RESUMO
BACKGROUND: While adolescents' access and utilization of health services is critical for ensuring their health, very few seek care, and if they do, it is primarily from family members, friends, or other non-formal sources of care. Examining the influence of the social context on adolescent health care seeking behaviors may provide us with a better understanding for how interventions can increase adolescents' utilization of formal health care services. METHODS: The study is based on qualitative and quantitative data collected as part of the Well Being of Adolescents in Vulnerable Environments (WAVE) study, one of the first global studies to focus on very disadvantaged urban adolescents (aged 15-19 years) across five diverse sites, which include: Baltimore (USA), Ibadan (Nigeria), Johannesburg (South Africa), New Delhi (India), and Shanghai (China). Qualitative data was based on numerous methodologies, including key informant interviews, a Photovoice exercise, community mapping, focus groups and in-depth interviews. Quantitative data was gathered from a cross-sectional Audio Computer Assisted Self Interview (ACASI) survey that was administered to approximately 450-500 adolescents per site, yielding a total of 2,393 adolescents. Respondent-driven sampling was used to ensure the sample include out-of-school youth and unstably housed youth who are often underrepresented in school-based or household-based samples. RESULTS: While adolescents in Baltimore, New Delhi, and Johannesburg were more likely to seek health services if they felt illness symptoms, a fairly large proportion of adolescents indicated that even when they needed health care, they didn't seek it. In Johannesburg, more than 30 % of adolescents did not seek care even when they knew it was needed. Similarly, nearly a quarter of adolescents in Baltimore and in Shanghai indicated not seeking care when needed. Qualitative data indicated that adolescents exhibited a general lack of trust in providers and often felt embarrassed or stigmatized for seeking services. Multivariate analysis revealed that perceived fear and exposure to community violence was associated with a decreased likelihood of seeking care, while adult support from the home increased adolescents' likelihood to seek care in Baltimore and Johannesburg. CONCLUSIONS: Adolescent health care seeking patterns vary substantially by setting and gender. Neighborhood and family environments are important contexts in which health seeking behaviors are shaped. Efforts to connect adolescents to health care will need to target neighborhood safety as well as trust and support among adults outside of provider settings.
Assuntos
Serviços de Saúde do Adolescente/estatística & dados numéricos , Características de Residência , Serviços Urbanos de Saúde/estatística & dados numéricos , Adolescente , China , Estudos Transversais , Feminino , Grupos Focais , Habitação/estatística & dados numéricos , Humanos , Índia , Masculino , Nigéria , Percepção , Áreas de Pobreza , Características de Residência/estatística & dados numéricos , Estudos de Amostragem , Instituições Acadêmicas , Distribuição por Sexo , Meio Social , África do Sul , Violência/estatística & dados numéricos , Populações Vulneráveis , Adulto JovemRESUMO
OBJECTIVES: Achieving accurate, timely, and complete HIV surveillance data is complicated in the United States by migration and care seeking across jurisdictional boundaries. To address these issues, public health entities use the ATra Black Box-a secure, electronic, privacy-assuring system developed by Georgetown University-to identify and confirm potential duplicate case records, exchange data, and perform other analytics to improve the quality of data in the Enhanced HIV/AIDS Reporting System (eHARS). We aimed to evaluate the ability of 2 ATra software algorithms to identify potential duplicate case-pairs across 6 jurisdictions for people living with diagnosed HIV. METHODS: We implemented 2 matching algorithms for identifying potential duplicate case-pairs in ATra software. The Single Name Matching Algorithm examines only 1 name for a person, whereas the All Names Matching Algorithm examines all names in eHARS for a person. Six public health jurisdictions used the algorithms. We compared outputs for the overall number of potential matches and changes in matching level. RESULTS: The All Names Matching Algorithm found more matches than the Single Name Matching Algorithm and increased levels of match. The All Names Matching Algorithm identified 9070 (4.5%) more duplicate matches than the Single Name Matching Algorithm (n = 198 828) and increased the total number of matches at the exact through high levels by 15.4% (from 167 156 to 192 932; n = 25 776). CONCLUSIONS: HIV data quality across multiple jurisdictions can be improved by using all known first and last names of people living with diagnosed HIV that match with eHARS rather than using only 1 first and last name.