There are 11 females who are ages 50 to 70 that gave the overall health rating as 5 and smoke less than 10 in one day.
Among 339 individuals who rated fatigue score in the past 7 days higher than 3, 23% of these are Hispanics who had a Charleston chronic disease score of less than 2. When compare with total participants, Hispanics who had a fatigue score greater than 3 and a Charleston chronic disease score less than 2 are only 79 out of 2,356 participants, accounting for 3.35%.
A t-test and an OLS regression were used to determine the differences of pain rating in the past seven days between males and females. The t-test output indicates a significant difference of pain score between females and males, t (2130) = 5.8629, p<0.001.
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Consistent with the result of regression test, the F test is also 31.40(p<0.001). Moreover, black and other race/ethnicity have a significantly higher age than white race/ethnicity. So, age at that time of interview differs by race.
According to the table, the majority of participants are Black, accounting for 55%, following by Hispanic, white and other race/ethnicities. Of these, 58% are females. The mean of fatigue score is 2.66 (S.D.=0.94) and 43% reported the fatigue score as moderate level. The participants rated the various pain score from 0 to 10 and the mean of pain score is 4.64 (S.D.=3.01). Other factors such as a satisfaction with social activities score, mental health score, and quality of life score in moderate level with 39%, 36%, and 42%. While, nearly 42% of participants rated a physical health score as lower level.
These model including of quality of life, mental health rating, Physical health, satisfaction with social activities, pain score, race/ethnicity, and sex explain 33% of the variance in fatigue rating (R2 = 0.33, F(9,1697) = 92.34, p < 0.001). There is a strongly significant relationship between fatigue score and a set of predictors. Hispanic and other race/ethnicity have not a statistically significant effect. For calculating the estimated value of fatigue score, we can put this information into this equation:
Unstandardized slope: Fatigue rating increases by 0.0954 units with each 1
Using a true experimental study and a between-subject design, the forty-five participants are to be randomly assigned to one of three treatment conditions. In an effort to eliminate negative expectancy biases, demand characteristics, and reactivity on assessments, participants are not to be informed of which one of the three conditions they are to be assigned to. Using a ABA design, participants are going to first be assessed using the GAD-7 to establish a baseline of symptoms. The GAD-7 is a short seven-item self-report questionnaire that is proven to have strong reliability as well as good construct and procedural validity (Spitzer, et al., 2006). Upon establishing a baseline for each participant, one of the three treatment conditions are to be implemented as the studies independent variables. After
Three different measurements were taken before and after the study. They included, pain intensity, disability, and quality of life. Pain was taken using a visual analog scale (VAS) which ranges from 0 to 10; 0 equaling no pain at all and 10 equaling the worst pain ever felt. Disability was taken using the Neck Disability Index (NDI). The NDI consisted of 10 items and were scored using percentages, the higher the percentage the higher the disability. And lastly, quality of life was taken using the Medical Outcome Study Short-Form 36 Health Survey (SF-36). Scores in SF-36 ranged from 0 to 100 and the higher the patients number got, the better quality of life.
In the study, the between-groups design and the cross-sectional design were used for research. There were 243 participants between the ages of 18 and 39, and the majority were females and Caucasians. The average age was about 21 years old.
The researchers used a coin to select the sample for the two groups of the study, a demographic questionnaire to collect data, a Wong-Baker FACES Pain Rating Scale to assess the children pain level before and after the procedure, and an elastic soft ball. The study clearly described the tools, provided a detailed explanation of the Wong-Baker FACES and how it was used during the procedures, which proved the validity and reliability of the instruments used in the study. Validity is defined as a determination of how well the instrument reflects the concept being examined, and reliability is demonstrated when consistent results are produced using the same instruments (Grove et al., 2015). Lastly, to evaluate the data of the results the authors used SPSS program which evaluate the frequency, mean, percent and standard deviation, they used the chi-square test to evaluate the homogeneity of the two groups, the kolmogorov-smirnov test to assess the normality of the data, and the independent t-test to compare children’s pain in the intervention and control
The studied group consisted of 253 participants. The participants’ characteristics were the following: (1) their average age was 9.4 years (with a standard deviation of 1.1 years of age), (2) 130 were female and 123 were male, and (3) 126 were in the third-grade and 127 were in the fifth-grade. Their Family Cultural Status (FCS) characteristics were the following: (A) Low: consisting of 86 participants (34% of the total pool of subjects)— (1) their average age was 9.5 years (with a standard deviation of 1.0 years of age), (2) 38 were female and 48 were male, and (3) 39 were in the third-grade and 47 were in the fifth-grade; (B) Moderate: consisting of 97 participants (38% of the
Results: The study evaluated 22,599 samples representing 503,374,648 weighted individuals nationally from 2005-2008. Average age was 49 years, female 57%, Caucasian 83%, and the greatest percentage were from the South region of United States of America (36.8%).
This questionnaire has several subdomain scores including Vitality, Physical Functioning or Emotional Role Functioning and two component scores Physical (SF-PCS) respectively Mental (SF-MCS), the scores ranging from 0 (worst possible) to 100 (best possible) [10]. In this study, SF-36 was used to compare HRQoL in both populations and in particular, to detect the presence of the clinically significant fatigue: this is defined with scores for Vitality subdomain of 50 or less. This cut-off being validated in other autoimmune debilitating diseases such as multiple sclerosis or rheumatoid arthritis [11-13].
To find the 95% of the men’s scores you would again use the formula:. The Mean=52.53 and the SD=30.90. These scores were found on pg. 134 in table 2 column labeled Male in the pain category.
The data that will be shown will be as mean values, and standard deviations. Descriptive statistics was computed. T-tests was used to examine the two population means of each variable. One-way Repeated-measures Analysis of Variance (ANOVA) was used as the statistical tool in order to analyze pain score, systolic and diastolic blood pressure, pulse rate, and respiratory rate over time between the two groups. It is a requirement if the subjects will be exposed to three, or if greater, treatment conditions and/or when multiple measures of the same dependent variables, in which are collected longitudinally, to use repeated-measures. (Polit & Beck, 2003) A statistically-significant level of 0.05 is
The participants recorded their pain during activity using the numerical rating scale (NRS) during the initial examination. The participants received three IASTM treatments a week
The Shapiro-Wilk statistical test is used to assess the normal distribution of the pain intensity before conducting subsequent statistical tests. Data analysis is performed using mixed models with two-sided, with a type I error set as .05. Concerning the primary objective, the comparison between randomized groups will be performed using ANOVA with a baseline score as a covariate. The correlation between baseline and follow-up scores is also calculated (Vickers, 2001). In the secondary analysis, chi-square is carried out to express the frequencies of adverse effects and response rate. Also, A paired student test is suggested to evaluate the pain reduction within the two groups. Sensitivity analysis will be proposed to assess the robustness of the data based on the pattern-mixture and selection
Data was presented with the aid of (1) a figure depicting the scale used by patients to quantify each of the six qualities of self-perceived well-being, and (2) a table presenting mean and standard deviations of each reported value before and after treatment. Statistical tests used to analyze data included (1) a Wilks’s test to investigate change between pre-and post-treatment, regardless of session type, (2) an interaction effect analysis to determine if the measured effect differed among treatment types and durations, (3) one-way ANOVAs to further examine the potential differences in changes dependent on therapy, (4) Tukey HSD to consider pairwise differences, and (5) mean comparison. Wilks’s and interaction effects were performed to measure the significance of each of the six characteristics of patient well-being. ANOVAs and Tukey HSD were further used in the analysis of pain, while mean comparison was used for overall wellness and quality of life. All p-values reported were <0.001, indicating statistical significance.
As regards association between sociodemographic variable and pain intensity, there was a significant relation between pain and socio-demographic data as presented in table (4) where p value <0.005 and there was an overall decrease of pain level on Heifer technique than Traditional technique. Regarding age , the age group from (20-29) have the higher pain level as mean standard was 8±2.4on traditional technique and 5.5±2.5 on Heifer technique , while the patient aged (50-60) have the lowest pain level as mean standard was 6.5±2.1on traditional technique and 5±1.9 on Heifer technique . Regarding gender , the female have highest degree of pain mean standard was 8±2.7on traditional technique and 5.8±2.3 on Heifer technique . Regarding marital
In the following paragraphs, an attempt to group several related independent factors affecting quality of life is undertaken. Wherever possible these socio-demographic variables, clinical variables are linked with evidence from literature to reduce conjecture.
The first step in the analysis is to graphically display major outcome and explanatory variables to: 1) identify outlying or influential observations and the need for transformation to simplify analyses, and 2) summarize the relationships among key variables. Standard psychometric methods, including Cronbach alpha to assess internal consistency, reliability and factor analysis to assess the scale structure (partial construct validity), will be used to verify the psychometric properties of summary scales for each of the major measurement instruments. Prior to testing the theoretical model guided analysis, univariate distributions will be inspected to assess normality and identify outliers, skewness, or other abnormalities in distribution, and to determine appropriate summaries of location and spread and the need for transformation. Items with little variation, excessive numbers of missing responses,