:More than half of the youth were suffering from suicidal and violent behaviors. Since high-risk participants are less inclined to mental health help seeking, the health policymakers can successfully utilize the results in planning general health programs.