Consumer responses to rebranding to address racism.

In 2020, following the death of George Floyd and the renewed national focus on racism, many food brands with racist names and packages announced they would rebrand. Brands differed in their extent of rebranding (some only removed an image, whereas others also changed a brand name) and differed in the reasons they gave for the rebranding in PR statements and news interviews. At this point, little is known about how consumers responded to these branding changes. To address this, we conducted an online experiment using the case of Aunt Jemima pancake mix to evaluate how changes in the extent of rebranding and the reason for rebranding impact consumers' likelihood of purchase, expected taste, brand liking, and brand trust. We find that removing the image of Aunt Jemima brought moderate reductions to likelihood of purchase and expected taste and no changes to brand liking or brand trust. When the brand name was also changed to Pearl Milling Company we find larger reductions to likelihood of purchase and expected taste and reductions to brand liking and brand trust. Additionally, we find that informing consumers the change was done to address racism partially mitigated losses in likelihood of purchase following renaming the brand but provided no protection when only the image was removed. The information also had no impact on expected taste, brand liking, or brand trust following either image removal or brand name change. Last, we find evidence of heterogeneity in consumer responses across political ideologies, with liberals reacting more positively to the rebranding and conservatives reacting more negatively.

Disparities in autism spectrum disorder diagnoses among 8-year-old children in Colorado: Who are we missing?

LAY ABSTRACT: Although autism can be reliably diagnosed as early as 2 years of age, many children are not diagnosed with autism until much later. We analyzed data to determine why many of the 8-year-old children who resided in Colorado and were identified as having autism through a review of their health and/or educational records did not have a documented clinical diagnosis of autism and were not eligible for special education services under an autism eligibility. We found that children who did not have a documented clinical diagnosis of autism and were not eligible for special education services under an autism eligibility were more likely to be female, aggressive, and argumentative. They had a poorer quality of information in their records and were less likely to have had a developmental regression, sleep problems, or an autism screener or diagnostic measure in their records. These results suggest that the symptoms characteristic of autism among this group of children may have been attributed to another disorder and that clinicians may be able to recognize autism more readily in children with more functional impairment and those who experience a developmental regression. We also discovered that differences in symptom presentations among children who had a documented clinical diagnosis of autism and/or were eligible for special education services under an autism eligibility were associated with different ages at autism diagnosis.

Early Identification of Autism Spectrum Disorder Among Children Aged 4 Years - Early Autism and Developmental Disabilities Monitoring Network, Six Sites, United States, 2016.

PROBLEM/CONDITION: Autism spectrum disorder (ASD). PERIOD COVERED: 2016. DESCRIPTION OF SYSTEM: The Early Autism and Developmental Disabilities Monitoring (Early ADDM) Network, a subset of the overall ADDM Network, is an active surveillance program that estimates ASD prevalence and monitors early identification of ASD among children aged 4 years. Children included in surveillance year 2016 were born in 2012 and had a parent or guardian who lived in the surveillance area in Arizona, Colorado, Missouri, New Jersey, North Carolina, or Wisconsin, at any time during 2016. Children were identified from records of community sources including general pediatric health clinics, special education programs, and early intervention programs. Data from comprehensive evaluations performed by community professionals were abstracted and reviewed by trained clinicians using a standardized ASD surveillance case definition with criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). RESULTS: In 2016, the overall ASD prevalence was 15.6 per 1,000 (one in 64) children aged 4 years for Early ADDM Network sites. Prevalence varied from 8.8 per 1,000 in Missouri to 25.3 per 1,000 in New Jersey. At every site, prevalence was higher among boys than among girls, with an overall male-to-female prevalence ratio of 3.5 (95% confidence interval [CI] = 3.1-4.1). Prevalence of ASD between non-Hispanic white (white) and non-Hispanic black (black) children was similar at each site (overall prevalence ratio: 0.9; 95% CI = 0.8-1.1). The prevalence of ASD using DSM-5 criteria was lower than the prevalence using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) criteria at one of four sites that used criteria from both editions. Among sites where ≥60% of children aged 4 years had information about intellectual disability (intelligence quotient ≤70 or examiner's statement of intellectual disability documented in an evaluation), 53% of children with ASD had co-occurring intellectual disability. Of all children aged 4 years with ASD, 84% had a first evaluation at age ≤36 months and 71% of children who met the surveillance case definition had a previous ASD diagnosis from a community provider. Median age at first evaluation and diagnosis for this age group was 26 months and 33 months, respectively. Cumulative incidence of autism diagnoses received by age 48 months was higher for children aged 4 years than for those aged 8 years identified in Early ADDM Network surveillance areas in 2016. INTERPRETATION: In 2016, the overall prevalence of ASD in the Early ADDM Network using DSM-5 criteria (15.6 per 1,000 children aged 4 years) was higher than the 2014 estimate using DSM-5 criteria (14.1 per 1,000). Children born in 2012 had a higher cumulative incidence of ASD diagnoses by age 48 months compared with children born in 2008, which indicates more early identification of ASD in the younger group. The disparity in ASD prevalence has decreased between white and black children. Prevalence of co-occurring intellectual disability was higher than in 2014, suggesting children with intellectual disability continue to be identified at younger ages. More children received evaluations by age 36 months in 2016 than in 2014, which is consistent with Healthy People 2020 goals. Median age at earliest ASD diagnosis has not changed considerably since 2014. PUBLIC HEALTH ACTION: More children aged 4 years with ASD are being evaluated by age 36 months and diagnosed by age 48 months, but there is still room for improvement in early identification. Timely evaluation of children by community providers as soon as developmental concerns have been identified might result in earlier ASD diagnoses, earlier receipt of evidence-based interventions, and improved developmental outcomes.

Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2016.

PROBLEM/CONDITION: Autism spectrum disorder (ASD). PERIOD COVERED: 2016. DESCRIPTION OF SYSTEM: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance program that provides estimates of the prevalence of ASD among children aged 8 years whose parents or guardians live in 11 ADDM Network sites in the United States (Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin). Surveillance is conducted in two phases. The first phase involves review and abstraction of comprehensive evaluations that were completed by medical and educational service providers in the community. In the second phase, experienced clinicians who systematically review all abstracted information determine ASD case status. The case definition is based on ASD criteria described in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. RESULTS: For 2016, across all 11 sites, ASD prevalence was 18.5 per 1,000 (one in 54) children aged 8 years, and ASD was 4.3 times as prevalent among boys as among girls. ASD prevalence varied by site, ranging from 13.1 (Colorado) to 31.4 (New Jersey). Prevalence estimates were approximately identical for non-Hispanic white (white), non-Hispanic black (black), and Asian/Pacific Islander children (18.5, 18.3, and 17.9, respectively) but lower for Hispanic children (15.4). Among children with ASD for whom data on intellectual or cognitive functioning were available, 33% were classified as having intellectual disability (intelligence quotient [IQ] ≤70); this percentage was higher among girls than boys (39% versus 32%) and among black and Hispanic than white children (47%, 36%, and 27%, respectively) [corrected]. Black children with ASD were less likely to have a first evaluation by age 36 months than were white children with ASD (40% versus 45%). The overall median age at earliest known ASD diagnosis (51 months) was similar by sex and racial and ethnic groups; however, black children with IQ ≤70 had a later median age at ASD diagnosis than white children with IQ ≤70 (48 months versus 42 months). INTERPRETATION: The prevalence of ASD varied considerably across sites and was higher than previous estimates since 2014. Although no overall difference in ASD prevalence between black and white children aged 8 years was observed, the disparities for black children persisted in early evaluation and diagnosis of ASD. Hispanic children also continue to be identified as having ASD less frequently than white or black children. PUBLIC HEALTH ACTION: These findings highlight the variability in the evaluation and detection of ASD across communities and between sociodemographic groups. Continued efforts are needed for early and equitable identification of ASD and timely enrollment in services.

Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 4 Years - Early Autism and Developmental Disabilities Monitoring Network, Seven Sites, United States, 2010, 2012, and 2014.

PROBLEM/CONDITION: Autism spectrum disorder (ASD) is estimated to affect up to 3% of children in the United States. Public health surveillance for ASD among children aged 4 years provides information about trends in prevalence, characteristics of children with ASD, and progress made toward decreasing the age of identification of ASD so that evidence-based interventions can begin as early as possible. PERIOD COVERED: 2010, 2012, and 2014. DESCRIPTION OF SYSTEM: The Early Autism and Developmental Disabilities Monitoring (Early ADDM) Network is an active surveillance system that provides biennial estimates of the prevalence and characteristics of ASD among children aged 4 years whose parents or guardians lived within designated sites. During surveillance years 2010, 2012, or 2014, data were collected in seven sites: Arizona, Colorado, Missouri, New Jersey, North Carolina, Utah, and Wisconsin. The Early ADDM Network is a subset of the broader ADDM Network (which included 13 total sites over the same period) that has been conducting ASD surveillance among children aged 8 years since 2000. Each Early ADDM site covers a smaller geographic area than the broader ADDM Network. Early ADDM ASD surveillance is conducted in two phases using the same methods and project staff members as the ADDM Network. The first phase consists of reviewing and abstracting data from children's records, including comprehensive evaluations performed by community professionals. Sources for these evaluations include general pediatric health clinics and specialized programs for children with developmental disabilities. In addition, special education records (for children aged ≥3 years) were reviewed for Arizona, Colorado, New Jersey, North Carolina, and Utah, and early intervention records (for children aged 0 to <3 years) were reviewed for New Jersey, North Carolina, Utah, and Wisconsin; in Wisconsin, early intervention records were reviewed for 2014 only. The second phase involves a review of the abstracted evaluations by trained clinicians using a standardized case definition and method. A child is considered to meet the surveillance case definition for ASD if one or more comprehensive evaluations of that child completed by a qualified professional describes behaviors consistent with the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision (DSM-IV-TR) diagnostic criteria for any of the following conditions: autistic disorder, pervasive developmental disorder-not otherwise specified (PDD-NOS, including atypical autism), or Asperger disorder (2010, 2012, and 2014). For 2014 only, prevalence estimates based on surveillance case definitions according to DSM-IV-TR and the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) were compared. This report provides estimates of overall ASD prevalence and prevalence by sex and race/ethnicity; characteristics of children aged 4 years with ASD, including age at first developmental evaluation, age at ASD diagnosis, and cognitive function; and trends in ASD prevalence and characteristics among Early ADDM sites with data for all 3 surveillance years (2010, 2012, and 2014), including comparisons with children aged 8 years living in the same geographic area. Analyses of time trends in ASD prevalence are restricted to the three sites that contributed data for all 3 surveillance years with consistent data sources (Arizona, Missouri, and New Jersey). RESULTS: The overall ASD prevalence was 13.4 per 1,000 children aged 4 years in 2010, 15.3 in 2012, and 17.0 in 2014 for Early ADDM sites with data for the specific years. ASD prevalence was determined using a surveillance case definition based on DSM-IV-TR. Within each surveillance year, ASD prevalence among children aged 4 years varied across surveillance sites and was lowest each year for Missouri (8.5, 8.1, and 9.6 per 1,000, for 2010, 2012, and 2014, respectively) and highest each year for New Jersey (19.7, 22.1, and 28.4 per 1,000, for the same years, respectively). Aggregated prevalence estimates were higher for sites that reviewed education and health care records than for sites that reviewed only health care records. Among all participating sites and years, ASD prevalence among children aged 4 years was consistently higher among boys than girls; prevalence ratios ranged from 2.6 (Arizona and Wisconsin in 2010) to 5.2 boys per one girl (Colorado in 2014). In 2010, ASD prevalence was higher among non-Hispanic white children than among Hispanic children in Arizona and non-Hispanic black children in Missouri; no other differences were observed by race/ethnicity. Among four sites with ≥60% data on cognitive test scores (Arizona, New Jersey, North Carolina, and Utah), the frequency of co-occurring intellectual disabilities was significantly higher among children aged 4 years than among those aged 8 years for each site in each surveillance year except Arizona in 2010. The percentage of children with ASD who had a first evaluation by age 36 months ranged from 48.8% in Missouri in 2012 to 88.9% in Wisconsin in 2014. The percentage of children with a previous ASD diagnosis from a community provider varied by site, ranging from 43.0% for Arizona in 2012 to 86.5% for Missouri in 2012. The median age at earliest known ASD diagnosis varied from 28 months in North Carolina in 2014 to 39.0 months in Missouri and Wisconsin in 2012. In 2014, the ASD prevalence based on the DSM-IV-TR case definition was 20% higher than the prevalence based on the DSM-5 (17.0 versus 14.1 per 1,000, respectively). Trends in ASD prevalence and characteristics among children aged 4 years during the study period were assessed for the three sites with data for all 3 years and consistent data sources (Arizona, Missouri, and New Jersey) using the DSM-IV-TR case definition; prevalence was higher in 2014 than in 2010 among children aged 4 years in New Jersey and was stable in Arizona and Missouri. In Missouri, ASD prevalence was higher among children aged 8 years than among children aged 4 years. The percentage of children with ASD who had a comprehensive evaluation by age 36 months was stable in Arizona and Missouri and decreased in New Jersey. In the three sites, no change occurred in the age at earliest known ASD diagnosis during 2010-2014. INTERPRETATION: The findings suggest that ASD prevalence among children aged 4 years was higher in 2014 than in 2010 in one site and remained stable in others. Among children with ASD, the frequency of cognitive impairment was higher among children aged 4 years than among those aged 8 years and suggests that surveillance at age 4 years might more often include children with more severe symptoms or those with co-occurring conditions such as intellectual disability. In the sites with data for all years and consistent data sources, no change in the age at earliest known ASD diagnosis was found, and children received their first developmental evaluation at the same or a later age in 2014 compared with 2010. Delays in the initiation of a first developmental evaluation might adversely affect children by delaying access to treatment and special services that can improve outcomes for children with ASD. PUBLIC HEALTH ACTION: Efforts to increase awareness of ASD and improve the identification of ASD by community providers can facilitate early diagnosis of children with ASD. Heterogeneity of results across sites suggests that community-level differences in evaluation and diagnostic services as well as access to data sources might affect estimates of ASD prevalence and age of identification. Continuing improvements in providing developmental evaluations to children as soon as developmental concerns are identified might result in earlier ASD diagnoses and earlier receipt of services, which might improve developmental outcomes.

Assessment of racial and ethnic bias in autism spectrum disorder prevalence estimates from a US surveillance system.

This study assessed potential under-ascertainment of autism spectrum disorder due to missing administrative information for Hispanic and non-Hispanic Black children within the Autism and Developmental Disabilities Monitoring Network. We analyzed data from two Network sites (Colorado and Wisconsin) for surveillance years 2012 and 2014 to determine whether children excluded from autism spectrum disorder prevalence estimates due to missing residency and other information differed from those included by race and ethnicity. We used multiple approaches to impute missing information to evaluate impacts on racial and ethnic disparities in autism spectrum disorder prevalence. Compared with confirmed autism spectrum disorder cases, those excluded due to missing residency were more than twice as likely to be Hispanic (19% vs 44%; p < 0.002), yet the number of cases excluded due to missing residency information was too small to account for prevalence differences. Confirmation of autism spectrum disorder case status was more likely for children with relevant health records than for those with school records only. Moreover, relevant health records were more likely to be missing for Black and Hispanic children than for White children. Observed disparities in autism spectrum disorder prevalence were not accounted for by missing demographic data, but may reflect disparities in healthcare access for developmental evaluations.

Diet Quality and Nutrient Intake of Urban Overweight and Obese Primarily African American Older Adults with Osteoarthritis.

Diet quality may be a unique target for preventing and managing obesity-related osteoarthritis (OA). Using the Healthy Eating Index-2010 (HEI-2010), this study examined the nutrient intake and diet quality of 400 urban overweight and obese primarily African American older adults with self-reported lower extremity OA. Associations between sociodemographic and health-related factors and diet quality were explored. Participants (mean age 67.8 years, SD 5.9) were included. Habitual dietary intake was assessed using a food frequency questionnaire (FFQ). Nutrient intake and diet quality were calculated from the FFQ. Results indicated that diet quality needs improvement (HEI-2010: 66.3 (SD 10.5)). Age, body mass index, employment (multivariable model only), and OA severity (bivariate model only) were significant predictors of HEI-2010 total score in linear models. Mean intakes for fiber, calcium, and vitamin D were below recommendations, while percentage of calories as total fat exceeded recommendations. These findings can inform future dietary intervention trials and public health messaging for a sub-population at a high risk for obesity-related OA.

Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2014.

PROBLEM/CONDITION: Autism spectrum disorder (ASD). PERIOD COVERED: 2014. DESCRIPTION OF SYSTEM: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system that provides estimates of the prevalence of autism spectrum disorder (ASD) among children aged 8 years whose parents or guardians reside within 11 ADDM sites in the United States (Arizona, Arkansas, Colorado, Georgia, Maryland, Minnesota, Missouri, New Jersey, North Carolina, Tennessee, and Wisconsin). ADDM surveillance is conducted in two phases. The first phase involves review and abstraction of comprehensive evaluations that were completed by professional service providers in the community. Staff completing record review and abstraction receive extensive training and supervision and are evaluated according to strict reliability standards to certify effective initial training, identify ongoing training needs, and ensure adherence to the prescribed methodology. Record review and abstraction occurs in a variety of data sources ranging from general pediatric health clinics to specialized programs serving children with developmental disabilities. In addition, most of the ADDM sites also review records for children who have received special education services in public schools. In the second phase of the study, all abstracted information is reviewed systematically by experienced clinicians to determine ASD case status. A child is considered to meet the surveillance case definition for ASD if he or she displays behaviors, as described on one or more comprehensive evaluations completed by community-based professional providers, consistent with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) diagnostic criteria for autistic disorder; pervasive developmental disorder-not otherwise specified (PDD-NOS, including atypical autism); or Asperger disorder. This report provides updated ASD prevalence estimates for children aged 8 years during the 2014 surveillance year, on the basis of DSM-IV-TR criteria, and describes characteristics of the population of children with ASD. In 2013, the American Psychiatric Association published the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), which made considerable changes to ASD diagnostic criteria. The change in ASD diagnostic criteria might influence ADDM ASD prevalence estimates; therefore, most (85%) of the records used to determine prevalence estimates based on DSM-IV-TR criteria underwent additional review under a newly operationalized surveillance case definition for ASD consistent with the DSM-5 diagnostic criteria. Children meeting this new surveillance case definition could qualify on the basis of one or both of the following criteria, as documented in abstracted comprehensive evaluations: 1) behaviors consistent with the DSM-5 diagnostic features; and/or 2) an ASD diagnosis, whether based on DSM-IV-TR or DSM-5 diagnostic criteria. Stratified comparisons of the number of children meeting either of these two case definitions also are reported. RESULTS: For 2014, the overall prevalence of ASD among the 11 ADDM sites was 16.8 per 1,000 (one in 59) children aged 8 years. Overall ASD prevalence estimates varied among sites, from 13.1-29.3 per 1,000 children aged 8 years. ASD prevalence estimates also varied by sex and race/ethnicity. Males were four times more likely than females to be identified with ASD. Prevalence estimates were higher for non-Hispanic white (henceforth, white) children compared with non-Hispanic black (henceforth, black) children, and both groups were more likely to be identified with ASD compared with Hispanic children. Among the nine sites with sufficient data on intellectual ability, 31% of children with ASD were classified in the range of intellectual disability (intelligence quotient [IQ] <70), 25% were in the borderline range (IQ 71-85), and 44% had IQ scores in the average to above average range (i.e., IQ >85). The distribution of intellectual ability varied by sex and race/ethnicity. Although mention of developmental concerns by age 36 months was documented for 85% of children with ASD, only 42% had a comprehensive evaluation on record by age 36 months. The median age of earliest known ASD diagnosis was 52 months and did not differ significantly by sex or race/ethnicity. For the targeted comparison of DSM-IV-TR and DSM-5 results, the number and characteristics of children meeting the newly operationalized DSM-5 case definition for ASD were similar to those meeting the DSM-IV-TR case definition, with DSM-IV-TR case counts exceeding DSM-5 counts by less than 5% and approximately 86% overlap between the two case definitions (kappa = 0.85). INTERPRETATION: Findings from the ADDM Network, on the basis of 2014 data reported from 11 sites, provide updated population-based estimates of the prevalence of ASD among children aged 8 years in multiple communities in the United States. The overall ASD prevalence estimate of 16.8 per 1,000 children aged 8 years in 2014 is higher than previously reported estimates from the ADDM Network. Because the ADDM sites do not provide a representative sample of the entire United States, the combined prevalence estimates presented in this report cannot be generalized to all children aged 8 years in the United States. Consistent with reports from previous ADDM surveillance years, findings from 2014 were marked by variation in ASD prevalence when stratified by geographic area, sex, and level of intellectual ability. Differences in prevalence estimates between black and white children have diminished in most sites, but remained notable for Hispanic children. For 2014, results from application of the DSM-IV-TR and DSM-5 case definitions were similar, overall and when stratified by sex, race/ethnicity, DSM-IV-TR diagnostic subtype, or level of intellectual ability. PUBLIC HEALTH ACTION: Beginning with surveillance year 2016, the DSM-5 case definition will serve as the basis for ADDM estimates of ASD prevalence in future surveillance reports. Although the DSM-IV-TR case definition will eventually be phased out, it will be applied in a limited geographic area to offer additional data for comparison. Future analyses will examine trends in the continued use of DSM-IV-TR diagnoses, such as autistic disorder, PDD-NOS, and Asperger disorder in health and education records, documentation of symptoms consistent with DSM-5 terminology, and how these trends might influence estimates of ASD prevalence over time. The latest findings from the ADDM Network provide evidence that the prevalence of ASD is higher than previously reported estimates and continues to vary among certain racial/ethnic groups and communities. With prevalence of ASD ranging from 13.1 to 29.3 per 1,000 children aged 8 years in different communities throughout the United States, the need for behavioral, educational, residential, and occupational services remains high, as does the need for increased research on both genetic and nongenetic risk factors for ASD.

Enhancing Dental Students' Understanding of Poverty Through Simulation.

Dental students should develop an understanding of the barriers to and frustrations with accessing dental care and maintaining optimal oral health experienced by persons with limited resources rather than blaming the patient or caregiver. Developing this understanding may be aided by helping students learn about the lives of underserved and vulnerable patients they will encounter not only in extramural rotations, but throughout their careers. The aim of this study was to determine if dental students' understanding of daily challenges faced by families with low income changed as a result of a poverty simulation. In 2015 and 2016, an experiential poverty simulation was used to prepare third-year dental students at one U.S. dental school for their upcoming required community-based rotations. In 2015, United Way staff conducted the simulation using the Missouri Community Action Poverty Simulation (CAPS); in 2016, faculty members trained in CAPS conducted the simulation using a modified version of the tool. In the simulation, students were assigned to family units experiencing various types of hardship and were given specific identities for role-playing. A retrospective pretest and a posttest were used to assess change in levels of student understanding after the simulation. Students assessed their level of understanding in five domains: financial pressures, difficult choices, difficulties in improving one's situation, emotional stressors, and impact of community resources for those living in poverty. The survey response rates in 2015 and 2016 were 86% and 74%, respectively. For each of the five domains, students' understanding increased from 58% to 74% per domain. The majority reported that the exercise was very valuable or somewhat valuable (74% in 2015, 88% in 2016). This study found that a poverty simulation was effective in raising dental students' understanding of the challenges faced by low-income families. It also discovered that framing the issues in the context of accessing dental care was important.

More Than Numbers: Effects of Social Media Virality Metrics on Intention to Help Unknown Others in the Context of Bone Marrow Donation.

A bone marrow transplant is often the only key to recovery and survival for patients suffering from blood cancers. Social media platforms have allowed nonprofit organizations as well as family members and friends of patients in need of a matching donor to make their solicitation messages go viral and reach out to the broadest possible audience to increase the likelihood of finding a matching donor. Noting that social media audiences are exposed not only to the content of a social media message but also to the metrics representing the virality of the message (i.e., how many times the content has been shared), we conducted an online experiment to investigate the effects of virality metrics on perceived social norms and behavioral intention to join a bone marrow registry. In doing so, we considered the potential moderating role of perceived threat posed by blood cancers. The experiment was conducted with 152 participants who met the general eligibility guidelines set by the National Marrow Donor Program (NMDP). The results of the experiment showed that exposure to high virality metrics led to greater perceived injunctive norms. The results also revealed that the effect of virality metrics on perceived injunctive norms was significant among those perceiving low levels of blood cancer threat. Furthermore, the results demonstrated that high virality metrics led to greater intention to join a bone marrow registry through perceived injunctive norms only when perceived threat of blood cancers was low. Theoretical and practical implications of these findings are discussed.

Attitudinal factors protective against youth smoking: an integrative review.

PURPOSE: This review examines recent literature with the purpose of uncovering associations between attitudinal factors and smoking among youth populations. ORGANIZING CONSTRUCT AND METHODS: Researchers conducted an integrative review of the literature in late 2012 and early 2013. As inclusion criteria, potential articles were measured against the following statement: "There is valid evidence of (an) attitudinal factor(s) potentially associated with smoking among youth." FINDINGS: Researchers employed the salutogenic model as a theoretical framework to analyze search results. The narrative synthesis indicates that primary attitudinal factors protective against smoking among youth include the following: (a) a perception that there is little benefit to smoking, (b) a belief that smoking is likely harmful and addictive in the short term, and (c) a denial that smoking provides stress abatement, makes one look cool or more grown-up, or is common and accepted. Moreover, research signals that youth who smoke often demonstrate essentially the opposite beliefs and attitudes. CONCLUSIONS: Findings suggest attitudinal factors play a role in protection against youth smoking. Those youth who assign realistic values to smoking risks and benefits are more equipped to engage in the health-protective behavior of not smoking. Youth, adolescents, and young adults appear vulnerable to inappropriate designation of risk and benefit values of smoking. Theoretical interpretation suggests that bolstering attitudinal factors during youth might counteract immature risk assessment. These findings justify further research related to protective mechanisms against youth smoking and youth-based smoking prevention interventions. CLINICAL RELEVANCE: The establishment of associations between attitudinal factors and protection against smoking can help determine interventions effective in reducing smoking among youth.

Genetic diversity of the Kaposi's sarcoma herpesvirus K1 protein in AIDS-KS in Zimbabwe.

BACKGROUND: Kaposi's sarcoma-associated herpesvirus (KSHV) encodes genetically diverse K1 alleles which have unique geographic distributions. Little is known about K1 genetic diversity in Zimbabwe where acquired immunodeficiency syndrome-associated KS (AIDS-KS) is epidemic. OBJECTIVE: Evaluate K1 diversity in Zimbabwe and compare Zimbabwean K1 diversity to other areas in Africa. STUDY DESIGN: K1 nucleotide sequence was determined for AIDS-KS cases in Zimbabwe. K1 references sequences were obtained from Genbank. RESULTS: Among 65 Zimbabwean AIDS-KS cases, 26 (40%) were K1 subtype A and 39 (60%) were subtype B. Zimbabwean subtype A sequences grouped only with African intratype A5 variants. Zimbabwean subtype B sequences grouped with multiple intratype African variants: 26 B1 (26%), four B3 (6%) and nine highly divergent B4 (14%). Zimbabwean subtype B had a lower synonymous to nonsynonymous mutation ratio (median 0.59 versus 0.66; P=0.008) and greater distance to the most recent common ancestor (median 0.03 versus 0.009; P<0.001) compared to subtype A. Within the B subgroup, the distribution of intratype B variants differed in Zimbabwe and Uganda (P=0.004). CONCLUSIONS: Greater positive selection and genetic diversity in K1 subtype B compared to subtype A5 exist in Zimbabwe. However, there were no significant associations between K1 subtype and the clinical or demographic characteristics of AIDS-KS cases.

Varicella virus-mononuclear cell interaction.

Varicella zoster virus (VZV) causes varicella (chickenpox), becomes latent in cranial nerve, dorsal root, and autonomic ganglia; and reactivates decades later to produce zoster (shingles). The main complication of zoster is postherpetic neuralgia (PHN), pain that persists for months and often years after zoster. VZV also causes chronic radicular pain without rash (zoster sine herpete). Viremia is associated with each stage of VZV infection. Viral DNA has been found in peripheral blood mononuclear cells (MNCs) of patients with varicella, zoster, PHN, and zoster sine herpete. In varicella, viremia contributes to the widespread distribution of skin lesions and infection of multiple organs. Although the role of viremia in other VZV-associated diseases is not as clear, the detection of VZV DNA (and sometimes VZV RNA and proteins) helps diagnose neurological diseases produced by VZV, has indicated that PHN may reflect a chronic VZV ganglionitis, and has established that VZV reactivates subclinically, especially in immunocompromised humans. In vitro studies have established that VZV can productively infect MNCs for a short time and have identified the subpopulations of MNCs that are infected. Finally, simian varicella virus (SVV) infection of nonhuman primates shares clinical, pathological, and virologic features with VZV in humans. Like VZV, SV viremia in nonhuman primates during acute infection plays an important role in the pathogenesis of SVV. Infectious virus can be isolated from MNCs, and SVV DNA can be detected in MNCs during varicella. Further, SVV DNA can be detected for months in MNCs of monkeys after experimental infection with SVV. Herein, we review the current literature related to VZV infection of MNCs during naturally occurring varicella, PHN, and zoster sine herpete in humans, including studies of experimental infection of human MNCs with VZV. We also review SVV MNC interaction during naturally occurring simian varicella and after experimental infection of primates with SVV.

Persistence of simian varicella virus DNA in CD4(+) and CD8(+) blood mononuclear cells for years after intratracheal inoculation of African green monkeys.

Simian varicella virus (SVV) DNA was detected in blood mononuclear cells (MNCs) of adult African green monkeys 7 days to 23 months after intratracheal inoculation with 10(3) plaque forming units. Infectious virus was not detected in MNCs at 14 months postinfection (p.i.), and electron microscopic (EM) analysis of MNCs from two monkeys 21 months p.i. did not reveal virus particles. Real-time quantitative PCR analysis of DNA from blood MNCs taken at multiple intervals from SVV-infected monkeys M7 and M8 revealed a 10- to 100-fold decrease, but not clearance of SVV DNA in MNCs between 11 and 17 months p.i. Thereafter, the SVV DNA copy number did not decrease further between 17 and 23 months p.i. PCR analysis of MNCs sorted by flow cytometry revealed SVV DNA in T cells (CD4(+), CD8(+)) and B cells (CD20(+)), but not in monocyte-macrophages (CD14(+)), 10 days p.i. At 11 and 23 months p.i., SVV DNA was found exclusively in CD4(+) and CD8(+) T cells. Whether the detection of SVV DNA in CD4(+) and CD8(+) MNCs many months after the resolution of acute varicella reflects continued infection of these cells that began at the time of acute varicella or represents infection acquired by MNCs trafficking through infected tissues is unknown.

Simian varicella virus DNA is present and transcribed months after experimental infection of adult African green monkeys.

To study the pathogenesis of simian varicella virus (SVV) infection in its natural primate host, we inoculated adult SVV-seronegative African green monkeys intratracheally with 10(3)-10(4) PFU of SVV, sacrificed them 11 days, 2, 5, 10, and 12 months postinfection (p.i.), and examined lung, liver, and ganglia for SVV DNA and RNA. PCR analysis revealed SVV DNA in ganglia and viscera at 11 days and 2, 5, and 10 months p.i. Similarly, SVV transcripts corresponding to immediate early (IE), putative early (E), and late (L) SVV open-reading frames (ORFs) were found in liver, lung, and ganglia of most monkeys at multiple intervals for the 12-month study period. SVV-specific antigens were detected in ganglia and liver during acute varicella, but not in ganglia 12 months p.i. Analysis of control tissue (ganglia, lung, and liver) from uninfected SVV-seronegative adult African green monkeys did not reveal SVV DNA, SVV RNA, SVV-specific antigen, or varicella-specific pathological changes. Overall, intratracheal inoculation of SVV in African green monkeys resulted in the presence of viral DNA and transcription of multiple viral genes in many tissues for months after experimental infection.