Facility Service Environments, Staffing, and Psychosocial Care in Nursing Homes

Using 2003 Online Survey Certification and Reporting (OSCAR) data for Medicare and Medicaid certified facilities (N=14, 184) and multinomial logistic regression this study investigated if (1) psychosocial care quality was better in facilities where State requirements for qualified social services staffing exceeded Federal minimum regulations and (2) facility service environments are associated with psychosocial care quality. For-profit status and higher percentage of Medicaid residents are associated with lower quality. Staffing, market demand, and market competition are associated with better quality. Psychosocial care quality is more associated with payer status and market forces and less with regulatory requirements

Social Service Staffing in US Nursing Homes

Using data from the 2003 national Online Survey Certification and Reporting System, this study examines how the structure of social service staffing in nursing homes is affected by organizational and contextual factors. The results suggest that, although federal regulations impose minimal obligation, requiring only facilities with more than 120 beds to employ qualified social service providers, nearly 12 percent of these facilities failed to meet this staffing requirement in 2003. Results further suggest that the skill mix of social service providers in nursing homes is influenced by market competition, market demand, facility ownership, aggregate resident acuity, and the proportion of facility residents funded by Medicare

The impact of demographic and perceptual variables on a young adult\u27s decision to be covered by private health insurance

Background: The large number of uninsured individuals in the United States creates negative consequences for those who are uninsured and for those who are covered by health insurance plans. Young adults between the ages of 18 and 24 are the largest uninsured population subgroup. This subgroup warrants analysis. The major aim of this study is to determine why young adults between the ages of 18 and 24 are the largest uninsured population subgroup. Methods: The present study seeks to determine why young adults between the ages of 18 and 24 are the largest population subgroup that is not covered by private health insurance. Data on perceived health status, perceived need, perceived value, socioeconomic status, gender, and race was obtained from a national sample of 1,340 young adults from the 2005 Medical Expenditure Panel Survey and examined for possible explanatory variables, as well as data on the same variables from a national sample of 1,463 from the 2008 Medical Expenditure Panel Survey. Results: Results of the structural equation model analysis indicate that insurance coverage in the 2005 sample was largely a function of higher socioeconomic status and being a non-minority. Perceived health status, perceived need, perceived value, and gender were not significant predictors of private health insurance coverage in the 2005 sample. However, in the 2008 sample, these indicators changed. Socioeconomic status, minority status, perceived health, perceived need, and perceived value were significant predictors of private health insurance coverage. Conclusions: The results of this study show that coverage by a private health insurance plan in the 2005 sample was largely a matter of having a higher socioeconomic status and having a non-minority status. In 2008 each of the attitudinal variables (perceived health, perceived value, and perceived need) predicted whether subjects carried private insurance. Our findings suggest that among those sampled, the young adult subgroup between the ages of 18 and 24 does not necessarily represent a unique segment of the population, with behaviors differing from the rest of the sample

The impact of demographic and perceptual variables on a young adult\u27s decision to be covered by private health insurance

Background: The large number of uninsured individuals in the United States creates negative consequences for those who are uninsured and for those who are covered by health insurance plans. Young adults between the ages of 18 and 24 are the largest uninsured population subgroup. This subgroup warrants analysis. The major aim of this study is to determine why young adults between the ages of 18 and 24 are the largest uninsured population subgroup. Methods: The present study seeks to determine why young adults between the ages of 18 and 24 are the largest population subgroup that is not covered by private health insurance. Data on perceived health status, perceived need, perceived value, socioeconomic status, gender, and race was obtained from a national sample of 1,340 young adults from the 2005 Medical Expenditure Panel Survey and examined for possible explanatory variables, as well as data on the same variables from a national sample of 1,463 from the 2008 Medical Expenditure Panel Survey. Results: Results of the structural equation model analysis indicate that insurance coverage in the 2005 sample was largely a function of higher socioeconomic status and being a non-minority. Perceived health status, perceived need, perceived value, and gender were not significant predictors of private health insurance coverage in the 2005 sample. However, in the 2008 sample, these indicators changed. Socioeconomic status, minority status, perceived health, perceived need, and perceived value were significant predictors of private health insurance coverage. Conclusions: The results of this study show that coverage by a private health insurance plan in the 2005 sample was largely a matter of having a higher socioeconomic status and having a non-minority status. In 2008 each of the attitudinal variables (perceived health, perceived value, and perceived need) predicted whether subjects carried private insurance. Our findings suggest that among those sampled, the young adult subgroup between the ages of 18 and 24 does not necessarily represent a unique segment of the population, with behaviors differing from the rest of the sample

Structural equation modeling of the proximal-distal continuum of adherence drivers

Objectives: Nonadherence to prescription medications has been shown to be significantly influenced by three key medication-specific beliefs: patients\u27 perceived need for the prescribed medication, their concerns about the prescribed medication, and perceived medication affordability. Structural equation modeling was used to test the predictors of these three proximal determinants of medication adherence using the proximal-distal continuum of adherence drivers as the organizing conceptual framework. Methods: In Spring 2008, survey participants were selected from the Harris Interactive Chronic Illness Panel, an internet-based panel of hundreds of thousands of adults with chronic disease. Respondents were eligible for the survey if they were aged 40 years and older, resided in the US, and reported having at least one of six chronic diseases: asthma, diabetes, hyperlipidemia, hypertension, osteoporosis, or other cardiovascular disease. A final sample size of 1072 was achieved. The proximal medication beliefs were measured by three multi-item scales: perceived need for medications, perceived medication concerns, and perceived medication affordability. The intermediate sociomedical beliefs and skills included four multi-item scales: perceived disease severity, knowledge about the prescribed medication, perceived immunity to side effects, and perceived value of nutraceuticals. Generic health beliefs and skills consisted of patient engagement in their care, health information-seeking tendencies, internal health locus of control, a single-item measure of self-rated health, and general mental health. Structural equation modeling was used to model proximal-distal continuum of adherence drivers. Results: The average age was 58 years (range = 40-90 years), and 65% were female and 89% were white. Forty-one percent had at least a four-year college education, and just under half (45%) had an annual income of $50,000 or more. Hypertension and hyperlipidemia were each reported by about a quarter of respondents (24% and 23%, respectively). A smaller percentage of respondents had osteoporosis (17%), diabetes (15%), asthma (13%), or other cardiovascular disease (8%). Three independent variables were significantly associated with the three proximal adherence drivers: perceived disease severity, knowledge about the medication, and perceived value of nutraceuticals. Both perceived immunity to side effects and patient engagement was significantly associated with perceived need for medications and perceived medication concerns. Conclusion: Testing the proximal-distal continuum of adherence drivers shed light on specific areas where adherence dialogue and enhancement should focus. Our results can help to inform the design of future adherence interventions as well as the content of patient education materials and adherence reminder letters. For long-term medication adherence, patients need to autonomously and intrinsically commit to therapy and that, in turn, is more likely to occur if they are both informed (disease and medication knowledge and rationale, disease severity, consequences of nonadherence, and side effects) and motivated (engaged in their care, perceive a need for medication, and believe the benefits outweigh the risks)

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Correction to: Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

The original version of this article unfortunately contained a mistake

The Impact Of Tobacco-Free School Policies On Youth Smoking Rates In Florida Public School Districts

BACKGROUND: Developing and implementing policies to curb and prevent youth tobacco use is of the utmost importance. In Florida, public school districts were authorized to develop tobacco-free school policies through an amendment to the Florida Clean Indoor Air Act in 2011. The purpose of this study is to determine the impact of tobacco-free school policies on smoking rates among youth in Florida. METHODS: Analysis of covariance (ANCOVA) and a multiple regression analysis were used to determine whether the comprehensiveness and enforcement of tobacco-free school policies affect the youth smoking rates within Florida public school districts. The 2010 and 2014 youth smoking rates were calculated based on the Florida Youth Tobacco Survey results. RESULTS: The 2010 youth smoking rate and the inclusion of the enforcement component with provision of cessation resources were statistically significant predictors of the 2014 youth smoking rate. However, the comprehensiveness level of a policy and the inclusion of an enforcement component were not statistically significant predictors. CONCLUSIONS: The inclusion of an enforcement component with provision of cessation resources is important in efforts to reduce youth smoking rates. The content of the tobacco-free school policies seems to be less relevant to their effectiveness than the enforcement of the policies