Class Analysis Research Articles

Phenotypes of Dialysis-Requiring Acute Kidney Injury and Associations with Mortality in a South American Population.

Acute kidney injury (AKI) is a complex syndrome typically classified into strict categories. Alternatively, it may be more accurate to consider it as an intermediate event between an initiating cause and its outcome. Therefore, we investigated the burden of clinical scenarios associated with dialysis-requiring AKI (AKI-D) using latent class analysis (LCA) and examined the etiological spectrum and clinical phenotypes across different life stages. We analyzed 17,158 AKI-D patients from 170 medical facilities in Rio de Janeiro, Brazil (2002-2012). Utilizing survival curves and mixed-effects Cox regression for survival estimation, LCA classified patients based on clinical characteristics and outcomes, focusing on etiological variation over the human lifespan. The median age was 75 (IQR 59-83). Infections were the most common cause (44.2%), particularly community-acquired pneumonia (23.8%). Cardiovascular issues, especially ischemic heart disease (9.0%) and acute heart failure (8.1%), were also significant. LCA identified four distinct patient classes with varying clinical and outcome profiles. Class 1 patients were younger (median age 66), predominantly male, with lower ICU admission and higher rates of community-acquired AKI (60.8%). They had the lowest mortality (39.5%) and highest recovery rates. Class 2 had intermediate mortality (67.4%) and the highest comorbidity burden (mean Charlson score: 3.39). Classes 3 and 4 had the highest mortality (82.8% and 78.6%), requiring more mechanical ventilation and vasopressor use. Class 3 had a high prevalence of sepsis (92.7%) with lower comorbidities, while Class 4 had high chronic heart disease (76.3%) and perfusion factors (79.4%). Despite high mortality, Class 3 recovered better than Class 2 and 4. Survival analyses revealed diverse outcomes across etiological groups, with liver-related conditions being the most severe. This study highlights the complexity of AKI and the utility of LCA in revealing its clinical heterogeneity. It underscores distinct etiological trends across ages, suggesting future research should integrate clinical profiles with advanced diagnostics to understand AKI's clinical and molecular phenotypes throughout life.

School readiness profiles: Does the quality of preschool education matter?

Studies evaluating school readiness profiles and quality of early education are scarce and have produced inconsistent results. This study aimed to identify school readiness profiles, correlating them with the quality of education, in an epidemiological sample of 722 children (4 and 5 years old; 48.9% female). A four-class latent class analysis model best describes school readiness profiles. Fifty-eight percent of children were considered ready for school. The remaining children presented isolated or combined risks for academic underachievement and social maladjustment. High-quality preschools seem to be a protective factor only for at risk for poor academic achievement (OR = 1.22). The prioritization of high-quality preschools could mitigate risk factors at the family and socioeconomic levels, increasing the chances for academic success. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Pain, Substance Use Disorders, Mental Health, and Buprenorphine Treatment among Patients With and Without HIV.

Treatment of opioid use disorder (OUD) with buprenorphine improves outcomes and mortality among people with HIV (PWH). However, engagement is low and is influenced by comorbidities. We examined the impact of patterns of co-occurring pain, substance use disorders (SUDs), and mental health diagnoses on buprenorphine initiation and retention in PWH. The Veterans Aging Cohort Study contained 7,875 patients (2,702 PWH and 5,173 without HIV) with new OUD clinical encounters (2008-2017). Buprenorphine initiation and retention were derived from prescription data. We identified patterns of co-occurring diagnoses (via ICD codes) and assessed the effects of class membership on both outcomes using latent class analysis and regression analyses. The mean age of patients was 55, 98% were male, 58% Black, 8% Hispanic, and only 8% initiated buprenorphine within 12 months of OUD diagnosis. Four classes of co-occurring diagnoses were identified: "Few Co-occurring Diagnoses" (42.3%); "Multiple Pain Conditions" (21.3%); "Pain + SUD" (18.4%) and "Pain + SUD + Mental Health" (18.0%). Patients in the "Pain + SUD" class and "Pain + SUD + Mental Health" class were significantly less likely to initiate buprenorphine and had 59% and 45% lower odds, respectively, of initiating buprenorphine compared with patients in the "Few Co-occurring Diagnoses" class; this effect did not vary by HIV status. Buprenorphine retention was not significantly associated with HIV status or class membership. However, Black Veterans were less likely to initiate or be retained in buprenorphine treatment. Higher comorbidity burden was negatively associated with buprenorphine initiation but not with retention. More research is warranted to determine other factors that may influence treatment retention.

Resilience in the aftermath of trauma: Classes of adjustment in at-risk youth.

Youth who have been exposed to potentially traumatic events are at risk of developing chronic and severe adjustment problems. However, some youth exposed to potentially traumatic events exhibit better-than-expected adaptation. Person-centered analyses, based on multiple criteria for adaptive behavior and adversity, are well-suited to empirically identifying different patterns of adaptation among high-risk youth. Data from 381 youth from three at-risk subgroups in Portugal were collected using self-reported measures of trauma history, trauma-related symptomatology, coping skills, and perceived social support. Distinct classes of adaptation after traumatic experiences were examined with latent class analysis. Four classes were identified: (a) trauma-related psychopathology class (13.6%), (b) adaptive resilience class (36.8%), (c) low resources class (11.4%), and (d) high resources class (38.2%). Trauma-related psychopathology class and low resources class were characterized by high levels of maladjustment. Similarly to the low resources class, the trauma-related psychopathology class reported a significantly higher likelihood of trauma-related psychopathology and higher levels of problem-solving skills. The adaptive resilience class and high resources class also reported lower levels of maladjustment, and the high resources class reported higher levels of coping skills and lower levels of externalizing problems than any other class. Clinicians treating children's internalizing mental health or externalizing behavior problems should assess trauma history and trauma-related psychopathology, as well as protective resources that may enhance resilience such as skills for problem solving and social support seeking. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Trajectories of advanced math taking for low-income students of color in middle and high school

Differential access to and enrollment in advanced mathematics for historically underrepresented groups is a pervasive problem in education, however, research has primarily focused on achievement rather than access. This necessitates an examination of who is accessing advanced coursework and what differentiates the course trajectories students follow across middle and high school. We utilized data from a large (N = 18,841), majority Latinx (57.6 % Latinx, 35.5 % Black, 6.1 % White/Other, and 0.6 % Asian/Pacific Islander) and low-income (77 % free/reduced-price lunch) sample of students followed longitudinally from middle through high school. Latent class analysis (LCA) categorized students into 6 classes representing commonly followed pathways of advanced math course taking from grade 6 to 12. Multinomial logistic regression was used to connect individual demographics, school readiness skills, and prior achievement variables to the likelihood of being assigned to a particular class. Prior academic performance was most strongly related to advanced math pathway assignment, but even controlling for this, gender, disability status, and cognitive and fine motor skills at age 4 also impacted the math pathway a student was likely to follow in middle and high school. Race/ethnicity was a significant differentiator only when comparing the two most advanced pathways. These findings highlight the importance of early school readiness skills and demonstrate how early opportunity gaps impact later student outcomes. Tailored intervention and supports are necessary to ensure equitable access to coursework which expands a student’s opportunities and chances for postsecondary success.

Outcomes in clinical subgroups of patients with alcohol-related hospitalizations: a population-based retrospective cohort study

ObjectiveIndividuals who experience alcohol-related hospitalizations are at a high risk of recurrent harm and premature mortality. This project characterized the clinical subgroups of individuals who experience alcohol-related hospitalizations to understand who is at the highest risk of recurrent harm following discharge. ApproachPopulation-based retrospective cohort study of individuals with an alcohol-related hospitalization between 2017-2018 in two Canadian provinces (Ontario and Manitoba) using linked provincial health administrative databases. Clinical subgroups were identified with latent class analysis based on the type and frequency of alcohol-related health service use in the two-years preceding the index hospitalization. Associations between subgroup membership, readmission, and mortality in the year following discharge were evaluated using multivariable time-to-event regression. ResultsIn cohorts of 4,753 (Manitoba) and 29,290 (Ontario) individuals, seven subgroups were identified. These followed a severity gradient from low-frequency service use for acute intoxication to high-frequency service use for alcoholic liver disease. Individuals in the ‘liver disease’ subgroup had the highest risk of 1-year mortality relative to the rest of the cohort (adjusted hazard ratio [aHR]: 3.83, 95% confidence interval (CI): 2.80-5.24). A small subgroup of individuals with a history of high-frequency alcohol-related health service had the highest hazard of readmission (aHR: 5.09, 95% CI: 4.11-6.31). Conclusions and ImplicationsThere are distinct clinical subgroups of individuals who experience alcohol related hospitalizations and individuals with high-frequency health service use and alcohol-related liver disease are at the highest risk of readmission and mortality. These subgroups merit consideration in strategies aimed at reducing the risk of post-discharge harm.

Policy-driven multidisciplinary primary care after stroke or Transient Ischaemic Attack (TIA) improves survival – an observational target trial evaluation involving linked registry data

ObjectiveTo determine the effectiveness of government policies supporting coordinated multidisciplinary primary care (MDC) in improving long-term survival following stroke or Transient Ischaemic Attack (TIA). ApproachWe used the target trial framework for observational data to assess the average population effect of primary care MDC policies. The cohort comprised patients from the Australian Stroke Clinical Registry (January 2012-June 2015) linked with (i) Australian Medicare claims to define exposures (MDC claims in the 6-18 months post-stroke); (ii) hospital, pharmaceutical and aged care datasets for additional covariates; (iii) National Death Registry for survival outcomes (19-30 months post-stroke). Level of impairment was classified by latent class analysis using EQ-5D-3L questionnaire data obtained 90-180 days post-stroke. Multilevel survival analysis with inverse probability treatment weights was applied. ResultsAmong 7,255 people with stroke (42% female, median age 71 years, 24% TIA, level of impairment: 39% minimal, 32% moderate, 29% severe), 29% had a Medicare claim for MDC (23% minimal, 31% moderate, 39% severe). Mortality was reduced in those receiving a claim (vs non-receipt) in the minimal (adjusted Hazard Ratio (aHR): 0.50, 95%CI:0.27, 0.91) and severe (aHR: 0.65, 95%CI:0.46, 0.91) impairment groups, but not the moderate impairment group (aHR: 1.31, 95%CI:0.86, 1.99). Group differences in allied health services claimed during MDC were observed: secondary prevention (14% minimal vs 10% severe impairment), rehabilitation (21% minimal vs 25% severe impairment). ImplicationsDrawing causal inferences from linked observational data demonstrated the population effectiveness of primary care MDC policies, in improving survival following stroke/TIA, with variation by impairment class.

Patterns of antidepressant use among older adults in Northern Ireland: An administrative data study.

ObjectiveOver recent decades, there has been a noticeable increase in the prescription of antidepressant medications, particularly among older adults. This study examines the relationship between health outcomes and patterns of antidepressant use among older adults in Northern Ireland (NI). ApproachParticipants included all (General Practitioner) GP-registered hospital patients aged fifty-five years and above on 01/01/2010 (n =395,872). Administrative data linkage included demographic information (age, sex; urbanicity); data on antidepressant use from the NI Enhanced Prescribing Database (EPD); and hospital patient admissions/discharges. Repeated measures latent class analysis (RMLCA) identified patterns of antidepressant use (2010 to 2020) in relation to the association between these patterns and health-related outcomes in 2021. ResultsRMLCA identified four latent classes : long-term antidepressant use (17.4%); decreasing antidepressant use (7.1%); increasing antidepressant use (8.4%); no-antidepressant use (67.1%). Those in the long-term and increasing antidepressant use’ classes had the highest average number of hospital visits and recorded chronic conditions in 2021. ConclusionFindings show that two distinct subgroups (comprising 26% of the hospital population) were disproportionately impacted by increased antidepressant prescription rates. Because of their increased likelihood of experiencing higher ill-health, these people are crucial targets for additional psychosocial support. ImplicationsAnalyses of this kind emphasize the importance of widening access to administrative data, enabling researchers to identify and examine at-risk groups allowing more targeted policymaking to better address their needs. Data for this project was provided by the HSC Honest Broker Service; any views or opinions presented are solely those of the author.

Identifying patterns of Long-COVID diagnosis pathways: a Latent Class Analysis of Welsh clinical data

ObjectivesLong-COVID (LC) diagnosis remains challenging due to its variable, multisystem, episodic symptoms, and lack of uniformity in the critical time points. We aim to classify diagnosis pathways and associated demographic and health determinants for clinically diagnosed LC patients in Wales. ApproachWe created a cohort of LC-diagnosed adults in Wales from 2020 to 2023 using population-scale data within the SAIL Databank. To classify diagnosis pathways, we extracted a set of indicators suggestive of the general diagnosis process within 6-months before the diagnosis, including LC symptoms, clinical investigations, and management. We conducted Latent Class Analysis (LCA) to examine how these indicators cluster, adjusting the best-fit model for various covariates such as COVID-19 infection history and sociodemographic characteristics. ResultsOf the 7,973 identified LC patients, 59% had clinical investigations, 59% had a clinical management record, and 39% had at least one related symptom. Using LCA, we identified 7 distinct patterns of diagnosis pathways, and how background characteristics associated with each. ConclusionDespite existing guidelines, LC diagnosis is complex due to LC’s diverse manifestations and the absence of exclusive symptoms/tests. Late or missed LC diagnosis can have a detrimental effect at individual, community, and national levels. Previous UK studies have indicated low recording rates of LC compared with self-reported surveys. Understanding current diagnosis pathways can shed light on this discrepancy and identify potential confounding factors that delay/impact LC diagnosis. This insight is crucial for standardising diagnosis pathways, enabling earlier and more accurate detection of LC and thereby mitigating its impact.

Types of depression in patients with coronary heart disease: Results from the THORESCI study

BackgroundBoth coronary heart diseases (CHD) and depression are highly prevalent and bidirectionally related. The precise nature of this relationship remains unclear. Defining depressive subtypes could help unravel this relationship. Therefore, the aim of this study was to explore depressive subtypes in patients with CHD. Methods1530 patients (21.3 % women, mean age: 64.7 years (SD = 10.1)) were included in latent class analysis with nine indicators derived from the PHQ-9 and BDI-II representing symptoms of depression as described in the DSM-5 criteria. The best-fitting latent class model was confirmed with double cross-validation. Classes were characterized using demographic, medical, psychiatric, and cardiovascular (risk) factors. ResultsA 3-class model demonstrated the best fit to the data, resulting in a depressed (5.4 %), fatigued (13.5 %), and non-depressed class (81.1 %). Having medical comorbidities, a history of psychiatric problems, negative affectivity, and anxiety symptoms increased the odds of belonging to the depressed group (OR 3.02, 95%CI 1.19–7.68, OR 3.61, 95%CI 1.44–9.02, OR 1.16, 95%CI 1.04–1.30, and OR 1.89, 95%CI 1.66–2.15, respectively). Belonging to the fatigued group was associated with increased odds of having an elective PCI (OR 2.12, 95%CI 1.27–3.55), insufficient physical activity (OR 2.19, 95%CI 1.20–3.99), comorbid medical conditions (OR 2.15, 95%CI 1.21–3.81), a history of psychiatric problems (OR 2.25, 95%CI 1.25–4.05), and anxiety symptoms (OR 1.48, 95%CI 1.34–1.63) compared with the non-depressed group. LimitationsFuture studies should include more people with depressive symptoms. ConclusionsPatients with CHD and medical or psychiatric risk factors should be offered support to decrease or prevent depressive or fatigue symptoms.

Grade-Level Differences in the Profiles of Substance Use and Behavioral Health Problems: A Multi-Group Latent Class Analysis.

We investigated associations between polysubstance use and behavioral problems among adolescents. Because substance use becomes more developmentally normative with age, we examined whether polysubstance use was less likely to co-occur with behavioral problems among older (vs. younger) adolescents. Using data from a nationally representative survey of US high school students, we compared the association between polysubstance use (i.e., use of alcohol, cannabis, tobacco/nicotine, and illicit drugs) and behavioral problems (i.e., suicide attempts, depressive symptoms, poor school performance, and sexual risk behaviors) by grade level. We conducted latent class analysis (LCA) to characterize patterns of polysubstance use, and multi-group LCA to estimate invariance by grade. Among the three latent classes that emerged, classes were distinguished by having low, moderate, and high probabilities for behavior problems and use of substances. Class I comprised 52% of the sample, whereas classes II and III comprised 35% and 12% of the sample, respectively. The multi-group LCA showed that younger adolescents had a higher relative probability of co-occurring problem behaviors and polysubstance use. Findings may be helpful in targeting screening and prevention efforts of high school students by grade. Specifically, our results provide evidence that associations between behavioral problems and alcohol/drug use are weaker in later high school grades, suggesting that substance use may not be a weaker marker of behavioral problems for students in higher grades.

Islam and ethnic tolerance: assessing Kyrgyz’ Muslim religiosity and acceptance of Uzbeks in Kyrgyzstan

ABSTRACT Using a national opinion survey conducted in 2009 in Kyrgyzstan, we focused on responses from ethnic Kyrgyz respondents in the south where major riots between Kyrgyz and Uzbeks occurred in 1990 and 2010. We performed latent class analyses on these responses to assign Kyrgyz into Muslim religiosity categories and construct a social distance scale to measure Kyrgyz’ levels of acceptance of Uzbeks living in Kyrgyzstan. We discovered that, in spite of ongoing unresolved interethnic grievances in the south, Kyrgyz who were members of the highly active Muslim religiosity category exhibited a significantly higher probability for accepting the closest relations (kin through marriage) with Uzbeks than Kyrgyz who were members of the non-religious category. Because other researchers indicated that religion did not play any role in causing the riots in 2010, we believe that Muslim religiosity could potentially play a role in developing beneficial relations between these ethnic groups.

COVID-19 Vaccination Among Adolescents and Young Adults: Test of the Triandis Model of Interpersonal Behavior and the Health Belief Model.

This study purpose was to test the Health Belief Model (HBM) and the Triandis Model of Interpersonal Behavior (TMIB) in predicting COVID-19 vaccine uptake among adolescents and young adults (AYAs). Data from an anonymous online survey were collected. Clusters of risk perceptions of infection were identified using Latent Class Analysis, and predictive values of TMIB and HBM factors were evaluated using logistic regression models. Response rate was 30% (468 participants). There was a combined significant effect of TMIB model components (habitual health behavior, intention, and facilitation conditions) on having received ≥1 dose of COVID-19 vaccine. Having received influenza vaccine in the past 12 months was associated with higher odds of COVID-19 vaccine uptake. Perceived vaccination benefits, and perceived risks of infection were associated with vaccine receipt; however, the HBM model performed inadequately. The HBM is commonly used in vaccine acceptance research; however, the TMIB may be more effective among AYAs.

Exploring vaccine hesitancy among citizens of the Métis Nation of Ontario: a population-based data linkage study

Objective and ApproachUnderstanding vaccine hesitancy among distinct communities is crucial to ensuring equitable uptake of vaccination. The objective was to examine the influence of psychological antecedents of vaccine uptake, known as the “5Cs”, on COVID-19 vaccination among Métis Nation of Ontario (MNO) citizens. The Métis people are one of three Indigenous peoples in Canada. A population-based online survey was implemented by the MNO, including the short version of the “5C” (confidence, complacency, constraint, calculation, collective responsibility) psychological antecedents of vaccination scale. Census sampling achieved a 39% response rate and respondents were linked to the COVID-19 vaccine database (COVAX) in Ontario (n=4,012). Analyses included logistic regression models (adjusted for sociodemographics) and exploratory latent class analyses. ResultsIn logistic regression models, MNO citizens who were less confident that COVID-19 vaccines were safe (OR=0.04; 95% CI=0.03-0.06) and did not agree vaccination was a collective action to prevent the spread of disease (OR=0.11, 95% CI: 0.07-0.17) had lower odds of being vaccinated. MNO citizens who disagreed the risk of COVID-19 was small (OR=14.87, 95% CI: 9.99-22.13) had a higher odds of being vaccinated. Vaccine hesitancy profiles with (i) lower confidence in availability/safety of COVID-19 vaccines, (ii) lower perceptions about severity of COVID-19 and (iii) higher everyday life constraints/stressors were associated with lower vaccination rates (males, OR: 4.69; CI: 3.18–6.92; females, OR: 4.77, CI: 3.03–7.51) in latent class analyses. Conclusions and ImplicationsMétis-specific analyses enabled a community-driven response, resulting in low vaccine hesitancy and high uptake.

Profiles of nonverbal skills used by young pre-verbal children with autism on the ADOS-2: Relation to screening disposition and outcomes.

Autistic individuals exhibit differences in their use and understanding of nonverbal communication; however, individual patterns of nonverbal strengths and challenges vary significantly. This heterogeneity can complicate the diagnostic and screening processes and can result in delayed or missed diagnoses. In this study, we characterize various profiles of nonverbal communication skills among 215 pre-verbal children with autism (Mage = 36.27 months, range = 18-70) and explore how these profiles are related to screening outcomes, diagnostic certainty, and developmental and behavioral features. We conducted a latent class analysis of nine items assessing nonverbal communication skills from the Toddler Module and Module 1 of the Autism Diagnostic Observation Schedule, 2nd Edition. Five nonverbal profiles were identified that differentiated children based on the form, function, and frequency of their nonverbal communication skills. Furthermore, screening outcomes and clinician certainty in autism diagnosis varied by nonverbal profile. False negative screening outcomes based on parent report were highest for children who used a range of nonverbal skills but with limited frequency or consistency. Clinicians, on the other hand, tended to have high certainty in an autism diagnosis for children with this profile, and instead rated their lowest certainty in diagnosing children who demonstrated consistent integration of eye contact with their nonverbal communication. The profiles identified in this study could be clinically useful in helping to identify children at highest likelihood of being overlooked during the screening or diagnostic processes, providing an opportunity to improve early identification and intervention for autism.

Psychological capital and social class: A capital approach to understanding positive psychological states and their role in explaining social inequalities.

Psychological capital (PsyCap) is a multidimensional concept entailing hope, self-efficacy, optimism, and resilience. This paper argues that it can be considered a form of "capital" explaining social inequality. We test whether PsyCap can be integrated into the Bourdieusian capital framework by assessing its relationship with social, economic, and cultural capital. We also identify different types of social positions based on the volume and composition of psychological, economic, cultural, and social capital. We use cross-sectional data from the European Social Survey of 2012 (N = 35,313 respondents; 29 countries). To test the associations with the Bourdieusian capital types, we calculated multilevel spearman rank correlations and performed confirmatory factor analyses (CFA). Latent Class Analysis identified different types of social positions. We found positive weak correlations between PsyCap and the indicators of cultural capital (r ≤ .14) and positive moderate correlations with the indicators of economic and social capital (r ≤ .24). The results of the CFA showed that the fit of the 4-capital model was superior to that of the 3-capital model. We identified six types of social positions: two deprived types (with overall low capital levels); two well-off types (with overall high capital levels) and two types with high psychological and social capital in combination with varying levels of cultural and economic capital. Including PsyCap in the Bourdieusian capital framework acknowledges the power of positive psychological states regarding processes of social mobility and social inequality on the one hand and calls for understanding PsyCap as a social and group-level phenomenon on the other hand. As such, integrating PsyCap into the Bourdieusian framework can help to address the longstanding issue of understanding the relationship between social and individual differences in the study of social inequalities.

Fire Safety Disparities in Sweden: Sociodemographic Influences and the Impact of Societal Protection on Personal Fire Prevention Measures

AbstractPrevious research has identified sociodemographic inequalities in fire prevention measures. This study examined whether sociodemographic differences persist in the Swedish population concerning fire prevention measures and particularly whether there remains an inverted u-curve related to age in protection habits. Additionally, it investigated whether fire protection practices are influenced by the level of societal protection. The research utilised survey data and register data from The Swedish Civil Contingencies Agency and Statistics Sweden. A latent class analysis was conducted, dividing respondents into four latent classes, followed by two binomial regression analyses. The study revealed three key findings regarding fire protection measures. First, certain demographic groups, namely the young, women, single and childfree households, low-income and low-education individuals, immigrants, and urban residents, are disproportionately lacking optimal fire safety measures. Second, although a safety maturity curve is still observed, older adults in Sweden today are considerably more protected compared to 15–20 years ago, indicating that safety practices employed during middle age continue into old age. Third, a trend is observed where individuals living in areas with more efficient professional rescue services tend to have lower levels of personal fire protection, suggesting a rational choice based on the perceived level of societal protection.

A workflow for analyzing cultural schemas in texts

ABSTRACT Concept class analysis (CoCA) is a method for recovering cultural schemas in texts using a combination of word embedding and community detection models. Like survey-based forms of schematic class analysis (SCA), however, interpreting results can be difficult. Some of these interpretive difficulties are applicable across types of SCA, while others are unique to CoCA. In this paper, we propose a complete workflow for interpreting and analyzing CoCA output. We use the case of social identity schemas in a collection of over 13,000 U.S. political blog posts to outline a number of interpretive and analytical strategies and a robustness check to make sense of the cultural schemas recovered from texts.

Implementation of Electromagnetic Theory: Improved Analysis and Design for Class F Power Amplifier

ABSTRACTThe general electromagnetic (EM) theory has not yet been applied to the analysis of Class F (CF) power amplifier (PA). In this paper, an alternative approach for CF PA is presented based on the EM theory. Theoretical analysis shows that the CF PA can be divided into two broad categories, forward voltage gain, and reflected voltage gain PA. The existing CF PA belongs to the reflected voltage gain PA. Even though both the CF PAs have the same voltage gain, the PA with forward voltage gain provides higher fundamental power Ps,1@F and drain efficiency PAE@F than that CF PA with reflected voltage gain and Class B PA. This important conclusion is obtained as a result of this analysis, which cannot be explained by available theory in the literature. The theoretical analysis is validated at 2.2 GHz by fabrication and measurements. According to the results, Ps,1@B = 31.8 dBm and PAE@B = 53.27% in Class B PA. In CF PA with reflected voltage gain, Ps,1@F = 30.20 dBm and PAE@F = 48.6%. Both cases have lower power and PAE as compared to new category of CF PA. This new CF PA with forward voltage gain has, Ps,1@F = 33.04 dBm and PAE@F = 63.7%.

Effect of mothers‘ health literacy on early childhood allergy prevention behaviours: results from the KUNO-Kids health study

BackgroundParents can engage in several behaviours with regard to early childhood allergy prevention (ECAP). These can be related to diet of mother/child and the modification of the home environment; not all of them are justified by current evidence. Previous studies showed that parental health literacy (HL) is related to favourable health behaviours directed at the child. This study aimed to investigate the causal effect of mothers’ HL on ECAP behaviours and to test different moderators of this effect.MethodsOne thousand six hundred sixty-two mothers participating in the KUNO-Kids health study in the area of Regensburg, Germany were surveyed on HL (assessed via the health care scale of the Health Literacy Survey-EU questionnaire, HLS-EU-Q47) and ECAP behaviours implemented during pregnancy and the child’s first year of life. Patterns in ECAP behaviours were identified by latent class analysis. Multinomial regression modelling was performed with HL as exposure, ECAP as outcome variable, allergy risk, parental competence and bonding, anxiety and depression as moderators as well as potentially confounding variables.ResultsWe identified three classes of ECAP behaviours (class 1: „breastfeeding “ N = 871; class 2: „allergen-avoidance “ N = 490; class 3: „mixed behaviours “ N = 301). In univariable as well as fully adjusted regression models, compared to class 1, class 2 was negatively, and class 3 was not associated with HL. None of the tested moderating variables altered the association between HL and ECAP significantly.ConclusionsWe found an effect of mothers’ HL on ECAP behaviours: lower HL of mothers increased allergen-avoiding behaviour directed at their child, while decreasing the chance of exclusive breastfeeding. Improving HL could contribute to the implementation of recommended ECAP behaviours in families, especially to the reduction of allergen-avoiding behaviours.