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The dominant view of calling among management scholars is that it is a stable construct that does not change. This view has resulted in a research void about calling's early development and subsequent evolution. Insight into the dynamic process through which callings develop is fundamental to understanding its role in people's careers and lives. In this study, I focus on the antecedents of calling, a consuming, meaningful passion people can experience toward a domain. I propose a dynamic model in which calling can change over time and can be shaped by antecedent factors, specifically, through people's ability, behavioral involvement, and social comfort in the area toward which they feel a calling. I tested these ideas in a seven-year, four-wave prospective longitudinal survey study of 450 amateur musicians. Multilevel analyses indicate individuals who were more behaviorally involved and felt higher social comfort in the calling domain (e.g., music) experienced higher levels of calling early on but experienced a decline in calling over time. Individuals' ability in the calling domain was not related to initial calling or change in calling. I discuss the implications for theory and research on calling, meaning of work, and the dynamics of careers.

We report that regions‐of‐interest (ROIs) associated with idiosyncratic individual behavior can be identified from functional magnetic resonance imaging (fMRI) data using statistical approaches that explicitly model individual variability in neuronal activations, such as mixed‐effects multilevel analysis (MEMA). We also show that the relationship between neuronal activation in fMRI and behavioral data can be modeled using canonical correlation analysis (CCA). A real‐world dataset for the neuronal response to nicotine use was acquired using a custom‐made MRI‐compatible apparatus for the smoking of electronic cigarettes (e‐cigarettes). Nineteen participants smoked e‐cigarettes in an MRI scanner using the apparatus with two experimental conditions: e‐cigarettes with nicotine (ECIG) and sham e‐cigarettes without nicotine (SCIG) and subjective ratings were collected. The right insula was identified in the ECIG condition from the χ2‐test of the MEMA but not from the t‐test, and the corresponding activations were significantly associated with the similarity scores (r = −.52, p = .041, confidence interval [CI] = [−0.78, −0.17]) and the urge‐to‐smoke scores (r = .73, p <.001, CI = [0.52, 0.88]). From the contrast between the two conditions (i.e., ECIG > SCIG), the right orbitofrontal cortex was identified from the χ2‐tests, and the corresponding neuronal activations showed a statistically meaningful association with similarity (r = −.58, p = .01, CI = [−0.84, −0.17]) and the urge to smoke (r = .34, p = .15, CI = [0.09, 0.56]). The validity of our analysis pipeline (i.e., MEMA followed by CCA) was further evaluated using the fMRI and behavioral data acquired from the working memory and gambling tasks available from the Human Connectome Project. We report that regions‐of‐interest (ROIs) associated with idiosyncratic individual behavior can be identified from functional magnetic resonance imaging (fMRI) data using statistical approaches that explicitly model individual variability in neuronal activations, such as mixed‐effects multilevel analysis (MEMA). We also show that the relationship between neuronal activation in fMRI and behavioral data can be modeled using canonical correlation analysis (CCA). The validity of our analysis pipeline (i.e., MEMA followed by CCA) was evaluated using the fMRI and behavioral data in a small dataset from our nicotine craving experiment and a large dataset from the Human Connectome Project.

Background The prevalence of teenage pregnancy in Colombia is higher than the worldwide average. The identification of socio-geographical disparities might help to prioritize public health interventions. Aim To describe variation in the probability of teenage maternity across geopolitical departments and socio-geographical intersectional strata in Colombia. Methods A cross-sectional study based on live birth certificates in Colombia. Teenage maternity was defined as a woman giving birth aged 19 or younger. Multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) was applied using multilevel Poisson and logistic regression. Two different approaches were used: (1) intersectional: using strata defined by the combination of health insurance, region, area of residency, and ethnicity as the second level (2) geographical: using geopolitical departments as the second level. Null, partial, and full models were obtained. General contextual effect (GCE) based on the variance partition coefficient (VPC) was considered as the measure of disparity. Proportional change in variance (PCV) was used to identify the contribution of each variable to the between-strata variation and to identify whether this variation, if any, was due to additive or interaction effects. Residuals were used to identify strata with potential higher-order interactions. Results The prevalence of teenage mothers in Colombia was 18.30% (95% CI 18.20–18.40). The highest prevalence was observed in Vichada, 25.65% (95% CI: 23.71–27.78), and in the stratum containing mothers with Subsidized/Unaffiliated healthcare insurance, Mestizo, Rural area in the Caribbean region, 29.08% (95% CI 28.55–29.61). The VPC from the null model was 1.70% and 9.16% using the geographical and socio-geographical intersectional approaches, respectively. The higher PCV for the intersectional model was attributed to health insurance. Positive and negative interactions of effects were observed. Conclusion Disparities were observed between intersectional socio-geographical strata but not between geo-political departments. Our results indicate that if resources for prevention are limited, using an intersectional socio-geographical approach would be more effective than focusing on geopolitical departments especially when focusing resources on those groups which show the highest prevalence. MAIHDA could potentially be applied to many other health outcomes where resource decisions must be made.

INTRODUCTION Behavioral and psychological symptoms in dementia (BPSD) are dynamic phenomena with a high amount of intraindividual variability. We applied a multilevel framework to identify subsyndromes (between‐person factors) that represent clinically relevant profiles of BPSD and identify symptom clusters (within‐person factors) that represent contextually driven daily symptom experiences. METHODS This study used an intensive longitudinal design in which 68 co‐residing family caregivers to persons living with dementia were recruited to proxy report on their care recipient's daily symptom experiences of 23 different BPSD for eight consecutive days (n = 443 diaries). A multilevel exploratory/confirmatory factor analysis was used to account for nested data and separate within‐person variances from between‐level factor estimates. RESULTS Exploratory factor analysis identified a 4‐between 3‐within factor structure based on fit statistics and clinical interpretability. DISCUSSION This study offers major methodological and conceptual advancements for management of BPSD within Alzheimer's disease and related dementias by introducing two related but distinct concepts of subsyndromes and symptom clusters. Highlights Because behavioral and psychological symptoms of dementia (BPSD) are dynamic temporal phenomenon, this introduces measurement error into aggregate group‐level estimates when trying to create subsyndromes. We propose a multilevel analysis to provide a more valid and reliable estimation by separating out variance due to within‐person daily fluctuations. Using a multilevel exploratory factor analysis with intensive longitudinal data, we identified distinct and meaningful groups of BPSD. The four factors at the between‐person level represented subsyndromes that are based on how BPSD co‐occurred among persons with Alzheimer's disease (AD). These subsyndromes are clinically relevant because they share features of established clinical phenomena and may have similar neurobiological etiologies. We also found three within‐person factors representing distinct symptom clusters. They are based on how BPSD clustered together on a given day for an individual with AD and related dementias. These clusters may have shared environmental triggers.

Scholars who want to perform cross-national comparative research rely on data provided by International survey projects, which study the same concepts in varying countries and periods using different question wordings and scales. In this article, we propose a process to combine and analyse the data pertaining to the same concept—institutional trust—when measures and sources differ. We show how we combined 1327 surveys conducted from 1995 to 2017 by 17 survey projects in 142 countries. The database comprises close to 2 M respondents and 21 M answers to trust questions. We use local regression to visualize the trends in trust for different institutions and sources of data in different parts of the world. We complete these analyses with a 4-level longitudinal analysis of repeated measures. These analyses lead to reliably conclude that institutional trust is a property of the institutions themselves and of the context in which they operate since there is much more variance within respondents than between respondents and more variance between countries than over time. This research contributes to the current debates in political trust research. Since the process presented here can be applied to other fields of research, the research also contributes to enhance the possibilities for comparative cross-national analysis.

Background In neuroscience, experimental designs in which multiple measurements are collected in the same research object or treatment facility are common. Such designs result in clustered or nested data. When clusters include measurements from different experimental conditions, both the mean of the dependent variable and the effect of the experimental manipulation may vary over clusters. In practice, this type of cluster-related variation is often overlooked. Not accommodating cluster-related variation can result in inferential errors concerning the overall experimental effect. Results The exact effect of ignoring the clustered nature of the data depends on the effect of clustering. Using simulation studies we show that cluster-related variation in the experimental effect, if ignored, results in a false positive rate (i.e., Type I error rate) that is appreciably higher (up to ~20–~50 %) than the chosen α -level (e.g., α  = 0.05). If the effect of clustering is limited to the intercept, the failure to accommodate clustering can result in a loss of statistical power to detect the overall experimental effect. This effect is most pronounced when both the magnitude of the experimental effect and the sample size are small (e.g., ~25 % less power given an experimental effect with effect size d of 0.20, and a sample size of 10 clusters and 5 observations per experimental condition per cluster). Conclusions When data is collected from a research design in which observations from the same cluster are obtained in different experimental conditions, multilevel analysis should be used to analyze the data. The use of multilevel analysis not only ensures correct statistical interpretation of the overall experimental effect, but also provides a valuable test of the generalizability of the experimental effect over (intrinsically) varying settings, and a means to reveal the cause of cluster-related variation in experimental effect.

Web-based questionnaires are increasingly used in epidemiologic studies, as traditional methods are facing a decrease in response rates and an increase in costs. However, few studies have investigated factors related to the level of completion of internet-based epidemiologic questionnaires. Our objective was to identify person-level characteristics and item design factors associated with breakoff (not finishing the questionnaire) and item nonresponse in a Web-based questionnaire. This study was a cross-sectional analysis of the baseline questionnaire, applied from 2005 to 2016, of the Italian NINFEA (Nascita e Infanzia: gli Effetti dell'Ambiente) birth cohort. The baseline questionnaire was administered to enrolled women, who could register at any time during pregnancy. We used logistic regression to analyze the influence of person-level factors on questionnaire breakoff, and a logistic multilevel model (first level: items of the questionnaire; second level: sections of the questionnaire; third level: study participants) to analyze the influence of person-level and item design factors on item nonresponse. Since the number of applicable items depended on the respondent's characteristics and breakoff, we used inverse probability weighting to deal with missing by design. Of 5970 women, 519 (8.69%) did not finish the questionnaire. Older age (adjusted odds ratio 1.40, 95% CI 1.05-1.88), lower educational level (adjusted odds ratio [OR] 1.53, 95% CI 1.23-1.90), and earlier stage of pregnancy (adjusted OR 3.01, 95% CI 2.31-3.92) were positively associated with questionnaire breakoff. Of the 1,062,519 applicable items displayed for the participants, 22,831 were not responded to (overall prevalence of item nonresponse 2.15%). Item nonresponse was positively associated with older age (adjusted OR 1.25, 95% CI 1.14-1.38), being in the first trimester of pregnancy (adjusted OR 1.18, 95% CI 1.06-1.31), and lower educational level (adjusted OR 1.23, 95% CI 1.14-1.33). Dropdown menu items (adjusted OR 1.77, 95% CI 1.56-2.00) and items organized in grids (adjusted OR 1.69, 95% CI 1.49-1.91) were positively associated with item nonresponse. It is important to use targeted strategies to keep participants motivated to respond. Item nonresponse in internet-based questionnaires is affected by person-level and item design factors. Some item types should be limited to reduce item nonresponse.

Electrocorticography (ECoG) in humans yields data with unmatched spatio-temporal resolution that provides novel insights into cognitive operations. However, the broader application of ECoG has been confounded by difficulties in accurately depicting individual data and performing statistically valid population-level analyses. To overcome these limitations, we developed methods for accurately registering ECoG data to individual cortical topology. We integrated this technique with surface-based co-registration and a mixed-effects multilevel analysis (MEMA) to control for variable cortical surface anatomy and sparse coverage across patients, as well as intra- and inter-subject variability. We applied this surface-based MEMA (SB-MEMA) technique to a face-recognition task dataset (n=22). Compared against existing techniques, SB-MEMA yielded results much more consistent with individual data and with meta-analyses of face-specific activation studies. We anticipate that SB-MEMA will greatly expand the role of ECoG in studies of human cognition, and will enable the generation of population-level brain activity maps and accurate multimodal comparisons. •Accurate registration of ECoG data to individual cortical topology.•Statistically valid grouped ECoG analysis.•Methods enabling accurate multimodal comparisons between ECoG and fMRI

The objective of our study was to investigate differences in the management of men and women treated for hypertension while considering the gender of their physicians. We used the data from the cross-sectional Paris Prevention in General Practice survey, where 59 randomly recruited general practitioners (42 men and 19 women) from the Paris metropolitan area enroled every patient aged 25–79 years taking antihypertensive medication and seen during a 2-week period (520 men and 666 women) in 2005–6. The presence in the medical files of six items recommended for hypertension management (blood pressure measurement, smoking status, cholesterol, creatinine, fasting blood glucose and electrocardiogram) was analysed with mixed models with random intercepts and adjusted for patient and physician characteristics. We found that the presence of all items was lower in the records of female than male patients (3.9 vs. 6.9%, p = 0.01), as was the percentage of items present (58.5 vs. 64.2%, p = 0.003). The latter gender difference was substantially more marked when the physician was a man (69.3 vs. 63.4%, p = 0.0002) rather than a woman (63.5 vs. 61.0%, p = 0.46). Although all guidelines recommend the same management for both genders, the practices of male physicians in hypertension management appear to differ according to patient gender although those of women doctors do not. Male physicians must be made aware of how their gender influences their practices.

Social exclusion is increasingly considered to be a multi‐faceted concept involving more than simply material disadvantage among older people. The process of social exclusion may be driven by various factors and at different levels, including individual, household, group, community, country and global levels. Using data from the 2014 China Longitudinal Aging Social Survey focusing on respondents aged over 60, we employed multivariate multilevel models to simultaneously estimate four dimensions of social exclusion among older people. The results show that the social exclusion of older people varies not only among individuals but also among provinces. From an individual perspective, older people with lower educational attainment (often illiterate), in the lowest quintile of personal income and in poor health were the most likely to be excluded. From a geographical perspective, although there are no province‐level characteristics (social, economic and social security development) significantly related to the four dimensions of social exclusion, there is nevertheless significant unexplained variation for all dimensions of social exclusion at the province level. The negative relationships between exclusion from social relationships and exclusion from financial products, between subjective feeling of exclusion and social activities, and between subjective feeling of exclusion and exclusion from financial products at the provincial level indicate that a province may do well on one dimension of social exclusion but it will not automatically do well on the other dimensions. This study explored social exclusion of older people from individual and geographic perspectives simultaneously and depict the experience of disadvantage that older people living in different area via different form of social exclusion. From the individual perspective, older people with lower educational attainment (often illiterate), in the lowest quintile of personal income and in poor health condition, were the most likely to be excluded. From a geographical perspective, there are negative relationships between exclusion from social relationships and exclusion from financial products, between subjective feeling of exclusion and social activities, and between subjective feeling of exclusion and exclusion from financial products at the provincial level indicate that a province may do well on one dimension of social exclusion, but it will not automatically do well on the other dimensions.