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On many occasions, organizational science research has been referred to as fragmented and disjointed, resulting in a literature that is, in the opinion of many, difficult to navigate and comprehend. One potential explanation is that scholars have failed to comprehend that organizations are complex and intricate systems. In order to move us past this morass, we recommend that researchers extend beyond traditional rational, mechanistic, and variable-centered approaches to research and integrate a more advantageous pattern-oriented approach within their research program. Pattern-oriented methods approximate real-life phenomena by adopting a holistic, integrative approach to research wherein individual- and organizational-systems are viewed as non-decomposable organized wholes. We argue that the pattern-oriented approach has the potential to overcome a number of breakdowns faced by alternate approaches, while offering a novel and more representative lens from which to view organizational- and HRM-related issues. The proposed incorporation of the pattern-oriented approach is framed within a review and evaluation of current approaches to organizational research and is supplemented with a discussion of methodological and theoretical implications as well as potential applications of the pattern-oriented approach.

This paper compares two alternative methods for measuring multidimensional poverty. This question has become extremely important in recent years, both in the scientific literature and in social policy. We propose to use latent class analysis to evaluate poverty in Spain. We make use of the “fuzzy set” approach, and compare the results achieved from these two methodologies.

Research on the intergenerational transmission of violence has been limited by reliance on variable-oriented methodology that does not capture heterogeneity that exists within experiences of violent interpersonal conduct. The current study therefore examines the utility of a person-oriented statistical method in understanding patterns of maltreatment and intimate partner violence.

Guided by person-oriented theory, the current study utilizes latent class analysis, a person-oriented method used with cross-sectional data, to examine the heterogeneity within this transmission process in a sample of emerging adults (N = 150). This study also examined whether the classes identified differed on reported emotional reactivity and childhood family environment.

Three classes emerged from the latent class analysis, labeled full transmission, psychological transmission, and no transmission. Those comprising the full transmission subgroup reported the lowest levels of childhood family cohesion, accord, and closeness. The full transmission subgroup also reported significantly more emotional reactivity than the psychological transmission and no transmission subgroups.

To understand fully the etiology of intimate partner violence for maltreated offspring, a multidimensional view of violence is needed. The current study represents a step in this direction by demonstrating the utility of a person-oriented approach in understanding the IGT of violence.

We discuss adoption as a diverse family structure in America. Adoption has existed in some form throughout the history with the portrayal varying by historical epoch. Adoption has been both disparaged and idealized to perpetuate the interest of elite players. This chapter discusses adoption in terms of the changing demographic which 21st century families face. In this manuscript, we first discuss the history of adoption in the United States including its impact as social control of premarital sex. Then the three players in the adoption triad are discussed and analyzed. Finally, we highlight how demographics of race, class, gender, and sexuality impact the adoption experience by 21st century families. Specifically, we explore the recent National Survey of Adoptive Parents from the United States Center for Disease Control and look at the modern adoption experience

The present study uses data from the National Longitudinal Study of Adolescent Health (Ad Health) to evaluate the effects of exposure to violent victimization in childhood on adolescent delinquency and subsequent adult criminality.

Using Longitudinal Latent Class Analysis (LLCA), the present study investigates whether there are distinct and diverse longitudinal delinquency trajectories among those exposed to violence in childhood.

Findings from the current study indicate that there are three distinct trajectories of delinquency and offending from age 14 to 27 for both males and females exposed to violence in childhood. Further, it appears that violent victimization in childhood bridges the gender gap in delinquency between males and females. Thus, childhood violent victimization, and the fact that females are victimized by parents/caregivers and romantic partners at higher rates than males, might be partially responsible in explaining the narrowing of the gender gap between male and female offending in the recent decades. At the same time, childhood violent victimization also seems to impact males and females in somewhat different ways. Practically, all female victims stop offending by their late 20s, whereas a fairly large proportion of males exposed to violent victimization in childhood steadily continue offending.

Although this study was able to identify the diverse impacts of violence exposure on engagement in subsequent delinquency, it did not examine the unique contributions of each type of violence on adolescent outcomes or the chronicity of exposure to each of these types of violent victimization. We were also not able to measure all types of violence experiences in childhood, such as exposure to parents’ or caregivers’ intimate partner violence.

While early prevention would be the most desirable option for both genders for the most optimal outcome, the retrospective intervention and treatment programs should be gender-specific. For males, they should heavily focus on providing alternative ways to cope with anger, impulse control and frustration, as well as teach empathy, cognitive problem solving skills, verbal communication skills, and tangible life and job skills. For females, most successful intervention and treatment programs may focus on helping the girls through a transition from adolescence to adulthood while providing mental health, medical, and family support services.

The paper uses a unique methodological approach to identify distinct and diverse longitudinal delinquency trajectories. The findings demonstrate how more resilient individuals (in terms of externalizing behaviors) can bring down the mean scores of delinquency even though many other individuals can be severely affected by violence exposure in childhood.

Extant research on job insecurity has traditionally investigated this construct as a hindrance stressor, based on theoretical developments and meta-analytical results that have shown consistent negative relationships between job insecurity and a host of organizational outcomes. In this chapter, the authors take a person-centered perspective based on the transactional theory of stress and argue that employees can and do appraise job insecurity in different ways which is manifested by qualitatively distinct latent profiles. The authors also argue that certain positive psychological variables (i.e., hope, optimism, self-efficacy, and grit) might influence one’s odds to belong to specific appraisal latent classes. Using a cross-lagged dataset of 322 US-based employees, the authors found evidence of five qualitatively different latent profiles (i.e., employees who viewed job insecurity as: (1) irrelevant, (2) simultaneously moderately challenging and hindering, (3) primarily hindering, (4) both highly challenging and highly hindering, or (5) primarily challenging). Further, the results showed that higher grit was associated with higher odds of belonging to any of the appraisal profiles compared to the high challenge/high hindrance group whereas higher self-efficacy was associated with higher odds of belonging to the irrelevant group compared to any of the appraisal profiles. Hope and optimism, however, did not influence latent class membership. The authors discuss the implications for theory and practice considering seemingly paradoxical findings demonstrating sometimes positive and sometimes negative outcomes of job insecurity, as well as traditional assumptions that employees primarily view job insecurity as either a hindrance or a challenge.

Multilevel approaches are generally well suited to group communication because what people say and do in groups is a function of intra- and trans-individual mechanisms. This chapter first provides a brief overview of group research as a multilevel problem and then describes more modern approaches to modeling nested data using latent variable models, including multilevel structural equation modeling and latent class analysis. The chapter concludes by addressing conceptual opportunities provided by multilevel latent modeling approaches to group communication.

Alongside structural equation modeling (SEM), the complementary technique of partial least squares (PLS) path modeling helps researchers understand relations among sets of observed variables. Like SEM, PLS began with an assumption of homogeneity – one population and one model – but has developed techniques for modeling data from heterogeneous populations, consistent with a marketing emphasis on segmentation. Heterogeneity can be expressed through interactions and nonlinear terms. Additionally, researchers can use multiple group analysis and latent class methods. This chapter reviews these techniques for modeling heterogeneous data in PLS, and illustrates key developments in finite mixture modeling in PLS using the SmartPLS 2.0 package.

Recently, the institutional performance model has been used to explain the increased distrust of health care system by arguing that distrust is a function of individuals’ perceptions on the quality of life in neighborhood and social institutions. We examined (1) whether individuals assess two dimensions of distrust consistently, (2) if the multilevel institutional performance model explains the variation of distrust across neighborhoods, and (3) how distrust patterns affect preventive health care behaviors.

Using data from 9,497 respondents in 914 census tracts (neighborhoods) in Philadelphia, we examined the patterns of how individuals evaluate the competence and values distrust using the Multilevel Latent Class Analysis (MLCA), and then investigated how neighborhood environment factors are associated with distrust patterns. Finally, we used regression to examine the relationships between distrust patterns and preventive health care.

The MLCA identified four distrust patterns: Believers, Doubters, Competence Skeptics, and Values Skeptics. We found that 55 percent of the individuals evaluated competence and values distrust coherently, with Believers reporting low levels and Doubters having high levels of distrust. Competence and Values Skeptics assessed distrust inconsistently. Believers were the least likely to reside in socioeconomically disadvantaged and racially segregated neighborhoods among these patterns. In contrast to Doubters, Believers were more likely to use preventive health care, even after controlling for other socioeconomic factors including insurance coverage.

Our findings suggest that distrust patterns are a function of neighborhood conditions and distrust patterns are associated with preventive health care. This study provides important policy implications for health care and future interventions.

The effects of the COVID-19 pandemic on cities have transformed the lives of urban societies across the globe. One of such effects has been the redefinition of access and urban mobility patterns, exposing divides and inequalities along the lines of class, gender and social positions. In Latin America, long-term lockdowns and widespread containment-oriented restrictions have deepened already acute conditions of poverty and deprivation. Low-income and socially vulnerable households and individuals in countries such as Colombia find themselves unable, or in a disadvantaged position, to work from home, access goods and services securely and avoid transport modes that increase exposure to contagion. This chapter examines inequalities in urban mobility and access to essential opportunities in urban settings in Colombia, through data collected from 3,900 respondents to a web survey organised during the national lockdown in the country in April 2020. The chapter presents a Latent Class Analysis model exploring how intersecting differences in class, gender, ethnicity, age and other relevant socioeconomic characteristics, influence the degree of adaptability and capacity to adapt to the challenging conditions posed by COVID-19 for physical travel and carrying out everyday activities. Building on three distinct classes of mobility and access-related conditions, the chapter reflects on structural inequalities associated with Colombian cities’ urban form, functional and productive structures and its wide social gaps. The chapter builds on empirical findings to reflect on urban policy and discuss avenues for addressing social and spatial inequalities worsened by the pandemic.