Participant Characteristics Sample Clauses

Participant Characteristics. Twenty-three healthy male R.O.T.C. cadets, as described in Table 1 (Mean ± SD & range), participated in this study. As seen in Table 1, the mean percentage body fat was significantly lower when analyzed with taping than with DXA (p < 0.001). Based on questionnaire data, the men self-reported to consume an average of 2,364.45 ± 1,479.78 mL water daily.

Participant Characteristics. In the full analysis, we included all 157 patients and 24 physicians who were eligible for and participated in our larger CHD prevention trial (see Tables 1 and 2). The sub-sample analysis of 20 clinic visits involved 20 patients and 9 different physicians. See Fig. 2 for a flow dia- gram of these samples. Patients in our full sample were mostly white, male, had at least some college education and a good self-perceived health status. Their mean predicted CHD risk over 10 years was 11.3%. Most patients expressed a preference for shared decision making about CHD prevention. Char- acteristics of patients who agreed with physi- cians about having CHD discussions (N = 103) were similar to those of the full sample. Char- acteristics of patients in the sub-sample were also similar to those in the full sample, although those in the sub-sample who reported discus- sions were slightly more likely to be male. Physicians in our full sample were mostly at- tendings (physicians-in-practice) and most also indicated a preference for shared decision mak- ing about CHD prevention. The sub-sample of physicians was slightly older and contained a higher proportion of males and attendings than the full sample. Those physicians reporting CHD discussions in both the full sample and sub-sample had similar characteristics to their respective full groups. Full sample analysis: patient–physician agreement on visit content Patients and physicians agreed 83% of the time (95% CI: 72–86%) about whether they had a CHD prevention discussion during their clinic visit (see Table 3), with a kappa value of 0.55 (95% CI: 0.40–0.70) indicating moderate agree- ment. We found 27 cases where both patient and physician agreed that no CHD prevention dis- 157 patient-physician clinic visits completed Excluded: 27 visits where patient and physician agreed no CHD discussion occurred Figure 2 Study flow diagram. Table 3 Patient and physician agree- ment on CHD prevention discussions Number of patients and physicians agreeing Percent agreement (95% CI) Kappa (95% CI) Presence of CHD discussion (N = 157) Reported they talked about CHD Yes 103 83% 0.55 No 27 (72–86%) Content of discussion (N = 103) Reported they talked about Mostly pros 31 53% (0.40–0.70) 0.15 Pros and cons 24 Mostly cons 0 Patient expressed preferences (N = 103) (45–64%) (–0.01–0.30) A lot 16 41% 0.16 A little 19 Not really 8 Patient alone 0 43% 0.13 Patient with physician opinion 5 (32–54%) (–0.11–0.37) Shared decision 34 Physician alone ...

Participant Characteristics. The research question underlying these studies referred to “producers” opinions on the effect of regulation and policy on their companies. “Producers” are here understood as commercial organisations forming part of the relevant value chains, and so including farmers, equipment suppliers and processors of the farmed product. In most of the countries studied as part of AquaVitae T8.2, the LTS aquaculture and IMTA sector(s) are comparatively small – compared with (for example) salmonid aquaculture in Norway or Scotland, they consist of relatively small companies employing relatively few people. Thus, in most cases there was a relatively small population from which to recruit industry representatives. While this eased the challenge of identifying and recruiting participants, especially when drawing on meetings or workshops organised by the industry, it may also have resulted in ‘stakeholder fatigue’. For example, the Scottish study used questionnaires, to avoid repeating a producer consultation workshop held one year before by another research project. Thus, those participating in the workshops etc. reported here, may have been more strongly motivated than those who did not participate. Nevertheless, there is no reason to think that industry participants, and their opinions, were unrepresentative of their sector. Most events also included representatives of other sectors with an interest in the industry, especially researchers, regulators, and local government representatives. The effect of this heterogeneity remains to be examined. Table 3 summarises information relevant to the representativeness and heterogeneity of the event participants. the appropriate value chain (including farmers, equipment suppliers, and processors). Offshore workshop, Sweden 27% An open invitation was sent to the organisers networks and key actors networks, and industry representatives registered to participate in the workshop. Some industry representatives were engaged as presenters with offer of travel expenses to encourage attendance. An estimated 40-50% of the LTS offshore industry was represented. Macroalgae workshop, Norway 26% Open invitation sent to organisers networks, and industry representatives registered to participate in the workshop. The percentage of industry (macroalgae cultivation companies) represented could not be estimated reliably. However, representatives from several leading companies and from network organisations for macroalgae producers in Norway participat...

Participant Characteristics. Characteristics Homeless Non-homeless Probability % % Statistic* Age 0.388 26-40 15.2 8.9 41-55 48.5 45.6 55-70 30.3 41.8 >70 3.0 3.8 Gender 0.146 Male 69.7 58.2 Female 30.3 41.8 Race 0.496 White 21.2 9.0 Black/African American 78.8 88.5 Other 0 2.6 Ethnicity 0.496 Non-Hispanic/Latino 100 97.5 Hispanic/Latino 0.0 2.5 Income ($/month) 0.024 0-750 75.0 46.1 751-999 18.8 23.7 1000-1999 3.1 19.7 2000-2999 3.1 1.3 ≥3000 0 9.2 Health Insurance 0.093 Medicaid 27.3 24.1 Medicare 12.1 22.8 Uninsured 54.5 34.2 Other 6.1 19.0 Education Level 0.332 8th grade or less 9.1 2.5 9-11 grade 24.2 20.3 Graduated High School/GED 45.5 39.2 Some college/2-year degree 9.1 25.3 4-year college degree 6.1 7.6 Graduate school 6.1 5.1 History Alcohol Abuse 51.5 25.3 0.007 History of Drug abuse 69.7 31.6 <0.001 History of psychiatric diagnosis 63.6 32.9 0.003 Reported General Health Status 0.728 Excellent 3.0 5.1 Very Good 12.1 5.1 Good 24.2 29.1 Fair 48.5 48.1 Poor 12.1 12.7 Participants had no statistical differences between reasons for hospitalization, day of hospitalization or number of other comorbid conditions on admission (Table 5). In both cohorts, the most common cause for hospitalization reported in the history and physical admissions note was cardiovascular with 33.3% in the homeless population and 25.1% in the non-homeless population. Cardiovascular included conditions such as myocardial infarction, hypertension, hypotension, chest pain, and congestive heart failure, arrhythmias, among others. Infection included conditions such as cellulitis, sepsis, pneumonia, influenza, HIV, among others. Respiratory conditions included chronic obstructive pulmonary disease, respiratory failure, dyspnea, and pulmonary embolism. Neurologic included strokes, altered mental status, headaches, seizures, etc. The category “other” include a myriad of conditions, including glycemic control issues, liver conditions, cancer, social issues, kidney problems, and electrolyte imbalances. The absolute number value for any one of these conditions was too insignificant to warrant separate categories. For example, glycemic control concerns were the most common conditions in the “other” category, with an n of 3 individuals. Both sets of participants had a similar number of comorbid conditions as well, with both groups having approximately four other conditions, in addition to the admission diagnosis, documented in the history and physical admission note. Finally, both sets of participants had roughly compa...

Participant Characteristics. There were 12,032 AYMSM aged 15 to 24 years who were included in our study. Overall, 47% of participants reported receiving free condoms (Table 3.1). AYMSM in the most disadvantaged ZCTAS had a mean age of 21 years (SD 2.4), were 11% Black and 33% Hispanic, and resided primarily in urban areas (45%). In comparison, AYMSM in the least disadvantaged ZCTAs were younger (mean age 20 years, SD 2.5), predominantly White (78%), and more likely to reside in suburban areas (49%). Among AYMSM in the most disadvantaged ZCTAs, 11% reported not having any health insurance, compared to 5% among AYMSM in the least disadvantaged ZCTAs. Having seen a health care provider in the past year was high in both groups. AYMSM in the most disadvantaged ZCTAs reported higher levels of CAI (67%) and STI diagnosis (10%) in the past year than AYMSM in the least disadvantaged ZCTAs, among whom 59% reported CAI and 7% an STI diagnosis. AYMSM in the most disadvantaged ZCTAs reported higher levels of STI testing in the past year (38%) and having ever tested for HIV (61%). AYMSM in the least disadvantaged ZCTAs reported less STI testing in the past year (31%), and less than half (47%) had ever been tested for HIV. Approximately two-thirds (67%) of AYMSM in the most disadvantaged ZCTAs and 55% of AYMSM in the least disadvantaged ZCTAs had heard of PrEP. Receipt of free condoms was reported by 53% of AYMSM in the most disadvantaged ZCTAs and 45% of AYMSM in the least disadvantaged ZCTAs. By ICE, AYMSM who resided in ZCTAs with the highest concentration of POC individuals (Q5) were correspondingly, more racially and ethnically diverse, with 54% Hispanic and 14% Black, whereas AYMSM who resided in ZCTAs with the highest concentration of White individuals (Q1) were 91% White, 7% Hispanic, and 1% Black. Among AYMSM in the highest POC concentration ZCTAs, 67% identified as gay and 25% were bisexual, whereas 72% of AYMSM in the highest White concentration ZCTAs identified as gay and 22% as bisexual. AYMSM in the highest POC concentration ZCTAs primarily resided in the South (45%) and West (33%) and in urban areas (57%). AYMSM in the highest White concentration ZCTAs were largely from the Midwest (43%) and Northeast (30%) and resided in rural (35%) and small and medium metropolitan (34%) areas. Across both groups, AYMSM were similar in age (mean age of 20 years). Among AYMSM in the highest POC concentration ZCTAs, 88% were on track with their education, and 13% reported being uninsured. For AYMSM in...

Participant Characteristics. All (n = 15) AB Regular Users (n = 7) AB Non-Regular Users (n = 8) Mean (SD) Minimum Maximum Mean (SD) Mean (SD) Age 28.9 (8.3) 21 53 34.8 (10.5) 25.3 (2.7) Height (cm) 172.5 (7.8) 152.5 186.5 173.5 (7.4) 174.0 (5.2) Body Mass (kg) 74.6 (15.5) 54.1 110.3 76.1 (12.0) 75.9 (17.5) BF (%) 19.0 (6.0) 10.2 30.8 17.0 (5.0) 21.0 (7.0) FFM (kg) 63.5 (11.2) 44.2 86.6 63.3 (12.7) 65.7 (9.0) FM (kg) 15.9 (9.1) 8.4 40.7 12.8 (3.2) 18.6 (11.4) Resting HR (bpm) 62.3 (11.8) 47 91 59.2 (16.0) 64.9 (9.2) Agreement measures between the VȮ 2max protocols were evaluated using several statistical analyses, including ICC (Table 2). The ICC results demonstrated good to excellent agreement in V̇O2max (ICC = 0.92 [0.32, 0.98], F(14,14) = 27, p < 0.001), maximum HR (ICC = 0.89 [0.49, 0.97], F(14,14) = 14, p < 0.001), and RPE (ICC = 0.91 [0.74, 0.97], F(14,14) = 11, p < 0.001). However, paired t-tests indicated significant differences between the VȮ 2max protocols in several measures. Specifically, there were significant differences observed in V̇O2max (t(14) = 4.344, p < 0.001), maximum HR (t(14) = 3.137, p = 0.007), HR at ventilatory threshold (t(14) = 3.543, p = 0.003), and test duration (t(14) = 5.572, p < 0.001). Furthermore, ▇▇▇▇▇-▇▇▇▇▇▇ analyses revealed a systematic bias of 3.31 mL/kg/min (treadmill > AB, 95%CI[1.67, 4.94]), with a lower limit of agreement of -2.59 (95%CI[-5.42, 0.24]) and an upper limit of agreement of 9.20 (95%CI[6.38, 12.03]). Notably, no proportional bias was observed between the two protocols (Figure 2). There was no difference in V 2max on the AB between participants who reported regular use of the AB compared to those who did not use the AB regularly (W = 13.5, p = 0.105, d = 0.80). The only V̇O2max test parameter found to differ between the regular and non-regular AB users was test duration (regular user > non-regular user duration; W = 9, p = 0.029, d = 1.26). However, subsequent analyses (Table 3) revealed a higher level of agreement in VȮ 2max measures among participants who regularly use the AB (Figure 3) compared to those who do not (Figure 4). Specifically, a systematic bias of 1.27 (95%CI[0.20, 2.34]) mL/kg/min was observed among regular AB users, with a lower and upper limit of agreement of -2.60 (95%CI[-4.46, -0.74]) and 5.15 (95%CI[3.29, 7.00]) mL/kg/min, respectively. Whereas, participants who did not regularly use the AB exhibited a systematic bias of 5.09 (95%CI[3.69, 6.49]) mL/kg/min, with a lower limit of agreement of 0.03 (95%CI[-2.40, 2....

Participant Characteristics. Table 2. Means, Standard Deviations, and Stability of Maternal Distress across Time Table 3. Descriptive Statistics – Birth Outcomes at Time 3 Table 4. Descriptive Characteristics – Infant Outcomes Table 5. Simple Regression Analyses: Fetal Heart Rate Responses on Birth Outcomes Table 6. Logistic Regression of Fetal Responsivity Variables Predicting Non-optimal ▇▇▇▇▇ Scores at 5min Table 7. Simple Regression Analyses: Fetal Movement Responses on Birth Outcomes Table 8. Simple Regression Analyses: Fetal Heart Rate Responses on Infant Outcomes Table 9. Simple Regression Analyses: Fetal Movement Responses on Infant Outcomes Table 10. Correlations: All Study Variables Table 11. Intercorrelations between Measures of Distress and Infant/Fetal Outcomes Figure 1. Time course and events of study participation.

Participant Characteristics. A total of 16 people were recruited for each discussion session, with the expectation that no fewer than 12 would actually participate due to last-minute cancellations. Respondents were, with some exceptions, randomly recruited from telephone exchange areas of targeted geographic locations. The goal was to have a robust mix of people with different transportation/travel experiences and needs represented in each session. For the Twin Cities, the recruitment area was the seven-county region; respondents were given a choice of which session to attend. For Greater Minnesota locations, participants were recruited from a 30-mile radius of the targeted city. The selection process yielded both male and female participants, at least 21 years of age, with a variety of travel modes and occupations, including those who were employed outside the home and those who were not (see Figure 2). Screening criteria were applied to respondents to ensure representation of certain types of travelers. The criteria included employment status, primary travel mode, work trip travel time, and occupation. These recruitment criteria varied by session as listed below. It should be noted that the data shown in Figure 2 does not include participants from the "dry run" and professional driver sessions. The "dry run" participant profile data was not included in Figure 2 because the main purpose of that session was to determine areas of the discussion sessions that needed refinement. Therefore, demographics on the screening criteria were not collected. However, the session data about transportation needs are included in the analysis found in the remainder of this document. The professional drivers session was not included because the main selection criteria for this session was that the participant's occupation involved heavy use of the transportation system, such as a delivery truck driver. Therefore, the other selection criteria were not relevant to this group.

Participant Characteristics. RTI International examined the sociodemograpic information of participants in order to determine how well focus group participants represented Legacy mothers overall, and clarify any contextual factors that may have contributed toward participants’ experience with and perspectives on the program. This information covered three general areas: racial/ethnic information, employment status, and language preference. Racial/ethnic information. In Miami, the majority of mothers identified as Black/non-Hispanic (75%). Seven percent of mothers identified as Hispanic, and one percent identified with another racial/ethnic group. In Los Angeles, the majority of mothers identified as Hispanic (52%), or Black/non-Hispanic (34%). Five percent of respondents identified as White/non-Hispanic, and another two percent identified as Asian. The remaining five percent identified with another racial/ethnic group. RTI International determined the racial/ethnic composition of focus groups mirrored that of Legacy participants overall.