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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.

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 purpose of this article is to investigate urban and rural differences for online activities and e‐payment behavior patterns.

This study applied the MLCA model to investigate Internet usage patterns from 11 online applications among 10,909 Taiwan residents in 25 different regions.

The results showed that online behavior patterns exhibited regional differences, as the regional segments affected the individual segments of different use patterns. For instance, the urban area comprised a higher proportion of members who were accustomed to internet applications and skilled in online shopping by using a credit card. The rural area made up a higher proportion of members who only occasionally used online services. Moreover, rural region residents used other payment methods (excluding credit cards) more often than urban region residents. As expected, users’ personal characteristics also dictated the online behavior pattern. For instance, people with higher‐level income spent relatively more money for online shopping and often used various internet applications than others.

The findings herein should help Internet service providers form an applicable guideline for developing service strategies of higher service satisfaction regarding products and users’ needs.

This study implemented a multilevel latent class model to investigate online behavior patterns that exhibited urban and rural differences, with the goal of providing service providers an understanding and mastery of their target users.

While school leadership literature has searched for practices with the largest effect on outcomes, we know little about how these behaviors vary by context. Further, recent shifts to include teachers in leadership have prompted a need for purposeful distinction between teacher and principal perceptions and roles. Person-centered statistics offer a means to study differences in how teachers and principals perceive leadership by context, how these perceptions interact, and the extent to which this interaction influences teacher decisions, such as whether or not to remain at their current school. The paper aims to discuss these issues.

This study applies a two-level latent class analysis (LCA) with a cross-level interaction to the 1999-2000 Schools and Staffing Survey (SASS), n=35,560 teachers across n=7,310 US public schools. SASS includes a comprehensive set of leadership measures, not found in other surveys, collected when US schools restructured to include teachers in leadership. Multilevel LCA helps to identify different types of teachers and principals in leadership, the distribution of teacher types across principal types and to test the extent that these types predict teacher retention decisions.

Teacher and principal types were best defined by the survey items that addressed their own role not the role of the other. The highest and lowest responding teacher types were evenly distributed across principal types. Teacher types who reported the lowest principal-directed leadership were more likely to leave their school regardless of principal type.

This study provides evidence for how leadership differs across perceptions and context and, in turn, influences teacher retention.

The environment surrounding U.S. higher education has changed substantially over the past 40 years. However, we have a limited understanding of what these changes mean for the higher education organizations (HEOs) that occupy this organizational field. In this paper, I use descriptive statistics and multilevel latent class analysis (MLCA) to analyze the financial behaviors of public four-year HEOs from 1986 to 2010 to evaluate how HEOs adapt financially to their changing environments. I advance the current conceptual and empirical understanding of public HEO behaviors by evaluating how public HEOs utilize combinations of revenue and spending streams to accomplish their mission and the extent to which the revenues and spending patterns of these institutions are related. Descriptive results confirm the shift away from state funding toward tuition revenues and the relative stability in spending patterns. MLCA results, which allow for the investigation of how combinations of revenue and spending streams work together, indicate that public HEOs are changing the combinations of revenues they rely on in different ways, revealing multiple specific pathways for how public HEOs adapt to their changing environments. The spending profiles, in contrast, remain stable with only a few HEOs changing their profile over time. I argue that the loose coupling between revenues and spending and discontinuity in their patterns of change over time suggests that public HEOs are able to establish a buffer between their environment and spending or activities that allows them to continue engaging in the same broad set of activities despite environmental changes.

Microfinance has become an important way to alleviate poverty. Though four decades have passed since its introduction, its impact is still not entirely clear. What makes it difficult to ascertain its efficacy is the existence of diverse types of microfinance organizations and client profiles. Microfinance institutions must primarily pay more attention to the client, and to the mechanism through which financial services are delivered. The purpose of this paper is to identify the profiles of microfinance customers and the features of their operations.

In this paper, multilevel latent class models were estimated to reveal clusters of operations and classes of clients.

The results show that there are six clusters of operations and four classes of clients in the market, each with distinct profiles and needs. Different strategies are recommended for each cluster and class.

Numerous studies have focused on the importance of getting to know the clients of microfinance programs, but none as yet have used market segmentation as a way to do so. The goal is to generate better strategies to help clients improve their business results. Applying market segmentation to the microfinance market may point to different products for different groups of clients, taking the real needs of each of them into account.

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.

The aim of this paper is to show that online learning behaviors are dictated by both personal characteristics and regional differences.

Data were collected from 16,133 users in 25 regions of Taiwan. The paper examined usage behaviors by looking at 11 items of categorical variables about online learning. This study implemented a multi‐level latent class model to investigate online learning behavior patterns that exhibit regional differences.

The results showed that online learning patterns do exhibit regional differences, as the regional segments are dictated by the individual segments of different use patterns. For instance, the urban area segment comprised a higher proportion of members who are good at using the internet. The rural area segment made up a higher proportion of members who occasionally use the internet. Interestingly, rural users went online more often than urban users when in search of e‐learning or entertainment. On the other hand, the individual segments are dictated by users' personal characteristics. For instance, younger people are good at employing online learning and entertainment services. Moreover, those who use many types of online applications pay less respect to intellectual property rights than those who only use a few types of applications.

By using a massive amount of survey data to show regional differences in online learning behavior patterns, the findings herein will help internet service providers form an applicable guideline for developing service strategies of higher service satisfaction between products and users' needs.

Leadership for learning emerged as an integrated leadership framework; however, attempts to establish an empirical measurement model have been limited. Critically, not much is known about how much teachers' beliefs (e.g. self-efficacy) can mediate leadership for learning impact on teacher behaviors. This study establishes a leadership for learning measurement model and examines whether teacher self-efficacy mediates the effect of leadership for learning tasks on teacher collaboration, instructional quality, intention to leave current schools and their confidence in equitable teaching practice.

Drawing on the most recent 2018 Teaching and Learning International Survey (TALIS), the study employed a structural equation modeling mediation approach.

Results suggested that teacher self-efficacy statistically significantly mediated 16 out of 20 of the relationships between leadership for learning task domains and teacher outcomes. Especially, in explaining the variance in instructional quality and teacher confidence in implementing equitable teaching practices, considerable proportions of the predictive power of leadership for learning tasks were accounted for (i.e. mediated) by teacher self-efficacy.

School-wide efforts to craft the school vision for learning must be coupled with enhancing teacher self-efficacy. Critically, leadership efforts may fall short of implementing equitable teaching practice and quality instruction without addressing teacher confidence in their ability in instruction, classroom management and student engagement.

This study is the first of its kind to evidence teacher self-efficacy mediates leadership for learning practice impact on teacher behaviors.

The aim of this research is to examine the impact of video-based learning on the cooking skills development of students. More specifically, exploring the first stages in the learning process through embedding declarative knowledge utilising both video content and learner profiles, with the purpose to make teaching practice more effectively and efficiently targeted.

A quantitative social experimental approach was employed. The sample consisted of 414 students from three post primary schools in Northern Ireland. Students were randomly allocated into both control and experimental video content groups. All participants were made aware of ethical procedures and the nature of the study.

Through the application of latent class analysis (LCA), three distinct types of students were classified. Class one (n = 250) students were termed independent learners, class two (n = 88) students were motivated and benefited from video-based learning and class three (n = 52) students demonstrated an inability to apply information because video did not assist in embedding declarative knowledge.

Implications from this research inform content generation for video-based cooking skills.

Given the unprecedented move towards online teaching in 2020 due to coronavirus disease 2019 (COVID-19) restrictions, there is increasing interest in targeting resources effectively to meet the requirements of all learning groups. This paper fulfils an identified need to study how video impacts on skills development and learning within specific learning typologies.

This research will be of interest to educationalists in promoting a cost-effective resource in line with constructivist values to streamline and meet the needs of individual learners.