Data cleaning for clinician researchers: Application and explanation of a data-quality framework

BACKGROUND

Data cleaning is the series of procedures performed before a formal statistical analysis, with the aim of reducing the number of error values in a dataset and improving the overall quality of subsequent analyses. Several study-reporting guidelines recommend the inclusion of data-cleaning procedures; however, little practical guidance exists for how to conduct these procedures.

OBJECTIVES

This paper aimed to provide practical guidance for how to perform and report rigorous data-cleaning procedures.

METHODS

A previously proposed data-quality framework was identified and used to facilitate the description and explanation of data-cleaning procedures. The broader data-cleaning process was broken down into discrete tasks to create a data-cleaning checklist. Examples of the how the various tasks had been undertaken for a previous study using data from the Australia and New Zealand Intensive Care Society Adult Patient Database were also provided.

RESULTS

Data-cleaning tasks were described and grouped according to four data-quality domains described in the framework: data integrity, consistency, completeness, and accuracy. Tasks described include creation of a data dictionary, checking consistency of values across multiple variables, quantifying and managing missing data, and the identification and management of outlier values. The data-cleaning task checklist provides a practical summary of the various aspects of the data-cleaning process and will assist clinician researchers in performing this process in the future.

CONCLUSIONS

Data cleaning is an integral part of any statistical analysis and helps ensure that study results are valid and reproducible. Use of the data-cleaning task checklist will facilitate the conduct of rigorous data-cleaning processes, with the aim of improving the quality of future research.

What does the MAIHDA method explain?

Multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) is a new approach to quantitative intersectional modelling. Along with an outcome of interest, MAIHDA entails the use of two sets of independent variables. These include group demographics such as race, gender, and poverty status as well as strata which are constructs such as Black female poor, Black female wealthy, and White female poor. These constructs represent the combination of the demographic variables. To operationalize the approach, an initial random intercepts model with strata as a level 2 context is specified. Then, another model is specified that includes the strata as well as the demographic variables as level 1 fixed effects. As such, it is argued that MAIHDA uniquely identifies the additive and intersectional effects for any given outcome. In this paper we show that MAIHDA falls short of this promise: the strata are an individual-level composite variable not a level 2 context. Rather than being analogous to neighborhoods as contexts, strata are analogous to socio-economic status which is a combination of individual-level demographic variables, albeit often presented as a group-level characteristic. The result is that the demographic variables are inserted in both level 2 and 1. This duplication across the levels in MAIHDA means that there is a built-in collinearity across the levels and that the models are mis-specified and, therefore, redundant. We conclude that single-level models with the demographic variables and interactions or with the strata as fixed effects are still the more accurate models for quantitative intersectional analyses.

Validity evidence and psychometric evaluation of a socially accountable health index for health professions schools

There is an expectation that health professions schools respond to priority societal health needs. This expectation is largely based on the underlying assumption that schools are aware of the priority needs in their communities. This paper demonstrates how open-access, pan-national health data can be used to create a reliable health index to assist schools in identifying societal needs and advance social accountability in health professions education. Using open-access data, a psychometric evaluation was conducted to examine the reliability and validity of the Canadian Health Indicators Framework (CHIF) conceptual model. A non-linear confirmatory factor analysis (CFA) on 67 health indicators, at the health-region level (n = 97) was used to assess the model fit of the hypothesized 10-factor model. Reliability analysis using McDonald's Omega were conducted, followed by Pearson's correlation coefficients. Findings from the non-linear CFA rejected the original conceptual model structure of the CHIF. Exploratory post hoc analyses were conducted using modification indices and parameter constraints to improve model fit. A final 5-factor multidimensional model demonstrated superior fit, reducing the number of indicators from 67 to 32. The 5-factors included: Health Conditions (8-indicators); Health Functions (6-indicators); Deaths (5-indicators); Non-Medical Health Determinants (7-indicators); and Community & Health System Characteristics (6-indicators). All factor loadings were statistically significant (p < 0.001) and demonstrated excellent internal consistency ( ω >0.95). Many schools struggle to identify and measure socially accountable outcomes. The process highlighted in this paper and the indices developed serve as starting points to allow schools to leverage open-access data as an initial step in identifying societal needs.

First-year nursing students' perceptions of health activism and social responsibility - A cross sectional study

BACKGROUND

Social responsibility and health activism both represent key concepts and professional values in nursing practice. Nevertheless, definitions in the nursing literature remain inconsistent, and little is known regarding nursing students' perceptions of these concepts or about the associations between these perceptions.

OBJECTIVES

This research explores: a) the associations between nursing students' perceptions of social responsibility and health activism; and b) the differences in nursing students' perceptions of social responsibility and health activism according to their personal characteristics.

DESIGN AND METHODS

Across-sectional survey design was conducted with a sample of 173 Israeli first-year undergraduate nursing students. Questions were uploaded in the format provided by a commercial Internet survey provider (Qualtrics.com) and distributed through social media groups.

RESULTS

Positive correlations were found between health activism and social responsibility and between health activism and philanthropic and environmental responsibility. Significant differences were found in the research variables according to the students' cultural group and voluntary service. Cultural group and social responsibility explained 25 % of students' variance in health activism.

CONCLUSIONS

Faculty and nurse educators should promote and develop nursing students' knowledge acquisition in health activism and social responsibility throughout all their years of study. It is recommended that nursing students be given meaningful opportunities to discuss, integrate, and apply health activism, guided by role models in clinical practice. Academic settings should also promote the value of social responsibility and support nursing students in taking active roles in social organizations in order to further develop and integrate the social component of their professional role.

A novel method for determining viable bacteria from a mixture of dead and viable bacteria: Delayed real-time PCR (DR-PCR) method

Aspiration pneumonia can occur in perioperative and older patients, and various oral care methods have been used to prevent it. To validate the effective oral care methods, measuring bacterial counts before and after oral care is necessary. However, isolating and quantifying viable bacteria from those that are inactivated by agents used in oral care is not possible. In this study, we developed a novel method, Delayed real-time PCR (DR-PCR), that can quantify only viable bacteria from mixed samples of viable and dead bacteria. This method takes advantage of the fact that dead bacteria do not grow but viable bacteria do. When the samples were incubated in a liquid medium for 4 hours, the higher the percentage of viable bacteria, the higher the rate of increase in the number of bacteria. This method showed that povidone‑iodine mouthwashing reduced the number of viable bacteria to approximately 1/4 of that before mouthwashing. Although DR-PCR is slightly more time consuming than real-time PCR, it is effective for studying changes in bacterial counts before and after oral care.

Computer-assisted evaluation of small airway disease in CT scans of Iran-Iraq war victims of chemical warfare by a locally developed software: comparison between different quantitative methods

OBJECTIVE

Diagnosis of small airway disease on computed tomography (CT) scans is challenging in patients with a history of chemical warfare exposure. We developed a software package based on different methodologies to identify and quantify small airway disease in CT images. The primary aim was to identify the best automatic methodology for detecting small airway disease in CT scans of Iran-Iraq War victims of chemical warfare.

METHODS

This retrospective case-control study enrolled 46 patients with a history of chemical warfare exposure and 27 controls with inspiratory/expiratory (I/E) CT scans and spirometry tests. Image data were automatically segmented, and inspiratory images were registered into the expiratory images' frame using the locally developed software. Parametric response mapping (PRM) and air trapping index (ATI) mapping were performed on the CT images. Conventional QCT methods, including expiratory/inspiratory mean lung attenuation (E/I MLA) ratio, normal density E/I (ND E/I) MLA ratio, attenuation volume Index (AVI), %low attenuation areas (LAA) < -856 in exhale scans, and %LAA < -950 in inhale scans were also computed. QCT measurements were correlated with spirometry results and compared across the two study groups.

RESULTS

The correlation analysis showed a significant negative relationship between three air trapping (AT) measurements (PRM, ATI, and %LAAExp < -856) and spirometry parameters (Fev1, Fvc, Fev1/Fvc, and MMEF). Moreover, %LAAExp < -856 had the highest significant negative correlation with Fev1/Fvc (r = -0.643, P-value < 0.001). Three AT measurements demonstrated a significant difference between the study groups. The E/I ratio was also significantly different between the two groups (P-value < 0.001). Binary logistic regression models showed PRMFsad, %LAAExp < -856, and ATI as significant and strong predictors of the study outcome. Optimal cut-points for PRMFsad = 19%, %LAAExp < -856 = 23%, and ATI = 27% were identified to classify the participants into two groups with high accuracy.

CONCLUSION

QCT methods, including PRM, ATI, and %LAAExp < -856 can greatly advance the identification and quantification of SAD in chemical warfare victims. The results should be verified in well-designed prospective studies involving a large population.

Association between antenatal care facility readiness and provision of care at the client level and facility level in five low- and middle-income countries

BACKGROUND

Despite growing interest in monitoring improvements in quality of care, data on service quality in low-income and middle-income countries (LMICs) is limited. While health systems researchers have hypothesized the relationship between facility readiness and provision of care, there have been few attempts to quantify this relationship in LMICs. This study assesses the association between facility readiness and provision of care for antenatal care at the client level and facility level.

METHODS

To assess the association between provision of care and various facility readiness indices for antenatal care, we used multilevel, multivariable random-effects linear regression models. We tested an inflection point on readiness scores by fitting linear spline models. To compare the coefficients between models, we used a bootstrapping approach and calculated the mean difference between all pairwise comparisons. Analyses were conducted at client and facility levels.

RESULTS

Our results showed a small, but significant association between facility readiness and provision of care across countries and most index constructions. The association was most evident in the client-level analyses that had a larger sample size and were adjusted for factors at the facility, health worker, and individual levels. In addition, spline models at a facility readiness score of 50 better fit the data, indicating a plausible threshold effect.

CONCLUSIONS

The results of this study suggest that facility readiness is not a proxy for provision of care, but that there is an important association between facility readiness and provision of care. Data on facility readiness is necessary for understanding the foundations of health systems particularly in countries with the lowest levels of service quality. However, a comprehensive view of quality of care should include both facility readiness and provision of care measures.

EEG Reveals Alterations in Motor Imagery in People With Amnestic Mild Cognitive Impairment

OBJECTIVES

Motor imagery has been used to investigate the cognitive mechanism of motor control. Although behavioral and electrophysiological changes in motor imagery in people with amnestic mild cognitive impairment (aMCI) have been reported, deficits in different types of imagery remain unclear. To explore this question, we used electroencephalography (EEG) to study neural correlates of visual imagery (VI) and kinesthetic imagery (KI) and their relationship to cognitive function in people with aMCI.

METHODS

A hand laterality judgment task was used to induce implicit motor imagery in 29 people with aMCI and 40 healthy controls during EEG recording. Mass univariate and multivariate EEG analysis was applied to explore group differences in a data-driven manner.

RESULTS

Modulation of stimuli orientation to event-related potential (ERP) amplitudes differed significantly between groups at 2 clusters located in the posterior-parietal and frontal areas. Multivariate decoding revealed sufficient representation of VI-related orientation features in both groups. Relative to healthy controls, the aMCI group lacked accurate representation of KI-related biomechanical features, suggesting deficits in automatic activation of KI strategy. Electrophysiological correlates were associated with episodic memory, visuospatial function, and executive function. Higher decoding accuracy of biomechanical features predicted better executive function via longer response time in the imagery task in the aMCI group.

DISCUSSION

These findings reveal electrophysiological correlates related to motor imagery deficits in aMCI, including local ERP amplitudes and large-scale activity patterns. Alterations in EEG activity are related to cognitive function in multiple domains, including episodic memory, suggesting the potential of these EEG indices as biomarkers of cognitive impairment.

Review of quantitative methods to assess impacts of changing climate and socioeconomic conditions on Arctic transportation systems

Rapid climate and socioeconomic changes are transforming Arctic human-earth systems. An integral part of these systems is mobility, which encompasses the transport of humans and goods into, out of, and between Arctic regions. Impacts of climate and socioeconomic drivers on Arctic mobility are heterogenous. Methodologies are needed to quantify these impacts in measures that can be linked with broader socioeconomic systems. This article reviews existing methods and organizes them into a conceptual framework to understand trends and gaps in the literature. We found methods quantifying impacts of a range of climate drivers on most transportation modes present in the Arctic, but few methods focused on socioeconomic drivers. In addition, underrepresented were methods explicitly considering adaptive capacity of transportation systems. We provide insight into the data and relationships relevant to understanding impacts of Arctic change on transportation systems, laying a foundation for future work that investigates how these impacts fit into broader human-arth systems.

Dynamical biomarkers in teams and other multiagent systems

Effective team behavior in high-performance environments such as in sport and the military requires individual team members to efficiently perceive the unfolding task events, predict the actions and action intents of the other team members, and plan and execute their own actions to simultaneously accomplish individual and collective goals. To enhance team performance through effective cooperation, it is crucial to measure the situation awareness and dynamics of each team member and how they collectively impact the team's functioning. Further, to be practically useful for real-life settings, such measures must be easily obtainable from existing sensors. This paper presents several methodologies that can be used on positional and movement acceleration data of team members to quantify and/or predict team performance, assess situation awareness, and to help identify task-relevant information to support individual decision-making. Given the limited reporting of these methods within military cohorts, these methodologies are described using examples from team sports and teams training in virtual environments, with discussion as to how they can be applied to real-world military teams.

An analysis of student numbers per class and educational performance in the Brazilian context

The relationship between class size and school performance has always been ambiguous and the current literature has found no direct connection between them, especially in the Brazilian context. Therefore, this study aimed to verify whether the number of students per class influences school performance. We used Microdata from the Prova Brazil of 2017. Using the propensity score matching statistical model, with the nearest neighbor matching estimator, we grouped the classes into clusters by similarity. The metric used to group the clusters was the Euclidean distance. We attempted to verify adherence to the normal distribution of data using the Kolmogorov Smirnov test and tested the null hypothesis of the medians using the Wilcoxon test. All the statistical analysis were performed using SPSS Statistic version 20. The results showed that the number of students per class has little influence on performance and, when the influence exists, larger classes perform better.

The relationship between buy-in and implementation: Measuring teacher buy-in to a high school reform effort

'Buy-in,' or the extent to which individuals believe in and actively support interventions, is an important but understudied component of program evaluation. This paper articulates a conceptual framework and describes survey scales for measuring buy-in. The paper applies the framework and survey to a program evaluation of an effort implementing the early college model in 16 high schools. The paper empirically connects teacher buy-in to perceptions of program implementation. In our main regression analysis, we found a significant relationship between teacher buy-in and model implementation. Through a dominance analysis, we also found that items related to collective buy-in were stronger predictors of implementation than items measuring individual buy-in. Our results suggest that it is important to measure both individual and collective buy-in because both are predictive of implementation. The survey items and framework presented could be of use to evaluators through modification for use in implementation studies of other program evaluations.

Child-therapist interaction features impact Autism treatment response trajectories

BACKGROUND

Identifying mechanisms of change in Autism treatment may help explain response variability and maximize efficacy. For this, the child-therapist interaction could have a key role as stressed by developmental models of intervention, but still remains under-investigated.

AIMS

The longitudinal study of treatment response trajectories considering both baseline and child-therapist interaction features by means of predictive modeling.

METHODS AND PROCEDURES

N = 25 preschool children were monitored for one year during Naturalistic Developmental Behavioral Intervention. N = 100 video-recorded sessions were annotated with an observational coding system at four time points, to extract quantitative interaction features.

OUTCOMES AND RESULTS

Baseline and interaction variables were combined to predict response trajectories at one year, and achieved the best predictive performance. The baseline developmental gap, therapist's efficacy in child engagement, respecting children's timing after fast behavioral synchronization, and modulating the interplay to prevent child withdrawal emerged as key factors. Further, changes in interaction patterns in the early phase of the intervention were predictive of the overall response to treatment.

CONCLUSIONS AND IMPLICATIONS

Clinical implications are discussed, stressing the importance of promoting emotional self-regulation during intervention and the possible relevance of the first period of intervention for later response.

Theoretical mediators of GlobalConsent: An adapted web-based sexual violence prevention program for university men in Vietnam

Sexual violence remains a global problem that disproportionately affects women. Though sexual violence interventions exist, few have been implemented in low- or middle-income countries, and none in Vietnam for young men. We adapted a sexual violence prevention intervention (RealConsent) developed for college men in the U.S. and conducted a randomized controlled trial of the adapted intervention (GlobalConsent) with college men in Vietnam. We assessed the effects of GlobalConsent on sexually violent behavior and prosocial bystander behavior, directly and through theoretically targeted mediators. The study design entailed a double-blind, parallel intervention-control-group design in two universities. Consenting heterosexual or bisexual men 18-24 years starting university in September 2019 (n = 793) completed a baseline survey and were assigned with 1:1 randomization to GlobalConsent or attention control. Both programs were web-based and lasted 12 weeks. Path analysis was performed to study the mediating effects of cognition/knowledge, beliefs/attitudes, affect, and efficacy/intention variables measured at six months on sexually violent behavior and prosocial bystander behavior measured at 12 months. In parallel multiple-mediator models, initiating GlobalConsent lowered the odds of sexually violent behavior mainly indirectly, via knowledge of sexual violence legality and harm and victim empathy and increased the odds of prosocial bystander behavior directly and indirectly, through knowledge of sexual violence legality and harm and bystander capacities. The efficacious direct and indirect effects of GlobalConsent support the cross-cultural applicability of its underlying theory of change and findings from mediation analyses of its sister program RealConsent, suggesting GlobalConsent's national scalability and adaptability across Southeast Asia.

Do Journals Have Preferences? Insights from The Journal of Higher Education

Using five years of publishing data from the Journal of Higher Education, we describe the publication pipeline at the journal, explore trends with respect to topic, the geographic distribution of authors, and each paper's methodological approach. Following the presentation of these trends, we discuss implications for the field of higher education and those publishing within it.

Item response theory in high-stakes pharmacy assessments

OUR SITUATION

Classical test theory (CTT) and item response theory (IRT) are two measurement models used to evaluate results from examinations, questionnaires, and instruments. To illustrate the benefits of IRT, we compared how results from multiple-choice tests can be interpreted using CTT and IRT.

METHODOLOGICAL LITERATURE REVIEW

IRT encompasses a collection of statistical models that estimate the probability of providing a correct response for a test item. The models are non-linear and generate item characteristic curves that illustrate the relationship between the examinee's ability level and whether they answered the item correctly. Several models can be used to estimate parameters such as item difficulty, discrimination, and guessing. In addition, IRT can generate item and test information functions to illustrate the accuracy of ability estimates.

OUR RECOMMENDATIONS AND THEIR APPLICATIONS

Researchers interested in IRT should gather the necessary resources early in the research process and collaborate with those experienced in quantitative and advanced statistical models. Researchers should confirm IRT is the optimal choice and select the model ideal for their needs. Once data are acquired, confirm model assumptions are met and model fit is appropriate. Lastly, researchers should consider disseminating the findings with accompanying visuals.

POTENTIAL IMPACT

IRT can be a valuable approach in assessment design and evaluation. Potential opportunities include supporting the design of computer adaptive tests, creating equivalent test forms that evaluate a range of examinee abilities, and evaluating whether items perform differently for examinee sub-groups. Further, IRT can have noteworthy visuals such as test information and functions.

Dosing interval strategies for two-dose COVID-19 vaccination in 13 middle-income countries of Europe: Health impact modelling and benefit-risk analysis

Background

In settings where the COVID-19 vaccine supply is constrained, extending the intervals between the first and second doses of the COVID-19 vaccine may allow more people receive their first doses earlier. Our aim is to estimate the health impact of COVID-19 vaccination alongside benefit-risk assessment of different dosing intervals in 13 middle-income countries (MICs) of Europe.

Methods

We fitted a dynamic transmission model to country-level daily reported COVID-19 mortality in 13 MICs in Europe (Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Georgia, Republic of Moldova, Russian Federation, Serbia, North Macedonia, Turkey, and Ukraine). A vaccine product with characteristics similar to those of the Oxford/AstraZeneca COVID-19 (AZD1222) vaccine was used in the base case scenario and was complemented by sensitivity analyses around efficacies similar to other COVID-19 vaccines. Both fixed dosing intervals at 4, 8, 12, 16, and 20 weeks and dose-specific intervals that prioritise specific doses for certain age groups were tested. Optimal intervals minimise COVID-19 mortality between March 2021 and December 2022. We incorporated the emergence of variants of concern (VOCs) into the model and conducted a benefit-risk assessment to quantify the tradeoff between health benefits versus adverse events following immunisation.

Findings

In all countries modelled, optimal strategies are those that prioritise the first doses among older adults (60+ years) or adults (20+ years), which lead to dosing intervals longer than six months. In comparison, a four-week fixed dosing interval may incur 10.1% [range: 4.3% - 19.0%; n = 13 (countries)] more deaths. The rapid waning of the immunity induced by the first dose (i.e. with means ranging 60-120 days as opposed to 360 days in the base case) resulted in shorter optimal dosing intervals of 8-20 weeks. Benefit-risk ratios were the highest for fixed dosing intervals of 8-12 weeks.

Interpretation

We infer that longer dosing intervals of over six months could reduce COVID-19 mortality in MICs of Europe. Certain parameters, such as rapid waning of first-dose induced immunity and increased immune escape through the emergence of VOCs, could significantly shorten the optimal dosing intervals.

Funding

World Health Organization.

Considering sex and gender in Epidemiology: a challenge beyond terminology. From conceptual analysis to methodological strategies

Background

Epidemiologists need tools to measure effects of gender, a complex concept originating in the social sciences which is not easily operationalized in the discipline. Our aim is to clarify useful concepts, measures, paths, effects, and analytical strategies to explore mechanisms of health difference between men and women.

Methods

We reviewed concepts to clarify their definitions and limitations for their translation into usable measures in Epidemiology. Then we conducted methodological research using a causal framework to propose methodologically appropriate strategies for measuring sex and gender effects in health.

Results

(1) Concepts and measures. We define gender as a set of norms prescribed to individuals according to their attributed-at-birth sex. Gender pressure creates a systemic gap, at population level, in behaviors, activities, experiences, etc., between men and women. A pragmatic individual measure of gender would correspond to the level at which an individual complies with a set of elements constituting femininity or masculinity in a given population, place and time. (2) Main analytical strategy. Defining and measuring gender are not sufficient to distinguish the effects of sex and gender on a health outcome. We should also think in terms of mechanisms, i.e., how the variables are linked together, to define appropriate analytical strategies. A causal framework can help us to conceptualize “sex” as a “parent” of a gender or gendered variable. This implies that we cannot interpret sex effects as sexed mechanisms, and that we can explore gendered mechanisms of sex-differences by mediation analyses. (3) Alternative strategy. Gender could also be directly examined as a mechanism, rather than through a variable representing its realization in the individual, by approaching it as an interaction between sex and social environment.

Conclusions

Both analytical strategies have limitations relative to the impossibility of reducing a complex concept to a single or a few measures, and of capturing the entire effect of the phenomenon of gender. However, these strategies could lead to more accurate analyses of the mechanisms underlying health differences between men and women.

A pragmatic individual measure of individual gender would correspond to the level at which an individual complies with a set of elements constituting femininity or masculinity in a given population, place and time

Comparing outcomes by sex and gender is not sufficient, and even misleading, to understand the mechanisms underlying biological and health differences between men and women

Causal analysis framework is a powerful tool for refining hypotheses and identifying the effects that can and should be estimated to meet the objectives

Gender could also be measured at the populational-level as an interaction between sex and environment, which would be more compatible with the sociological concept of gender

Associations between admissions factors and the need for remediation

This study examines the way in which student characteristics and pre-admissions measures are statistically associated with the likelihood a student will require remediation for academic and professionalism offenses. We anchor our inquiry within Irby and Hamstra's (2016) conceptual framework of constructs of professionalism. Data from five graduating cohorts (2014-2018) from McMaster University (Hamilton, Canada) (N = 1,021) were retroactively collected and analyzed using traditional and multinominal logistic regression analyses. The relationship among student characteristics, pre-admissions variables, and referral for potential remediation both by occurrence (yes/no) as well as type (academic/professional/no referral) were examined separately. Findings indicate that gender (OR = 0.519, 95% CI 0.326-0.827, p < 0.01) and undergraduate grade point average (GPA) (OR = 0.245, 95% CI 0.070-0.855, p < 0.05) were significantly associated with instances of referral for potential professionalism and academic remediation, respectively. Women were less likely than men to require remediation for professionalism (OR = 0.332, 95% CI 0.174-0.602, p < 0.001). Undergraduate GPAs (OR = 0.826, 95% CI 0.021-0.539, p < 0.01) were significantly associated with remediation for academic reasons. Lower undergraduate GPAs were associated with a higher likelihood of remediation. These findings point to the admissions variables that are associated with instances that prompt referral for potential remediation. Where associations are not significant, we consider the application of different conceptualizations of professionalism across periods of admissions and training. We encourage those involved in applicant selection and student remediation to emphasize the importance of the interactions that occur between personal and contextual factors to influence learner behaviour and professional identity formation.

Development of the ASSESS tool: a comprehenSive tool to Support rEporting and critical appraiSal of qualitative, quantitative, and mixed methods implementation reSearch outcomes

Background

Several tools to improve reporting of implementation studies for evidence-based decision making have been created; however, no tool for critical appraisal of implementation outcomes exists. Researchers, practitioners, and policy makers lack tools to support the concurrent synthesis and critical assessment of outcomes for implementation research. Our objectives were to develop a comprehensive tool to (1) describe studies focused on implementation that use qualitative, quantitative, and/or mixed methodologies and (2) assess risk of bias of implementation outcomes.

Methods

A hybrid consensus-building approach combining Delphi Group and Nominal Group techniques (NGT) was modeled after comparative methodologies for developing health research reporting guidelines and critical appraisal tools. First, an online modified NGT occurred among a small expert panel (n = 5), consisting of literature review, item generation, round robin with clarification, application of the tool to various study types, voting, and discussion. This was followed by a larger e-consensus meeting and modified Delphi process with implementers and implementation scientists (n = 32). New elements and elements of various existing tools, frameworks, and taxonomies were combined to produce the ASSESS tool.

Results

The 24-item tool is applicable to a broad range of study designs employed in implementation science, including qualitative studies, randomized-control trials, non-randomized quantitative studies, and mixed methods studies. Two key features are a section for assessing bias of the implementation outcomes and sections for describing the implementation strategy and intervention implemented. An accompanying explanation and elaboration document that identifies and describes each of the items, explains the rationale, and provides examples of reporting and appraising practice, as well as templates to allow synthesis of extracted data across studies and an instructional video, has been prepared.

Conclusions

The comprehensive, adaptable tool to support both reporting and critical appraisal of implementation science studies including quantitative, qualitative, and mixed methods assessment of intervention and implementation outcomes has been developed. This tool can be applied to a methodologically diverse and growing body of implementation science literature to support reviews or meta-analyses that inform evidence-based decision-making regarding processes and strategies for implementation.

Dynamic change meets mechanisms of change: Examining mediators in the latent change score framework

Researchers in behavioral sciences are often interested in longitudinal behavior change outcomes and the mechanisms that influence changes in these outcomes over time. The statistical models that are typically implemented to address these research questions do not allow for investigation of mechanisms of dynamic change over time. However, latent change score models allow for dynamic change (not just linear or exponential change) over time and have flexibility in parameter constraints that other longitudinal models do not have. Developmental researchers also frequently utilize mediation analyses to investigate mechanisms of influence in longitudinal research implemented in path analytic or latent growth curve models. In this article, we provide three examples of how mediation can be tested in the latent change score framework by combining aspects of traditional mediation models with latent change score models of repeated measures outcomes (and mediators and predictors) with more than two timepoints. We also provide the Mplus syntax to complete these analyses and practical considerations of latent change score mediation (LCSM) models.

Consistent Divisions or Methodological Decisions? Assessing the U.S. Racial Hierarchy Across Outcomes

Scholars have offered a range of perspectives on the twenty-first century racial landscape with little consensus about either the current state of the U.S. racial hierarchy or its future trajectory. We offer a more comprehensive assessment, using data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to study racial stratification across a number of socioeconomic outcomes. We pay particular attention to the robustness of results across different categorization schemes that account for self-identification and interviewer classification, as well as racial fluidity. Although we observe that White and Asian Americans generally have the best socioeconomic outcomes, on average, while Black Americans and American Indians have the worst, we also find meaningful differences in patterns of stratification both across outcomes and depending on how race is operationalized. These differences in stratification are reflected in the estimated number of strata as well as the rank order of racial categories. Our results suggest that ongoing debates about the nature of the U.S. racial hierarchy can be partly explained by methodological decisions about which outcomes to study and how best to measure race.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12552-021-09351-2.

Quantitative methods for predicting underground construction waste considering reuse and recycling

The construction industry has been greatly developed in the past few decades, especially in the extensive use of underground space. The increasing amount of waste (e.g., soil, sludge, and rock) generated in the underground construction constitutes an important part of construction and demolition waste (CDW), but the related problems are rarely addressed in an independent quantitative study. In order to facilitate recycling of underground construction waste (UCW), quantitative methods for predicting UCW are proposed based on mass conservation in this study. Through on-site investigation and literature review, the source characteristics of UCW and corresponding recycling potential are firstly analyzed. Secondly, the corresponding quantitative method is proposed for predicting each type of UCW according to the principle of mass conservation. Finally, the proposed quantitative methods are applied in two real underground infrastructure projects to verify the accuracy. The results show that the accuracy of quantitative methods for predicting shield sludge and engineering soil is 82.03-95.79% and 94.49% respectively. The quantitative methods for predicting the amount of UCW proposed in this study is effective. In both cases, underground construction produced a large amount of construction waste with great recycling potential. UCW can theoretically reach 100% recycling, and full reuse and recycling of UCW will bring huge benefits and be conducive to the sustainable development of the construction industry.

Emergency department presentations in the first weeks following release from prison among men with a history of injecting drug use in Victoria, Australia: A prospective cohort study

OBJECTIVE

Rates of emergency department (ED) use are higher among people released from prison than in the general population. However, little is known about ED presentations specifically among people with a history of injecting drug use (IDU) leaving prison. We measured the incidence of ED presentation in the three months following release from prison, among a cohort of men with histories of IDU, and determined pre-release characteristics associated with presenting to an ED during this period.

METHODS

We analysed linked survey and administrative data from the Prison and Transition Health (PATH) study (N = 400) using multiple-failure survival analysis.

RESULTS

Twenty-one percent (n = 81/393) of the cohort presented to an ED at least once within the three months after release from prison. The incidence of ED presentation was highest in the first six days after release. Cox proportional hazards modelling showed that a history of in-patient psychiatric admission and housing instability were associated with increased hazard of an ED presentation, and identifying as Aboriginal and Torres Strait Islander was associated with decreased hazard.

CONCLUSIONS

In our study, ED presentations following release from prison among people with a history of IDU was linked to acute health risks related to known mental health and social vulnerabilities in this population. Greater collaboration and systems integration between prison and community health and support services is needed to reduce presentations to ED and associated morbidities among people with a history of IDU after release from prison.

Addressing the need for indigenous and decolonized quantitative research methods in Canada

Though qualitative methods are often an appropriate Indigenous methodology and have dominated the literature on Indigenous research methods, they are not the only methods available for health research. There is a need for decolonizing and Indigenizing quantitative research methods, particularly in the discipline of epidemiology, to better address the public health needs of Indigenous populations who continue to face health inequities because of colonial systems, as well as inaccurate and incomplete data collection about themselves. For the last two decades, researchers in colonized countries have been calling for a specifically Indigenous approach to epidemiology that recognizes the limits of Western epidemiological methods, incorporates more Indigenous research methodologies and community-based participatory research methods, builds capacity by training more Indigenous epidemiologists, and supports Indigenous self-determination. Indigenous epidemiology can include a variety of approaches, including: shifting standards, such as age standardization, according to Indigenous populations to give appropriate weight to their experiences; carefully setting recruitment targets and using appropriate recruitment methods to fulfill statistical standards for stratification; acting as a bridge between Indigenous and Western technoscientific perspectives; developing culturally appropriate data collection tools; and developing distinct epidemiological methods based on Indigenous knowledge systems. This paper explores how decolonization and Indigenization of epidemiology has been operationalized in recent Canadian studies and projects, including the First Nations Regional Longitudinal Health Survey and how this decolonization and Indigenization might be augmented with the capacity-building of the future Our Health Counts Applied Indigenous Epidemiology, Health Information, and Health Services and Program Evaluation Training and Mentorship Program in Canada.

Local government responses for COVID-19 management in the Philippines

BACKGROUND

Responses of subnational government units are crucial in the containment of the spread of pathogens in a country. To mitigate the impact of the COVID-19 pandemic, the Philippine national government through its Inter-Agency Task Force on Emerging Infectious Diseases outlined different quarantine measures wherein each level has a corresponding degree of rigidity from keeping only the essential businesses open to allowing all establishments to operate at a certain capacity. Other measures also involve prohibiting individuals at a certain age bracket from going outside of their homes. The local government units (LGUs)-municipalities and provinces-can adopt any of these measures depending on the extent of the pandemic in their locality. The purpose is to keep the number of infections and mortality at bay while minimizing the economic impact of the pandemic. Some LGUs have demonstrated a remarkable response to the COVID-19 pandemic. The purpose of this study is to identify notable non-pharmaceutical interventions of these outlying LGUs in the country using quantitative methods.

METHODS

Data were taken from public databases such as Philippine Department of Health, Philippine Statistics Authority Census, and Google Community Mobility Reports. These are normalized using Z-transform. For each locality, infection and mortality data (dataset Y) were compared to the economic, health, and demographic data (dataset X) using Euclidean metric d=(x-y)2, where x∈X and y∈Y. If a data pair (x,y) exceeds, by two standard deviations, the mean of the Euclidean metric values between the sets X and Y, the pair is assumed to be a 'good' outlier.

RESULTS

Our results showed that cluster of cities and provinces in Central Luzon (Region III), CALABARZON (Region IV-A), the National Capital Region (NCR), and Central Visayas (Region VII) are the 'good' outliers with respect to factors such as working population, population density, ICU beds, doctors on quarantine, number of frontliners and gross regional domestic product. Among metropolitan cities, Davao was a 'good' outlier with respect to demographic factors.

CONCLUSIONS

Strict border control, early implementation of lockdowns, establishment of quarantine facilities, effective communication to the public, and monitoring efforts were the defining factors that helped these LGUs curtail the harm that was brought by the pandemic. If these policies are to be standardized, it would help any country's preparedness for future health emergencies.

Multi-Level Multi-Growth Models: New opportunities for addressing developmental theory using advanced longitudinal designs with planned missingness

Longitudinal models have become increasingly popular in recent years because of their power to test theoretically derived hypotheses by modeling within-person processes with repeated measures. Growth models constitute a flexible framework for modeling a range of complex trajectories across time in outcomes of interest, including non-linearities and time-varying covariates. However, these models can be expanded to include the effects of multiple growth processes at once on a single outcome. Here, I outline such an extension, showing how multiple growth processes can be modeled as a specific case of the general ability to include time-varying covariates in growth models. I show that this extension of growth models cannot be accomplished by statistical models alone, and that study design plays a crucial role in allowing for proper parameter recovery. I demonstrate these principles through simulations to mimic important theoretical conditions where modeling the effects of multiple growth processes can address developmental theory including, disaggregating the effects of age and practice or treatment in repeated assessments and modeling age- and puberty-related effects during adolescence. I compare how these models behave in two common longitudinal designs, cohort and accelerated, and how planned missingness in observations is key to parameter recovery. I conclude with directions for future substantive research using the method outlined here.

The achilles heel of democracy? A macro cross-national assessment of the correlates of state legitimacy

This study investigates the macro-level correlates of subjective state legitimacy using a cross-national panel dataset of 82 countries from 1989 to 2014. It conducts the first comprehensive multivariate assessment of the effect of democracy, while also evaluating the effects of the nationalist principle of ethnic self-rule and state endogeneity (i.e. colonialism), net of controls. The findings suggest that-contrary to certain theories and earlier empirical studies-democracy has a strong and negative association with legitimacy, which is robust across different measures of democracy and model specifications. The results also provide some evidence that adhering to the nationalist principle is related to subjective state legitimacy, while suggesting that state endogeneity is not. Moreover, democracy is the strongest correlate of subjective state legitimacy whose effect becomes stronger-rather than weaker, as some predict-in the presence of controls. Preliminary analyses provide some support to the claim that the freedom of expression contributes to the negative democracy/state legitimacy relationship.

Care in times of COVID-19: the impact of the pandemic on informal caregiving in Austria

Much attention has been paid to the effects of the COVID-19 pandemic on long-term care but the impact on informal caregivers has remained speculative. In Austria, like in other European countries, informal care is carried out overwhelmingly by (non-cohabiting) relatives. Limited care services available during the pandemic, social-distancing, increased unemployment and competing care needs within households (e.g. due to school closures) may have changed the prevalence and intensity of informal caregiving. Moreover, these changes may have increased the psychological strain experienced by caregivers. Focusing on Austria, this study aims to empirically analyse the following research questions: how have the prevalence and intensity of informal care changed due to the pandemic? How has the psychological well-being of informal caregivers been affected? We use a pre- and post-onset of the pandemic research design based on a representative survey carried out in Austria in June 2020 (N = 2000) in combination with comparable 2015 data from the European Social Survey. Findings suggest that neither prevalence nor intensity of informal care changed significantly due to the pandemic. However, the psychological well-being gap between carers and non-carers increased with the start of the pandemic, especially among men. Findings are discussed in relation to the policy measures implemented and possible policy implications for the future.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10433-021-00611-z.

Beyond the p-value: Bayesian Statistics and Causation

Statistical paradigms limit the perspective and tools social work researchers use to study the world and answer questions impacting people and policy. Currently, quantitative social work researchers overwhelmingly rely on the frequentist paradigm of statistics. This paper discusses foundational differences between the frequentist and Bayesian statistical paradigms, describes basic concepts of Bayesian analysis, compares Bayesian and frequentist statistical analysis for a sample social work problem, and introduces two types of causal analyses built on Bayesian statistical thinking: counterfactual causality, and causality based on work by computer scientist Judea Pearl. Implications for social work research are discussed.

Pilot Study of Quantitative Methods for Differentiating Pharyngeal Swallowing Mechanics by Dysphagia Etiology

Quantitative analysis of modified barium swallow (MBS) imaging is useful to determine the impact of various disease states on pharyngeal swallowing mechanics. In this retrospective proof of concept study, kinematic analysis and computational analysis of swallowing mechanics (CASM) were used to demonstrate how these methods differentiate swallowing dysfunction by dysphagia etiology. Ten subjects were randomly selected from four cohorts of dysphagic patients including COPD, head and neck cancer (HNC), motor neuron disease, and stroke. Each subject was age- and gender-matched with healthy, non-dysphagic controls. MBS videos of 5 ml thin and 5 ml thick bolus trials from each subject were used. A MATLAB tracker tool was adapted and updated to collect and compile data for each video (n = 160). For kinematic measurements, a MANOVA was performed with post-hoc analyses to determine group differences. For CASM measurements, a morphometric canonical variate analysis with post hoc analysis was performed to determine group differences. Kinematic analyses indicated statistically significant differences between HNC cohort and controls in distance measurements for hyolaryngeal approximation (p = .001), laryngeal elevation (p = 0.0001), pharyngeal shortening (p = 0.0002), and stage transition duration timing (p = 0.002). Timing differences were noted between the stroke cohort and controls for pharyngeal transit time (p = 0.007). Multivariate morphometric canonical variate analysis showed significant differences between etiology groups (p < 0.0001) with eigenvectors indicating differing patterns of swallowing mechanics. This study demonstrated that swallowing mechanics among cohorts of dysphagic patients can be differentiated using kinematics and CASM, providing different but complementary quantitative methods for investigating the impact of various disease states on swallowing function.

Associations Between Control Beliefs and Response Time Inconsistency in Older Adults Vary as a Function of Attentional Task Demands

OBJECTIVE

Control beliefs are established correlates of cognitive aging. Despite recent demonstrations that response time inconsistency (RTI) represents a proxy for cognitive processing efficiency, few investigations have explored links between RTI and psychosocial correlates. We examined associations among RTI and control beliefs (perceived competence and locus of control) for two choice-response time (RT) tasks varying in their attentional demands.

METHOD

Control beliefs and RTI were measured weekly for 5 weeks in a sample of 304 community-dwelling older adults (Mage = 74.11 years, SD = 6.05, range = 64-92, 68.58% female).

RESULTS

Multilevel models revealed that for the attentionally demanding task, reporting higher perceived competence than usual was associated with lower RTI for relatively younger participants and greater RTI for relatively older participants. For the less attentionally demanding task, reporting higher perceived competence than usual was associated with lower RTI for relatively older participants. Links between locus of control and RTI were comparatively scant.

DISCUSSION

Our findings suggest that control beliefs may have adaptive and maladaptive influences on RTI, depending on dimension of control beliefs, individual differences in level of control beliefs and age, as well as attentional task demands. Both for whom and when control beliefs can be leveraged to optimize cognitive aging are discussed.

Hallucinations and Delusions Signal Alzheimer's Associated Cognitive Dysfunction More Strongly Compared to Other Neuropsychiatric Symptoms

OBJECTIVES

Neuropsychiatric symptoms (NPS) are common among individuals with dementia of the Alzheimer's type (DAT). We sought to characterize which NPS more purely relate to cognitive dysfunction in DAT, relative to other NPS.

METHOD

Demographic, neurocognitive, neuroimaging, and NPS data were mined from the Alzheimer's Disease Neuroimaging Initiative database (n = 906). Using factor analysis, we analyzed the degree to which individual NPS were associated with DAT-associated cognitive dysfunction. We also employed item response theory to graphically depict the ability of individual NPS to index DAT-associated cognitive dysfunction across a continuum ranging from cognitively normal to mild DAT.

RESULTS

Psychotic symptoms (hallucinations and delusions) were more strongly related to the continuum of DAT-associated cognitive dysfunction than other NPS, with the strength of the relationship peaking at high levels of disease severity. Psychotic symptoms also negatively correlated with brain volume and did not relate to the presence of vision problems. Aberrant motor behavior and apathy had relatively smaller associations with DAT-associated cognitive dysfunction, while other NPS showed minimal associations.

DISCUSSION

Psychotic symptoms most strongly indexed DAT-associated cognitive dysfunction, whereas other NPS, such as depression and anxiety, were not as precisely related to the DAT-associated cognitive dysfunction.

Intersectionality in quantitative health disparities research: A systematic review of challenges and limitations in empirical studies

RATIONALE

Quantitative health disparities research has increasingly employed intersectionality as a theoretical tool to investigate how social characteristics intersect to generate health inequality. Yet, intersectionality was not designed to quantify, predict, or identify health disparities, and, as a result, multiple criticisms against its misapplication in health disparities research have been made. As such, there is an emerging need to evaluate the growing body of quantitative research that aims to investigate health disparities through an intersectional lens.

METHODS

We conducted a systematic review from earliest records to January 2020 to (i) describe the scope of limitations when applying intersectionality to quantitative health disparities research, and (ii) identify recommendations to improve the future integration of intersectionality with this scholarship. We identified relevant publications with electronic searches in PubMed and CA Web of Science. Studies eligible for inclusion were English-language publications that used quantitative methodologies to investigate health disparities among adults in the U.S. while explicitly claiming to adopt an intersectional perspective. Out of 1279 articles reviewed, 65 were eligible for inclusion.

RESULTS

Our review found that, while the value of intersectionality to the study of health disparities is evident, the existing research struggles with meeting intersectionality's fundamental assumptions. In particular, four limitations were found to be widespread: narrowing the measurements of intersectionality, intersectional groups, and health outcomes; placing primacy on the study of certain intersectional groups to the neglect of others; overlooking underlying explanatory mechanisms that contribute to the health disparities experienced by intersectional groups; and, lacking in the use of life-course perspectives to show how health disparities vary across different life stages.

CONCLUSION

If the goal of health equality is to be achieved among diverse intersectional groups, future research must be assisted by the collection and examination of data that overcomes these limitations.

Violence against women: An observational study in an Italian emergency department

Violence against women is a pervasive phenomenon affecting one in three women aged ≥15 in the world that are more likely to visit an emergency department (ED) for the serious physical and psychological consequences of the abuse. The aim of this observational single-centre study is to describe the socio-demographic and clinical variables associated with violence against women. We enrolled 425 female patients who attended an Italian ED for trauma on 2019 and the patients' information was collected and analyzed with descriptive statistics. The average age of the patients was 41.5 (standard deviation = 14.2) years. 74.6% of the women were Italians, and 86.6% were of metropolitan origin. The reasons for the ED visit included aggression (67.5%), accidental trauma (29.0%) and unknown reasons (3.5%). Multivariate analysis confirmed that three factors were independently associated with violence: nationality (odds ratio [OR] = 0.27; 95% confidence interval [CI], 0.09-0.77), head/face/neck injuries (OR = 7.32; 95% CI, 3.76-14.27) and multiple injuries (OR = 8.52; 95% CI, 1.03-70.47). Age over 25 was a protective factor. The study confirmed that being a foreigner and having head/face/neck injuries or multiple injuries are associated with violence against women.

Future Time Perspective in Mid-to-Later Life: The Role of Personality

OBJECTIVES

Future time perspective (FTP), or the way individuals orient to and consider their futures, is fundamental to motivation and well-being across the life span. There is a relative paucity of studies, however, that explore its contributing factors in mid-to-later life, specifically. Therefore, uncovering which variables contribute to individual differences in FTP, as well as the ways these variables interact, is paramount to developing a strong understanding of this construct during this life-span stage.

METHOD

This study used three data mining techniques (ie, elastic net, decision tree, and tree ensemble analyses) to simultaneously test several potential contributors identified in the literature, including the five-factor personality domains, several health indices, and age.

RESULTS

Personality, especially neuroticism, extraversion, conscientiousness, and agreeableness, had the most influence on FTP. Age and health were not among the most salient FTP contributors in mid-to-later life. Furthermore, decision tree analyses uncovered interactive effects of personality; several profiles of neuroticism, extraversion, and/or conscientiousness were linked with differing FTP levels.

DISCUSSION

Although the extant literature has indicated that FTP, age, and health are inextricably tied, these results indicate that there is more variability to be explained in FTP, perhaps especially when looking within specific age groups.

Quantitative analysis of air pollution and mortality in Portugal: Current trends and links following proposed biological pathways

A wealth of studies focusing on the relationships between negative health outcomes and short-term and long-term exposures to environmental risk factors have produced estimates of the burden of disease attributable to air pollution, which have led to the implementation of air pollution control strategies. However, the call to expand those studies, in terms of geographical units of analysis to produce more accurate estimates of the burden of disease in the different countries has been made. Studies of the specific environment-health relationship concerning air pollution in Portugal are scarce and rather descriptive. Therefore, this work assesses the trends both in atmospheric levels of pollutants including particulate matter (PM₁₀), ozone (O₃), nitrogen dioxide (NO₂) and sulphur dioxide (SO₂), and in mortality rates for diabetes, malignant neoplasms and diseases of the respiratory, digestive and circulatory systems, and explores the links between exposure to air pollutants and mortality, following proposed biological pathways and using inferential statistics methods, for the period 2010 to 2017 in Portugal. The following major conclusions were drawn: (i) despite a somewhat initial downward trend in PM₁₀ and a peak in O₃ levels, fairly constant air pollution levels were mostly observed; (ii) concomitantly, increases in age-adjusted mortality rates were significant for all diseases except diabetes; (iii) lower atmospheric levels of pollutants were observed in rural areas, when compared to urban areas, except for ozone; (iv) age-adjusted mortality rates were higher in rural regions, for diabetes, and in urban regions, for malignant neoplasms; (v) for a 10 μg/m³ increase in atmospheric levels of PM₁₀, regression analysis estimated an increase of 0.30% in the mortality rate for diseases of the respiratory, digestive and circulatory systems, and malignant neoplasms combined.

The FitSpirit approach for increasing physical activity in canadian teenage girls: protocol of a longitudinal, quasi-experimental study

Background

Worldwide, most adolescent girls do not meet physical activity (PA) recommendations and very few PA programs are tailored specifically towards them. Even fewer information exists about the long-term effects of such programs. Some Canadian schools have implemented the FitSpirit PA intervention designed specifically for girls aged 12 to 17 years old. This paper describes the protocol of a quasi-experimental study evaluating long-term changes in health behaviours and outcomes following FitSpirit participation.

Methods

The study is conducted among schools that partner with FitSpirit every year. It started in 2018 and will be completed in 2022. The intervention comprises motivational talks, a turnkey running program, PA sessions and special events. Study participants fill out an online questionnaire twice a year. Follow-up questionnaires are sent at the end of each school year to the study participants who dropout from FitSpirit. The main outcome, changes in PA levels, is evaluated using questions validated for adolescents. Secondary outcomes are health (perceived health); lifestyle habits (sedentary activities, eating and sleeping habits); psychosocial outcomes (physical self-efficacy and body satisfaction); and FitSpirit appreciation (activity participation and satisfaction). Most questions originate from questionnaires validated for the adolescent population. Cross-sectional and longitudinal analyses will be performed.

Discussion

This study will provide one of the first longitudinal reports on the impact of a large extra-curricular PA intervention designed specifically for adolescent girls. The current study will uniquely contribute to PA research by assessing outcomes additional to PA levels, including markers of health, lifestyle habits and psychosocial determinants.

Trial registration

NCT, NCT03804151, Registered on January 22, 2019; retrospectively registered.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-10200-5.

Evaluating the implementation of the SWITCH® school wellness intervention and capacity-building process through multiple methods

Background

School wellness programming is important for promoting healthy lifestyles and academic achievement in youth; however, research is needed on methods that can help schools implement and sustain such programs on their own. The purpose of this study was to investigate factors within and outside the school environment that influenced school capacity for implementation and potential sustainability of wellness programming.

Methods

As part of the School Wellness Integration Targeting Child Health (SWITCH®) intervention, elementary school wellness teams (N = 30) were guided through a capacity-building process focused on promoting the adoption of healthy lifestyle behaviors in students. Data on implementation were collected through three standardized surveys and interviews (pre-mid-post) and a post-implementation interview. Indicators of organizational capacity were assessed using the School Wellness Readiness Assessment (SWRA). Paired t-tests were run to assess changes in implementation (classroom, physical education, and lunchroom settings), capacity, and stakeholder engagement over time. One-way analysis of variance (ANOVA) tests were run to examine how implementation of best practices (low, moderate, high) explained differences in capacity gains. Qualitative data were analyzed through inductive and deductive analysis, following the Consolidated Framework for Implementation Research (CFIR).

Results

Paired t-tests showed non-significant increases in school and setting-specific capacity and implementation of SWITCH best practices over time, in addition to a consistent level of engagement from key stakeholders. ANOVA results revealed non-significant associations between implementation group and gains in school capacity (F [2, 24] = 1.63; p = .21), class capacity (F [2, 24]=0.20 p = .82), lunchroom capacity (F [2, 24]=0.29; p = .78), and physical education (F [2, 24]=1.45; p = .25). Qualitative data demonstrated that factors within the outer setting (i.e., engaging community partners) facilitated programming. Inner-setting factors (i.e., relationships with administration and staff) influenced implementation. Implementation process themes (e.g., planning, adaptation of resources to meet school capacity/needs, and engaging students as leaders) were cited as key facilitators. Schools discussed factors affecting sustainability, such as school culture and knowledge of school wellness policy.

Conclusions

The results from this implementation study document the importance of allowing schools to adapt programming to meet their local needs, and highlight the strengths of measuring multiple implementation outcomes. Increased support is needed for schools regarding the formation and improvement of wellness policies as a means to enhance sustainability over time.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-020-01070-y.

WU-NEAT: A clinically validated, open-source MATLAB toolbox for limited-channel neonatal EEG analysis

BACKGROUND

Limited-channel EEG research in neonates is hindered by lack of open, accessible analytic tools. To overcome this limitation, we have created the Washington University-Neonatal EEG Analysis Toolbox (WU-NEAT), containing two of the most commonly used tools, provided in an open-source, clinically-validated package running within MATLAB.

METHODS

The first algorithm is the amplitude-integrated EEG (aEEG), which is generated by filtering, rectifying and time-compressing the original EEG recording, with subsequent semi-logarithmic display. The second algorithm is the spectral edge frequency (SEF), calculated as the critical frequency below which a user-defined proportion of the EEG spectral power is located. The aEEG algorithm was validated by three experienced reviewers. Reviewers evaluated aEEG recordings of fourteen preterm/term infants, displayed twice in random order, once using a reference algorithm and again using the WU-NEAT aEEG algorithm. Using standard methodology, reviewers assigned a background pattern classification. Inter/intra-rater reliability was assessed. For the SEF, calculations were made using the same fourteen recordings, first with the reference and then with the WU-NEAT algorithm. Results were compared using Pearson's correlation coefficient.

RESULTS

For the aEEG algorithm, intra- and inter-rater reliability was 100% and 98%, respectively. For the SEF, the mean±SD Pearson correlation coefficient between algorithms was 0.96±0.04.

CONCLUSION

We have demonstrated a clinically-validated toolbox for generating the aEEG as well as calculating the SEF from EEG data. Open-source access will enable widespread use of common analytic algorithms which are device-independent and unlikely to become outdated as technology changes, thereby facilitating future collaborative research in neonatal EEG.

Considerations for using race and ethnicity as quantitative variables in medical education research

Throughout history, race and ethnicity have been used as key descriptors to categorize and label individuals. The use of these concepts as variables can impact resources, policy, and perceptions in medical education. Despite the pervasive use of race and ethnicity as quantitative variables, it is unclear whether researchers use them in their proper context. In this Eye Opener, we present the following seven considerations with corresponding recommendations, for using race and ethnicity as variables in medical education research: 1) Ensure race and ethnicity variables are used to address questions directly related to these concepts. 2) Use race and ethnicity to represent social experiences, not biological facts, to explain the phenomenon under study. 3) Allow study participants to define their preferred racial and ethnic identity. 4) Collect complete and accurate race and ethnicity data that maximizes data richness and minimizes opportunities for researchers' assumptions about participants' identity. 5) Follow evidence-based practices to describe and collapse individual-level race and ethnicity data into broader categories. 6) Align statistical analyses with the study's conceptualization and operationalization of race and ethnicity. 7) Provide thorough interpretation of results beyond simple reporting of statistical significance. By following these recommendations, medical education researchers can avoid major pitfalls associated with the use of race and ethnicity and make informed decisions around some of the most challenging race and ethnicity topics in medical education.

Leadership and administrative support for interprofessional collaboration in a cancer center

PURPOSE

The interprofessional collaboration is a key practice for providing cancer care. However, the realization of collaboration requires effective leadership and administrative support. In this study, the aim was to analyze healthcare professionals' perceptions of leadership and administrative support (strategic and management) in interprofessional collaboration for developing practices in cancer care.

DESIGN/METHODOLOGY/APPROACH

A descriptive survey design was used to collect data from healthcare professionals (n = 350, response rate 33.3%), including nurses, physicians and other professionals participating in patient care in one Finnish cancer center (out of five) in 05/2018-10/2018. The data were analyzed using descriptive and inferential statistics. The instrument focused on leadership in the work unit and administrative support including organization strategy and organizational management.

FINDINGS

Healthcare professionals perceived leadership in the work unit, organization strategy and management for the support of interprofessional collaboration as weak. However, the ratings of male respondents and those in leading positions were more positive. The findings indicate that healthcare professionals in the cancer care setting are dissatisfied with the leadership and administrative support.

RESEARCH LIMITATIONS/IMPLICATIONS

Interprofessional collaboration, including its leadership, requires systematic and constant evaluation and development.

ORIGINALITY/VALUE

Healthcare leaders in the cancer care setting can use the results to identify factors that might be in need of attention and development in the field of interprofessional collaboration.

[Understanding through qualitative methods - the contribution of interpretative social research to health reporting]

Health reporting normally uses quantitative data collected in a standardized manner. The use of qualitative data, using the methods of qualitative social research, is generally the exception. The present article would like to illustrate the potential benefits of using qualitative methods in health reporting. The focus is on the following questions: What characterizes qualitative methods, what is their theoretical and methodological basis, and what specific contribution can they make in health reporting?Qualitative research is based on the assumption that people generally act on the basis of subjective meanings they attach to objects in their environment and to the action of other people. Qualitative methods often provide better possibilities to investigate these subjective perspectives and action orientations than standardized procedures. Due to their methodological particularities, qualitative methods are suitable for the exploration of health-relevant perceptions, attitudes, and behaviors. The results could help to improve the appropriateness of prevention programs; they can also be the starting point for further quantitative research to test hypotheses.The openness that characterizes qualitative methods presupposes sufficient expertise, but beyond this, accurateness and a rule-governed procedure are necessary, as in quantitative research. Added to this is transparency; the data have to be precisely documented and the analytic method disclosed. Even the results of qualitative research must stand up to critical appraisal.

A case of validity evidence for the Interprofessional Attitudes Scale

Numerous measures have been developed for the assessment of interprofessional attitudes, including the Interprofessional Attitudes Scale (IPAS). The purpose of this study was to assess, and contribute to, the validity evidence for the IPAS. The IPAS was used in a three-year longitudinal study to collect data from first year health professionals. Three forms of assessment were conducted to accrue validity evidence for the IPAS: Exploratory Factor Analysis, Item Analysis, and analysis using Item Response Theory. Data was collected from 337 participants over three years. Separately, and cumulatively, the Exploratory Factor Analysis, Item Analysis and analysis using Item Response Theory identified issues with the content, response process, internal structure, and consequential validity of the IPAS. The outcomes of the present study call into question the use of the IPAS, and other measures, for the assessment of interprofessional attitudes. The present study contributes several pieces of evidence to the validity of the IPAS and the reevaluation of the use of attitude assessment in interprofessional education.

Does Opportunity Skip Generations? Reassessing Evidence From Sibling and Cousin Correlations

Sibling (cousin) correlations are empirically straightforward: they capture the degree to which siblings' (cousins') socioeconomic outcomes are similar. At face value, these quantities seem to summarize something about how families constrain opportunity. Their meaning, however, is complicated. One empirical set of sibling and cousin correlations can be generated from a multitude of distinct theoretical processes. I illustrate this problem in the context of multigenerational mobility: the relationship between the incomes of an ancestor and a descendant separated by several generations in a family. When cousins' outcomes are similar (an empirical fact), prior authors have favored the particular theoretical interpretation that extended kin affect life chances through pathways not involving the parents of the focal individual. I show that this evidence is consistent with alternative theories of latent transmission (measurement error) or dynamic transmission (a parent-to-child transmission process that changes over generations). Theoretical assumptions are required to lend meaning to a point estimate. Further, I show that point estimates alone may be misleading because they can be highly uncertain. To facilitate uncertainty estimation for the key test statistic, I develop a Bayesian procedure to estimate sibling and cousin correlations. I conclude by outlining how future research might use sibling and cousin correlations as effective descriptive quantities while remaining cognizant that these quantities could arise from a variety of distinct theoretical processes.

[Mixed-methods studies in the field of health promotion. Results of a systematic review of German publications]

Research in the field of health promotion generates evidence-based knowledge and has the potential to increase the acceptance, impact and long-term effectiveness of interventions. Typically, a distinction is made between qualitative and quantitative approaches. Yet, with complex and multidimensional re-search questions in the field of health promotion a combination of the two approaches has proven useful. Using mixed-methods designs promises, among other things, to compensate for weaknesses of the individual methods, to improve the scope of the results, and to provide a comprehensive insight into the topic. In this systematic review of two German journals we examine the role of the mixed-methods approach in the field of health promotion and how it can be translated into specific research projects. The review's results show that mixed-methods designs are implemented in various contexts. In most studies, the quantitative research strand plays the central role. The use of the mixed-methods designs in health promotion can be further discussed, especially taking into account technical innovations in the field of data collection or with regard to the interpretative potential of qualitative research. The presentation of the review is based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) by the Equator Network.

Callitrichid responses to dead and dying infants: the effects of paternal bonding and cause of death

Many primates show responses to dead infants, yet testing explanations for these behaviors has been difficult. Callitrichids present a unique opportunity to delineate between hypotheses, since unlike most species, male caretakers form closer social bonds with infants than mothers. Callitrichids are also known to commit infanticide, leaving obvious wounds that may enable them to more readily recognize death. We present: (1) a case study of a wild common marmoset (Callithrix jacchus) group responding to an infant's natural death, and (2) a review of published infant deaths across callitrichids (N = 16), testing for trends in the sex of reacting individuals and cause of death. In our case study, several group members frequently interacted with the dead infant, attempting to carry it. However, the strongest response was from a male that remained with the corpse for ~ 3 h, despite his group leaving the area. Across callitrichid species, corpse interactions were significantly sex-biased: 100% (N = 6) of accidental deaths involved corpse interaction by males (p = 0.007), compared to 60% (N = 3 of 5) by females (p = 0.095). Cause of death also played a significant role, with individuals attempting to carry dead infants in 100% (N = 6) of accidental deaths, but only 11.1% (N = 1 of 9) of infanticides (p = 0.001). Although the available literature is small and potentially subject to publication biases, these data support the idea that visually obvious wounds may influence callitrichids' perception of dead conspecifics. Additionally, male-biased patterns of corpse interaction in callitrichids indicate that social bonds likely shape reactions to the dead, in addition to kinship. While published data on primate thanatology are limited, this study demonstrates quantitative approaches that can provide empirical insights into primates' responses to dead conspecifics.

Quantitative Safety Monitoring in Clinical Trials: Application of Multiple Statistical Methodologies for Infrequent Events

BACKGROUND

There are limited quantitative approaches for evaluating rare safety outcomes from controlled clinical trials in either a blinded or unblinded setting. This manuscript demonstrates an application of three statistical methods for quantitative safety monitoring that can be implemented during any phase of a clinical trial, including open-label extension studies.

METHODS

An interactive safety monitoring (iSM) tool was developed using R language in the publicly available R-Shiny app and was implemented for three statistical methods of quantitative safety monitoring. These methods are sequential probability ratio test (SPRT), maximized SPRT (MaxSPRT), and Bayesian posterior probability threshold (BPPT). The iSM tool evaluated specific safety signals that incorporated pre-specified background rates or reference risk ratios.

RESULTS

Two sets of blinded clinical trial data were used for case studies to demonstrate the use the iSM tool. Two particular adverse events, myocardial infarction (MI) and serious infection, were monitored. Monte Carlo simulation was conducted to evaluate the operating characteristics of pre-specified parameters. It showed that after adjusting for exposure, the BPPT and MaxSPRT yielded similar results in identifying a pre-specified signals while the SPRT method failed to detect such signals.

CONCLUSION

Statistical methods shown for the case studies, as well as the application of the user-friendly iSM tool, greatly enhance the quantitative monitoring of safety events of interest in ongoing clinical trials The BPPT and MaxSPRT methods seem more sensitive in picking-up early signals than the SPRT method when the number of safety events is small.

Longitudinal evaluation of attitudes to interprofessional collaboration: time for a change?

Longitudinal evaluation of interprofessional programming is necessary to understand the impact of interprofessional education (IPE) for collaborative practice. Attitude is one measure of intended behavior. The Interprofessional Attitude Scale (IPAS) was developed as an improved measure to examine the readiness for interprofessional education and collaborative practice. As a means to pilot a protocol for a longitudinal comprehensive evaluation of an interprofessional program with 13 health professional programs in 6 health science faculties, the IPAS was administered over a 3-year period to three cohorts of students. The results of the IPAS indicated no significant differences detected across the 3 years. Although there was a significant difference on the Patient Centredness subscale for Cohorts 2 and 3 the effect size was small. Previous experience in an interprofessional course was a predictor of more positive patient centeredness attitudes, but other IPE experience and years of education were not predictors of any interprofessional attitudes. Students from the Medicine & Dentistry (M&D) faculty ranked significantly lower on the teamwork roles and responsibilities subscale compared to the other faculties, except Rehabilitation Medicine (RM). However, once the outliers in RM were removed, there was a significant difference on this subscale between RM and M&D. This paper outlines the challenges with using the IPAS as part of a comprehensive program evaluation and identifies issues with longitudinal data collection for evaluation with large student cohorts.