Development and Preliminary Validation of Stigma Measures for Care Partners of Persons Who Are d/Deaf or Hard of Hearing.

OBJECTIVES: A great deal of literature documents the significant demands, both physical and psychosocial, that care partners experience when providing care to persons with a range of health conditions. There is, however, far less research available on care partners of adult persons who are d/Deaf or hard of hearing (d/DHH). In response to this gap, the authors developed measures of d/DHH stigma among care partners as part of the work of the Lancet Commission on Hearing Loss' Measures, Models, and Stigma Reduction Subgroup. The measures examined in this article are part of a larger set of parallel measures to enable comparison of stigma measurement across groups. DESIGN: The present study describes the preliminary validation of five stigma scales specifically tailored for use to assess the prevalence and effect of stigma on the care partners of adult people who are d/DHH in the United States. Care partners in this context are defined broadly and can include spouses, partners, adult children, siblings, and friends of persons who are d/DHH. The scales describe the care partner's own assessment of how the person who is d/DHH experiences and perceives stigma as well as the care partner's own internalized, experienced, and perceived stigma as a result of their association with a person who is d/DHH. This latter set of three scales describes secondary stigma, or the stigma a person experiences related to their association with a member of a stigmatized group. Measures were developed through a process that included a literature review, Delphi groups with people who became d/DHH after they developed spoken language, cognitive interviews, and a pretest. An online, self-administered preliminary validation survey was conducted with 151 care partners. RESULTS: Results support the internal reliability of each of the five stigma scales (ordinal α's all greater than 0.9) and that each scale is assessing a single factor. CONCLUSIONS: Additional testing is needed to confirm the validity of these measures. After further validation, they can be used to assess the prevalence and effect of stigma on care partners of persons who are d/DHH and to evaluate the success of interventions developed to address stigma and its effects both on the care partner and the person who is d/DHH and receiving the care.

Preliminary Validation of Experienced Ageism Measures With Four Populations in the United States.

OBJECTIVES: Ageism appears widely across the globe and poses an important threat to older people's well-being and health. With respect to hearing health, experiences, perceptions, and fear of ageism can delay the diagnosis of hearing loss, reduce pursuit of hearing care, and fuel reluctance to wear a hearing device. Ageism intertwines with hearing loss stigma, which potentially deepens the negative effects of both; however, little evidence exists to quantify the effects of the intersection of ageism and hearing loss stigma. This lack of data on both hearing loss stigma and ageism, and their intersection, may stem from the lack of validated measures for both. Therefore, as part of a parent study to develop and preliminarily validate d/Deaf and hard of hearing stigma measures, we also adapted and preliminarily validated measures of both experienced and observed ageism. DESIGN: We adapted four ageism measures through a literature review, expert discussions, and cognitive interviews and validated them in the United States through self-administered online surveys with convenience samples of (1) people aged 60 and older who became d/Deaf or hard of hearing (d/DHH) after developing language or in adulthood ("acquired" d/DHH), (2) care partners of people aged 60 or older who are d/DHH (acquired), (3) health care providers, and (4) the general population. For each of the scales, we applied exploratory factor analysis and estimated scale reliability with ordinal α. RESULTS: For the population of persons over age 60 who are d/DHH (acquired) (N = 146), nine social stigma items and four employment discrimination items loaded well onto two separate factors, one which measures social stigma and one which measures employment discrimination. All loadings were >0.7. The two factors were moderately correlated at 0.428. For care partners of people aged 60 or older who are d/DHH (N = 72), nine items loaded well onto a single factor, with loadings between 0.650 and 0.936 and an ordinal α of 0.95. Among the general population (N = 312), 10 items loaded cleanly onto a single factor, with loadings between 0.702 and 0.919 and an ordinal α of 0.96. For the health care providers (N = 203), 11 items loaded well onto a single factor, with loadings between 0.541 and 0.874. For these three populations, each of the single factors measure social stigma. CONCLUSIONS: Ageism threatens the health and wellbeing of older people in both high- and low-income countries. Validated measures of ageism are necessary to understand the relationship between ageism, d/DHH stigma and the well-being of older adults and to design effective ageism-reduction and mitigation interventions. This preliminary validated set of experienced ageism measures offers a starting point for more studies that not only further validate these measures but are larger in scale, occur in more diverse settings, and provide insights into the experience of ageism and its effects on the health and well-being of older adults.

Preliminary Validation of Hearing Device-Related Stigma Measures in Four United States Populations.

OBJECTIVES: Although hearing devices such as cochlear implants and hearing aids often improve communication, many people who are d/Deaf or hard of hearing (d/DHH) choose not to use them. Hearing device-related stigma, or negative societal beliefs about people who use hearing devices, often drives this decision. Although much research has documented the negative effects of hearing device-related stigma, no widely accepted, validated measure to quantify such stigma across populations currently exists. In this article, we describe the preliminary validation of four distinct but related scales measuring hearing device-related stigma in different populations, including people who use hearing devices and those close to them. DESIGN: We preliminarily validated four measures for quantifying hearing device-related stigma in different populations that were previously developed and refined through a literature review, Delphi interviews, cognitive interviews, and a pretest. We preliminarily validated these measures through self-administered online surveys in a convenience sample in the United States. Among participants who use a hearing device and who either (a) self-identified as being d/DHH before they developed language (lifelong; n = 78) or (b) those who self-identified as having acquired a d/DHH identity after they developed language (acquired n = 71), we validated an anticipated hearing device-related stigma scale (d/DHHS-LE-HDA). We validated three scales that measure perceived hearing device-related stigma observed by parents of children who are d/DHH and who use a hearing device (n = 79) (d/DHHS-P-HDPO), care partners of adults who are d/DHH and use a hearing device (n = 108) (d/DHHS-CP-HDPO), and health care providers (n = 203) (d/DHHS-HCP-HDSH). Exploratory factor analysis assessed the reliability of each measure. RESULTS: Each of the four scales loaded onto one factor. Factor loadings for the eight-item scale measuring anticipated hearing device-related stigma among the two populations with lived experience ranged from 0.635 to 0.910, with an ordinal α of 0.93 in the lifelong d/DHH participants and 0.94 among the acquired d/DHH participants. The six-item scale of perceived stigma observed by parents had item loadings from 0.630 to 0.920 (α = 0.91). The nine-item scale of hearing device-related stigma observed by care partners had item loadings from 0.554 to 0.922 (α = 0.95). The eight-item scale of hearing device-related stigma reported by health care providers had item loadings from 0.647 to 0.941 (α = 0.89). CONCLUSIONS: Preliminary validation results show that the four stigma measures perform well in their respective populations. The anticipated stigma scale performed similarly well for both lifelong d/DHH and acquired d/DHH, which suggests that it could perform well in different contexts. Future research should further validate the scales described here as well as measure hearing device-related stigma in different populations-including people who live in different geographic regions and people using different kinds of hearing devices-and evaluate the success of interventions developed to reduce hearing device-related stigma.

Research Agenda and Applications for Preliminarily Validated Measures of d/Deaf and Hard of Hearing Stigma.

In this special supplement of Ear and Hearing, we have presented preliminarily validated measures for stigma related to being d/Deaf or hard of hearing (d/DHH) in the United States and Ghana. In this concluding article, we suggest avenues for the future refinement and use of these measures. First, the measures should be further validated. Second, they should be used to assess the current state of d/DHH stigma and the importance of different kinds of stigma in different populations, which should in turn drive the development of interventions to reduce d/DHH stigma. Third, these measures can assist in evaluating the effectiveness and cost-effectiveness of those interventions. The evidence from this work can then inform investment cases and cost-of-condition studies, which will support advocacy efforts and policy development for reducing stigma and improving the lives of people who are d/DHH.

Preliminary Validation of Stigma Measures Among Parents of Children Who Are d/Deaf or Hard of Hearing in the United States and Ghana.

OBJECTIVES: Parents are integral to the development and overall well-being of their child. Previous research has studied the emotional effects parenting experiences have on parents. However, parents caring for children with disabilities have unique parenting experiences, filled with both victories and challenges. Parenting a child with disabilities can bring additional responsibilities as parents respond to their child's special needs. Specifically, parents of children who are d/Deaf or hard of hearing (d/DHH) are required to make ongoing life-changing decisions about their child's life, including mode of communication, medical care, and education. Across the world, many adults who are d/DHH experience stigma. However, less is known about the stigma faced by children who are d/DHH and their parents. Measuring the nature and magnitude of stigma-affecting parents of children who are d/DHH could offer insights into how to additionally support these parents. Nonetheless, there is a gap in validated scales to measure stigma among parents of children who are d/DHH. In response, we developed and preliminarily validated five measures of stigma among parents of children who are d/DHH. DESIGN: Measures were developed through a mixed-method process: (1) a scoping literature review, (2) a modified Delphi process consisting of two group discussions (n = 3, n = 4) and two individual discussions with parents of children who are d/DHH from high-income countries (HICs) and low- and middle-income countries (LMICs), (3) cognitive interviews with parents of children who are d/DHH in the United States (U.S.) (n = 5) and Ghana (n = 5), and (4) a pretest of the survey in the U.S. (n = 28) and Ghana (n = 30). Modifications to the measures were made after each stage. This article focuses on evaluating the psychometric performance of the developed measures. Parents were recruited in the U.S. (n = 100) and Ghana (n = 173). Convenience sampling was used in both countries. In Ghana, survey administration was in-person with trained interviewers collecting data on tablets. In the U.S. data were collected online through self-administered surveys. RESULTS: The final five scales measured: (1) parental observation of stigma their child experiences (seven items), (2) parental perceptions of stigma toward their child (eight items), (3) parental secondary experienced stigma (eight items), (4) perceived parental secondary stigma (five items), and (5) parental internalized stigma (seven items). All scales performed strongly and similarly across both country samples. The scales had ordinal αs ranging from 0.864 to 0.960, indicating strong reliability. CONCLUSIONS: This study provides a set of preliminarily validated stigma measures to capture the experience of parents of children who are d/DHH. Measuring stigma among parents is critical to understanding parental mental health, as parental well-being affects the health and development of their child. Furthermore, measuring observed stigma by parents can allow the researcher to gain an understanding of the stigma experienced by children who are d/DHH that they may not be able to communicate. Further studies testing these measures across other countries and with more diverse samples are needed.

Preliminary Validation of Measures of Experienced, Perceived, and Internalized Stigma Among Adults Who Are d/Deaf or Hard of Hearing in the United States and Ghana.

OBJECTIVES: In this article, we examine the psychometric performance of 3 scales measuring experienced, perceived, and internalized d/Deaf or hard of hearing (d/DHH) stigma among adult (18 and older) populations of individuals who are d/DHH, including those who have been d/DHH since before they developed language (lifelong) and those who became d/DHH after they developed language (acquired) in the United States and Ghana. DESIGN: The preliminary validation study took place in the Greater Accra and Eastern regions of Ghana and across the United States. In the United States, all data were collected online via self-administered surveys in English. In Ghana, trained interviewers who are d/DHH and fluent in Ghanaian Sign Language conducted interviews with participants who are lifelong d/DHH using a video survey. Ghanaian participants with acquired d/DHH status were surveyed by trained hearing interviewers. We calculated polychoric correlation matrices between the measures to remove redundant and unrelated items and used exploratory factor analysis to create the final scales. We also tested the association between the factor scores and a simple summing method for calculating the scale. RESULTS: The study sample included people who have been d/DHH since before they developed language (Ghana: n = 171, United States n = 100) and people who became d/DHH after they developed language (Ghana: n = 174, United States: n = 219). The final experienced, perceived, and internalized scales included six, seven, and five items, respectively. All three scales performed well as unidimensional measures across all four samples. Across the four samples, the experienced, perceived, and internalized stigma scales yielded ordinal αs ranging from 0.725 to 0.947, 0.856 to 0.935, and 0.856 to 0.935, respectively. It would be acceptable to operationalize all stigma scales as sum-of-item scores. CONCLUSIONS: The scales performed well and appear to provide a valid means of measuring different types of stigma among diverse groups of people who are d/DHH. Future work should refine and validate these scales in additional contexts.

Development of Measures for d/Deaf and Hard of Hearing Stigma: Introduction to the Special Supplement on Stigma Measurement Tools.

People who are d/Deaf or hard of hearing (d/DHH) often experience stigma and discrimination in their daily lives. Qualitative research describing their lived experiences has provided useful, in-depth insights into the pervasiveness of stigma. Quantitative measures could facilitate further investigation of the scope of this phenomenon. Thus, under the auspices of the Lancet Commission on Hearing Loss, we developed and preliminarily validated survey measures of different types of stigma related to d/Deafness and hearing loss in the United States (a high-income country) and Ghana (a lower-middle income country). In this introductory article, we first present working definitions of the different types of stigma; an overview of what is known about stigma in the context of hearing loss; and the motivation underlying the development of measures that capture different types of stigma from the perspectives of different key groups. We then describe the mixed-methods exploratory sequential approach used to develop the stigma measures for several key groups: people who are d/DHH, parents of children who are d/DHH, care partners of people who are d/DHH, healthcare providers, and the general population. The subsequent manuscripts in this special supplement of Ear and Hearing describe the psychometric validation of the various stigma scales developed using these methods.

A repeated cross-sectional study of the association of community health worker intervention with the maternal continuum of care in rural Liberian communities.

BACKGROUND: The maternal continuum of care (CoC) (antenatal care, facility-based delivery, postnatal care) is critical to maternal and neonatal health and reducing mortality, but completion in rural areas of low- and middle-income countries is often limited. We used repeated cross-sectional household surveys from a rural Liberian county to explore changes in rates of completion of all steps and no steps in the maternal CoC after implementation of the National Community Health Assistant Program (NCHAP), a community health worker (CHW) intervention designed to increase care uptake for families over five kilometers from a facility. METHODS: We analyzed repeated cross-sectional household surveys of women aged 18-49 served by NCHAP in Rivercess County, Liberia. We measured survey-weighted, before-to-after implementation difference in completion of all steps and no steps in the maternal CoC. We used multivariable regression to explore covariates associated with completion rates before and after NCHAP implementation. RESULTS: Data from surveys conducted at three timepoints (2015, n = 354; 2018, n = 312; 2021, n = 302) were analyzed. A significant increase in completing the full maternal CoC (2015:23.6%, 2018:53.4%, change:29.7% points (pp), 95% confidence interval (CI) [21.0,38.4]) and a decrease in completing no steps in the CoC (2015:17.6%, 2018:4.0%, change: -12.4pp [-17.6, -7.2]) after implementation of NCHAP were observed from 2015 to 2018, with rates maintained from 2018 to 2021. Living farther from a facility was consistently associated with less care across the continuum. Following implementation, living in a motorbike accessible community was associated with completing the CoC while living in a mining community was negatively associated with omitting the CoC. Household wealth was associated with differences in rates pre-NCHAP but not post-NCHAP. CONCLUSIONS: Following NCHAP implementation, completion rate of the full maternal CoC in Rivercess County more than doubled while the rate of completing no steps in the continuum fell below 5%. These rates were sustained over time including during COVID-19 with reduced differences across wealth groups, although far distances remained a risk for less care. CHW programs providing active outreach to remote communities can be important tools for improving uptake of interventions and reducing risk of no formal care during and after pregnancy.

Does it matter that standard preparedness indices did not predict COVID-19 outcomes?

A number of scientific publications and commentaries have suggested that standard preparedness indices such as the Global Health Security Index (GHSI) and Joint External Evaluation (JEE) scores did not predict COVID-19 outcomes. To some, the failure of these metrics to be predictive demonstrates the need for a fundamental reassessment which better aligns preparedness measurement with operational capacities in real-world stress situations, including the points at which coordination structures and decision-making may fail. There are, however, several reasons why these instruments should not be so easily rejected as preparedness measures.From a methodological point of view, these studies use relatively simple outcome measures, mostly based on cumulative numbers of cases and deaths at a fixed point of time. A country's "success" in dealing with the pandemic is highly multidimensional - both in the health outcomes and type and timing of interventions and policies - is too complex to represent with a single number. In addition, the comparability of mortality data over time and among jurisdictions is questionable due to highly variable completeness and representativeness. Furthermore, the analyses use a cross-sectional design, which is poorly suited for evaluating the impact of interventions, especially for COVID-19.Conceptually, a major reason that current preparedness measures fail to predict pandemic outcomes is that they do not adequately capture variations in the presence of effective political leadership needed to activate and implement existing system, instill confidence in the government's response; or background levels of interpersonal trust and trust in government institutions and country ability needed to mount fast and adaptable responses. These factors are crucial; capacity alone is insufficient if that capacity is not effectively leveraged. However, preparedness metrics are intended to identify gaps that countries must fill. As important as effective political leadership and trust in institutions, countries cannot be held accountable to one another for having good political leadership or trust in institutions. Therefore, JEE scores, the GHSI, and similar metrics can be useful tools for identifying critical gaps in capacities and capabilities that are necessary but not sufficient for an effective pandemic response.

Measuring health system responsiveness in a national community health worker primary care programme in rural Liberia.

As many low- and middle-income countries scale up community health worker (CHW) programmes to achieve universal health coverage, ensuring quality as well as access is critical. Health system responsiveness (HSR) is a core domain of quality patient-centred care but has not been widely measured in CHW-delivered care. We report results from a household survey measuring HSR and health systems' quality of CHW-delivered care in two Liberian counties where the national CHW programme of Community Health Assistants (CHAs) for communities ≥5 km from a health centre has been implemented. We conducted a cross-sectional population-based household survey in 2019 in Rivercess (RC) and Grand Gedeh (GG) counties, using a two-stage cross-sectional cluster sampling approach. We included validated HSR questions on six responsiveness domains and patient-reported health system outcomes, such as satisfaction and trust in the CHA's skills and abilities. The HSR questions were administered to women aged 18-49 years who reported seeking care from a CHA in the 3 months prior to the survey. A composite responsiveness score was calculated and divided into tertiles. Multivariable analysis using Poisson regression with log link and adjusting for respondent characteristics was used to determine the association between responsiveness and patient-reported health system outcomes. The proportion of individuals rating responsiveness as very good or excellent was similar across all domains within a district, with ratings being lower in RC (23-29%) than in GG (52-59%). High ratings in both counties were seen for high trust in the CHA's skills and abilities (GG 84%, RC 75%) and high confidence in the CHA (GG 58%, RC 60%). Compared with women in the lowest responsiveness tertile (score ≤3), women in the highest tertile (score $ \ge $4.25) were significantly more likely to report high quality of CHA-delivered care (prevalence ratio, PR = 14.1), very good/excellent at meeting health needs (PR = 8.0), high confidence in the CHA to provide future care (PR = 2.4), and a high level of trust in CHA's skills and abilities (PR = 1.4). Controlling for respondent characteristics, the composite responsiveness score was significantly associated with all patient-reported health system outcomes (P < 0.001). We found that HSR was associated with important patient-reported health system quality outcomes, including satisfaction, trust, and confidence in the CHA. Measuring patients' experience and outcomes of care is important to complement more common measures of technical quality for CHW-delivered care to ensure that this domain of quality is central to the community health programme design and delivery.

Adjusting COVID-19 Seroprevalence Survey Results to Account for Test Sensitivity and Specificity.

Population-based seroprevalence surveys can provide useful estimates of the number of individuals previously infected with serious acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and still susceptible, as well as contribute to better estimates of the case-fatality rate and other measures of coronavirus disease 2019 (COVID-19) severity. No serological test is 100% accurate, however, and the standard correction that epidemiologists use to adjust estimates relies on estimates of the test sensitivity and specificity often based on small validation studies. We have developed a fully Bayesian approach to adjust observed prevalence estimates for sensitivity and specificity. Application to a seroprevalence survey conducted in New York State in 2020 demonstrates that this approach results in more realistic-and narrower-credible intervals than the standard sensitivity analysis using confidence interval endpoints. In addition, the model permits incorporating data on the geographical distribution of reported case counts to create informative priors on the cumulative incidence to produce estimates and credible intervals for smaller geographic areas than often can be precisely estimated with seroprevalence surveys.

Complex relationship between household wealth, location of residence, road crash injury incidence and injury severity in Uganda.

BACKGROUND: Limited evidence exists about associations between road crash injury and economic status in sub-Saharan Africa from large, population-based data sets. Existing studies generally do not incorporate fatal crashes. This study aims to understand the relationship between relative wealth and road crash injury and severity using population-representative cross-sectional data from Uganda's 2016 Demographic and Health Survey . METHODS: One-year road crash risk was flexibly modelled as a function of wealth using fractional polynomial models, stratified by sex and rural/urban residence. Wealth was operationalised as 1/20th quantiles of the first principal component from a polychoric principal component analysis. Injury severity was coded as a three-level ordinal variable; associations with wealth were modelled with ordinal logistic regression on quintiles of relative wealth, stratified by residence. RESULTS: Overall, injury risk peaked in the upper middle of the wealth distribution. Rural resident injury risk increased monotonically with wealth. Urban resident risk had an upside-down U shape. Risk peaked in the distribution's middle at about double the lowest levels. Only urban men had higher risk among the least wealthy than most wealthy (3.2% vs 1.7%; difference=1.5 percentage points, 95% CI 0.2 to 2.7). Among those with road crash injuries, greater relative wealth was associated with decreased likelihood of more severe injury (33.2 percentage points lower in the highest category than lowest, 95% CI 18.4 to 48.1) or death (5.9 percentage points, 95% CI -0.1 to 11.8) for urban residents but not rural residents. CONCLUSION: Relationships between relative wealth and injury risk and severity are complex and different for urban and rural Ugandans.

Female sex and cardiovascular disease risk in rural Uganda: a cross-sectional, population-based study.

BACKGROUND: Sex-based differences in cardiovascular disease (CVD) burden are widely acknowledged, with male sex considered a risk factor in high-income settings. However, these relationships have not been examined in sub-Saharan Africa (SSA). We aimed to apply the American Heart Association (AHA) ideal cardiovascular health (CVH) tool modified by the addition of C-reactive protein (CRP) to examine potential sex-based differences in the prevalence of CVD risk in rural Uganda. METHODS: In a cross-sectional study nested within a population-wide census, 857 community-living adults completed physical and laboratory-based assessments to calculate individual ideal CVH metrics including an eight category for CRP levels. We summarized sex-specific ideal CVH indices, fitting ordinal logistic regression models to identify correlates of improving CVH. As secondary outcomes, we assessed subscales of ideal CVH behaviours and factors. Models included inverse probability of sampling weights to determine population-level estimates. RESULTS: The weighted-population mean age was 39.2 (1.2) years with 52.0 (3.7) % females. Women had ideal scores in smoking (80.4% vs. 68.0%; p < 0.001) and dietary intake (26.7% vs. 16.8%; p = 0.037) versus men, but the opposite in body mass index (47.3% vs. 84.4%; p < 0.001), glycated hemoglobin (87.4% vs. 95.2%; p = 0.001), total cholesterol (80.2% vs. 85.0%; p = 0.039) and CRP (30.8% vs. 49.7%; p = 0.009). Overall, significantly more men than women were classified as having optimal cardiovascular health (6-8 metrics attaining ideal level) (39.7% vs. 29.0%; p = 0.025). In adjusted models, female sex was correlated with lower CVH health factors sub-scales but higher ideal CVH behaviors. CONCLUSIONS: Contrary to findings in much of the world, female sex in rural SSA is associated with worse ideal CVH profiles, despite women having better indices for ideal CVH behaviors. Future work should assess the potential role of socio-behavioural sex-specific risk factors for ideal CVH in SSA, and better define the downstream consequences of these differences.

A Community Health Worker Intervention to Increase Childhood Disease Treatment Coverage in Rural Liberia: A Controlled Before-and-After Evaluation.

OBJECTIVES: To assess a community health worker (CHW) program's impact on childhood illness treatment in rural Liberia. METHODS: We deployed CHWs in half of Rivercess County in August 2015 with the other half constituting a comparison group until July 2016. All CHWs were provided cash incentives, supply chain support, and monthly clinical supervision. We conducted stratified cluster-sample population-based surveys at baseline (March-April 2015) and follow-up (April-June 2016) and performed a difference-in-differences analysis, adjusted by inverse probability of treatment weighting, to assess changes in treatment of fever, diarrhea, and acute respiratory infection by a qualified provider. RESULTS: We estimated a childhood treatment difference-in-differences of 56.4 percentage points (95% confidence interval [CI] = 36.4, 76.3). At follow-up, CHWs provided 57.6% (95% CI = 42.8, 71.2) of treatment in the intervention group. The difference-in-differences diarrhea oral rehydration therapy was 22.4 percentage points (95% CI = -0.7, 45.5). CONCLUSIONS: Implementation of a CHW program in Rivercess County, Liberia, was associated with large, statistically significant improvements treatment by a qualified provider; however, improvements in correct diarrhea treatment were lower than improvements in coverage. Findings from this study offer support for expansion of Liberia's new National Community Health Assistant Program.

Relative household wealth and non-fatal road crashes: analysis of population-representative data of Kenyan adults.

Background: This study aims to examine potential road crash disparities across relative wealth and location of residence in Kenya by analyzing population-representative Demographic and Health Survey data. Methods: Relative wealth was measured by household assets, converted into an index by polychoric principal components analysis. Location and sex-stratified associations between wealth quantiles and crashes were flexibly estimated using fractional polynomial models. Structural equation models were fit to examine whether observed differences may operate through previously identified determinants. Results: In rural areas, crashes were least common for both the poorest men (-5.2 percentage points, 95% CI: -7.3 to -3.2) and women (-1.6 percentage points, 95% CI: -2.9 to -0.4). In urban areas, male crashes were lowest (-3.0 percentage points, 95% CI: -5.2 to -0.8) among the wealthiest, while they peaked in the middle of the female wealth distribution (2.0 percentage points, 95% CI: 0.3-3.8). Male differences operate partially though occupational driving and vehicle ownership. Urban female differences operate partially through household vehicle ownership, but differences for rural women were not explained by modeled determinants. Conclusions: Relative wealth and road crash have opposite associations in rural and urban areas. Especially in rural areas, it is important to mitigate potential unintended effects of economic development.

Implementation research on community health workers' provision of maternal and child health services in rural Liberia.

OBJECTIVE: To assess changes in the use of essential maternal and child health services in Konobo, Liberia, after implementation of an enhanced community health worker (CHW) programme. METHODS: The Liberian Ministry of Health partnered with Last Mile Health, a nongovernmental organization, to implement a pilot CHW programme with enhanced recruitment, training, supervision and compensation. To assess changes in maternal and child health-care use, we conducted repeated cross-sectional cluster surveys before (2012) and after (2015) programme implementation. FINDINGS: Between 2012 and 2015, 54 CHWs, seven peer supervisors and three clinical supervisors were trained to serve a population of 12 127 people in 44 communities. The regression-adjusted percentage of children receiving care from formal care providers increased by 60.1 (95% confidence interval, CI: 51.6 to 68.7) percentage points for diarrhoea, by 30.6 (95% CI: 20.5 to 40.7) for fever and by 51.2 (95% CI: 37.9 to 64.5) for acute respiratory infection. Facility-based delivery increased by 28.2 points (95% CI: 20.3 to 36.1). Facility-based delivery and formal sector care for acute respiratory infection and diarrhoea increased more in agricultural than gold-mining communities. Receipt of one-or-more antenatal care sessions at a health facility and postnatal care within 24 hours of delivery did not change significantly. CONCLUSION: We identified significant increases in uptake of child and maternal health-care services from formal providers during the pilot CHW programme in remote rural Liberia. Clinic-based services, such as postnatal care, and services in specific settings, such as mining areas, require additional interventions to achieve optimal outcomes.

Crowdsourced data collection for public health: A comparison with nationally representative, population tobacco use data.

INTRODUCTION: Internet-based crowdsourcing is increasingly used for social and behavioral research in public health, however the potential generalizability of crowdsourced data remains unclear. This study assessed the population representativeness of Internet-based crowdsourced data. METHODS: A total of 3999 U.S. young adults ages 18 to 30years were recruited in 2016 through Internet-based crowdsourcing to complete measures taken from the 2012-2013 National Adult Tobacco Survey (NATS). Post-hoc sampling weights were created using procedures similar to the NATS. Weighted analyses were conducted in 2016 to compare crowdsourced and publicly-available 2012-2013 NATS data on demographics, tobacco use, and measures of tobacco perceptions and product warning label exposure. RESULTS: Those in the crowdsourced sample were less likely to report an annual household income of $50,000 or greater, and e-cigarette, waterpipe, and cigar use were more prevalent in the crowdsourced sample. High proportions of both samples indicated cigarette smoking is very harmful and very addictive. Comparable proportions of non-smokers and smokers reported cigarette warning label exposure, however the likelihood of reporting that smoking is very harmful by frequency of warning label exposure was lower among smokers in the crowdsourced sample. CONCLUSIONS: Our findings indicate that crowdsourced samples may differ demographically and may not produce generalizable estimates of tobacco use prevalence relative to population data after post-hoc sample weighting. However, correlational analyses in crowdsourced samples may reasonably approximate population data. Future studies can build from this work by testing additional methodological strategies to improve crowdsourced sampling strategies.

Validation Relaxation: A Quality Assurance Strategy for Electronic Data Collection.

BACKGROUND: The use of mobile devices for data collection in developing world settings is becoming increasingly common and may offer advantages in data collection quality and efficiency relative to paper-based methods. However, mobile data collection systems can hamper many standard quality assurance techniques due to the lack of a hardcopy backup of data. Consequently, mobile health data collection platforms have the potential to generate datasets that appear valid, but are susceptible to unidentified database design flaws, areas of miscomprehension by enumerators, and data recording errors. OBJECTIVE: We describe the design and evaluation of a strategy for estimating data error rates and assessing enumerator performance during electronic data collection, which we term "validation relaxation." Validation relaxation involves the intentional omission of data validation features for select questions to allow for data recording errors to be committed, detected, and monitored. METHODS: We analyzed data collected during a cluster sample population survey in rural Liberia using an electronic data collection system (Open Data Kit). We first developed a classification scheme for types of detectable errors and validation alterations required to detect them. We then implemented the following validation relaxation techniques to enable data error conduct and detection: intentional redundancy, removal of "required" constraint, and illogical response combinations. This allowed for up to 11 identifiable errors to be made per survey. The error rate was defined as the total number of errors committed divided by the number of potential errors. We summarized crude error rates and estimated changes in error rates over time for both individuals and the entire program using logistic regression. RESULTS: The aggregate error rate was 1.60% (125/7817). Error rates did not differ significantly between enumerators (P=.51), but decreased for the cohort with increasing days of application use, from 2.3% at survey start (95% CI 1.8%-2.8%) to 0.6% at day 45 (95% CI 0.3%-0.9%; OR=0.969; P<.001). The highest error rate (84/618, 13.6%) occurred for an intentional redundancy question for a birthdate field, which was repeated in separate sections of the survey. We found low error rates (0.0% to 3.1%) for all other possible errors. CONCLUSIONS: A strategy of removing validation rules on electronic data capture platforms can be used to create a set of detectable data errors, which can subsequently be used to assess group and individual enumerator error rates, their trends over time, and categories of data collection that require further training or additional quality control measures. This strategy may be particularly useful for identifying individual enumerators or systematic data errors that are responsive to enumerator training and is best applied to questions for which errors cannot be prevented through training or software design alone. Validation relaxation should be considered as a component of a holistic data quality assurance strategy.

Mind the Scales: Harnessing Spatial Big Data for Infectious Disease Surveillance and Inference.

Spatial big data have the velocity, volume, and variety of big data sources and contain additional geographic information. Digital data sources, such as medical claims, mobile phone call data records, and geographically tagged tweets, have entered infectious diseases epidemiology as novel sources of data to complement traditional infectious disease surveillance. In this work, we provide examples of how spatial big data have been used thus far in epidemiological analyses and describe opportunities for these sources to improve disease-mitigation strategies and public health coordination. In addition, we consider the technical, practical, and ethical challenges with the use of spatial big data in infectious disease surveillance and inference. Finally, we discuss the implications of the rising use of spatial big data in epidemiology to health risk communication, and public health policy recommendations and coordination across scales.

Facility-Based Delivery during the Ebola Virus Disease Epidemic in Rural Liberia: Analysis from a Cross-Sectional, Population-Based Household Survey.

BACKGROUND: The Ebola virus disease (EVD) epidemic has threatened access to basic health services through facility closures, resource diversion, and decreased demand due to community fear and distrust. While modeling studies have attempted to estimate the impact of these disruptions, no studies have yet utilized population-based survey data. METHODS AND FINDINGS: We conducted a two-stage, cluster-sample household survey in Rivercess County, Liberia, in March-April 2015, which included a maternal and reproductive health module. We constructed a retrospective cohort of births beginning 4 y before the first day of survey administration (beginning March 24, 2011). We then fit logistic regression models to estimate associations between our primary outcome, facility-based delivery (FBD), and time period, defined as the pre-EVD period (March 24, 2011-June 14, 2014) or EVD period (June 15, 2014-April 13, 2015). We fit both univariable and multivariable models, adjusted for known predictors of facility delivery, accounting for clustering using linearized standard errors. To strengthen causal inference, we also conducted stratified analyses to assess changes in FBD by whether respondents believed that health facility attendance was an EVD risk factor. A total of 1,298 women from 941 households completed the survey. Median age at the time of survey was 29 y, and over 80% had a primary education or less. There were 686 births reported in the pre-EVD period and 212 in the EVD period. The unadjusted odds ratio of facility-based delivery in the EVD period was 0.66 (95% confidence interval [CI] 0.48-0.90, p-value = 0.010). Adjustment for potential confounders did not change the observed association, either in the principal model (adjusted odds ratio [AOR] = 0.70, 95%CI 0.50-0.98, p = 0.037) or a fully adjusted model (AOR = 0.69, 95%CI 0.50-0.97, p = 0.033). The association was robust in sensitivity analyses. The reduction in FBD during the EVD period was observed among those reporting a belief that health facilities are or may be a source of Ebola transmission (AOR = 0.59, 95%CI 0.36-0.97, p = 0.038), but not those without such a belief (AOR = 0.90, 95%CI 0.59-1.37, p = 0.612). Limitations include the possibility of FBD secular trends coincident with the EVD period, recall errors, and social desirability bias. CONCLUSIONS: We detected a 30% decreased odds of FBD after the start of EVD in a rural Liberian county with relatively few cases. Because health facilities never closed in Rivercess County, this estimate may under-approximate the effect seen in the most heavily affected areas. These are the first population-based survey data to show collateral disruptions to facility-based delivery caused by the West African EVD epidemic, and they reinforce the need to consider the full spectrum of implications caused by public health emergencies.