Covert contraceptive use is a strategy to avoid unintended pregnancy. However, evidence regarding the multilevel factors linking past experiences of unintended pregnancy with covert contraceptive use is limited. The objective of this study was to identify the compositional and contextual factors associated with covert contraceptive use among women with a prior unintended pregnancy. Framed by the socio-ecological model, a cross-sectional study was conducted using data from Round 5 of the Performance Monitoring and Accountability 2020 project in Nigeria. Non-pregnant women aged 15–49 years who reported a previous mistimed or unwanted pregnancy were included (N = 1631). Multilevel logistic regression models with random intercepts were specified to investigate the relationship between covert contraceptive use and compositional and contextual factors. Approximately 4.54% (95% CI = 3.28–6.25) of women reported covert contraceptive use. At the individual level, having less than secondary education (aOR = 5.88, 95% CI = 1.20–28.72) and being single (aOR = 11.29, 95% CI = 2.93–43.56) were associated with higher odds of covert contraceptive use. There was no significant association between covert contraceptive use and the type of unintended pregnancy (mistimed: aOR = 3.13, 95% CI = 0.88–11.13). At the community level, living in a community with average poverty levels (aOR = 6.18, 95% CI = 1.18–32.55) and high exposure to family planning mass media (aOR = 6.84, 95% CI = 1.62–29.11) were associated with higher odds of covert contraceptive use. Measures of variation showed significant variation in covert contraceptive use across communities. Further research is warranted to better understand the underlying mechanisms in these observed associations and variations in covert contraceptive use among women following the experience of an unintended pregnancy. Additionally, there is a need to design family planning strategies that integrate community-level structures.

We introduce multilevel multivariate meta-analysis methodology designed to account for the complexity of contemporary psychological research data. Our methodology directly models the observations from a set of studies in a manner that accounts for the variation and covariation induced by the facts that observations differ in their dependent measures and moderators and are nested within, for example, papers, studies, groups of subjects, and study conditions. Our methodology is motivated by data from papers and studies of the choice overload hypothesis. It more fully accounts for the complexity of choice overload data relative to two prior meta-analyses and thus provides richer insight. In particular, it shows that choice overload varies substantially as a function of the six dependent measures and four moderators examined in the domain and that there are potentially interesting and theoretically important interactions among them. It also shows that the various dependent measures have differing levels of variation and that levels up to and including the highest (i.e., the fifth, or paper, level) are necessary to capture the variation and covariation induced by the nesting structure. Our results have substantial implications for future studies of choice overload.

Common applications of latent variable analysis fail to recognize that data may be obtained from several populations with different sets of parameter values. This article describes the problem and gives an overview of methodology that can address heterogeneity. Artificial examples of mixtures are given, where if the mixture is not recognized, strongly distorted results occur. MIMIC structural modeling is shown to be a useful method for detecting and describing heterogeneity that cannot be handled in regular multiple-group analysis. Other useful methods instead take a random effects approach, describing heterogeneity in terms of random parameter variation across groups. These random effects models connect with emerging methodology for multilevel structural equation modeling of hierarchical data. Examples are drawn from educational achievement testing, psychopathology, and sociology of education. Estimation is carried out by the LISCOMP program.

Weekly cycles in emotion were examined by combining item response modeling and spectral analysis approaches in an analysis of 179 college students' reports of daily emotions experienced over 7 weeks. We addressed the measurement of emotion using an item response model. Spectral analysis and multilevel sinusoidal models were used to identify interindividual differences in intraindividual cyclic change. Simulations and incomplete data designs were used to examine how well this combination of analysis techniques might work when applied to other practical data problems. Empirically, we found systematic individual differences in the extent to which individuals' emotions follow a weekly cycle, and in how such cycles are exhibited. Weekly cycles accounted for very little variance in day to day emotions at the individual level. Analytically, we illustrate how measurement, change, and interindividual difference models from different traditions may be combined in a practical manner to describe some of the complexities of human behavior.

Hierarchical bullying in public healthcare organizations is an entrenched negative behaviour that results in a range of adverse outcomes for staff, including diminished wellbeing. This study integrates social exchange and conservation of resources theories as a lens for formulating hypotheses and employs multilevel statistical modelling to examine whether team-level compassion moderates the impact of hierarchical bullying on wellbeing. Using multilevel statistical modelling, the study analysed cross-sectional data from 632 healthcare workers nested within 48 teams in a single public health district in Australia. The findings indicate that work teams with higher levels of team compassion can mitigate the negative effects of hierarchical bullying on employee wellbeing. The results imply that investing in developing compassion within teams is an effective strategy for mitigating some harmful effects of hierarchical bullying on employee outcomes.

The effectiveness of entrepreneurial leadership (EL) at different levels has been widely recognized by scholars who have carried out substantial exploration; however, the empirical studies on the effectiveness of EL are scattered and their results are mixed. This study aims to organize these findings, advance knowledge about the multilevel effectiveness of EL and clarify the heterogeneity in the relationship between EL and effectiveness outcomes. Based on a systematic review of the extant literature and the construction of an integrated framework, this study examines the influence of EL on effectiveness outcomes at multiple levels and the moderators of this relationship through meta-analysis of 35 empirical studies including 35 independent samples. The results show that EL can improve effectiveness outcomes at different levels of organization, team and individual; cultural context obviously moderates this relationship, whereas the moderating effects of enterprise type and EL measure are all not significant. This study helps to determine the specific association of EL with effectiveness outcomes at different levels, and identify important factors influencing this relationship, which broadens the understanding of leadership effectiveness and provides certain value for enterprises to give full play to the role of EL at all levels.

Caesarean section delivery rates in India have doubled from 9% in 2005–06 to 17% in 2015–16, increasing the clinical and economic burden on the health care system. This study applied multilevel models to assess the role of household- and community-level factors in Caesarean section (CS) deliveries among low-risk women in India using data from Round 4 of the National Family Health Survey (NFHS-4) conducted in 2015–16. The sample size was 59,318 low-risk women who had their last birth in an institution during the 5 years preceding the survey. These women were nested in 57,279 households, which were nested in 22,183 communities, which were further nested in 640 districts in India. Around 21% of the low-risk women and 24% of all women who had delivered in an institution had undergone CS. The CS rates among low-risk women were extremely high in private institutions (40%) and in southern India (43%). The explanatory variables age, education of women, household wealth and number of antenatal visits were significantly positively associated, while women’s parity was negatively associated, with CS delivery among low-risk women. The multilevel analysis suggested that the likelihood of a low-risk woman opting for CS was influenced by a similar decision of another woman from the same household (37%) and/or community (18%). Furthermore, women with low-risk pregnancies from higher educated communities were less likely (OR 0.92) to undergo CS. There is therefore a need for a community-level awareness programme on the risks and benefits of low-risk CS and vaginal delivery, particularly in the southern region of India.

Recent research on morality policy has focused on policy change, morality framing and the presence of favourable cultural opportunity structures (COSs). The resulting literature describing various aspects of morality policy has failed to discuss the impact of multilevel dynamic in this field. This contribution examines gambling policy in Italy, applying a multilevel approach to detect the presence of favourable COSs, and whether policymakers frame policies morally. Italy offers a particularly fertile field for the study of morality policy, featuring a liberal national approach versus local restrictive policy. By applying a methodology based on semistructured interviews and secondary sources, we examine the national and local political spheres, demonstrating that morality framing, when detected, is more likely to be found at the local level where the influence of experts and interest groups on legislators may result in the transformation of a health policy based on paternalistic considerations.

Building on prior work regarding the potential for peer contagion or deviance training in group delivered interventions (Dishion & Dodge, 2005, 2006; Dodge, Dishion, & Lansford, 2006), we leveraged data from a randomized trial, testing the integration of two preventive interventions (Promoting Alternative THinking Strategies and PAX Good Behavior Game), to explore the extent to which classroom contextual factors served as either a barrier to or a motivator for teachers to implement the evidence-based PAX Good Behavior Game with high frequency or dosage. We included students’ baseline levels of behavior, measured with regard to both positive (i.e., engagement and social emotional skills) and negative (i.e., hyperactive and aggressive-disruptive) behaviors. Data were collected from 204 teachers in 18 urban elementary schools. A series of multilevel structural equation models were fit to the data. The analyses indicated that classrooms with higher classroom levels of aggressive behavior, on average, at baseline had teachers with lower implementation dosage (i.e., played fewer games) across the school year. In addition, teachers who reported higher baseline levels of emotional exhaustion, regardless of student behavior, also reported lower implementation dosage. Taken together, the results indicated that negative, but not positive, contextual factors at baseline were related to lower implementation dosage; this, in turn, suggests that negative contextual factors may serve as a barrier, rather than a motivator, of teachers’ implementation dosage of classroom-based preventive interventions.

In this article, three important issues in organizational multilevel research are discussed and clarified, namely: (a) The interpretation of “cross-level direct effects” in theoretical and research multilevel models, (b) the specification of the emergence processes involved in higher-level constructs, and (c) the sample size recommendations for using multilevel statistical methods. By doing so, this article hopes to contribute to the improvement of organizational multilevel research.

Family business owners and researchers tend to overwhelmingly focus on the top-level structure of firms but ignore the middle-level practice – involving family members in the middle-management team. Compared to top managers at the strategic apex, middle-level managers are mainly responsible for internal operations and control, and the composition of the middle-management team has an immediate and direct impact on the overall workforce efficiency of family firms. Integrating agency theory and organizational justice perspective, we proposed that family involvement in middle management would have a negative impact on the labor productivity of family firms. We further corroborated this effect by identifying three boundary conditions at the individual (i.e., familial CEO), organizational (i.e., firm size), and regional (i.e., labor mobility) levels. Using a sample of 1,284 privately owned family firms in China, we found that family involvement in middle management, measured as the percentage of familial middle-level managers, was negatively associated with labor productivity. Furthermore, this negative relationship existed only when the CEO is a family member rather than a professional manager, when the size of the firm is large rather than small, or when the firm is located in regions with low rather than high labor mobility. These findings contribute to family business literature and provide practical implications for human resource management in family firms.

Psychological capital (PsyCap) is a higher-order construct reflecting the psychological resources of hope, efficacy, resilience and optimism. This study adopted a multilevel approach to investigate relationships between team-level PsyCap and team- and individual-level outcomes. We also compared two compositional models of aggregation to represent team-level PsyCap. Findings revealed significant associations between team-level PsyCap and team- (performance and satisfaction) and individual-level (job satisfaction, turnover intent) outcomes, particularly when a referent-shift model of aggregation was employed. We also investigated PsyCap strength to explore the degree to which team member consensus regarding PsyCap perceptions may moderate these relationships. We found that team PsyCap strength had a significant influence in the prediction of most outcomes. Our findings emphasize the importance of fostering team-level positivity, as the benefits of team-level PsyCap can operate at both the individual and team level. Theoretical and practical implications of the findings are discussed, along with avenues for future research.