Arizona\u27s Vulnerable Populations

Arizona’s vulnerable populations are struggling on a daily basis but usually do so in silence, undetected by traditional radar and rankings, often unaware themselves of their high risk for being pushed or pulled into a full crisis. Ineligible for financial assistance under strict eligibility guidelines, they don’t qualify as poor because vulnerable populations are not yet in full crisis. To be clear, this report is not about the “poor,” at least not in the limited sense of the word. It is about our underemployed wage earners, our single-parent households, our deployed or returning military members, our under-educated and unskilled workforce, our debt-ridden neighbors, our uninsured friends, our family members with no savings for an emergency, much less retirement

Psychological care algorithm.

Adolescents account for an estimated 800,000 incident tuberculosis (TB) cases annually and are at risk for suboptimal adherence to TB treatment. Most studies of adolescent TB treatment adherence have used surveillance data with limited psychosocial information. This prospective cohort study aimed to identify risk factors for suboptimal adherence to rifampicin-susceptible TB treatment among adolescents (10–19 years old) in Lima, Peru. We collected psychosocial data using self-administered surveys and clinical data via medical record abstraction. Applying k-means cluster analysis, we grouped participants by psychosocial characteristics hypothesized to impact adherence. Then, we conducted mixed effects regression to compare suboptimal adherence–defined as 10% of doses)–between clusters. Treatment setting (facility vs. home) and drug formulation (single drug vs. fixed dose combination) were interaction terms. Of 249 participants, 90 (36.1%) were female. Median age was 17 (IQR: 15, 16.6) years. We identified three clusters–A, B, and C–of participants based on psychosocial characteristics. Cluster C had the lowest support from caregivers, other family members, and friends; had the weakest motivation to complete TB treatment; were least likely to live with their mothers; and had experienced the most childhood adversity. Among the 118 (47.4%) participants who received facility-based treatment with single drug formulations, adherence did not differ between Clusters A and B, but Cluster C had six-fold odds of suboptimal adherence compared to Cluster A. In Clusters B and C, adherence worsened over time, but only in Cluster C did mean adherence fall below 90% within six months. Our findings have implications for the care of adolescents with TB. When caring for adolescents with low social support and other risk factors, clinicians should take extra measures to reinforce adherence, such as identifying a community health worker or peer to provide treatment support. Implementing newly recommended shorter regimens also may facilitate adherence.</div

Survey development, including scale validation.

Adolescents account for an estimated 800,000 incident tuberculosis (TB) cases annually and are at risk for suboptimal adherence to TB treatment. Most studies of adolescent TB treatment adherence have used surveillance data with limited psychosocial information. This prospective cohort study aimed to identify risk factors for suboptimal adherence to rifampicin-susceptible TB treatment among adolescents (10–19 years old) in Lima, Peru. We collected psychosocial data using self-administered surveys and clinical data via medical record abstraction. Applying k-means cluster analysis, we grouped participants by psychosocial characteristics hypothesized to impact adherence. Then, we conducted mixed effects regression to compare suboptimal adherence–defined as 10% of doses)–between clusters. Treatment setting (facility vs. home) and drug formulation (single drug vs. fixed dose combination) were interaction terms. Of 249 participants, 90 (36.1%) were female. Median age was 17 (IQR: 15, 16.6) years. We identified three clusters–A, B, and C–of participants based on psychosocial characteristics. Cluster C had the lowest support from caregivers, other family members, and friends; had the weakest motivation to complete TB treatment; were least likely to live with their mothers; and had experienced the most childhood adversity. Among the 118 (47.4%) participants who received facility-based treatment with single drug formulations, adherence did not differ between Clusters A and B, but Cluster C had six-fold odds of suboptimal adherence compared to Cluster A. In Clusters B and C, adherence worsened over time, but only in Cluster C did mean adherence fall below 90% within six months. Our findings have implications for the care of adolescents with TB. When caring for adolescents with low social support and other risk factors, clinicians should take extra measures to reinforce adherence, such as identifying a community health worker or peer to provide treatment support. Implementing newly recommended shorter regimens also may facilitate adherence.</div

Distribution of adherence by cluster.

Adolescents account for an estimated 800,000 incident tuberculosis (TB) cases annually and are at risk for suboptimal adherence to TB treatment. Most studies of adolescent TB treatment adherence have used surveillance data with limited psychosocial information. This prospective cohort study aimed to identify risk factors for suboptimal adherence to rifampicin-susceptible TB treatment among adolescents (10–19 years old) in Lima, Peru. We collected psychosocial data using self-administered surveys and clinical data via medical record abstraction. Applying k-means cluster analysis, we grouped participants by psychosocial characteristics hypothesized to impact adherence. Then, we conducted mixed effects regression to compare suboptimal adherence–defined as 10% of doses)–between clusters. Treatment setting (facility vs. home) and drug formulation (single drug vs. fixed dose combination) were interaction terms. Of 249 participants, 90 (36.1%) were female. Median age was 17 (IQR: 15, 16.6) years. We identified three clusters–A, B, and C–of participants based on psychosocial characteristics. Cluster C had the lowest support from caregivers, other family members, and friends; had the weakest motivation to complete TB treatment; were least likely to live with their mothers; and had experienced the most childhood adversity. Among the 118 (47.4%) participants who received facility-based treatment with single drug formulations, adherence did not differ between Clusters A and B, but Cluster C had six-fold odds of suboptimal adherence compared to Cluster A. In Clusters B and C, adherence worsened over time, but only in Cluster C did mean adherence fall below 90% within six months. Our findings have implications for the care of adolescents with TB. When caring for adolescents with low social support and other risk factors, clinicians should take extra measures to reinforce adherence, such as identifying a community health worker or peer to provide treatment support. Implementing newly recommended shorter regimens also may facilitate adherence.</div

Covid-related variables, stratified by cluster.

Adolescents account for an estimated 800,000 incident tuberculosis (TB) cases annually and are at risk for suboptimal adherence to TB treatment. Most studies of adolescent TB treatment adherence have used surveillance data with limited psychosocial information. This prospective cohort study aimed to identify risk factors for suboptimal adherence to rifampicin-susceptible TB treatment among adolescents (10–19 years old) in Lima, Peru. We collected psychosocial data using self-administered surveys and clinical data via medical record abstraction. Applying k-means cluster analysis, we grouped participants by psychosocial characteristics hypothesized to impact adherence. Then, we conducted mixed effects regression to compare suboptimal adherence–defined as 10% of doses)–between clusters. Treatment setting (facility vs. home) and drug formulation (single drug vs. fixed dose combination) were interaction terms. Of 249 participants, 90 (36.1%) were female. Median age was 17 (IQR: 15, 16.6) years. We identified three clusters–A, B, and C–of participants based on psychosocial characteristics. Cluster C had the lowest support from caregivers, other family members, and friends; had the weakest motivation to complete TB treatment; were least likely to live with their mothers; and had experienced the most childhood adversity. Among the 118 (47.4%) participants who received facility-based treatment with single drug formulations, adherence did not differ between Clusters A and B, but Cluster C had six-fold odds of suboptimal adherence compared to Cluster A. In Clusters B and C, adherence worsened over time, but only in Cluster C did mean adherence fall below 90% within six months. Our findings have implications for the care of adolescents with TB. When caring for adolescents with low social support and other risk factors, clinicians should take extra measures to reinforce adherence, such as identifying a community health worker or peer to provide treatment support. Implementing newly recommended shorter regimens also may facilitate adherence.</div