Introduction COVID-19 disrupted traditional research infrastructures and processes most notably in-person community recruitment, especially in underrepresented populations like racial ethnic minorities. To find creative and effective strategies, our group implemented and tested the efficacy of a culturally tailored community outreach plan (COP) developed during the US COVID-19 pandemic. Methods In February 2021, we developed an 11 step culturally-tailored community outreach program to support the implementation of three NIH funded community-based sleep studies. The following steps include: (1) description of the situation statement, 2) definition of goals, 3) engagement of audience/stakeholders, 4) tailoring message, 5) defining incentives, 6) choice of outreach methods, 7) identification of spokesperson, 8) choice of tools to assess progress, 9) identification of media outlets, 10) creation of study timeline, and 11) implementation of the plan. The studies leveraged several recruitment channels: 1) community settings (Place of worship, “community recruiter”, health fairs, word of mouth, & healthcare providers/doctors’ clinics), 2) online platforms (Facebook, Twitter, LinkedIn and Research Match), and 3) preexisting datasets in NYC. Results All three studies successfully met recruitment goals. ESSENTIAL [n= 224, 69% females, mean age= 36], MOSAIC [n=109, 61% females; mean age= 64] and Latinx/Hispanics: DORMIR[n=260, 61.3% of female; 32.4]. Among the three NYC cohorts, the most common recruitment channels were: preexisting datasets (74%), community settings (19%), & online platform (7%) for ESSENTIAL; preexisting datasets (85%) & community settings (15%) for MOSAIC, and (71.7%) online platform for DORMIR. However, the Miami cohorts came mostly from community settings 90% for Essential and 97% for MOSAIC. Conclusion Overall, the TSCS community outreach plan seems to be an effective tool to engage minoritized populations in greater NY and Miami. Our current field experience indicates that recruitment channels must be adapted to age, and community resources. Limited access to technology, particularly among older Blacks seem to be a major barrier for field staff to successfully engage the disenfranchised communities. Support (If Any) NIH R01HL142066-04; R01HL152453-01 R01HL142066, R01HL095799, RO1MD004113
Introduction In two waves of data we collected in Brooklyn New York, we observed blacks were at high risk for obstructive sleep apnea (OSA). In the NIH-funded study ‘Metabolic Syndrome Outcome Study (MetSO), blacks enrolled from primary-care settings had a 59% risk of OSA. Similarly, blacks surveyed in churches and barbershops had a 43% risk of OSA. While these studies showed higher than expected risk as noted in the general population (29%), it remains uncertain how many of those blacks would be diagnosed with OSA in that population. The purpose of this study was to explore the rate of OSA using the WatchPat device in a community-based setting. Methods Data were collected from an NIH-funded study ‘Peer-Enhanced Education to Reduce Sleep Ethnic Disparities, designed to navigate blacks at risk of OSA to receive timely diagnosis and treatment using peer-delivered linguistically and culturally tailored sleep health education. Blacks were screened for OSA using the Apnea Risk Evaluation System (ARES) Questionnaire; a score ≥6 denoted moderate-high OSA risk. Individuals were asked to wear the WatchPAT 200 for one night during a week-long sleep assessment. WatchPat 200 measures SaO2 to determine respiratory-related arousals, defined as an Apnea-Hypopnea Index (AHI) ≥5, which is used to identify and diagnose OSA. We used SPSS 25.0 to perform logical regression analysis to assess associations between ARES and WatchPat AHI. Results A sample of 111 blacks provided valid ARES and WatchPat data for the present analyses. Of the sample, the mean age was 62.26 (SD=13.52 years; female = 55%); 49% reported annual income >20K and 79.5% reported a high school education. Moreover, 27% reported high blood pressure, 13%, diabetes, and 65% were overweight/obese. Multivariate-adjusted logical regression analyses indicated that blacks at risk for OSA were 66% more likely to receive an OSA diagnosis based on WatchPat AHI data (OR = 1.662, p < 0.01). The model adjusted for age, sex, income, and education. Conclusion The present study demonstrated that blacks at risk for OSA at the community level have a significant likelihood of receiving an OSA diagnosis using home-based recordings. Support NIH Support (T32HL129953, RO1MD007716, K01HL135452 and K07AG052685).
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