Study Sample Sample Clauses

Study Sample. Sixty five of the 98 laboratories in the Netherlands eventually responded. Sixteen hospitals, of which the reported list could not be confirmed by a local obstetrician for logistical reasons, were excluded, leaving 49 hospitals available for final analysis. In total, 986 cases were reported by the 49 participating BTLs. The 49 hospitals appeared to be a representative sample of all hospitals in the Netherlands: the sample included three academic hospitals, 19 non-academic teaching hospitals and 27 other hospitals and centres were geographically equally distributed. Furthermore, the proportions of low, moderate and high volume hospitals were comparable to those of the Netherlands. In 162 cases (16.4%), the woman appeared not to have delivered at or around the day of transfusion according to the local birth register, leaving 824 confirmed cases of MOH. During the same period, 727 cases of MOH were reported to LEMMoN by the 49 eligible hospitals. After cross matching, we identified 1018 unique cases of MOH from both databases during the study period (Table 1). The estimated number of women not identified through either of the sources, ‘x’ in table 1, was calculated to be 105. Thus the total number of women with MOH is estimated at 1123. Only 727 cases were reported to LEMMoN, underreporting being estimated at 35% (396/1123). The other way around, 27% (299/1123) of cases would have been missed by only relying on transfusion data from BTLs, after consecutive confirmation by birth registers. Using both sources together would have still yielded an underreporting of 9% (105/1123). The use of a cell saver for auto transfusion was reported to XXXXxX in only four cases. This item was not registered by BTLs.

Study Sample. Our analysis included NCPs who: were over the age of 18; had a current child or family support order in 2020, with current support owed to a custodial parent (as opposed to the state); were insured by Medicaid in 2020; and, had a valid social security number in the state’s administrative records. There were 155,094 NCPs who owed current child support or family support in the year 20201 including NCPs with multiple child support orders in 20202; we included one record per NCP, regardless of the number of cases and we also included an indicator for NCPs with multiple orders. Our final sample is comprised of the 17% of NCPs with current support orders who were Medicaid-insured in 2020 (n=47,751). 1We began with the universe of NCPs who had current orders in 2020 (N=176,946). We excluded cases where the payee is the state of Wisconsin, not identified, not in our administrative records, or unknown, resulting in a universe of 157,162 NCPs. Of this sample, we find 47,751 NCPs who are Medicaid insured. 219.27 percent of the NCPs in our sample had more than one child or family support order. 2020; partial compliance, which includes those who paid greater than 0 and less than 90 percent; and full compliance, which includes those who paid at least 90 percent of their child support owed for 2020. For NCPs with multiple orders, we summed payments and order amounts across all orders to create one measure of compliance. Our primary models focus on a binary indicator for full compliance (defined as 90% or higher). In addition, some of our models include a variety of other measures that may be related to substance use or child support compliance. To account for differences in child support owed, from KIDS, we include the total current child support due in 2020. We also include wages as measured from the quarterly UI wage data. This allows us to include a measure of NCPs’ income from employers in Wisconsin for 2020. We created the following income categories based on annual wages in 2020: 1) $0 earners3, 2) $1 to $10,000, 3) $10,001 to $20,000, and 4) $20,001 to $30,000, and 5) $30,001 or more. Additional relevant NCP sociodemographic characteristics extracted from the administrative data include: age; race (White, Black, Native American, Asian / Pacific Islander); ethnicity (Hispanic/non-Hispanic); and gender (Male/Female). We have categorized age as follows: 18 to 29; 30 to 49; and 50 years and above. 3For purposes of this report, we treat any NCP without a wage record in...

Study Sample. The Sibanye Health Project was a pilot combination HIV prevention trial with MSM living in Cape Town and Port Xxxxxxxxx, South Africa. All participants enrolled in the study had to be at least 18 years old and male sex at birth. Other inclusion criteria included: reported anal sex with a man in the past 12 months, reported being a current resident of the study city, ability to complete all study instruments in English, Xhosa or Afrikaans, and having a telephone. Participants were recruited at events and venues, online, and by participant referral. Following written consent, all participants recruited into the study completed a self-administered baseline survey and a clinical exam. The baseline visit took approximately 2.25 hours. The baseline survey had information regarding demographics, use of health care services, history of HIV/STI testing, male sex disclosure, alcohol and substance use, condom use history, barriers to safe sex, current HIV knowledge, and sexual network assessment. The clinical exam included rapid HIV testing with laboratory confirmation and laboratory testing for syphilis, chlamydia and gonorrhea (urethral and rectal). Participants received 65 Rand for completing baseline study procedures. This study was reviewed and approved by appropriate humans subjects research review boards.

Study Sample. We included all women aged 19-64 diagnosed with breast cancer who are eligible for BCCPTA with those in the same age spectrum diagnosed with any one of five other cancers and enrolled in Medicaid in or after the month of their cancer diagnoses. We excluded those who enrolled in Medicaid over 65 since we were unable to observe their medical claims once they were into Medicare. We also excluded those who were enrolled prior to diagnosis because they would not be affected by the new eligibility rules under BCCPTA. These exclusions resulted in 3,238 observations, among whom 2,502 were breast cancer patients and 736 were control cancer patients. Those for which stage was missing in the GCCR and/or Medicaid claims data and those who had more than one primary cancer site over their lifetime were also omitted (N=826). The latter exclusion was made since the regional and distant codes in claims data could easily represent regional or distant disease progression from a different primary cancer than the one we observed. The final sample size was 2,412 women diagnosed with breast (N=1,898) and control cancers (N=514).

Study Sample. The couples sub-sample was obtained by matching male heads of households with their spouses in a secondary data analysis exercise (details Table 1). Overall at baseline, 5,232 women and 5,547 men completed interviews within households selected for a male interview. We excluded: 2,251 women because they were not designated as the spouse of a head of the household, 214 because they were not legally married or cohabitating, and 7 were not full time residents of the home*. A similar exclusion criteria was used among the 5,547 men surveyed. Overall, 2,760 women and 2,510 men were considered eligible to be matched. During the matching process, we could not identify partners for 576 women and 399 men, so these individuals were excluded from final analysis. Thus, the final matched sample includes 2,184 couples (2,184 women and 2,111 men since some men had multiple wives with whom they matched). The MLE project obtained ethical clearance from the University of North Carolina at Chapel Hill Institutional Review Board (UNC IRB) and the National Health Research Ethics Committee of Nigeria to conduct the surveys. This secondary data analysis was also approved by the UNC IRB.

Study Sample. Recruitment took place at the participating GDPH clinics. Aside from the eligibility conditions previously outlined for entrance into the MFHP, the primary inclusion criterion for this research was randomization into the intervention arm of the parent study. Individuals allocated to the education arm of the study were excluded. The projected recruitment rate for the MFHP was 15 persons per month from all five sites; therefore, it was anticipated that 180 people would enter the study in a one-year timeframe. Using Xxxxxxx et al.’s (2013) previous music-based research as a guide, a sample size of 149 was calculated using an attrition rate of 17%. However, this sub-study only focused on the intervention subjects, which was expected to yield a sample size of 75 subjects. For the three aims stated above, all of which were to have involved multivariate regression of one to three variables tested after controlling for one to two covariates, moderate effect sizes were expected for Δr2 (change in r-squared) of 0.13 for a sample size of 75 at 80% power and 5% level of significance. Power analyses were completed using PASS, Version 13 (Xxxxxx, 2014). Between March 2015 and February 2016, 34 participants were randomized into the intervention arm of the MFHP. Recruitment rates were inconsistent across all sites despite active screening efforts by study personnel and clinic liaisons, with some going weeks with few or no new participants. Factors contributing to the low recruitment rate are detailed in Chapter 5. Because the sample size was less than half of the expected 75 participants and data results had limited variability, adjustments were made to the initial statistical analysis plan. Specifically, hypothesis testing was conducted using nonparametric statistics, as opposed to the originally planned parametric tests. The Statistical Analysis section of this chapter gives a more thorough accounting of which tests were employed.

Study Sample. State-years are included in this analysis based on the presence (or absence) of a contraceptive coverage mandate and the years of availability in PRAMS. The study sample includes 11 treatment states that implemented contraceptive coverage mandates 2000-2008 and 13 control states that did not implement contraceptive coverage mandates (Table 1). The remaining 26 states and the District of Columbia are excluded from the study due to a lack of participation in PRAMS or missing data years surrounding mandate implementation (Table 2). The state of Texas chose not to release their PRAMS data to be used in this study. First, individual-level analysis uses a quasi-experimental study design exploiting variation in the year of implementation of state prescription contraception coverage mandates using a two-way fixed-effect method. I create a dummy variable indicating the presence or absence of a state contraception coverage mandate for each state-year based on the year of mandate implementation. I then use logistic and multinomial logistic analysis of pooled PRAMS data to estimate the effect of a mandate on the likelihood of each dichotomous measure of the three outcomes of interest: pregnancy prevention efforts, problems getting birth control, and unintended birth. These models compare the treatment group of privately insured recent mothers in state-years with mandates to privately-insured recent mothers in state-years without mandates. All models include state and year fixed effects, robust standard errors clustered at the state level, and PRAMS survey-weights. The base version of these models is presented below: 𝑃(𝑌)𝑖𝑠𝑡 = 𝛽0+ 𝛽1𝑀𝑎𝑛𝑑𝑎𝑡𝑒𝑖𝑠𝑡 + 𝛽2𝑋𝑖𝑠𝑡 + 𝛽3𝑍𝑠𝑡 + 𝑈𝑠 + 𝑇𝑡 + 𝜖 Where 𝑃(𝑌)𝑖𝑠𝑡 is the probability of an outcome variable for a mother (i) in state (s) during year (t); 𝑀𝑎𝑛𝑑𝑎𝑡𝑒𝑠𝑡 is a dummy variable indicating the presence of a contraception coverage mandate in state (s) during year (t); 𝑋𝑖 is a vector of individual characteristics for mother (i); 𝑍𝑠𝑡 is a measure of the percentage of employees insured through self-insured firms in state (s) during year (t); 𝑈𝑠 is a state effect; 𝑇𝑡 is a year effect; and 𝜖 is an unobserved error term.

Study Sample. The overall study sample, outlined in Table 2.1a, contains 35 patients with early psychosis, 44 patients with chronic psychosis, 69 unaffected first-degree relatives, 40 ARMS individuals and 76 unrelated controls with no history of psychosis. From this sample, I selected sub-samples for analysis, based on the availability of the EEG data. An overview of this process and the various samples investigated in the course of this thesis is presented in Figure 2.1a. The vast majority of patients included in this study had schizophrenia, schizoaffective disorder or another psychotic disorder (Table 2.1a), however a small number of bipolar disorder patients were also included, if the patient had a lifetime DSM-IV diagnosis of bipolar affective disorder type-1 with clear psychotic features (experiencing hallucinations and/or delusions at some point during their symptom exacerbation). All but 6 psychosis patients were medicated, the majority with an antipsychotic or a combination of antipsychotic + mood stabilizer/antidepressant (Figure 2.1b). Most participants (controls, ARMS and early psychosis patients) were recruited individually, but part of the chronic patients and relatives groups were recruited as part of a family study. Of the 264 participants, 181 (68.56%) were singletons, 58 (21.97%) were part of families with two members in the study, 21 (0.08%) were in three-person families, and 4 (0.015%) were part of one family with four members participating. COMBINED STUDY SAMPLE N=264 79 CONTROLS, 69 RELATIVES, 35 EARLY PSYCHOSIS PATIENTS, 44 CHRONIC PSYCHOSIS PATIENTS & 40 ARMS SUBEJCTS Oddball task Passive oddball paradigm Paired-click paradigm CHAPTER THREE CHAPTER FOUR CHAPTER FIVE N= 261 N=256 N=252 76 CONTROLS, 68 RELATIVES, 74 CONTROLS, 68 RELATIVES, 69 CONTROLS, 67 RELATIVES, 35 EARLY PSYCHOSIS 34 EARLY PSYCHOSIS 35 EARLY PSYCHOSIS PATIENTS, 43 CHRONIC PATIENTS, 43 CHRONIC PATIENTS, 43 CHRONIC PSYCHOSIS PATIENTS & 39 PSYCHOSIS PATIENTS & 39 PSYCHOSIS PATIENTS & 38 ARMS SUBJECTS ARMS SUBJECTS ARMS SUBJECTS CHAPTER SIX COMBINED PARADIGMS EROS SAMPLE N=246 69 CONTROLS, 66 RELATIVES, 34 EARLY PSYCHOSIS PATIENTS, 40 CHRONIC PSYCHOSIS PATIENTS & 37 ARMS SUBJECTS Figure 2.1a Breakdown of samples under investigation N ♀ : ♂ (% Male)a Mean Age (SD)b Tobacco2 – Non-Smokers : Smokers (% Smokers)c DSM-IV Diagnosis Positive Positive (SD) And Negative Negative (SD) Symptoms General (SD) Scale3 Total (SD) 76 69 79 40 34 : 35 (51%) 41 : 28 (41%) 20 : 59 (75%)** 16 : 24 (60%...

Study Sample. Due to resource limitations, we extracted hospitals in 12 states (CA, IL, IN, MA, MI, MN, MO, NY, OH, PA, TX, and WA) from the 2008 AHA EHR Dataset. All acute care hospitals in these states with a Medicare provider ID were included in our analysis. In the CMS dataset, hospitals were excluded if all of the measures they reported were based on fewer than 25 patients in the given year. After merging the aforementioned three datasets, the sample available for this analysis was 969 hospitals. It encompasses approximately 24% of the non-federal, acute care hospitals in the United States.

Study Sample. The inclusion criteria for the sample frame includes attending or resident psychiatrists that have worked at the Behavioral Health Outpatient Center at Xxxxx Memorial Hospital within the last three academic years, employed by either Emory University School of Medicine or Xxxxxxxxx School of Medicine (n=39). Three resident and three attending psychiatrists participated in the study. This study used purposive sampling (Hennink, 2011) in order to learn more about psychiatrists’ experiences in an outpatient setting. However, there was also an element of convenience sampling (Xxxxxxxx, 1996); restricting recruitment to those who had worked within the past three years allowed for a larger sample frame by including psychiatric residents who had recently cycled through the Outpatient Center as part of their training, and who were easy to contact since they were still residents with the Schools of Medicine. Limited demographic information was collected during the interview on participants’ gender, current year of residency, and number of years of experience at the Outpatient Center. The participants included four male and two female psychiatrists. The participants were three attending psychiatrists and three resident psychiatrists. Four psychiatrists has fewer than 2 years of experiences at the Outpatient Center. The research study is a part of larger study on SRH. It received IRB approval by Emory University’s IRB via amendment on November 19, 2015 (Study No.: IRB00078443).