{"title":"Community-Focused Policy Advocacy: Evaluating Hawai'i's Historical Trauma Legislation.","authors":"Lorinda Riley, Anamalia Su'esu'e","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Research aimed at reducing health disparities must move beyond the academic and provide practical value. Developing policy briefs that provide a description of the current policy framework along with evidence-based recommendations that can be shared with decision-makers is one way to accomplish this. Researchers, then, can lend their authority to increase awareness moving the policy process forward. The purpose of this paper is to outline a way to develop policy briefs and provide an example of this methodological framework through a case study. The case study was developed as part of a community-engaged research project exploring the conceptualization of historical trauma among Native Hawaiian youth. The policy brief was developed by first searching the Hawai'i State Legislature database in Westlaw limiting the search to the past 10 years for legislation related to historical trauma, structural racism, or related concepts. The results encompassed 104 bills and resolutions, of which 11 passed and 93 failed to pass. Successful legislation acknowledged the role of racism to health and supported the use of trauma-informed care but stopped short of addressing historical trauma. Several gaps were identified including a failure to address collective trauma or trauma specific to colonization suggesting a reluctance to acknowledge intergenerational trauma as an element of present experiences. The policy brief developed for this project was provided to community partners to support their advocacy efforts. This manuscript showcases a process researchers can use to analyze legislative records and develop policy briefs that can support their community partners.</p>","PeriodicalId":36659,"journal":{"name":"Hawai''i journal of health & social welfare","volume":"82 10 Suppl 1","pages":"44-50"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612421/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71414399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jeanelle J Sugimoto-Matsuda, Jennifer W Kaminski, Earl S Hishinuma, Janice Y Chang, Fa'apisa M Soli, D Michele Hoover, Randy Paul M Bautista
{"title":"A Comparison of Strategies to Increase Household Survey Response Rates in a Predominantly Indigenous Community Population.","authors":"Jeanelle J Sugimoto-Matsuda, Jennifer W Kaminski, Earl S Hishinuma, Janice Y Chang, Fa'apisa M Soli, D Michele Hoover, Randy Paul M Bautista","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>The present study describes 4 strategies for increasing response rates to a community-based survey on youth violence in an ethnically diverse population in Hawai'i. A total of 350 households were mailed a Safe Community Survey using 4 different randomly assigned incentive strategies. The strategies varied by length of survey and timing of incentive for completion (given before completion, after completion, or both). In univariate analyses, there were no significant differences across survey strategies on participant demographics, community perceptions of violence-related behaviors, or percent of missing items. However, in multivariate regressions, respondents' sex and percent of missing items on the surveys were consistently significant predictors across multiple outcomes. Although the use of strategies to increase response rates in community-based surveys might be desirable, resulting data need to be examined for the potential that strategies might recruit different populations, which may have an impact on the data obtained. This study offers lessons and recommendations for surveying Native and Indigenous communities.</p>","PeriodicalId":36659,"journal":{"name":"Hawai''i journal of health & social welfare","volume":"82 10 Suppl 1","pages":"51-57"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612423/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71414397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Pacific Innovations, Knowledge, and Opportunities (PIKO) Program: A Data Lifecycle Research Experience.","authors":"Rylan Chong, Laura Tipton","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Pacific evidence-based clinical and translational research is greatly needed. However, there are research challenges that stem from the creation, accessibility, availability, usability, and compliance of data in the Pacific. As a result, there is a growing demand for a complementary approach to the traditional Western research process in clinical and translational research. The data lifecycle is one such approach with a history of use in various other disciplines. It was designed as a data management tool with a set of activities that guide researchers and organizations on the creation, management, usage, and distribution of data. This manuscript describes the data lifecycle and its use by the Biostatistics, Epidemiology, and Research Design core data science team in support of the Center for Pacific Innovations, Knowledge, and Opportunities program.</p>","PeriodicalId":36659,"journal":{"name":"Hawai''i journal of health & social welfare","volume":"82 10 Suppl 1","pages":"117-120"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612409/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71414469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Prioritizing Connection and Centering on Community: Take Your Shoes Off and Don't Put Your Feet on the Furniture.","authors":"Gerard Akaka, Sheri Daniels, Kamalei Davis, Adrienne Dillard, Kamahanahokulani Farrar, Deborah Goebert, Jocelyn Howard, Charis Kaio, Emily Makahi, Megan Inada, Mary Oneha, Malia Purdy","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>This column describes what it means to be \"in\" a community and how to create a leading role for community partners in shaping research. It highlights essential components for conducting clinical and translational research in the community, including: (1) invitation to share history and purpose; (2) community-initiated collaboration and engagement; (3) focus on social and cultural determinants of health; (4) community-driven measures and frameworks; (5) application of Indigenous methods and approaches; and (6) implementation of Indigenous and adaptable interventions. Partnering with a community entails building relationships and positioning research around community interests, using methodologies and interventions right for the community.</p>","PeriodicalId":36659,"journal":{"name":"Hawai''i journal of health & social welfare","volume":"82 10 Suppl 1","pages":"10-13"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612427/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71414443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Scoping Review of Interventional Studies in Chronic Disease for Native Hawaiian, Pacific Islander, and Filipino Populations in the United States.","authors":"Munirih R Taafaki, Deborah Taira, Kathryn L Braun","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Native Hawaiians (NHs), Pacific Islanders (PIs), and Filipinos experience health disparities in the United States (US) and need interventions that work for them. The purpose of this paper is to present a review of interventions designed to address chronic disease in Native Hawaiian, Pacific Islander, and Filipino populations in the US that were tested for clinical impact through a randomized controlled trial (RCT). Articles were identified through a search of 4 databases, citation chasing, and colleagues. The 23 included articles reported on 21 interventions addressing 4 chronic conditions-cancer, obesity, cardiovascular disease, and diabetes. All projects were guided by advisory groups, and all interventions were theory-based and tailored to the population, with culturally- and language-appropriate educational materials delivered by same-race individuals in familiar church, club, or home settings. About half were tested through cluster RCT. The majority of the interventions were successful, confirming the value of developing and delivering interventions in partnership with community. Given the growing numbers of NHs, PIs, and Filipinos in the US, more investigational studies are needed to develop and test culturally tailored and grounded interventions that meet the health needs of these populations.</p>","PeriodicalId":36659,"journal":{"name":"Hawai''i journal of health & social welfare","volume":"82 10 Suppl 1","pages":"58-66"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612424/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71414465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
James Davis, Deborah A Taira, Eunjung Lim, John Chen
{"title":"Modeling Poverty and Health for Native Hawaiian and Pacific Islander and Asian Ethnic Populations.","authors":"James Davis, Deborah A Taira, Eunjung Lim, John Chen","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>This study examined differences in poverty and health among Native Hawaiians and Pacific Islanders (NHPI) and 6 disaggregated Asian ethnic subgroups and an aggregated Other Asian category. Participants were followed longitudinally for 2 years using data from 2009 to 2019 from the Current Population Survey, a monthly survey conducted by the Census Bureau. Having 2 years of data enabled the study to assess both prevalence of poverty and fair/poor health in only 1 of the 2 years and in both years. For NHPI, 13.5% were in poverty 1of the 2 years and 7.1% in both years. Asian ethnicities showed high variability ranging from a low of 6.4% for 1 year and 1.9% for 2 years among Asian Indians to 16.0% for 1 year and 6.3% for 2 years among Vietnamese. Fair/poor health also showed ethnic variability, made most apparent after age-sex adjustment in regression models. For poverty, after adjustment, Asian Indians, Filipinos and Japanese had significantly lower odds of being in poverty at least 1 year than NHPI. For having fair/poor health, Asian Indians and Japanese experienced lower odds than NHPI for both 1 and 2 years and Filipinos for 1 year, after age/sex adjustment. The results emphasize the diversity of Asian and Pacific Islander populations, the variability of poverty over time, and the importance of using disaggregated data to understand ethnic differences in poverty and health. These findings can be used to inform future modeling of social determinants on poverty and health among NHPI and Asian subgroups.</p>","PeriodicalId":36659,"journal":{"name":"Hawai''i journal of health & social welfare","volume":"82 10 Suppl 1","pages":"77-83"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612419/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71414404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eunjung Lim, James Davis, Devashri Prabhudesai, Deborah Taira
{"title":"Inventory of Survey Databases for Native Hawaiian, Pacific Islander, and Filipino Health Disparities Research.","authors":"Eunjung Lim, James Davis, Devashri Prabhudesai, Deborah Taira","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>The aim of this scoping review was to assist researchers who want to use survey data, either in academic or community settings, to identify and comprehend health disparities affecting Native Hawaiian (NH), Pacific Islander (PI), and/or Filipino populations, as these are groups with known and numerous health disparities. The scoping review methodology was used to identify survey datasets that disaggregate data for NH, PI, or Filipinos. Healthdata.gov was searched, as there is not an official index of databases. The website was established by the United States (US) Department and Health and Human Services to increase accessibility of health data for entrepreneurs, researchers, and policy makers, with the ultimate goal of improving health outcomes. Using the search term 'survey,' 332 datasets were retrieved, many of which were duplicates from different years. Datasets were included that met the following criteria: (1) related to health; (2) disaggregated NH, PI, and/or Filipino subgroups; (3) administered in the US; (4) publicly available; (5) individual-level data; (6) self-reported information; and (7) contained data from 2010 or later. Fifteen survey datasets met the inclusion criteria. Two additional survey datasets were identified by colleagues. For each dataset, the dataset name, data source, years of the data availability, availability of disaggregated NH, PI, and/or Filipino data, data on health outcomes and social determinants of health, and website information were documented. This inventory of datasets should be of use to researchers who want to advance understanding of health disparities experienced by NH, PI, and Filipino populations in the US.</p>","PeriodicalId":36659,"journal":{"name":"Hawai''i journal of health & social welfare","volume":"82 10 Suppl 1","pages":"104-110"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612417/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71414403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Masako Matsunaga, Kyle M Ishikawa, Chathura Siriwardhana, Hyeong Jun Ahn, John J Chen
{"title":"Stepwise Proportional Weighting Algorithm for Single-Race Population Estimation Using Hawai'i Census Data.","authors":"Masako Matsunaga, Kyle M Ishikawa, Chathura Siriwardhana, Hyeong Jun Ahn, John J Chen","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Many health and health disparities studies require population prevalence information of various race groups, but the estimation of single-race population sizes using the US Census data has been challenging. For each Census race group, Census only provides the counts of those reported being single race (\"race alone\") and those reported of that specific race regardless of whether the individuals were multiracial or not (\"race alone or in (any) combination\"). The issue of how to classify Census multiracial individuals is especially important for the state of Hawai'i due to its large multiracial population. The current study developed the Stepwise Proportional Weighting Algorithm (SPWA) for single-race population estimation using US Census data for major race groups in the Census and their nested detailed races. Additionally, given that \"partial Native Hawaiian\" has often been treated as \"Native Hawaiian\" in health disparities studies in Hawai'i, the algorithm can also adjust for the unique partial Native Hawaiian race categorization. This paper describes the estimation process with the SPWA and demonstrates its ability to estimate single-races for the 5 most common race groups in Hawai'i. This new methodology addresses an important concern regarding how to classify multiracial individuals to strengthen health and health disparities research in Hawai'i.</p>","PeriodicalId":36659,"journal":{"name":"Hawai''i journal of health & social welfare","volume":"82 10 Suppl 1","pages":"97-103"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612413/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71414466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Potential Errors in Health Disparities Research Resulting from Lack of Unique Patient Identifiers: Analysis of Diabetes-related Preventable Hospitalizations.","authors":"Hyeong Jun Ahn","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>All-payer, population-level hospital discharge data have been used to identify health disparities across racial/ethnic and other demographic groups. However, researchers are often unable to identify unique patients in the data sets if a unique patient identifier is not provided. The lack of the unique patient identifier can result in biased estimates of research outcomes using discharge data. This could then mislead the researchers, public, or policy-makers who utilize such biased results. This study examined estimation bias of health disparities due to rehospitalizations considering diabetes-related preventable hospitalizations using 6 years of state-level data from Hawai'i Health Information Corporation. Different analyses methods showed different probabilities of having multiple visits by age, race/ethnicity and payer subgroups. Charge analysis results also showed that ignoring the multiple visits could result in significance error. For a patient with multiple hospitalizations, rehospitalizations are often dependent upon the discharge status of previous visits, and the independence assumption of the multiple visits may not be appropriate. Ignoring the multiple visits in population-level analyses could result in severe health disparities significance errors. In this hospitalization charge analysis, the Chinese group was not significantly different than the White group (relative risk ratio - RR: [95% CI]: 0.93 [0.80, 1.08]), while the difference was signficant (RR [95% CI]: 0.86 [0.77,0.96]) when the multiple visits were ignored.</p>","PeriodicalId":36659,"journal":{"name":"Hawai''i journal of health & social welfare","volume":"82 10 Suppl 1","pages":"111-116"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612426/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71414442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Janira M Navarro Sanchez, Tiffany Oommen, Christopher Lum, Zan Halford, Koah Vierkoetter
{"title":"Mediastinal Epithelioid Angiosarcoma, New Insights into an Uncommon Diagnosis: A Case Report and Literature Review.","authors":"Janira M Navarro Sanchez, Tiffany Oommen, Christopher Lum, Zan Halford, Koah Vierkoetter","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Angiosarcoma is an uncommon malignant mesenchymal neoplasm, accounting for 1-2% of all sarcomas. More than half are cutaneous, with the remainder arising in the deep soft tissue, breast, bone or viscera, particularly the liver, spleen and heart. Mediastinal angiosarcomas are exceedingly uncommon. While epithelioid morphology is sometimes a minor component in conventional angiosarcoma, tumors with a predominance of epithelioid morphologic features are designated as epithelioid angiosarcoma (EAS). This is a report of a 58-year-old woman presenting with severe chest pain, accompanied by worsening dyspnea and dysphagia. Chest computed tomography (CT) revealed a large pericardial effusion and a bulky mediastinal mass. Biopsy revealed a malignant neoplasm with vascular differentiation consistent with high-grade EAS. By immunohistochemistry, epithelioid angiosarcomas express endothelial cell markers, such as CD31, CD34, ERG and FLI-1. A variable proportion express low molecular weight cytokeratin (CK), epithelial membrane antigen (EMA) and CD30. The use of molecular techniques has proven useful in the diagnosis of this rare neoplasm. Targeted next generation sequencing showed aberrations in multiple genes including NRAS, KRAS, MYC and TP53.</p>","PeriodicalId":36659,"journal":{"name":"Hawai''i journal of health & social welfare","volume":"82 9","pages":"208-212"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10485769/pdf/hjhsw8209_0208.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10220080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}