Participant Characteristics. Table 1 summarizes the descriptive data on socio-demographic characteristics and depression variables. There were statistically significant differences between the two groups in age, gender and level of education (6-10 vs. ≥ 11 years of formal education). Healthy participants were slightly older (F(1, 120) = 3.66, p = .058), counted a higher proportion of males (χ2(1) = 15.67, p <.001) and were higher educated (χ2(1) = 21.54, p <.001). All analyses comparing these two groups were corrected for age, gender and education. There were no significant differences in age or gender between the puzzle and music groups in the ND group; subsequently these variables were ignored in the analyses in this group. Although the mean CES-D found in the clinical group was below the cut point of 16, it was much higher than the mean reported in Beekman et al. (1994), who found in a sample of the normal population of Dutch elders [M = 8.8, SD = 6.9), t(62) = 5.44, p <.001]. In the clinical group, the correlation between the AMT and the CES-D (r = -.021, p = .87) and the association between the AMT and the use of antidepressants/tranquilizers (t = -0.31, p = .76) were non-significant. Hence, the analyses of AMT scores were not corrected for depression severity or use of antidepressants or tranquilizers. Table 1. Socio-demographic and mental health characteristics Remitted Depressed N=63 Never Depressed N=58 Test statistic p Age 55-86 F(1) = 3.41 .067 Mean (SD) 64.92 (6.84) 67.5 (8.5) 55 – 59 16 11 60 - 64 20 11 65 – 69 10 12 70 - 75 9 12 75 – 85 8 11 Gender M 15 (24%) 34 (58.6%) χ2(1) = 15.19 <.001 Cohabiting 38 (60.3%) 39 (67.6%) χ2(1) = 0.63 .429 EDU ≥ 11 yrs 30 (47.6%) 51 (88%) χ2(1) = 22.18 <.001 Mental Health Characteristics Previous MDD ≥ 2 episodes CES-D Mean (SD) Range ≥ 16 ≥ 22 Antidepressants or Tranquilliser a a five missing 54 (85.7%) 37 (59.7%) 15.07 (9.14) 0 – 43 29 (46%) 12 (19%) 13 (22%) Group differences on the AMT were analyzed with a multivariate ANOVA with group, gender and education level as BS variables and age as covariate. Only age had a significant main effect [Λ = 0.82, F(2, 111) = 12.15, p <.001]. Univariate tests showed that age affected the positive but not the negative cue words (F = 24.50, p <.001). Mood changes and the test-retest effect of the AMT were analyzed with a 2 (induction type: puzzle or music) x 2 (word valence: negative, positive) ANOVA repeated measures on the second factor. No different response pattern to positive and negative cue wo...
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. 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. A total of 79 HIV-negative, non-pregnant women aged 18-50, with at least one HIV risk factor were included in the statistical analysis. Table 1 provides a summary of the demographic characteristics of the sample of 79 women. The total mean age was 34 years with a standard deviation of 8.53, while the mean number of children was 1.95 with a standard deviation of 1.84. Eighty percent (80% or 63/79) of the subjects self reported as Black, while 18% (14/79) self reported as White. Furthermore, 52% (41/79) of subjects reported receiving an education beyond school, 42% (33/79) received an education between 9th grade and a high school diploma, while 6% (5/79) reported that they were not educated beyond the 8th grade. Sixty-three percent (63% or 50/79) of the women stated that they were unemployed, while 75% (59/79) reported earning less than $10,000 a year. Only 3% (4/79) of participants reported being married. Approximately two-thirds (64% or 50/78) of women reported testing in the past year.
Participant Characteristics. A total of six key informants participated in interviews. Three of them were senior level employees at Xxxxxx Xxxxxxx, one from each of the three target countries. An employee involved in public engagement and fundraising at CARE Australia was also interviewed. The other two participants were experts in the field of social marketing – the CEO of a brand communications agency based in Australia and an employee at a social campaigning consultancy in the UK. All six participants had previous professional experience in social cause campaigning, including gender equality advocacy. The participants from CARE Australia and Xxxxxx Xxxxxxx Mexico had been aware of #ThisIsNotWorking prior to this research, as they worked on the initial launch of the campaign in their respective regions. Eight themes were identified based on the analysis. Four of the eight themes describe potential challenges for a global advocacy campaign, which were shaped by sociocultural factors present in the target countries. The other four themes discuss strategic considerations for improving the #ThisIsNotWorking campaign. such as immigration and national healthcare would be considered more important by the public. In Australia, large-scale problems, like global warming, have garnered more attention than GBV because it is believed that the latter “only affects half the population” (Australia, brand communications agency). Second, though there are some public discussions on gender equality in the workforce, GBV does not appear to be the main point of interest. The level of public awareness is higher when it concerns more pervasive and visible problems, such as gender pay gap and lack of female representation in business leadership. A comment from one of the participants from the UK exemplified such lack of public awareness about GBV at work, as she said she was not aware of any previous gender equality campaigns that focused on the issue. She explained; “There is a lot of talk in the UK at the moment about gender equality from a paid perspective in the workplace… So that’s been more of the focus rather than matters like violence in the workplace… I think modern slavery as well gets some coverage. I’m not sure exactly how big of an issue [GBV at work] is here, if I’m honest” (UK, Xxxxxx Xxxxxxx) Third, participants noted that GBV at work, including sexual harassment, tends to be overlooked due to cultural interpretations that downplay abusive treatment of women. In the UK, sexual harassment is ...
Participant Characteristics. Agencies were selected to represent diverse state, county and city transportation service providers: roadway operations, regional planning, transit operations, emergency services, public works, traffic management, environmental control and tourism. Arrowhead Transit is the only private organization that participated in the discussion sessions. Arrowhead Transit provides transit service in the Arrowhead Region in northeastern Minnesota and is a division of the Arrowhead Economic Opportunity Agency, a private, non-profit organization that provides various human services in the area. Each session included participants representing a mix of different agencies and transportation services. Table 2 is a list of agency departments and divisions whose representatives participated in the discussion sessions. Agency Name Department/Division Anoka County Anoka County Traveler Arrowhead Economic Opportunity Agency Arrowhead Transit City of Bloomington Public Works City of Duluth Duluth Transit Authority City of Minneapolis Police, Public Works City of Richfield Public Works City of St. Xxxx Public Works Hennepin County Medical Center, Traffic Metropolitan Council Planning, Transit Operations Minnesota Department of Tourism Travel Information Minnesota Department of Transportation Traffic; Truck Center; Traffic Management Center; Office of Electronic Communications; Districts 1, 6 and Metro; Freeway Operations Minnesota Pollution Control Agency Air and Noise Minnesota State Patrol Districts 2100, 2700, 3100 Rochester - Xxxxxxxx Council of Governments Transportation St. Louis County Public Works University of Minnesota Transportation
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, Xxxxx-Xxxxxx 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....
Participant Characteristics. Among the 2,865 participants who participated in the study, the average age was 20.53 (SD=1.93), 64.4% (n=1846) were female, 1,823 (63.6%) were White, 645 (22.5%) Black, 192 (6.7%) Asian, 205 (7.2%) Other, and 218 (7.6%) Hispanic. In our sample, never users comprised 56.3%, current (past 4 month) users 12.4%, and former users (those who had used in their lifetime but not in the past 4 months) 31.3%.
Participant Characteristics. Characteristic Measure N=60
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...
