Hierarchical linear models (2nd ed.)
... We analyzed the data we collected with SAS version 9.2 and its PROC MIXED procedure for hierarchical linear modeling (HLM) (Raudenbush & Bryk, 2002;Singer, 1998). Of the 307 questionnaires that we sent to potential respondents, we received 248 (81%) completed questionnaires in return. ...
... Because individual respondents are nested in teams, we analyzed the data's intrinsically hierarchical structure with HLM, which considers the dependence of clustered data. Moreover, HLM allows one to test cross-level interactions (Raudenbush & Bryk, 2002). To analyze the data, we first ran an empty model without team-level or individual-level predictors of satisfaction; it included a random effect to capture team membership. ...
... To analyze the data, we first ran an empty model without team-level or individual-level predictors of satisfaction; it included a random effect to capture team membership. The intra-class correlation for team member satisfaction was 0.31, which suggests that satisfaction assessments in teams were quite clustered and that an ordinary least squares approach would likely yield misleading results (Raudenbush & Bryk, 2002). Since we identified non-normally distributed errors at the group level, we used a robust approach with a "sandwich" estimator to estimate the variance-covariance matrix of the fixed parameters (Maas & Hox, 2004). ...
... "In the multilevel organizational literature, reliability is commonly assessed by two forms of intraclass correlation coefficient (ICC): the ICC (1) and T ICC (2) " (Bliese, 2000, p. 354). ICC (1) represents the proportion of the total variance that can be explained by group level membership (Bryk & Raudenbush, 1992) and the minimum value of ICC (1) for conducting multilevel analysis is 0.05 (Bryk & Raudenbush, 1992). While ICC (2) provides the reliability of the group means. ...
... "In the multilevel organizational literature, reliability is commonly assessed by two forms of intraclass correlation coefficient (ICC): the ICC (1) and T ICC (2) " (Bliese, 2000, p. 354). ICC (1) represents the proportion of the total variance that can be explained by group level membership (Bryk & Raudenbush, 1992) and the minimum value of ICC (1) for conducting multilevel analysis is 0.05 (Bryk & Raudenbush, 1992). While ICC (2) provides the reliability of the group means. ...
... The hypotheses were tested by hierarchical linear modeling (HLM). HLM is a multilevel statistical method that can decompose the variance of the constructs into within-group and between-group components and estimate the relationships between constructs within each level and across levels simultaneously (Bryk & Raudenbush, 1992). ...
Little research has empirically examined how leadership factors influence food safety promotive and prohibitive voice differently. Also, little research has examined the moderating effects of leadership on the relationship between individual antecedents and promotive and prohibitive voice as contextual factors. The current study developed and tested a multilevel model regarding how leaders' food safety orientation and authentic leadership influence employees' food safety-related prohibitive and promotive voices. The results showed that leaders' food safety orientation is an important antecedent of employees' food safety prohibitive and promotive voices and both relationships are partially mediated by employees' food safety consciousness. Additionally, the results suggested that authentic leadership works as a contextual factor that moderates the relationship between em-ployees' food safety consciousness and food safety prohibitive voice, but the moderating effect is not significant in the relationship between employees' food safety consciousness and promotive voice. The results of this study provide meaningful insights for researchers by empirically examining how leadership factors influence food safety prohibitive and promotive voice differently as antecedent and moderator.
... HLM allows for the estimation of OLS regression, taking into account the nested structure of the data, a unit of measurement. Thus, HLM can use data clusters to avoid grouping errors [57], which is helpful for drawing out accurate estimate slopes for each level. ...
... In Model 2, all the regression slopes of individual predictors were fixed at the country-level (level-2), since the outcomes among the given OECD countries showed only relatively small variations. This was also done to methodologically secure statistical stability [57]. The final model (Model 2) can be briefly represented as follows: ...
This study is concerned with the central issues of community service engagement (CSE) in 21st century democratic societies around the world. To examine the factors influencing postsecondary education attainment’s relationship to CSE, this study utilized data from the Organization for Economic Co-operation and Development (OECD) countries using ordinary least square (OLS) and two-level hierarchical linear modeling (HLM) methods, including various factors for each country’s individual and country levels. The results show that attainment in postsecondary education at the individual level and investment and enrollments in tertiary education both have an influence on increasing CSE in 18 OECD countries. The present study is expected to contribute to an understanding of the relationship between postsecondary education and CSE across the world.
... To test the impact of distinct neighborhood conditions on surgical patients' experience ratings, we estimated multilevel linear regression models 16,17 with Stata 16 software. 18 We performed a series of conditional models that first include the covariates of individual patient sociodemographic and health characteristics at level-1 (age, gender, race/ethnicity, primary language spoken at home, educational attainment, insurance type, physical and mental health status, length of stay, and average pain levels) followed by models that add the neighborhood conditions at level-2 (population density, community-level education, unemployment rate, percent of female-headed households, percent receiving public assistance, percent in poverty, percent of homes in the tract that are rented, and racial and ethnic composition). ...
... All models use maximum likelihood estimation with adaptive quadrature. 16 This approach controls for the lack of independence of data within higher level groups and adjusts for problems that otherwise downwardly bias estimated standard errors including individual clustering within neighborhoods, different sample sizes for level-1 and level-2 units, heteroscedastic error terms, and variable numbers of cases within level-2 units. 17 We first estimated a model with only individual-level predictors included to test the influence of individual social determinants on the scores of patient experience. ...
Objective:. Through geocoding the physical residential address included in the electronic medical record to the census tract level, we present a novel model for concomitant examination of individual patient-related and residential context-related factors that are associated with patient-reported experience scores.
Summary Background Data:. When assessing patient experience in the surgical setting, researchers need to examine the potential influence of neighborhood-level characteristics on patient experience-of-care ratings.
Methods:. We geocoded the residential address included in the electronic medical record (EMR) from a tertiary care facility to the census tract level of Orange County, CA. We then linked each individual record to the matching census tract and use hierarchical regression analyses to test the impact of distinct neighborhood conditions on patient experience. This approach allows us to estimate how each neighborhood characteristic uniquely influences Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) scores.
Results:. Individuals residing in communities characterized by high levels of socioeconomic disadvantage have the highest experience ratings. Accounting for individual patient’s characteristics such as age, gender, race/ethnicity, primary language spoken at home, length of stay, and average pain levels during their hospital stay, neighborhood-level characteristics such as proportions of people receiving public assistance influence the ratings of hospital experience (0.01, P
... For example, the r wg(j) index is a measure of inter-rater agreement and the closest to +1 the better [42]. Type 1 Intra-class correlation describes the amount of variance explained by the team-level while the type 2 index is an indicator of the reliability of the mean at the team level [40,43]. One can see that team-level patient-centered care perceptions has 13% of variance available to be explained at the team level. ...
... r wg(j) : Inter-rater agreement index with a slightly skewed null distribution (LeBreton & Senter, 2008). ICC1: Type 1 intra-class correlation; proportion of variance accounted for by teams (Raudenbush & Bryk, 2002). ICC2: Type 2 intra-class correlations; reliability of the team means (Bliese, 2000). ...
Background: The successful combination of interprofessional collaboration in multidisciplinary teams with patient-centered care is necessary when it comes to delivering complex mental health services. Yet collaboration is challenging and patient-centered care is intricate to manage. This study examines correlates of patient-centered care such as team adaptivity and proactivity, collaboration, belief in interprofessional collaboration and informational role self-efficacy in multidisciplinary mental health teams.
Method: A cross-sectional multilevel survey design was used, based on self-administered bilingual validated questionnaires. Participants (N=314) were mental health professionals and managers working in public primary care or specialized mental health services, in inpatient or outpatient settings.
Results: This study showed that belief in interprofessional collaboration’s relationship with patient-centered perceptions is increased in teams with high collaboration. Collaboration is also found as a mediator, representing a process by which team adaptive and proactive behaviors are transformed into positive patient-centered perceptions.
Conclusions: Our results were in line with recent studies on team processes establishing that collaboration is a key component in multilevel examinations of predictors of patient-centered care. In terms of practice, our study showed that multidisciplinary teams should know that working hard on collaboration is an answer to the complexity of patient-centered care. Collaboration is related to the teams’ ability to respond to its challenges. It is also related to individuals’ beliefs central to the delivery of interprofessional care.
... The hierarchical regression model, which already has been applied to family planning decisions (Hirschman & Guest 1990;Entwisle et al. 1984) but has not been explored in migration decision studies, has the potential to solve all the problems mentioned above. The characteristics of hierarchies, current studies that focus only on one level of the variables can only explain variations at that level (Bryk & Raudenbush 1992). This limitation has generated concerns of ecological or atomistic fallacies (Green & Flowerdew 1996;Wrigley et al. 1996;Robinson 1950). ...
... Moreover, the hierarchical regression approach has its own weaknesses (Bryk & Raudenbush 1992). Firstly, in a hierarchical regression model, each level has its specification assumptions as does the standard multivariate regression model. ...
This paper provides a nascent look at the application as well as the advantages of the hierarchical regression model in studying migration decision making. The aim of this study is to examine economic migrants' decision to migrate, focusing specifically on potential migrants who can choose if and where to migrate, and which conditions facilitate their migration. We explored migration decisions using in-depth, semi-structured interviews with male and female migrants from two Bangladeshi communities, one with high and one with low Italy migration density. Half were returning migrants and half were non-migrants with relatives in Italy. Using households survey data from Bangladeshi migrants to Italy for a two-level hierarchy individual/household level and public use micro-data , it takes a fresh look at how a hierarchical logit model can improve migration studies by including demographic, socioeconomic , and bio-geo-physical factors. Reasons for return were related to migrants' initial social and economic motivations for migration. A greater understanding of factors influencing migration decisions may provide insight into the vulnerability of immigrant youth along the journey, their adaptation process in Italy, and their reintegration in Bangladesh. Finally, the findings indicate that the hierarchical regression approach provides significant advantages in studying migration decision-making.
... For example, the r wg(j) index is a measure of inter-rater agreement and the closest to +1 the better [42]. Type 1 Intra-class correlation describes the amount of variance explained by the team-level while the type 2 index is an indicator of the reliability of the mean at the team level [40,43]. One can see that team-level patient-centered care perceptions has 13% of variance available to be explained at the team level. ...
... r wg(j) : Inter-rater agreement index with a slightly skewed null distribution (LeBreton & Senter, 2008). ICC1: Type 1 intra-class correlation; proportion of variance accounted for by teams (Raudenbush & Bryk, 2002). ICC2: Type 2 intra-class correlations; reliability of the team means (Bliese, 2000). ...
Background: The successful combination of interprofessional collaboration in multidisciplinary teams with patient-centered care is necessary when it comes to delivering complex mental health services. Yet collaboration is challenging and patient-centered care is intricate to manage. This study examines correlates of patient-centered care such as team adaptivity and proactivity, collaboration, belief in interprofessional collaboration and informational role self-efficacy in multidisciplinary mental health teams.
Method: A cross-sectional multilevel survey design was used, based on self-administered bilingual validated questionnaires. Participants (N=314) were mental health professionals and managers working in public primary care or specialized mental health services, in inpatient or outpatient settings.
Results: This study showed that belief in interprofessional collaboration’s relationship with patient-centered perceptions is increased in teams with high collaboration. Collaboration is also found as a mediator, representing a process by which team adaptive and proactive behaviors are transformed into positive patient-centered perceptions.
Conclusions: Our results were in line with recent studies on team processes establishing that collaboration is a key component in multilevel examinations of predictors of patient-centered care. In terms of practice, our study showed that multidisciplinary teams should know that working hard on collaboration is an answer to the complexity of patient-centered care. Collaboration is related to the teams’ ability to respond to its challenges. It is also related to individuals’ beliefs central to the delivery of interprofessional care.
... For the statistical analysis of the data, power means per subject, electrode pool and frequency band were subjected to a multilevel model (Bliese 2009, Bryk & Raudenbush 1992, as they do not require normal or parametric data, and allow controlling intraclass correlation. Intraclass correlation coefficient (ICC) was used as a measure of whether measurements of ERP amplitude were independent within subjects in order to determine the necessity of multilevel (i.e. ...
... It is The copyright holder for this preprint this version posted October 4, 2020. For the statistical analysis of the ERP data, the mean voltage amplitudes relative to the start of the critical noun were subjected to a multilevel model (Bliese 2009, Bryk & Raudenbush 1992. All values were standardized before entering into the models. ...
In this pilot study, we evaluated the use of electrophysiological measures at rest as paradigm-independent predictors of L2 development for the first time in older adult learners. We then assessed EEG correlates of the learning outcome in a language-switching paradigm after the training, which to date has only been done in younger adults and at intermediate to advanced L2 proficiency. Ten (Swiss) German-speaking adults between 65-74 years of age participated in an intensive three-weeks English training for beginners. A resting-state EEG was recorded before the training to predict the ensuing L2 development (Experiment 1). A language-switching ERP experiment was conducted after the training to assess the learning outcome (Experiment 2). All participants improved their L2 skills but differed noticeably in their individual development. Experiment 1 showed that beta1 oscillations at rest (13-14.5Hz) predicted these individual differences. We interpret resting-state beta1 oscillations as correlates of attentional capacities and semantic working memory that facilitate the extraction and processing of novel forms and meanings from the L2 input. In Experiment 2, we found that language-switching from the L2 into the native language (L1) elicited an N400 component, which was reduced in the more advanced learners. Thus, for learners beginning the acquisition of an L2 in third age, language switching appears to become less effortful with increasing proficiency, suggesting that the lexicons of the L1 and L2 become more closely linked. In sum, our findings indicate that individual differences in L2 development and proficiency in older adults operate through similar electrophysiological mechanisms as those observed in younger adults.
... Multilevel models are appropriate here because we are interested in individual-level outcomes that may be influenced by both individual-and contextual-level characteristics. In our analysis, respondents are nested within counties, and ignoring this clustering could underestimate standard errors of parameter estimates possibly leading to Type I error in which the wrong conclusions are observed for nonexistent relationships (Raudenbush and Bryk 2002). Multilevel modeling accounts for this form of non-independence and produces correct estimates of the standard errors (Raudenbush and Bryk 2002). ...
... In our analysis, respondents are nested within counties, and ignoring this clustering could underestimate standard errors of parameter estimates possibly leading to Type I error in which the wrong conclusions are observed for nonexistent relationships (Raudenbush and Bryk 2002). Multilevel modeling accounts for this form of non-independence and produces correct estimates of the standard errors (Raudenbush and Bryk 2002). This technique also is useful because it allows us to isolate the independent effects of both individual-and county-level variables, as well as test for cross-level interaction effects. ...
A well-established body of research focuses on the relationship between criminal threat and the exercise of formal social control, and a largely separate literature examines the effects of victim race in criminal punishment. Despite their close association, few attempts have been made to integrate these related lines of empirical inquiry in the sociology of punishment. In this article, we address this issue by examining relationships among criminal threat, victim race, and punitive sentiment toward black and Latino defendants. We analyze nationally representative survey data that include both subjective and objective measures of criminal threat, and we incorporate unique information on victim/offender dyads to test research questions about the that role victim race plays in the formation of anti-black and anti-Latino sentiment in the criminal justice system. The results indicate that both subjective perceptions of criminal threat and minority population growth are significantly related to punitiveness among whites, and that punitive sentiment is enhanced in situations that involve minority offenders and white victims. Moreover, we show that aggregate indicators of racial threat strongly condition the effect of victim race on punitive attitudes. Implications of these findings are discussed in relation to racial group threat theories and current perspectives on the exercise of state-sponsored social control.
... Because moderating effects may vary in magnitude and direction within and between countries, including a certain moderator as a single variable in the meta-regression model yields a meta-regression coefficient that comprises a mixture of the within-and between-country relationships. 58,59 To disentangle these within-and between-country relationships, the metaregression model should contain (a) the aggregated country-specific mean of the moderator (e.g., the country-specific value of a certain gender equality indicator averaged across time) to estimate the moderating effect at the country level and (b) the centered value of the moderator (e.g., the deviation of a gender equality indicator as observed at a certain point in time from the country-specific average) to estimate the moderating effect within countries. 59 ...
Descriptive analyses of socially important or theoretically interesting phenomena and trends are a vital component of research in the behavioral, social, economic, and health sciences. Such analyses yield reliable results when using representative individual participant data (IPD) from studies with complex survey designs, including educational large‐scale assessments (ELSAs) or social, health, and economic survey and panel studies. The meta‐analytic integration of these results offers unique and novel research opportunities to provide strong empirical evidence of the consistency and generalizability of important phenomena and trends. Using ELSAs as an example, this tutorial offers methodological guidance on how to use the two‐stage approach to IPD meta‐analysis to account for the statistical challenges of complex survey designs (e.g., sampling weights, clustered and missing IPD), first, to conduct descriptive analyses (Stage 1), and second, to integrate results with three‐level meta‐analytic and meta‐regression models to take into account dependencies among effect sizes (Stage 2). The two‐stage approach is illustrated with IPD on reading achievement from the Programme for International Student Assessment (PISA). We demonstrate how to analyze and integrate standardized mean differences (e.g., gender differences), correlations (e.g., with students’ socioeconomic status [SES]), and interactions between individual characteristics at the participant level (e.g., the interaction between gender and SES) across several PISA cycles. All the datafiles and R scripts we used are available online. Because complex social, health, or economic survey and panel studies share many methodological features with ELSAs, the guidance offered in this tutorial is also helpful for synthesizing research evidence from these studies. This article is protected by copyright. All rights reserved.
... With the focus on two predictors from two raters (i.e., the second and third categories), it is possible that different levels of analyses between two predictors are involved, as multiple followers are nested under a common leader in the data structure (i.e., dependent dyads; Gooty & Yammarino, 2011). In this vein, multilevel modeling techniques (e.g., random coefficient modeling [RCM]; Bryk & Raudenbush, 1992;Hofmann & Gavin, 1998) should be applied to PRA, as Bliese et al. (2018) noted "failing to use mixed effects to model nested data can result in too liberal Type I Errors (for group-level effects) and too conservative Type II Errors (for lower-level effects)" (p.14). While multilevel modeling techniques are used in PRA, contemplating centering decisions (i.e., grand-mean or group-mean centering; Bliese et al., 2018;Dalal & Zickar, 2012;McNeish & Kelley, 2019) based on different level assumptions in nested data is important to provide an unbiased estimate. ...
Congruence has served as an important research framework for many leadership research topics. Perhaps the most frequently used methodological/statistical approach for testing the congruence framework is polynomial regression analysis (PRA) with response surface methodology (RSM). As this approach was introduced to organizational sciences more than two decades ago, we can now identify the main issues with the use of this approach in leadership research. To systematically investigate these issues, we first review how PRA and RSM have been used in various leadership studies. We then review the levels-of-analysis and rater model assumptions prevalent in PRA in terms of multilevel techniques, choice of centering options, and issues of endogeneity. Finally, to better understand the inconsistencies and variabilities that exist in leadership research, we review the use of two main RSM features and summarize additional statistical techniques for assessment in this realm. Overall, we aim to promote the rigorousness of this methodology within the study of congruence in leadership research by enhancing its capability in theory testing and building.
... Specifically, to operationalize partners' emotional linkage, the R lme4 package (Bates et al., 2015) was used to run a series of 2-level multi-level models in which each of the 10 emotion variables (i.e., happiness, calmness, vigorous/exhausted, sadness, and nervousness, reported by each partner) served as an outcome which was predicted by all the other nine variables (e.g., men's happiness was predicted by their other 4 emotions, as well as by all of their partners' 5 emotions). We then extracted the empirical Bayes estimates (Raudenbush & Bryk, 2002; random effects) for each couple and computed the average of the absolute estimates that represented the linkage between partners' emotions (e.g., the association between men's sadness and women's calmness). ...
Introduction: Romantic partners’ emotions show a degree of interdependence, a process that is often described as emotional linkage. The current study sought to test the effects of emotional linkage in emotionally reactive individuals (i.e., those who easily become emotionally aroused and find it hard to regulate their emotions) and their partners. Specifically, we examined the interplay between emotional linkage and reactivity in predicting partners’ depressive symptoms over time. Method: To assess emotional linkage and reactivity, we collected daily diary data from two samples of cohabiting couples (N couples =76 and 84 in samples 1 and 2, respectively). Partners’ depressive symptoms were assessed before and after the diary. Results: In dyads with low emotional linkage men's emotional reactivity predicted their greater depressive symptoms in Sample 1, and women's greater depressive symptoms in Sample 2. Discussion: The study's results suggest that dyads’ emotional linkage can moderate the negative effects of men's emotional reactivity on their and their partners’ psychological distress.
... The data were obtained from the university and faculty members layers at the macro level (Level 2) and from the student layer at the micro level (Level 1) (Fig. 1). Considering education hierarchically, individual students cluster in universities (Bryk & Raudenbush, 1992;Goldstein, 1995;Hox, 2010). Therefore, an estimate related to a student is influenced by the student's variables, the qualifications of the faculty member and university at he or she is studying. ...
COVID-19 pandemic triggered distance education in higher education. Decisions such as isolation, social distancing and quarantine made by countries unexpectedly and suddenly forced face-to-face education to change to distance education within days. All academics around the world had to move online overnight. All the educational and academic activities in higher education (courses, exams, meetings, etc.) had to be conducted online in a few days. Based on these changes, this study aimed to analyze the relationships among student, faculty (adaptations of faculty members to distance education) and institutional (distance learning capacities of the universities) variables that affected satisfaction of the students related to distance education in higher education institutions in Turkey during COVID-19 pandemic using hierarchical linear modeling (HLM). The study group included 14,962 students and 3631 academics from 30 universities. The results showed that universities with higher distance education capacities got higher satisfaction scores. HLM analysis showed that 43% of the variation in satisfaction scores resulted from universities. The second HLM analysis showed that 44% of the overall satisfaction score variance of the students could be explained by the factors of university features (Level 2: distance education capacity and acceptance and use of distance education systems of faculty members). Thus, it was determined that 44% of the university factor calculated as 43% in Model 1 (which is calculated within students’ general satisfaction scores) resulted from the distance education capacity and the acceptance and use of distance education systems of faculty members. The findings of this study provide insights to improve distance education by stakeholders of higher education institutions.
... Multilevel modeling, also known as hierarchical linear modeling (Bryk & Raudenbush, 1992) and mixed-effects modeling (Laird & Ware, 1982), is commonly used across various disciplines to analyze clustered data. A multilevel model consists of two types of effect: fixed effects, which represent the average effects across clusters, and random effects, which represent individual clusters' deviations from the fixed effects. ...
Random effects in longitudinal multilevel models represent individuals’ deviations from population means and are indicators of individual differences. Researchers are often interested in examining how these random effects predict outcome variables that vary across individuals. This can be done via a two‐step approach in which empirical Bayes (EB) estimates of the random effects are extracted and then treated as observed predictor variables in follow‐up regression analyses. This approach ignores the unreliability of EB estimates, leading to underestimation of regression coefficients. As such, previous studies have recommended a multilevel structural equation modeling (ML‐SEM) approach that treats random effects as latent variables. The current study uses simulation and empirical data to show that a bias–variance tradeoff exists when selecting between the two approaches. ML‐SEM produces generally unbiased regression coefficient estimates but also larger standard errors, which can lead to lower power than the two‐step approach. Implications of the results for model selection and alternative solutions are discussed.
... Table 4). In addition, using information estimated in the null model, an intraclass correlation coefficient (ICC [1]) and reliability of the mean (ICC [2]) are computed, representing the percentage of the total between-group variance in the dependent variable [6]. The ICC [1] of confirmation is .165, ...
... While there are good power formulae for MLM clustered designs and repeated measures designs, as yet there is no specific formula for calculating power for dyadic analyses. Using a formula provided by Raudenbush and [51,52] for individual repeated measures and estimates from our previous dyadic models, we calculate a sample of 264 couples measured 4 times over a 12month period has a power of 0.80 to detect a moderate effect (d = .40) on change over time. ...
Background
Most cancer survivors are married, and cancer strains the physical and mental health of each partner and their intimate relationship. We created a partnered strength training program, Exercising Together©, where the survivor and his/her partner exercise as a team in order to improve physical and mental health of both members of the couple as well as the quality of their relationship. We have not yet determined if Exercising Together© is similarly effective in couples coping with different types of cancer nor if training as a team has unique and added benefits over those derived from supervised group training and/or shared behavior change. The purpose of this study is to determine the unique benefits of Exercising Together© on physical, mental, and relational health in couples coping with breast, prostate, or colorectal cancer.
Methods
Survivors of prostate, breast and colorectal cancer ( N = 294, 98 per cancer site) and their intimate, co-residing partners are recruited to participate in a single-blind, parallel group, randomized trial comparing three exercise groups that train twice per week for 6 months. Couples are randomized to one of three groups: (1) Exercising Together© where partners train as a team in a supervised group setting; (2) separate supervised group exercise classes for survivors or partners, respectively; (3) unsupervised home exercise program provided to each partner. The primary outcome is relationship quality (dyadic coping by the Dyadic Coping scale, emotional intimacy by the Dyadic Adjustment Scale, physical intimacy by the Physical Intimacy Behavior Scale, and symptom incongruence). Secondary outcomes are physical health (% body fat by DXA, serum fasting lipids (triglycerides, HDL, and LDL cholesterol), insulin resistance (HOMA-IR), resting blood pressure, C-reactive protein, TNF alpha, and physical functioning by the short Physical Performance Battery and SF-36) and mental health (depressive symptoms, anxiety, fear of recurrence) of each partner. Outcomes are collected at baseline, mid (3 months), post-intervention (6 months), and follow-up (12 months).
Discussion
Exercising Together© could shift the paradigm of survivorship care toward novel couple-based approaches that could optimize outcomes for each partner because their health is interdependent on each other and their relationship.
Trial registration
ClinicalTrials.gov NCT03630354 . Registered August 14, 2018
... Data were analyzed using multilevel modeling techniques (Bryk & Raudenbush, 1992). Multilevel models attempt to predict measurable behaviors from independent variables that are at different hierarchies. ...
The purpose of the present study was to evaluate whether the motivation of principals and teachers plays a significant role in the achievement of elementary school students. Participants were 193 elementary school students who attended grades 3 through 6 of 2 schools in a large metropolitan area of Greece. Students' achievement in language was estimated using normative scales. Teachers' motivation was assessed using Elliot's achievement goal measure. Data were analyzed using mixed modeling due to the hierarchical structure of the data. Results indicated that there were no differences between principal and teacher's adoption of goals. Further analyses focused on teachers and indicated that their adoption of mastery goals (approach or avoidance) were positive predictors of students' achievement in reading comprehension. Performance approach goals were negative predictors of both reading comprehension and spelling. Last, performance-avoidance goals were positive predictors of vocabulary. It is concluded that teachers' motivational dispositions play a significant role in the achievement levels of their students.
... Data were analyzed using multilevel modeling techniques (Bryk & Raudenbush, 1992). Specifically, the EEG and EMG waves (Time Series) comprised the dependent variables, whose point estimates and slopes over time were predicted by goal orientations (Level-1 predictors). ...
The purpose of the present study was to test the hypothesis that goal orientations are defined by saliently different physiological responses in students with dyslexia. Using a single-subject alternating conditions design a series of goal conditions were implemented. Participants were 16 college students and English as a Foreign Language (EFL) learners with a diagnosis of dyslexia. Electroencephalographic (EEG), Electromyographic (EMG) and Blood Volume Pulse (BVP) activities were monitored using Nexus-4. Results indicated that the performance goal conditions were manifested with significantly elevated abnormal cortical activity. Among goal orientations, performance goals with a focus on normative evaluations (Grant & Dweck, 2003) were associated with the most debilitating changes in participants' physiology. It is suggested that the early negative effects of performance goals could be attributed to their foci on normative evaluations.
... The present research got samples of 505 employees and their supervisors. That is to say, there is no nested framework (Raudenbush and Bryk, 2002) in the present research, and an individual-level statistical technique (e.g., latent growth model) rather than a cross-level statistical technique (e.g., hierarchical linear modeling) should be employed to test the samples. Based on the valid samples, 59% are male and the average age is 28 years. ...
Counterproductive work behaviors are a crucial issue for practice and academic because it influences employees’ job performance and career development. The present research conceptualizes Kahn’s employee engagement theory and employs transformational leadership, ethical leadership, and participative leadership as its antecedents to predict counterproductive work behaviors through a latent growth model. The present research collected empirical data of 505 employees of fintech businesses in Great China at three waves over 6 months. The findings revealed that as employees perceived higher transformational leadership, ethical leadership, and participative leadership at the first time point, they may demonstrate more positive growths in employee engagement development behavior, which in turn, caused more negative growths in counterproductive work behaviors. The present research stresses a dynamic model of the three leaderships that can alleviate counterproductive work behaviors through the mediating role of employee engagement over time.
... Step 1, we explored a null model with no predictors in order to calculate the intraclass correlation coefficient (ICC) to determine the strength of the nonindependence (Bryk & Raudenbush, 1992;Singer & Willett, 2003). This is a simple model consisting only of the repeated measures of intention to retire without including the time variable. ...
... To calculate the number of participants required for this study, the free Statistics Calculators ver. 4.0 [16] was employed to ascertain the minimum sample size required to perform hierarchical linear regression [17] using the following parameters: nine independent variables in Block 1, two independent variables in Block 2, a two-sided significance level (α) of 0.05, statistical power (1-β) of 0.9, and medium effect size (f 2 ) of 0.15 [18]. The required number of participants, accounting for a 10% withdrawal rate, was computed as 107. ...
This study investigated the association between the quality of life (QOL) and type 1 diabetes mellitus (DM), a lifelong disease that requires constant management. A complex set of factors influence the QOL of people with type 1 DM, and understanding these factors requires further research. This research is a cross-sectional descriptive study. A survey on related variables such as acceptance of disease and efficacy for self-management of diabetes, was conducted among 111 participants with type 1 DM. The collected data were analyzed using PASW Statistics program, and factors influencing participants’ QOL were identified through hierarchical multiple regression. The study followed the Guidelines of Systematic Reporting of Examination in the STROBE checklist. The results showed that four variables exerted a significant effect on QOL (blood glucose level at hypoglycemia and complications in Model 1; efficacy for self-management of diabetes and acceptance and action in Model 2), and all the variables explained a majority of the variance in QOL. The results indicate that management of severe hypoglycemia and prevention of complications is crucial. Interventions should be developed to enhance coping abilities to improve efficacy for self-management for those with diabetes and promote their acceptance of the disease.
... Hence, we analyzed the data using random coefficient modeling (RCM; Goldstein, 1987) with the SAS Mixed procedure. The advantage of RCM is that by modeling residuals at Level 2 or 3 (with the employee serving as the level-one unit of analysis), such models acknowledge that employees working within the context of the same department may be more similar to one another than to employees affiliated with different departments (Bryk & Raudenbush, 1992). We framed our analysis around the moderated mediation model implied by our hypotheses. ...
Frontline hotel employees face a complex organizational environment that constantly makes multiple demands, creating a persistent trade-off between service as a key element of the organization’s strategy and other competing or even conflicting goals. This study proposes an integrated and unique way of discerning the relationship between service climate and service performance through the prism of surface and deep acting emotional labor and suggests a new dimension of the service climate—the service priority climate. Specifically, we examined employees’ use of emotional labor strategies as
a mechanism that explains the relationship between service priority climate and service performance. We also investigated whether workload pressure influences this relationship. Using a multilevel, multisource study, we surveyed a sample of 245 hotel employees working in 39 departments and their direct managers. The results demonstrated that when employees regarded service as a priority compared with other competing goals, they used more deep acting emotional labor strategies, resulting in better service performance. However, this was apparent only when workload pressure was low. Implications for hospitality organizations are discussed.
... Notably, the relations between shifting and grammar/syntax and listening comprehension could not be examined because of too few studies reporting effects between these constructs. 3 Heterogeneity in effect sizes is indicated based on the Q (Cochran, 1954) and I 2 statistics (Bryk & Raudenbush, 1992;Higgins & Thompson, 2002;Maas et al., 2004). Traditional Q statistics, calculated by summing the square deviations of study effect size estimates while weighting each effect estimate by its inverse variance, were utilized for the three-level meta-analyses (Cheung, 2014). ...
The primary goal of this study was to examine developmental patterns among the relations between components of executive function (EF; working memory [WM], inhibitory control, shifting), and academic outcomes (reading, mathematics, language) in elementary school-age children. These relations were examined within the context of the development of EF and of academic skills utilizing an extension of the unity and diversity, intrinsic cognitive load, and dual process theories. Using meta-analytic methods, we summarized results from 299 studies from 293 articles/dissertations, representing 65,605 elementary school-age children (42-191 months old [M = 101 months, SD = 24.49 months]). Results indicated that accounting for general EF (by including the correlations among EF tasks in meta-analytic path models and accounting for effects between all three EF components and academic outcomes simultaneously) produced weaker relations between EF and academic skills than the bivariate relations which have been reported in prior meta-analytic reviews. However, although reduced, all relations between EF and academic outcomes remained significant throughout elementary school. Whereas WM was consistently moderately associated with reading, math, and oral language across development, the developmental trends for the relations between inhibitory control and shifting with academic outcomes varied based upon the academic skill examined. On the academic side, whereas the relations between reading and language skills with EF components varied throughout elementary school, few developmental changes were found in the relations between EF components and math skills across elementary school. Future directions and implications of findings for the conceptualization of the impact of EF on academics are discussed within the context of relevant theoretical models. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
... Since the model consists of the cross-level constructs, Hierarchical Linear Modeling (HLM) is used in the analysis as it can simultaneously estimate the effects of factors from different levels on outcomes at the individual-level while maintaining the predictors' appropriate levels of analysis (Bryk & Raudenbush, 1992;Hofmann, Morgeson, & Gerras, 2003). ...
Using both experimental and field data, we examined how and what style of leader humor expression leads to positive work outcomes. We develop and test a dual process model (the affective mechanism and the cognitive mechanism) delineating the psychological process by which leader humor expressions influence follower outcomes. We test our model across two studies. Study 1 demonstrates in an experiment that the perceived funniness of leader humor causes followers to report greater positive affect as well as positive evaluation of the leader. Extending these findings into organizational field context, Study 2 surveys a sample of 211 employees and 47 managers and finds that employees’ positive affect at work and their positive evaluation of their manager mediated the relationship between perceived funniness of manager’s humor and employee performance. However, the mediation path of positive evaluation is negatively moderated by manager’s humor style such that when the manager has a self-deprecating humor style, the positive effect of perceived humor funniness will decrease. We also contribute to the leadership, affect and humor literature by suggesting the need to view leader humor expression as a perception by the recipient rather than intention of the sender, proposing two features of leader humor expression (perceived humor funniness and humor style) that have been neglected by past research.
... Underestimation of the standard error in Step 2 is related to the reliability of the individual slope estimates reflecting stress reactivity. This reliability depends on various factors (e.g. the number of measurement occasions in the case of intensive longitudinal data, level-1 predictor variance; Liu et al., 2019;Neubauer et al., 2020;Raudenbush & Bryk, 2002). It may thus vary across studies with different numbers of occasions, but also across individuals of the same study. ...
Recent theoretical accounts on the causes of trait change emphasize the potential relevance of states. In the same vein, reactions to daily stress have been shown to prospectively predict change in well-being, speaking for the proposition that state dynamics can be a precursor to long-term change in more stable individual-differences characteristics. A common analysis approach towards linking state dynamics such as stress reactivity and change in some more stable individual differences characteristic has been a two-step approach, modeling state dynamics and trait change separately. In this paper, we elaborate on one-step procedures to simultaneously model state dynamics and trait change, realized in the multilevel structural equation modeling framework. We highlight three distinct advantages over the two-step approach which pre-exists in the methodological literature, and we disseminate these advantages to a larger audience. We target a readership of substantive researchers interested in the relationships between state dynamics and traits or trait change, and we provide them with a tutorial style paper on state-of-the-art methods on these topics.
... As we collected data from multiple organizations, it was necessary to control for organizational effects. Multilevel modeling such as hierarchical linear modeling (HLM) is a more appropriate analytical tool than ordinary regression for handling nonindependence of data structures caused by group clusters (Bliese, 2000;Bryk & Raudenbush, 1992). Accordingly, following Hofmann (1997), we ran a series of HLMs to test our hypotheses. ...
Although previous studies have found that positive group affective tone is generally good for team creativity, the reported effects of negative group affective tone (NGAT) are mixed. Drawing on the team goal orientation composition literature, we propose that team trait learning goal orientation (TTLGO; aggregated level of team members’ trait learning goal orientation) will moderate the relationship between NGAT and team creativity. Specifically, NGAT will be positively related to team creativity when TTLGO is high but becomes negative when TTLGO is low. We further theorize that team information exchange accounts for this moderating effect. Employing a multiple-source and time-lag design, we conducted two studies to test the hypotheses. In Study 1, we collected data from 270 information technology engineers working in 62 R&D teams in a software development company and examined the moderating effect of TTLGO on the NGAT-team creativity relationship. In Study 2, we replicated the findings of Study 1 and further tested the mediating role of team information exchange (i.e., Hypothesis 2) using data from 237 members of 43 diversified teams (e.g., R&D, advertising and marketing, technical services, and quality improvement). The results of these two studies support our hypotheses. Theoretical and practical implications for group affect and creativity literature are further discussed.
... The multilevel dataset is conducted using a random intercepts model (Bryk and Raudenbush 1992;Luke 2004) where lower level observations are the districts and upper level are the countries. For robustness all models are rerun using random slopes, with the results showing little differences. ...
How do new party systems evolve over time? This paper argues that party system evolution requires the solution of coordination problems voters face in early elections; this happens through a learning mechanism. Elections reveal information to voters, who update their beliefs about party viability and the distribution of voters’ preferences and adjust their behaviour. The institutional setting, however, strongly conditions the pace of learning. Restrictive electoral systems (SMD) accelerate learning through the harsh penalties they impose on miscoordination, while permissive ones (PR) prolong it. Testing the argument on a district-level dataset in new democracies provides ample support; voters learn to cast fewer wasted votes over time and this happens faster in SMD systems. The findings point to a trade-off between consolidation and representation; while party system evolution is facilitated by restrictive electoral systems the presence of distinct social groups in the political arena is better served by permissive ones.
... From a statistical perspective, a good agreement among teachers within the same school suggests that the proposed constructs are reliable. A within-group similarity or agreement index (rWG; James et al., 1993) and Intraclass Correlation Coefficients (ICCs), which is considered as a measure of the variability in individuals' responses that can be explained by or related to group membership (Bryk & Raudenbush, 1992), indicated good agreement among teachers, suggesting that the variables of school violence and academic emphasis are therefore reliable (see Table 1). In addition, following Podsakoff et al. (2003), it was explicitly stated that the respondents' identities were kept anonymous, and the participants were assured that there are no right or wrong answers, thus also reducing bias. ...
The call for a more collective approach to school leadership motivated the present study. The proposed model examined the mediating role of school management team (SMT) effectiveness in the relationship of SMT characteristics of goal interdependence (the extent to which a shared goal requiring cooperation is present) and functional heterogeneity (the diversity of team member knowledge and skills) to school violence, academic emphasis and teacher absenteeism. Data were collected from a sample of 92 schools randomly selected from all state-secular and state-religious schools in Israel. A multi-source survey design from a sample of 92 SMTs, their principals, and teachers who are not SMT members was used. Data were aggregated at the school level of analysis. The results from structural equation model indicated that SMT effectiveness mediated the relationship of SMT goal interdependence to school violence, academic emphasis and teachers’ absenteeism. SMT effectiveness facilitates the shift from more independent practices of teaching to teamwork, building leadership capacity promoting a positive and safely school learning environment. A work environment that promotes effective teamwork facilitating social relationships and knowledge exchange can provide a mechanism to create norms of teamwork that would benefit school effectiveness. The implications of these findings for both theory and practice are discussed.
... The mean of this variable is 3.1 (SD = 0.8). The independent variables for self-concept in German language arts and socio-economic status were group-centred (Raudenbush and Bryk 2002). ...
This study investigates the impact of the presence of students identified as having special needs (SEN) on their classmates’ achievements in reading comprehension. Multi-level regression modelling was conducted with the data of more than 75,000 fourth graders of 4,937 classes in Austria. Students’ scores of reading comprehension were used as the dependent variable in the models. The number of students with SEN was used as the independent variable, besides other class-level predictors like the socio-economic status or the self-concept. To disentangle individual from classroom composition aspects, variables at the individual level were used as independent variables as well (gender, age, first language, number of books at home, socio-economic background, kindergarten attendance, and self-concept). Results show only a small relationship (Cohen’s d = −0.16) between the presence of students with special needs on their classmates’ national standard scores, in particular compared to other class-composition effects like socio-economic status or self-concept.
... For example, the r wg(j) index is a measure of inter-rater agreement and the closest to + 1 the better [42]. Type 1 Intra-class correlation describes the amount of variance explained by the team-level while the type 2 index is an indicator of the reliability of the mean at the team level [40,43]. One can see that team-level patient-centered care perceptions has 13% of variance available to be explained at the team level. ...
Background
The successful combination of interprofessional collaboration in multidisciplinary teams with patient-centered care is necessary when it comes to delivering complex mental health services. Yet collaboration is challenging and patient-centered care is intricate to manage. This study examines correlates of patient-centered care such as team adaptivity and proactivity, collaboration, belief in interprofessional collaboration and informational role self-efficacy in multidisciplinary mental health teams.
Method
A cross-sectional multilevel survey design was used, based on self-administered bilingual validated questionnaires. Participants ( N =314) were mental health professionals and managers working in public primary care or specialized mental health services, in inpatient or outpatient settings.
Results
This study showed that belief in interprofessional collaboration’s relationship with patient-centered perceptions is increased in teams with high collaboration. Collaboration is also found as a mediator, representing a process by which team adaptive and proactive behaviors are transformed into positive patient-centered perceptions.
Conclusions
Our results were in line with recent studies on team processes establishing that collaboration is a key component in multilevel examinations of predictors of patient-centered care. In terms of practice, our study showed that multidisciplinary teams should know that working hard on collaboration is an answer to the complexity of patient-centered care. Collaboration is related to the teams’ ability to respond to its challenges. It is also related to individuals’ beliefs central to the delivery of interprofessional care.
... The author argues that the lack of support for these relationships may be due to some of the community blocks comprising two study participants. The author recommends that future research follow Bryk and Raudenbush's (1992) rule of thumb, which suggests 15 cases per geographic unit. ...
The purpose of this research is to form an overarching definition of community membership that encompasses all community contexts.
Utilizing qualitative interviews with 102 members of five known community contexts (communities of action, circumstance, interest, place, and practice), the authors use cross-case analysis to explore common, transcendent themes of membership. Three takeaways emerge: first, that individuals identify with communities to address personal needs
but come to see social benefits; second, that individuals join communities
to deepen existing relationships, but develop new ones; and third,
that through engagement, individuals strengthen a sense of self that
is unique to community context. Through these takeaways, we define
community as a reciprocal and emergent system of interactions
through which individuals seek to address personal and shared physiological, social, and self-actualizing needs.
... La extensión de esta línea de estudios dio lugar al Segundo Reporte Coleman de los 80 y a la perspectiva neoinstitucional en la cual, una vez controlado el hogar de origen, los colegios privados eran mejores que los públicos y, de entre los privados, los católicos (Chubb, Moe, Tweedie y Riley, 1990;Coleman, Hoffer y Kilgore, 1982). El refinamiento metodológico posterior y la aplicación de técnicas de investigación más avanzadas hacia modelos de tipo multinivel permitieron por primera vez cuantificar el efecto puro del centro educativo (Bryk y Raudenbush, 1992). Esto permitió identificar una serie de factores organizacionales que no eran intrínsecos a la gestión privada: i) cooperación y coordinación entre docentes; ii) conciencia de la responsabilidad colectiva de los aprendizajes de los alumnos; iii) atención a los estudiantes en riesgo académico; iv) consenso sobre las competencias a impartir; y v) definición de experiencias de aprendizaje exigentes y significativas (Lee y Smith, 1996). ...
Uruguay tiene vocación por la inclusión educativa desde finales del siglo XIX. Desde un punto de vista teórico, la desigualdad educativa siempre ha estado solapada por algún elemento de desigualdad socioeconómica. Ergo, la mayoría de las reivindicaciones y políticas educativas han estado centradas en igualar condiciones del hogar de origen. No obstante, pese a una importante serie de políticas y programas de inclusión social, en uno de los países con mejores indicadores sociales y de equidad del continente, aproximadamente el 60% de la población nunca va a culminar la Educación Media. Este artículo ensaya una sistematización y comparación teórica de los principales trabajos asociados a la desigualdad educativa a nivel nacional e internacional. Entre las principales conclusiones, se destaca la idea de que la desigualdad socioeconómica es solo una pieza de la desigualdad educativa. Por tanto, actuar únicamente sobre la desigualdad socioeconómica es una reducción teórica y empírica agotada. El articulo ensaya una sistematización y comparación teórica de los principales trabajos asociados a la desigualdad educativa a nivel nacional e internacional. Entre las principales conclusiones, destaca la idea de que la desigualdad socioeconomica es solo una pieza de la desigualdad educativa. Por tanto, actuar únicamente sobre la desigualdad socioeconómica, es una reducción teórica y empírica agotada.
... In this model, we followed the suggestion of Hofmann and Gavin (1998) to grand the mean center of our research variables. By considering that athletes from different teams may vary in their emotional and physical exhaustion level, a random effect was introduced for the Level-2 intercept to control the team effects (Bryk & Raudenbush, 1992). Furthermore, we included team-level predictors, including team performance climate (i.e., the mean of performance climate for each team), team mastery climate (i.e., the mean of mastery climate for each team), and team sports-specific gratitude (i.e., the mean of sports-specific gratitude for each team), as control variables in our models when testing the interaction effects (Aguinis et al., 2013). ...
Motivational climate (i.e., mastery and performance climate) has been found to shape athletes’ emotional and physical exhaustion, the core dimension of burnout. However, the interactional effect between mastery and performance climate on emotional and physical exhaustion has been rarely examined. In this study, we proposed that athletes’ gratitude will determine the interaction effect of mastery climate and performance climate on emotional and physical exhaustion. Specifically, we hypothesized that among athletes high in gratitude, mastery climate can mitigate the association between performance climate and emotional and physical exhaustion; among those low in gratitude, mastery climate can intensify the association between performance climate and emotional and physical exhaustion. Using a time-lagged survey, data from 293 athletes revealed a three-way interaction effect among mastery climate, performance climate, and gratitude. We did not find that mastery climate can mitigate the association between performance climate and emotional and physical exhaustion for those high in gratitude but found that among athletes low in gratitude, the positive association between performance climate and emotional and physical exhaustion was stronger in a higher mastery climate than in a lower mastery climate. Our study offers an interactionist perspective to help further understand the joint effect of mastery and performance climates on emotional and physical exhaustion by taking the role of individual differences into account. (PsycInfo Database Record (c) 2021 APA, all rights reserved)
... Because completion rates have previously been shown to decline over the duration of EMA study protocols, 33,35 changes in EMA completion rates were also examined. Multilevel growth models were used for this purpose, 36 where the number of daily completed EMA prompts served as dependent variable, and day of study served as predictor variable, allowing for random effects (individual differences) in the (linear) time trend of completed daily prompts. ...
Pain intensity represents the primary outcome in most pain clinical trials. Identifying methods to measure aspects of pain that are most sensitive to treatment may facilitate discovery of effective interventions. In this third of 3 articles examining alternative indices of pain intensity derived from ecological momentary assessments (EMA), we compare treatment effects based on Average Pain, Maximum Pain, Minimum Pain, Pain Variability, Time in High Pain, Time in Low Pain, and Pain After Wake-Up. We also examine which indices contribute to Patient Global Impressions of Change (PGIC). Data came from 2 randomized, double-blind, placebo-controlled trials examining the efficacy of milnacipran for fibromyalgia treatment; 2,084 patients provided >1 million EMA pain intensity ratings over 24 (Study 1) or 26 (Study 2) treatment weeks. Pain Variability and Time in High Pain produced significantly smaller treatment effects than Average Pain; other pain indices showed effects that were numerically smaller, but not significantly different from Average Pain. Changes in all pain indices were significantly associated with PGIC, with improvements in Maximum Pain and in Pain Variability offering small incremental contributions to understanding PGIC over Average Pain. Results suggest that different pain indices could be used to detect treatment effects in pain clinical trials.
Perspective: Alternative summary measures of pain intensity derived from EMA may broaden the scope of outcomes useful in pain clinical trials. In this analysis of a pharmacological treatment for fibromyalgia, most pain summary measures indicated similar effects; improvements in Maximum Pain and Pain Variability contributed to understanding PGIC over Average Pain.
Este trabalho tem o intuito de analisar como o nível de desenvolvimento urbano das estruturas produtivas das microrregiões de Minas Gerais afeta a probabilidade de um indivíduo estar ou não ocupado no mercado de trabalho. Para tanto, utilizando dados do Censo (2010), estimou-se um modelo logístico hierárquico de dois níveis para verificar em que medida varia a probabilidade de trabalhadores, com características semelhantes, estarem ocupados (nível 1), dado que estes residem em diferentes microrregiões mineiras (nível 2). Os resultados apontam que a probabilidade do indivíduo estar ocupado é maior se ele for homem, branco, residir na área rural, ser mais velho e mais escolarizado. Ademais, os atributos urbanos das microrregiões, por meio da taxa de urbanização e da densidade de serviços modernos, têm influência positiva sobre a condição de ocupação dos indivíduos, porém, pouco representativa, comparada aos atributos individuais.
Objective:
In psychotherapy, strength-based methods (SBM) represent efforts to build on patients' strengths while addressing the deficits and challenges that led them to come to therapy. SBM are incorporated to some extent in all major psychotherapy approaches, but data on their unique contribution to psychotherapy efficacy is scarce.
Methods:
First, we conducted a systematic review and narrative synthesis of eight process-outcome psychotherapy studies that investigated in-session SBM and their relation to immediate outcomes. Second, we conducted a systematic review and multilevel comparative meta-analysis contrasting strength-based bona fide psychotherapy vs. other bona fide psychotherapy at post-treatment (57 effect sizes nested in 9 trials).
Results:
Despite their methodological variability, the pattern of results in the process-outcome studies was generally positive, such that SBM were linked with more favorable immediate, session-level patient outcomes. The comparative meta-analysis found an overall weighted average effect size of g = 0.17 (95% CIs [0.03, 0.31], p < .01) indicating a small but significant effect in favor of strength-based bona fide psychotherapies. There was non-significant heterogeneity among the effect sizes (Q(56) = 69.1, p = .11; I2 = 19%, CI [16%, 22%]).
Conclusion:
Our findings suggest that SBMs may not be a trivial by-product of treatment progress and may provide a unique contribution to psychotherapy outcomes. Thus, we recommend integration of SBM to clinical training and practice across treatment models.
One prominent theory of social change predicts secularization—when societies prosper, people rely less on religion for ensuring survival, social order, and meaning of life. While some researchers claimed that secularization is universal, critics contended that it does not explain patterns of religious change in non-Western societies. To settle this debate, we applied multilevel modeling to analyze historical, socio-economic factors that moderated the process of secularization around the world. We predicted that secularization occurs as a result of modernization in societies where historical wealth and democratic institutions were established to ensure social, political, and ecological complexity for citizens. We also used the cultural evolutionary account of religion to predict that modernization strengthens people's need for religiosity in societies without well-functioning institutions to mitigate increased social complexity. We used GDP and infant mortality as indices of modernization, the Gini index as an indicator of social complexity, and communist history (non-communist vs. post-communist) and the proportion of Christianity as historical contexts to explain variability in the within-society processes of secularization. Analyzing religiosity data with over 100 countries over 30 years, we found support for the secularization hypothesis primarily among formerly wealthy countries: in years when economic wealth increased, religiosity declined. However, an increase in GDP predicted increasing religiosity among formerly poor countries. We also found that increased economic inequality was linked with greater religiosity only among post-communist countries or Christian-minority countries: when economic inequality increased in those countries, religiosity increased. We integrate these findings and the present analytical approach to discuss implications for cross-cultural research and the study of cultural change.
Background/Context
Prior research has investigated differences in course-taking patterns and achievement growth in public and Catholic schools, but the nature of instruction in Catholic schools is currently understudied. One important dimension of instruction that impacts student engagement is the prevalence of developmental or student-centered instruction.
Purpose/Objective/Research Question/Focus of Study
The overall goal of the present study was to investigate whether student and teacher reports of developmental instruction differ in public and Catholic schools. In addition, is a teacher's approach to instruction shaped by the social context of the school, as measured by the teacher's perception of her students? Finally, can differences in the social context of schools explain reported differences in the prevalence of developmental instruction in public and Catholic schools?
Population, Participants/Subjects
Data for this analysis came from the Chicago School Study, a large longitudinal study of public and Catholic schools in the Chicago area.
Research Design
The prevalence of developmental instruction in public and Catholic schools was analyzed using three student-reported measures of developmental instruction and one teacher-reported measure. Multilevel regression models were used to investigate the relationship between four potential predictors of developmental instruction—teachers’ perceptions of challenging instruction, teachers’ expectations of students’ future educational attainment, teachers’ knowledge of their students’ cultural backgrounds, and principals’ endorsement of developmental instruction—and teacher reports of developmental instruction.
Conclusions
Catholic school teachers and students were less likely to report the use of developmental instruction than public school teachers and students. This finding was particularly striking given Catholic school teachers’ high expectations for their students’ future educational attainments, a factor that was associated with an increased likelihood of reporting developmental methods in the classroom.
The present study examines the shape, determinants, and outcomes of autonomous and controlled motivation trajectories over the course of aprofessional training program. Asample of 43 employees completed the measures on four occasions over the course of a14-week professional training program. This study also relies on aburst design, whereby employees completed each measure twice (with ahalf-day interval) at each measurement occasion to achieve amore accurate representation of occasion-specific ratings. Results from three-level growth analyses (with the two bursts at Level 1, four occasions at Level 2, and participants at Level3) showed that autonomous motivation, negative affect, learning, and satisfaction appeared to follow curvilinear trajectories, whereas autonomy support and positive affect followed linear trajectories. In contrast, controlled motivation, fatigue, and engagement levels remained stable over time, consistent with an intercept-only model. Furthermore, higher levels of autonomy support were associated with higher levels of autonomous motivation, and lower levels of controlled motivation over time. Finally, higher initial levels of autonomous motivation predicted higher levels of positive affect, learning, satisfaction, and engagement, and lower levels of fatigue over time, whereas higher initial levels of controlled motivation predicted higher levels of fatigue over time.
Los ciudadanos de América Latina se preocupan por las consecuencias del cambio climático más que los de cualquier otra región del mundo. Sin embargo, esta preocupación no siempre conduce a la priorización del medioambiente sobre el crecimiento económico. Este artículo argumenta que los constreñimientos económicos de los individuos condicionan la relación entre sus creencias acerca de la gravedad de las consecuencias del cambio climático y sus preferencias frente al dilema entre priorizar el medioambiente o el crecimiento económico. El análisis de encuestas del Barómetro de las Américas (Lapop) de 2016 en 18 países de América Latina, con modelos jerárquicos lineales y ecuaciones estructurales generalizadas, muestra que las creencias acerca de la seriedad de las consecuencias del cambio climático tienen un efecto positivo y significativo sobre la priorización del medioambiente entre los individuos con una riqueza patrimonial por encima de la media y un efecto negativo entre los individuos con riqueza patrimonial por debajo de la media. Este artículo hace dos contribuciones. Primero, el estudio analiza el efecto condicionado de la preocupación por el cambio climático sobre la priorización del medioambiente dependiendo de los constreñimientos económicos individuales. En segundo lugar, aporta a la investigación acerca de las actitudes medioambientales en América Latina.
While hierarchical linear modeling is often used in social science research, the assumption of normally distributed residuals at the individual and cluster levels can be violated in empirical data. Previous studies have focused on the effects of nonnormality at either lower or higher level(s) separately. However, the violation of the normality assumption simultaneously across all levels could bias parameter estimates in unforeseen ways. This article aims to raise awareness of the drawbacks associated with compounded nonnormality residuals across levels when the number of clusters range from small to large. The effects of the breach of the normality assumption at both individual and cluster levels were explored. A simulation study was conducted to evaluate the relative bias and the root mean square of the model parameter estimates by manipulating the normality of the data. The results indicate that nonnormal residuals have a larger impact on the random effects than fixed effects, especially when the number of clusters and cluster size are small. In addition, for a simple random-effects structure, the use of restricted maximum likelihood estimation is recommended to improve parameter estimates when compounded residuals across levels show moderate nonnormality, with a combination of small number of clusters and a large cluster size.
In this study, we investigated the effect of cross‐level factors, including team members’ altruistic personalities, the quality of team member exchange (TMX), interdependence of team structure, as well as interactions between these variables, on team members’ organisational citizenship behaviour (OCB). Using the military teams in Taiwan as samples, we collected empirical data of 90 teams, each with three team members and one team leader. Results of hierarchical linear modelling analysis showed that (a) a team member’s altruistic personality has no significant relationship with OCB, (b) both TMX and team interdependence have positive relationships with OCB, and (c) team interdependence has a cross‐level moderating effect on the relationship between TMX and OCB. For team management, establishing high TMX and interdependent working styles can promote OCB among team members. The results of this study add to knowledge on team members’ display of OCB from a holistic perspective. Findings of this study also support the important influence of TMX and team interdependence, especial for team management, strengthening the cross‐level theory in the study of OCB.
Objective
The purpose of this study was to evaluate the efficacy of need-supportive teaching in physical education on girls' daily moderate-to-vigorous physical activity using a mixed method evaluation.
Methods
507 sixth-grade girls aged 9 to 14 years of 33 single-sex physical education classes participated in the cluster randomized control trial. During the 16-week intervention period, trained teachers conducted enhanced physical education lessons which were designed based on self-determination theory. In a randomized process, independent researchers using a computer-based algorithm allocated classes to the trial groups. (IG n=19 classes, CG n=14). These lessons were subject to repeated systematic observations. The students' perceptions of basic psychological need support and satisfaction in physical education were measured using repeated self-report questionnaires. Students' daily moderate-to-vigorous physical activity (MVPA) was assessed by accelerometry. Semi-structured interviews provided a deeper understanding of how purposively sampled focus groups perceived teacher behavior in physical education. After a separate analysis of qualitative and quantitative data, results were merged to investigate the intervention's efficacy and treatment fidelity.
Findings
Throughout the school year, the girls' MVPA levels decreased in both groups. Girls who reported their complete physical activity data had a lower body mass index than girls who reported no, or only one or two sets of physical activity data. Results of mixed measures converge on the finding that the teachers in the intervention group provided slightly stronger need support than the control teachers, however, intervention components were not delivered consistently. Therefore, a significant intervention effect on daily MVPA could not be quantified. Autonomy satisfaction significantly predicted MVPA.
Conclusion
Qualitative insights of teaching behavior in PE underlined the importance of need support and revealed structural barriers, which compromised the implementation quality.
Trial Registration
Ethics Committee of the Technical University of Munich 155/16S; Bavarian Ministry of Education IV.8-BO6106/52/12
Funding
German Research Foundation grant DE2680/3-1
Intensive longitudinal research designs are becoming more common in the field of neuropsychology. They are a powerful approach to studying development and change in naturally occurring phenomena. However, to fully capitalize on the wealth of data yielded by these designs, researchers have to understand the nature of multilevel data structures. The purpose of the present article is to describe some of the basic concepts and techniques involved in modeling multilevel data structures. In addition, this article serves as a step-by-step tutorial to demonstrate how neuropsychologists can implement basic multilevel modeling techniques with real data and the R package, lmerTest. R may be an ideal option for some empirical scientists, applied statisticians, and clinicians, because it is a free and open-source programming language for statistical computing and graphics that offers a flexible and powerful set of tools for analyzing data. All data and code described in the present article have been made publicly available.
Research on leadership and creativity is dominated by the study of leadership from people in formal leadership positions. The very nature of creativity requires self‐direction, however. This points to shared leadership, a process in which members dynamically share the leadership role, as a particularly relevant influence to consider. Drawing on psychological empowerment theory, we develop the shared leadership perspective on individual creativity. We argue that shared leadership has a cross‐level influence on individual creativity that is mediated by the experience of meaning of work and moderated by individual differences in power distance value: for individuals lower on power distance, shared leadership has a positive linear relationship with individual creativity; for individuals higher on power distance, shared leadership has a curvilinear relationship with individual creativity that is decreasingly positive. Using a sample of 623 members from 95 teams in 34 Chinese organizations, we find support for this multilevel model. Findings offer theoretical implications for shared leadership and creativity research and provide managerial implications.
Dieser Beitrag stellt die Grundzüge der bayesianischen Inferenz vor und argumentiert, dass es sich dabei um das ideale statistische Paradigma für die empirische Politikwissenschaft handelt. Die Politikwissenschaft ist in der Regel mit methodischen Herausforderungen und Daten konfrontiert, die mit den Vorstellungen der klassischen „frequentistischen“ Statistik nur unzureichend vereinbar sind. Bayesianische Methoden dagegen kombinieren Priori-Annahmen über interessierende Phänomene mit empirischer Evidenz, um dadurch zu informierten Wahrscheinlichkeitsaussagen zu gelangen. Darüber hinaus steht der moderne bayesianische Ansatz in enger Verbindung mit Markov Chain Monte Carlo (MCMC) Simulationsalgorithmen. Diese ermöglichen es, komplexere Modelle zu schätzen, als dies für herkömmliche Schätzverfahren der Fall ist. Schließlich überzeugt die bayesianische Herangehensweise durch die intuitive Form und Interpretierbarkeit der durch sie erzielten Ergebnisse. Wir demonstrieren die Nützlichkeit des bayesianischen Ansatzes anhand eines Beispiels aus der empirischen Demokratieforschung: der Frage, welchen Einfluss die staatliche Unterstützung von Religion für religiöses Sozialkapital im europäischen Vergleich besitzt.
This article presents rates of violence against dating partners by students at 31 universities in 16 countries (5 in Asia and the Middle East, 2 in Australia-New Zealand, 6 in Europe, 2 in Latin America, 16 in North America). Assault and injury rates are presented for males and females at each of the 31 universities. At the median university, 29% of the students physically assaulted a dating partner in the previous 12 months (range = 17% to 45%) and 7% had physically injured a partner (range = 2% to 20%). The results reveal both important differences and similarities between universities. Perhaps the most important similarity is the high rate of assault perpetrated by both male and female students in all the countries.
Recently, the traditional approach to high-performance work systems (HPWS) research has been questioned, primarily in regard to the following two areas: (1) its organizational-level measure cannot capture variability within organizations, and (2) its utilization of the summation index is predicated upon the individual HR practices that constitute HPWS having a synergistic impact on important outcomes. Despite the prevalence of this approach, empirical studies on the internal fit premise in the context of HRM are startlingly rare. Furthermore, the existing research has often reported mixed results. Herein, our study attempts to replicate recent developments by categorizing employee-rated HPWS along three subdimensions: ability-, motivation-, and opportunity-enhancing HR practices. Next, we conduct two different tests; namely, additive and interactive models, to predict individual performance. The results of the hierarchical linear modeling (HLM) demonstrate general support for the additive model. Most conspicuously, we find that motivation-enhancing HR practices negatively moderate the relationships between the other two dimensions and the outcomes. Only the interaction of ability- and opportunity-enhancing HR practices positively influences individual performance. Based upon the findings of the current research, we argue that the internal fit assumption should be viewed more cautiously and understood in the broader context wherein HPWS operate.
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