Development of Data Quality Indicators for Improving Hospital International Classification of Diseases-coded Health Data Quality Globally.

BACKGROUND: Hospital inpatient data, coded using the International Classification of Diseases (ICD), is widely used to monitor diseases, allocate resources and funding, and evaluate patient outcomes. As such, hospital data quality should be measured before use; however, currently, there is no standard and international approach to assess ICD-coded data quality. OBJECTIVE: To develop a standardized method for assessing hospital ICD-coded data quality that could be applied across countries: Data quality indicators (DQIs). RESEARCH DESIGN: To identify a set of candidate DQIs, we performed an environmental scan, reviewing gray and academic literature on data quality frameworks and existing methods to assess data quality. Indicators from the literature were then appraised and selected through a 3-round Delphi process. The first round involved face-to-face group and individual meetings for idea generation, while the second and third rounds were conducted remotely to collect online ratings. Final DQIs were selected based on the panelists' quantitative and qualitative feedback. SUBJECTS: Participants included international experts with expertise in administrative health data, data quality, and ICD coding. RESULTS: The resulting 24 DQIs encompass 5 dimensions of data quality: relevance, accuracy and reliability; comparability and coherence; timeliness; and Accessibility and clarity. These will help stakeholders (eg, World Health Organization) to assess hospital data quality using the same standard across countries and highlight areas in need of improvement. CONCLUSIONS: This novel area of research will facilitate international comparisons of ICD-coded data quality and be valuable to future studies and initiatives aimed at improving hospital administrative data quality.

Crop rotational diversity can mitigate climate-induced grain yield losses.

Diversified crop rotations have been suggested to reduce grain yield losses from the adverse climatic conditions increasingly common under climate change. Nevertheless, the potential for climate change adaptation of different crop rotational diversity (CRD) remains undetermined. We quantified how climatic conditions affect small grain and maize yields under different CRDs in 32 long-term (10-63 years) field experiments across Europe and North America. Species-diverse and functionally rich rotations more than compensated yield losses from anomalous warm conditions, long and warm dry spells, as well as from anomalous wet (for small grains) or dry (for maize) conditions. Adding a single functional group or crop species to monocultures counteracted yield losses from substantial changes in climatic conditions. The benefits of a further increase in CRD are comparable with those of improved climatic conditions. For instance, the maize yield benefits of adding three crop species to monocultures under detrimental climatic conditions exceeded the average yield of monocultures by up to 553 kg/ha under non-detrimental climatic conditions. Increased crop functional richness improved yields under high temperature, irrespective of precipitation. Conversely, yield benefits peaked at between two and four crop species in the rotation, depending on climatic conditions and crop, and declined at higher species diversity. Thus, crop species diversity could be adjusted to maximize yield benefits. Diversifying rotations with functionally distinct crops is an adaptation of cropping systems to global warming and changes in precipitation.

Evaluating the coding accuracy of type 2 diabetes mellitus among patients with non-alcoholic fatty liver disease.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) describes a spectrum of chronic fattening of liver that can lead to fibrosis and cirrhosis. Diabetes has been identified as a major comorbidity that contributes to NAFLD progression. Health systems around the world make use of administrative data to conduct population-based prevalence studies. To that end, we sought to assess the accuracy of diabetes International Classification of Diseases (ICD) coding in administrative databases among a cohort of confirmed NAFLD patients in Calgary, Alberta, Canada. METHODS: The Calgary NAFLD Pathway Database was linked to the following databases: Physician Claims, Discharge Abstract Database, National Ambulatory Care Reporting System, Pharmaceutical Information Network database, Laboratory, and Electronic Medical Records. Hemoglobin A1c and diabetes medication details were used to classify diabetes groups into absent, prediabetes, meeting glycemic targets, and not meeting glycemic targets. The performance of ICD codes among these groups was compared to this standard. Within each group, the total numbers of true positives, false positives, false negatives, and true negatives were calculated. Descriptive statistics and bivariate analysis were conducted on identified covariates, including demographics and types of interacted physicians. RESULTS: A total of 12,012 NAFLD patients were registered through the Calgary NAFLD Pathway Database and 100% were successfully linked to the administrative databases. Overall, diabetes coding showed a sensitivity of 0.81 and a positive predictive value of 0.87. False negative rates in the absent and not meeting glycemic control groups were 4.5% and 6.4%, respectively, whereas the meeting glycemic control group had a 42.2% coding error. Visits to primary and outpatient services were associated with most encounters. CONCLUSION: Diabetes ICD coding in administrative databases can accurately detect true diabetic cases. However, patients with diabetes who meets glycemic control targets are less likely to be coded in administrative databases. A detailed understanding of the clinical context will require additional data linkage from primary care settings.

Automated extraction of weight, height, and obesity in electronic medical records are highly valid.

Objective: Coding of obesity using the International Classification of Diseases (ICD) in healthcare administrative databases is under-reported and thus unreliable for measuring prevalence or incidence. This study aimed to develop and test a rule-based algorithm for automating the detection and severity of obesity using height and weight collected in several sections of the Electronic Medical Records (EMRs). Methods: In this cross-sectional study, 1904 inpatient charts randomly selected in three hospitals in Calgary, Canada between January and June 2015 were reviewed and linked with AllScripts Sunrise Clinical Manager EMRs. A rule-based algorithm was created which looks for patients' height and weight values recorded in EMRs. Clinical notes were split into sentences and searched for height and weight, and BMI was computed. Results: The study cohort consisted of 1904 patients with 50.8% females and 43.3% > 64 years of age. The final model to identify obesity within EMRs resulted in a sensitivity of 92.9%, specificity of 98.4%, positive predictive value of 96.7%, negative predictive value of 96.6%, and F1 score of 94.8%. Conclusions: This study developed a highly valid rule-based EMR algorithm that detects height and weight. This could allow large-scale analyses using obesity that were previously not possible.

Cerebrovascular disease case identification in inpatient electronic medical record data using natural language processing.

BACKGROUND: Abstracting cerebrovascular disease (CeVD) from inpatient electronic medical records (EMRs) through natural language processing (NLP) is pivotal for automated disease surveillance and improving patient outcomes. Existing methods rely on coders' abstraction, which has time delays and under-coding issues. This study sought to develop an NLP-based method to detect CeVD using EMR clinical notes. METHODS: CeVD status was confirmed through a chart review on randomly selected hospitalized patients who were 18 years or older and discharged from 3 hospitals in Calgary, Alberta, Canada, between January 1 and June 30, 2015. These patients' chart data were linked to administrative discharge abstract database (DAD) and Sunrise™ Clinical Manager (SCM) EMR database records by Personal Health Number (a unique lifetime identifier) and admission date. We trained multiple natural language processing (NLP) predictive models by combining two clinical concept extraction methods and two supervised machine learning (ML) methods: random forest and XGBoost. Using chart review as the reference standard, we compared the model performances with those of the commonly applied International Classification of Diseases (ICD-10-CA) codes, on the metrics of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). RESULT: Of the study sample (n = 3036), the prevalence of CeVD was 11.8% (n = 360); the median patient age was 63; and females accounted for 50.3% (n = 1528) based on chart data. Among 49 extracted clinical documents from the EMR, four document types were identified as the most influential text sources for identifying CeVD disease ("nursing transfer report," "discharge summary," "nursing notes," and "inpatient consultation."). The best performing NLP model was XGBoost, combining the Unified Medical Language System concepts extracted by cTAKES (e.g., top-ranked concepts, "Cerebrovascular accident" and "Transient ischemic attack"), and the term frequency-inverse document frequency vectorizer. Compared with ICD codes, the model achieved higher validity overall, such as sensitivity (25.0% vs 70.0%), specificity (99.3% vs 99.1%), PPV (82.6 vs. 87.8%), and NPV (90.8% vs 97.1%). CONCLUSION: The NLP algorithm developed in this study performed better than the ICD code algorithm in detecting CeVD. The NLP models could result in an automated EMR tool for identifying CeVD cases and be applied for future studies such as surveillance, and longitudinal studies.

A comparison of machine learning algorithms and traditional regression-based statistical modeling for predicting hypertension incidence in a Canadian population.

Risk prediction models are frequently used to identify individuals at risk of developing hypertension. This study evaluates different machine learning algorithms and compares their predictive performance with the conventional Cox proportional hazards (PH) model to predict hypertension incidence using survival data. This study analyzed 18,322 participants on 24 candidate features from the large Alberta's Tomorrow Project (ATP) to develop different prediction models. To select the top features, we applied five feature selection methods, including two filter-based: a univariate Cox p-value and C-index; two embedded-based: random survival forest and least absolute shrinkage and selection operator (Lasso); and one constraint-based: the statistically equivalent signature (SES). Five machine learning algorithms were developed to predict hypertension incidence: penalized regression Ridge, Lasso, Elastic Net (EN), random survival forest (RSF), and gradient boosting (GB), along with the conventional Cox PH model. The predictive performance of the models was assessed using C-index. The performance of machine learning algorithms was observed, similar to the conventional Cox PH model. Average C-indexes were 0.78, 0.78, 0.78, 0.76, 0.76, and 0.77 for Ridge, Lasso, EN, RSF, GB and Cox PH, respectively. Important features associated with each model were also presented. Our study findings demonstrate little predictive performance difference between machine learning algorithms and the conventional Cox PH regression model in predicting hypertension incidence. In a moderate dataset with a reasonable number of features, conventional regression-based models perform similar to machine learning algorithms with good predictive accuracy.

Health data governance for research use in Alberta.

Alberta has rich clinical and health services data held under the custodianship of Alberta Health and Alberta Health Services (AHS), which is not only used for clinical and administrative purposes but also disease surveillance and epidemiological research. Alberta is the largest province in Canada with a single payer centralised health system, AHS, and a consolidated data and analytics team supporting researchers across the province. This paper describes Alberta's data custodians, data governance mechanisms, and streamlined processes followed for research data access. AHS has created a centralised data repository from multiple sources, including practitioner claims data, hospital discharge data, and medications dispensed, available for research use through the provincial Data and Research Services (DRS) team. The DRS team is integrated within AHS to support researchers across the province with their data extraction and linkage requests. Furthermore, streamlined processes have been established, including: 1) ethics approval from a research ethics board, 2) any necessary operational approvals from AHS, and 3) a tripartite legal agreement dictating terms and conditions for data use, disclosure, and retention. This allows researchers to gain timely access to data. To meet the evolving and ever-expanding big-data needs, the University of Calgary, in partnership with AHS, has built high-performance computing (HPC) infrastructure to facilitate storage and processing of large datasets. When releasing data to researchers, the analytics team ensures that Alberta's Health Information Act's guiding principles are followed. The principal investigator also ensures data retention and disposition are according to the plan specified in ethics and per the terms set out by funding agencies. Even though there are disparities and variations in the data protection laws across the different provinces in Canada, the streamlined processes for research data access in Alberta are highly efficient.

Personalized prediction of incident hospitalization for cardiovascular disease in patients with hypertension using machine learning.

BACKGROUND: Prognostic information for patients with hypertension is largely based on population averages. The purpose of this study was to compare the performance of four machine learning approaches for personalized prediction of incident hospitalization for cardiovascular disease among newly diagnosed hypertensive patients. METHODS: Using province-wide linked administrative health data in Alberta, we analyzed a cohort of 259,873 newly-diagnosed hypertensive patients from 2009 to 2015 who collectively had 11,863 incident hospitalizations for heart failure, myocardial infarction, and stroke. Linear multi-task logistic regression, neural multi-task logistic regression, random survival forest and Cox proportional hazard models were used to determine the number of event-free survivors at each time-point and to construct individual event-free survival probability curves. The predictive performance was evaluated by root mean squared error, mean absolute error, concordance index, and the Brier score. RESULTS: The random survival forest model has the lowest root mean squared error value at 33.94 and lowest mean absolute error value at 28.37. Machine learning methods provide similar discrimination and calibration in the personalized survival prediction of hospitalizations for cardiovascular events in patients with hypertension. Neural multi-task logistic regression model has the highest concordance index at 0.8149 and lowest Brier score at 0.0242 for the personalized survival prediction. CONCLUSIONS: This is the first personalized survival prediction for cardiovascular diseases among hypertensive patients using administrative data. The four models tested in this analysis exhibited a similar discrimination and calibration ability in predicting personalized survival prediction of hypertension patients.

Integrating Care from Home to Hospital to Home: Using Participatory Design to Develop a Provincial Transitions in Care Guideline.

Introduction: Patients worldwide experience fragmented and uncoordinated care as they transition between primary and acute care. To improve system integration and outcomes for patients, in 2017/2018 Alberta Health Services (largest health services delivery organization in Canada) called for a coordinated approach to improve transitions in care (TiC). Healthcare leadership responded by initiating the development of a province-wide guideline outlining core components of effective transitions in care. This case study highlights the extensive design process used to develop this guideline, with a focus on the participatory design (PD) approach used throughout. Methods: An iterative, mixed methods PD approach was used to engage over 750 stakeholders through the following activities to establish Guideline content: i) learning collaborative; ii) design-team; iii) targeted online surveys; iv) primary care stakeholder consultation; v) modified Delphi panel; and vi) patient advisory committee. Results: The result was Alberta's first guideline for supporting patients through TiC: "Alberta's Home to Hospital to Home Transitions Guideline". Conclusion: The extensive design process used to create the Guideline was instrumental in establishing content, encouraging system integration, and creating conditions to support provincial implementation. While intended to improve and standardize patient care in Alberta, the methods used and lessons learned throughout the development of the Guideline are applicable internationally.

Supporting wild pollinators in agricultural landscapes through targeted legume mixtures.

Insect-pollinated legumes are rich in plant-based proteins making them a vital constituent of sustainable healthy diets for people and livestock. Furthermore, they deliver or support a range of ecosystem services that underpin agricultural production and their prevalence in agricultural landscapes is likely to increase. Under typical implementation and management, the value of legumes to pollinators has, however, been questioned. Through exploring a range of legume crops, grown as monocultures and mixtures, this study aims to identify multifunctional legume cropping systems that optimise forage availability for a diversity of wild pollinators whilst delivering a wide range of agronomic and environmental benefits. This study innovatively explores legume mixtures concurrently with monocultures of the component species using replicated small-plot field trials established in two geographical locations. Observational plots assessed the richness and abundance of floral resources, and wild pollinators (i.e. bumblebees and hoverflies) throughout the peak flowering period. Densely flowering, highly profitable legumes (e.g. Trifolium incarnatum and Trifolium mixes) supported abundant and rich pollinator assemblages. The functional makeup of floral visitors was strongly influenced by flower structure and hoverflies, with their shorter proboscises, were largely constrained to legumes with shallower corolla and open weed species. Floral richness was not a key driver of pollinator assemblages; however, clear intra-specific differences were observed in flowering phenology. Combining functionally distinct legumes with respect to flower structure and phenology, will support a wider suite of pollinating insects and help stabilise the temporal availability of forage. For highly competitive legumes (e.g. Vicia faba and Vicia sativa), planting in discrete patches is recommended to reduce the risk of less competitive species failing in mixtures. Legumes can provide valuable forage for pollinators; however, they fail to meet all resource requirements. They should therefore be used in combination with agri-environmental measures targeted to promote early-season forage (e.g. hedgerows and farm woodlands), open flowers for hoverflies, saprophytic hoverfly larval resources (e.g. ditches and ponds) and nesting habitats (e.g. undisturbed field margins).

A comparison of reading, in people with simulated and actual central vision loss, with static text, horizontally scrolling text, and rapid serial visual presentation.

Reading with central vision loss (CVL), as caused by macular disease, may be enhanced by presenting text using dynamic formats such as horizontally scrolling text or rapid serial visual presentation (RSVP). The rationale for these dynamic text formats is that they can be read while holding gaze away from the text, potentially supporting reading while using the eccentric viewing strategy. This study was designed to evaluate the practice of reading with CVL, with passages of text presented as static sentences, with horizontal scrolling sentences, or as single-word RSVP. In separate studies, normally sighted participants with a simulated (artificial) central scotoma, controlled by an eye-tracker, or participants with CVL resulting from macular degeneration read passages of text using the eccentric viewing technique. Comprehension was better overall with scrolling text when reading with a simulated CVL, whereas RSVP produced lower overall comprehension and high error rates. Analysis of eye movement behavior showed that participants consistently adopted a strategy of making multiple horizontal saccades on the text itself. Adherence to using eccentric viewing was better with RSVP, but this did not translate into better reading performance. Participants with macular degeneration and an actual CVL also showed the highest comprehension and lowest error rates with scrolling text and the lowest comprehension and highest errors with RSVP. We conclude that scrolling text can support effective reading in people with CVL and has potential as a reading aid.

Methane-derived carbon flows into host-virus networks at different trophic levels in soil.

The concentration of atmospheric methane (CH4) continues to increase with microbial communities controlling soil-atmosphere fluxes. While there is substantial knowledge of the diversity and function of prokaryotes regulating CH4 production and consumption, their active interactions with viruses in soil have not been identified. Metagenomic sequencing of soil microbial communities enables identification of linkages between viruses and hosts. However, this does not determine if these represent current or historical interactions nor whether a virus or host are active. In this study, we identified active interactions between individual host and virus populations in situ by following the transfer of assimilated carbon. Using DNA stable-isotope probing combined with metagenomic analyses, we characterized CH4-fueled microbial networks in acidic and neutral pH soils, specifically primary and secondary utilizers, together with the recent transfer of CH4-derived carbon to viruses. A total of 63% of viral contigs from replicated soil incubations contained homologs of genes present in known methylotrophic bacteria. Genomic sequences of 13C-enriched viruses were represented in over one-third of spacers in CRISPR arrays of multiple closely related Methylocystis populations and revealed differences in their history of viral interaction. Viruses infecting nonmethanotrophic methylotrophs and heterotrophic predatory bacteria were also identified through the analysis of shared homologous genes, demonstrating that carbon is transferred to a diverse range of viruses associated with CH4-fueled microbial food networks.

The presence of placeholders modulates the naso-temporal asymmetry in the remote distractor effect.

The remote distractor effect (RDE) is a well-known and robust phenomenon whereby latencies of saccades are increased when a distractor is presented simultaneously along with the saccade target. Studies of the RDE in patients with a loss of vision in one visual field (hemianopia) following damage to primary visual cortex have provided conflicting results. Rafal, Smith, Krantz, Cohen, and Brennan (1990) reported a naso-temporal asymmetry in the RDE in patients with hemianopias, with a greater influence of distractors presented in their blind temporal visual field. This asymmetry was not observed in typically sighted controls. By contrast, Walker, Mannan, Maurer, Pambakian, and Kennard (2000) observed no effect of distractors presented to either the blind nasal or blind temporal hemifield of hemianopes, but the naso-temporal asymmetry was observed in typically sighted controls. The present study addressed one potential methodological differences between the two studies by investigating the inhibitory effect of a distractor on saccade latency in neurotypical participants. Here participants were tested monocularly and the effect of a nasal/temporal hemifield distractor on saccade latency observed in the presence or absence of peripheral placeholders. Our results showed a naso-temporal asymmetry in the magnitude of the RDE in the no placeholder condition, with a greater RDE when the distractor was presented in the temporal visual field. However, in the placeholder condition the opposite asymmetry was observed, that is an increased RDE when the distractor was presented in the nasal visual field. Our results suggest that the presence/absence of a placeholder might be the critical factor explaining the discrepancy between Rafal et al. (1990) and Walker et al. (2000) in participants without visual field loss. The current results can be interpreted in terms of additional inhibitory or attentional processes that bias selection towards stimuli in the nasal hemifield in the presence of placeholders, still, the mechanisms underlying these effects remain unclear.

Association between continuity and access in primary care: a retrospective cohort study.

BACKGROUND: Continuity of care is a tenet of primary care. Our objective was to explore the relation between a change in access to a primary care physician and continuity of care. METHODS: We conducted a retrospective cohort study among physicians in a primary care network in southwest Alberta who measured access consistently between 2009 and 2016. We used time to the third next available appointment as a measure of access to physicians. We calculated the provider and clinic continuity, discontinuity and emergency department use based on the physicians' own panels. Physicians who improved, worsened or maintained their level of access within a given year were assessed in multilevel models to determine the association with continuity of care at the physician and clinic levels and the emergency department. RESULTS: We analyzed data from 190 primary care physicians. Physicians with improved access increased provider continuity by 6.8% per year, reduced discontinuity by 2.1% per year, and decreased emergency department encounters by 78 visits per 1000 patients per year compared to physicians with stable access. Physicians with worsening access had a 6.2% decrease in provider continuity and an increased number of emergency department encounters (64 visits per 1000 panelled patients per year) compared to physicians with stable access. INTERPRETATION: Changes in access to primary care can affect whether patients seek care from their own physician, from another clinic or at the emergency department. Improving access by reducing the delay in obtaining an appointment with one's primary care physician may be one mechanism to improve continuity of care.

Informing Primary Care Changes in Alberta: Continuity and Potential Impacts on Acute Care.

Health systems across Canada are embarking on initiatives to enhance access to primary care services, with the intent of improving patient outcomes and mitigating escalating healthcare costs. However, it is important that such initiatives be carefully weighed with the evidence that the changes will indeed have the desired impact. In Alberta, part of the informative process involved an analysis to examine links between continuity with primary care and utilization of acute care services. The findings provide information regarding expectations for outcomes and potentially useful (and not so useful) measures for monitoring progress and performance.

Increased Word Spacing Improves Performance for Reading Scrolling Text with Central Vision Loss.

SIGNIFICANCE: Scrolling text can be an effective reading aid for those with central vision loss. Our results suggest that increased interword spacing with scrolling text may further improve the reading experience of this population. This conclusion may be of particular interest to low-vision aid developers and visual rehabilitation practitioners. PURPOSE: The dynamic, horizontally scrolling text format has been shown to improve reading performance in individuals with central visual loss. Here, we sought to determine whether reading performance with scrolling text can be further improved by modulating interword spacing to reduce the effects of visual crowding, a factor known to impact negatively on reading with peripheral vision. METHODS: The effects of interword spacing on reading performance (accuracy, memory recall, and speed) were assessed for eccentrically viewed single sentences of scrolling text. Separate experiments were used to determine whether performance measures were affected by any confound between interword spacing and text presentation rate in words per minute. Normally sighted participants were included, with a central vision loss implemented using a gaze-contingent scotoma of 8° diameter. In both experiments, participants read sentences that were presented with an interword spacing of one, two, or three characters. RESULTS: Reading accuracy and memory recall were significantly enhanced with triple-character interword spacing (both measures, P ≤ .01). These basic findings were independent of the text presentation rate (in words per minute). CONCLUSIONS: We attribute the improvements in reading performance with increased interword spacing to a reduction in the deleterious effects of visual crowding. We conclude that increased interword spacing may enhance reading experience and ability when using horizontally scrolling text with a central vision loss.

Evaluation of the nutritive value of legume alternatives to soybean meal for broiler chickens.

Five experiments were conducted to investigate the nutritional value of various legumes and a faba beans processing co-product for broilers. In Expt. 1 and 3, metabolizable energy (AME) content was evaluated for 2 batches of bean starch concentrate (BSC) that differed in physical and chemical characteristics. Standardized ileal amino acid digestibility (SIAAD) was determined for BSC in Expt. 2, and for corn, soybean meal (SBM), organic and conventional faba beans, and quinoa (Expt. 4). The growth performance response of broiler chickens to partial replacement of wheat and SBM with various legumes was investigated in Expt. 5. The AME of the BSC assayed in Expt. 1 was lower (P < 0.01) than that of the BSC assayed in Expt. 3. The SIAAD was generally high for BSC in Expt. 2 although the content and digestibility of sulfur amino acids were low. In Expt. 4, there was no difference in SIAAD of Arg, Phe, Asp, and Gly among the different feedstuffs assayed. SIAAD was largely similar for both conventional and organic faba bean. The SIAADs of Met, Thr, Ser, and Tyr were lower (P < 0.05) for quinoa compared with SBM or corn. In Expt. 5, FCR was greater (P < 0.05) for broiler chickens receiving faba beans+barley mix or lupins compared with the wheat-SBM control diet. Amino acid digestibility was greater (P < 0.01) for the diets containing lupins compared with the other diets except for Lys, Met, Thr, Ala, Asp, and Ser. On the other hand, amino acid digestibility in diet with faba beans+barley mix was lower (P < 0.05) compared with all the other diets, except for Arg, Asp, Lys, and Thr. It was concluded from the current studies that there is scope for using the assayed legumes, co-products, and quinoa in broiler chickens to partly replace SBM as protein feedstuffs.

Nocturnal Enuresis.

Nocturnal enuresis is a common problem that children may present with in a primary care setting. It is important to take a detailed history to rule out secondary causes; however, most cases are primary in nature. It is essential to demystify the problem and reassure parents by educating them that the episodes are nonvolitional and most children outgrow the problem over time. Behavioral interventions are considered first line and are most successful when the child is invested in succeeding. Interventions should be initiated with specific goals in mind. Medications are effective and should be used in conjunction with behavioral interventions.

Evidence for a reduction of the rightward extent of the perceptual span when reading dynamic horizontally scrolling text.

The dynamic horizontally scrolling text format produces a directional conflict in the allocation of attention for reading, with a necessity to track each word leftward (in the direction of movement) concurrently with normal rightward shifts made to progress through the text (in left-to-right orthographies such as English). The gaze-contingent window paradigm was used to compare the extent of the perceptual span in reading of scrolling and static sentences. Across two experiments, this investigation confirmed that the allocation of attentional resources to the right of fixation was compressed with scrolling text. There was no evidence for a reversal of the direction of asymmetry or a confounding shift of landing position. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Spirituality in African-American Breast Cancer Patients: Implications for Clinical and Psychosocial Care.

Spirituality has been shown to be important to many individuals dealing with a cancer diagnosis. While African-American breast cancer survivors have been reported to have higher levels of spirituality compared to White women, little is known about how levels of spirituality may vary among African-American breast cancer survivors. The aims of this study were to examine factors associated with spirituality among African-American survivors and test whether spirituality levels were associated with women's attitudes about treatment or health care. The primary outcome, spirituality, was nine-item scale (Cronbach's α = .99). Participants completed standardized telephone interviews that captured sociocultural, healthcare process, and treatment attitudes. Medical records were abstracted post-adjuvant therapy for treatment and clinical information. In bivariate analysis, age was not correlated with spirituality (p = .40). Married/living as married women had higher levels of spirituality (m = 32.1) than single women (m = 30.1). Contextual factors that were associated with higher levels spirituality were: collectivism (r = .44; p < 0.0001, Afrocentric worldview (r = .185; p = .01), and self-efficacy scale (r = .17; p = .02). In multivariable analysis, sociodemographic factors were not significant. Collectivism remained a robust predictor (p < 0.0001). Attitudes about the efficacy of cancer treatment were not associated with spirituality. The high levels of spirituality in African-American survivors suggest consideration of integrating spiritual care within the delivery of cancer treatment. Future studies should consider how spirituality may contribute to positive coping and/or behaviors in African-American women with high levels of spirituality.