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Table of Contents
ORIGINAL ARTICLE  
Year : 2019  |  Volume : 22  |  Issue : 1  |  Page : 67-72
Descriptive statistics and normality tests for statistical data

Prabhaker Mishra1, Chandra M Pandey1, Uttam Singh1, Anshul Gupta2, Chinmoy Sahu3, Amit Keshri4
1 Department of Biostatistics and Health Informatics, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
2 Department of Haematology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
3 Department of Microbiology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India
4 Department of Neuro-Otology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India

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Date of Web Publication14-Jan-2019
 

   Abstract 


Descriptive statistics are an important part of biomedical research which is used to describe the basic features of the data in the study. They provide simple summaries about the sample and the measures. Measures of the central tendency and dispersion are used to describe the quantitative data. For the continuous data, test of the normality is an important step for deciding the measures of central tendency and statistical methods for data analysis. When our data follow normal distribution, parametric tests otherwise nonparametric methods are used to compare the groups. There are different methods used to test the normality of data, including numerical and visual methods, and each method has its own advantages and disadvantages. In the present study, we have discussed the summary measures and methods used to test the normality of the data.

Keywords: Biomedical research, descriptive statistics, numerical and visual methods, test of normality

How to cite this article:
Mishra P, Pandey CM, Singh U, Gupta A, Sahu C, Keshri A. Descriptive statistics and normality tests for statistical data. Ann Card Anaesth 2019;22:67-72

How to cite this URL:
Mishra P, Pandey CM, Singh U, Gupta A, Sahu C, Keshri A. Descriptive statistics and normality tests for statistical data. Ann Card Anaesth [serial online] 2019 [cited 2022 May 27];22:67-72. Available from: https://www.annals.in/text.asp?2019/22/1/67/250184





   Introduction Top


A data set is a collection of the data of individual cases or subjects. Usually, it is meaningless to present such data individually because that will not produce any important conclusions. In place of individual case presentation, we present summary statistics of our data set with or without analytical form which can be easily absorbable for the audience. Statistics which is a science of collection, analysis, presentation, and interpretation of the data, have two main branches, are descriptive statistics and inferential statistics.[1]

Summary measures or summary statistics or descriptive statistics are used to summarize a set of observations, in order to communicate the largest amount of information as simply as possible. Descriptive statistics are the kind of information presented in just a few words to describe the basic features of the data in a study such as the mean and standard deviation (SD).[2],[3] The another is inferential statistics, which draw conclusions from data that are subject to random variation (e.g., observational errors and sampling variation). In inferential statistics, most predictions are for the future and generalizations about a population by studying a smaller sample.[2],[4] To draw the inference from the study participants in terms of different groups, etc., statistical methods are used. These statistical methods have some assumptions including normality of the continuous data. There are different methods used to test the normality of data, including numerical and visual methods, and each method has its own advantages and disadvantages.[5] Descriptive statistics and inferential statistics both are employed in scientific analysis of data and are equally important in the statistics. In the present study, we have discussed the summary measures to describe the data and methods used to test the normality of the data. To understand the descriptive statistics and test of the normality of the data, an example [Table 1] with a data set of 15 patients whose mean arterial pressure (MAP) was measured are given below. Further examples related to the measures of central tendency, dispersion, and tests of normality are discussed based on the above data.
Table 1: Distribution of mean arterial pressure (mmHg) as per sex

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Descriptive Statistics

There are three major types of descriptive statistics: Measures of frequency (frequency, percent), measures of central tendency (mean, median and mode), and measures of dispersion or variation (variance, SD, standard error, quartile, interquartile range, percentile, range, and coefficient of variation [CV]) provide simple summaries about the sample and the measures. A measure of frequency is usually used for the categorical data while others are used for quantitative data.


   Measures of Frequency Top


Frequency statistics simply count the number of times that in each variable occurs, such as the number of males and females within the sample or population. Frequency analysis is an important area of statistics that deals with the number of occurrences (frequency) and percentage. For example, according to [Table 1], out of the 15 patients, frequency of the males and females were 8 (53.3%) and 7 (46.7%), respectively.


   Measures of Central Tendency Top


Data are commonly describe the observations in a measure of central tendency, which is also called measures of central location, is used to find out the representative value of a data set. The mean, median, and mode are three types of measures of central tendency. Measures of central tendency give us one value (mean or median) for the distribution and this value represents the entire distribution. To make comparisons between two or more groups, representative values of these distributions are compared. It helps in further statistical analysis because many techniques of statistical analysis such as measures of dispersion, skewness, correlation, t-test, and ANOVA test are calculated using value of measures of central tendency. That is why measures of central tendency are also called as measures of the first order. A representative value (measures of central tendency) is considered good when it was calculated using all observations and not affected by extreme values because these values are used to calculate for further measures.


   Computation of Measures of Central Tendency Top


Mean

Mean is the mathematical average value of a set of data. Mean can be calculated using summation of the observations divided by number of observations. It is the most popular measure and very easy to calculate. It is a unique value for one group, that is, there is only one answer, which is useful when comparing between the groups. In the computation of mean, all the observations are used.[2],[5] One disadvantage with mean is that it is affected by extreme values (outliers). For example, according to [Table 2], mean MAP of the patients was 97.47 indicated that average MAP of the patients was 97.47 mmHg.
Table 2: Descriptive statistics of the mean arterial pressure (mmHg)

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Median

The median is defined as the middle most observation if data are arranged either in increasing or decreasing order of magnitude. Thus, it is one of the observations, which occupies the central place in the distribution (data). This is also called positional average. Extreme values (outliers) do not affect the median. It is unique, that is, there is only one median of one data set which is useful when comparing between the groups. There is one disadvantage of median over mean that it is not as popular as mean.[6] For example, according to [Table 2], median MAP of the patients was 95 mmHg indicated that 50% observations of the data are either less than or equal to the 95 mmHg and rest of the 50% observations are either equal or greater than 95 mmHg.

Mode

Mode is a value that occurs most frequently in a set of observation, that is, the observation, which has maximum frequency is called mode. In a data set, it is possible to have multiple modes or no mode exists. Due to the possibility of the multiple modes for one data set, it is not used to compare between the groups. For example, according to [Table 2], maximum repeated value is 116 mmHg (2 times) rest are repeated one time only, mode of the data is 116 mmHg.


   Measures of Dispersion Top


Measures of dispersion is another measure used to show how spread out (variation) in a data set also called measures of variation. It is quantitatively degree of variation or dispersion of values in a population or in a sample. More specifically, it is showing lack of representation of measures of central tendency usually for mean/median. These are indices that give us an idea about homogeneity or heterogeneity of the data.[2],[6]

Common measures

Variance, SD, standard error, quartile, interquartile range, percentile, range, and CV.


   Computation of Measures of Dispersion Top


Standard deviation and variance

The SD is a measure of how spread out values is from its mean value. Its symbol is σ (the Greek letter sigma) or s. It is called SD because we have taken a standard value (mean) to measures the dispersion. Where xi is individual value, x̄ is mean value. If sample size is <30, we use “n-1” in denominator, for sample size ≥30, use “n” in denominator. The variance (s2) is defined as the average of the squared difference from the mean. It is equal to the square of the SD (s).



For example, in the above, SD is 11.01 mmHg When n<30 which showed that approximate average deviation between mean value and individual values is 11.01. Similarly, variance is 121.22 [i.e., (11.01)2], which showed that average square deviation between mean value and individual values is 121.22 [Table 2].

Standard error

Standard error is the approximate difference between sample mean and population mean. When we draw the many samples from same population with same sample size through random sampling technique, then SD among the sample means is called standard error. If sample SD and sample size are given, we can calculate standard error for this sample, by using the formula.

Standard error = sample SD/√sample size.

For example, according to [Table 2], standard error is 2.84 mmHg, which showed that average mean difference between sample means and population mean is 2.84 mmHg [Table 2].

Quartiles and interquartile range

The quartiles are the three points that divide the data set into four equal groups, each group comprising a quarter of the data, for a set of data values which are arranged in either ascending or descending order. Q1, Q2, and Q3 are represent the first, second, and third quartile's value.[7]

For ith Quartile = [i * (n + 1)/4]th observation, where i = 1, 2, 3.

For example, in the above, first quartile (Q1) = (n + 1)/4= (15 + 1)/4 = 4th observation from initial = 88 mmHg (i.e., first 25% number of observations of the data are either ≤88 and rest 75% observations are either ≥88), Q2 (also called median) = [2* (n + 1)/4] = 8th observation from initial = 95 mmHg, that is, first 50% number of observations of the data are either less or equal to the 95 and rest 50% observations are either ≥95, and similarly Q3 = [3* (n + 1)/4] = 12th observation from initial = 107 mmHg, i.e., indicated that first 75% number of observations of the data are either ≤107 and rest 25% observations are either ≥107. The interquartile range (IQR) is a measure of variability, also called the midspread or middle 50%, which is a measure of statistical dispersion, being equal to the difference between 75th (Q3 or third quartile) and 25th (Q1 or first quartile) percentiles. For example, in the above example, three quartiles, that is, Q1, Q2, and Q3 are 88, 95, and 107, respectively. As the first and third quartile in the data is 88 and 107. Hence, IQR of the data is 19 mmHg (also can write like: 88–107) [Table 2].



Percentile

The percentiles are the 99 points that divide the data set into 100 equal groups, each group comprising a 1% of the data, for a set of data values which are arranged in either ascending or descending order. About 25% percentile is the first quartile, 50% percentile is the second quartile also called median value, while 75% percentile is the third quartile of the data.

For ith percentile = [i * (n + 1)/100]th observation, where i = 1, 2, 3.,99.

Example: In the above, 10th percentile = [10* (n + 1)/100] =1.6th observation from initial which is fall between the first and second observation from the initial = 1st observation + 0.6* (difference between the second and first observation) = 83.20 mmHg, which indicated that 10% of the data are either ≤83.20 and rest 90% observations are either ≥83.20.




   Coefficient of Variation Top


Interpretation of SD without considering the magnitude of mean of the sample or population may be misleading. To overcome this problem, CV gives an idea. CV gives the result in terms of ratio of SD with respect to its mean value, which expressed in %. CV = 100 × (SD/mean). For example, in the above, coefficient of the variation is 11.3% which indicated that SD is 11.3% of its mean value [i.e., 100* (11.01/97.47)] [Table 2].

Range

Difference between largest and smallest observation is called range. If A and B are smallest and largest observations in a data set, then the range (R) is equal to the difference of largest and smallest observation,th at is, R = A−B.

For example, in the above, minimum and maximum observation in the data is 82 mmHg and 116 mmHg. Hence, the range of the data is 34 mmHg (also can write like: 82–116) [Table 2].

Descriptive statistics can be calculated in the statistical software “SPSS” (analyze → descriptive statistics → frequencies or descriptives.

Normality of data and testing

The standard normal distribution is the most important continuous probability distribution has a bell-shaped density curve described by its mean and SD and extreme values in the data set have no significant impact on the mean value. If a continuous data is follow normal distribution then 68.2%, 95.4%, and 99.7% observations are lie between mean ± 1 SD, mean ± 2 SD, and mean ± 3 SD, respectively.[2],[4]

Why to test the normality of data

Various statistical methods used for data analysis make assumptions about normality, including correlation, regression, t-tests, and analysis of variance. Central limit theorem states that when sample size has 100 or more observations, violation of the normality is not a major issue.[5],[8] Although for meaningful conclusions, assumption of the normality should be followed irrespective of the sample size. If a continuous data follow normal distribution, then we present this data in mean value. Further, this mean value is used to compare between/among the groups to calculate the significance level (P value). If our data are not normally distributed, resultant mean is not a representative value of our data. A wrong selection of the representative value of a data set and further calculated significance level using this representative value might give wrong interpretation.[9] That is why, first we test the normality of the data, then we decide whether mean is applicable as representative value of the data or not. If applicable, then means are compared using parametric test otherwise medians are used to compare the groups, using nonparametric methods.

Methods used for test of normality of data

An assessment of the normality of data is a prerequisite for many statistical tests because normal data is an underlying assumption in parametric testing. There are two main methods of assessing normality: Graphical and numerical (including statistical tests).[3],[4] Statistical tests have the advantage of making an objective judgment of normality but have the disadvantage of sometimes not being sensitive enough at low sample sizes or overly sensitive to large sample sizes. Graphical interpretation has the advantage of allowing good judgment to assess normality in situations when numerical tests might be over or undersensitive. Although normality assessment using graphical methods need a great deal of the experience to avoid the wrong interpretations. If we do not have a good experience, it is the best to rely on the numerical methods.[10] There are various methods available to test the normality of the continuous data, out of them, most popular methods are Shapiro–Wilk test, Kolmogorov–Smirnov test, skewness, kurtosis, histogram, box plot, P–P Plot, Q–Q Plot, and mean with SD. The two well-known tests of normality, namely, the Kolmogorov–Smirnov test and the Shapiro–Wilk test are most widely used methods to test the normality of the data. Normality tests can be conducted in the statistical software “SPSS” (analyze → descriptive statistics → explore → plots → normality plots with tests).

The Shapiro–Wilk test is more appropriate method for small sample sizes (<50 samples) although it can also be handling on larger sample size while Kolmogorov–Smirnov test is used for n ≥50. For both of the above tests, null hypothesis states that data are taken from normal distributed population. When P > 0.05, null hypothesis accepted and data are called as normally distributed. Skewness is a measure of symmetry, or more precisely, the lack of symmetry of the normal distribution. Kurtosis is a measure of the peakedness of a distribution. The original kurtosis value is sometimes called kurtosis (proper). Most of the statistical packages such as SPSS provide “excess” kurtosis (also called kurtosis [excess]) obtained by subtracting 3 from the kurtosis (proper). A distribution, or data set, is symmetric if it looks the same to the left and right of the center point. If mean, median, and mode of a distribution coincide, then it is called a symmetric distribution, that is, skewness = 0, kurtosis (excess) = 0. A distribution is called approximate normal if skewness or kurtosis (excess) of the data are between − 1 and + 1. Although this is a less reliable method in the small-to-moderate sample size (i.e., n <300) because it can not adjust the standard error (as the sample size increases, the standard error decreases). To overcome this problem, a z-test is applied for normality test using skewness and kurtosis. A Z score could be obtained by dividing the skewness values or excess kurtosis value by their standard errors. For small sample size (n <50), z value ± 1.96 are sufficient to establish normality of the data.[8] However, medium-sized samples (50≤ n <300), at absolute z-value ± 3.29, conclude the distribution of the sample is normal.[11] For sample size >300, normality of the data is depend on the histograms and the absolute values of skewness and kurtosis. Either an absolute skewness value ≤2 or an absolute kurtosis (excess) ≤4 may be used as reference values for determining considerable normality.[11] A histogram is an estimate of the probability distribution of a continuous variable. If the graph is approximately bell-shaped and symmetric about the mean, we can assume normally distributed data[12],[13] [Figure 1]. In statistics, a Q–Q plot is a scatterplot created by plotting two sets of quantiles (observed and expected) against one another. For normally distributed data, observed data are approximate to the expected data, that is, they are statistically equal [Figure 2]. A P–P plot (probability–probability plot or percent–percent plot) is a graphical technique for assessing how closely two data sets (observed and expected) agree. It forms an approximate straight line when data are normally distributed. Departures from this straight line indicate departures from normality [Figure 3]. Box plot is another way to assess the normality of the data. It shows the median as a horizontal line inside the box and the IQR (range between the first and third quartile) as the length of the box. The whiskers (line extending from the top and bottom of the box) represent the minimum and maximum values when they are within 1.5 times the IQR from either end of the box (i.e., Q1 − 1.5* IQR and Q3 + 1.5* IQR). Scores >1.5 times and 3 times the IQR are out of the box plot and are considered as outliers and extreme outliers, respectively. A box plot that is symmetric with the median line at approximately the center of the box and with symmetric whiskers indicate that the data may have come from a normal distribution. In case many outliers are present in our data set, either outliers are need to remove or data should treat as nonnormally distributed[8],[13],[14] [Figure 4]. Another method of normality of the data is relative value of the SD with respect to mean. If SD is less than half mean (i.e., CV <50%), data are considered normal.[15] This is the quick method to test the normality. However this method should only be used when our sample size is at least 50.
Figure 1: Histogram showing the distribution of the mean arterial pressure

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Figure 2: Normal Q–Q Plot showing correlation between observed and expected values of the mean arterial pressure

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Figure 3: Normal P–P Plot showing correlation between observed and expected cumulative probability of the mean arterial pressure

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Figure 4: Boxplot showing distribution of the mean arterial pressure

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For example in [Table 1], data of MAP of the 15 patients are given. Normality of the above data was assessed. Result showed that data were normally distributed as skewness (0.398) and kurtosis (−0.825) individually were within ±1. Critical ratio (Z value) of the skewness (0.686) and kurtosis (−0.737) were within ±1.96, also evident to normally distributed. Similarly, Shapiro–Wilk test (P = 0.454) and Kolmogorov–Smirnov test (P = 0.200) were statistically insignificant, that is, data were considered normally distributed. As sample size is <50, we have to take Shapiro–Wilk test result and Kolmogorov–Smirnov test result must be avoided, although both methods indicated that data were normally distributed. As SD of the MAP was less than half mean value (11.01 <48.73), data were considered normally distributed, although due to sample size <50, we should avoid this method because it should use when our sample size is at least 50 [Table 2] and [Table 3].
Table 3: Skewness, kurtosis, and normality tests for mean arterial pressure (mmHg)

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   Conclusions Top


Descriptive statistics are a statistical method to summarizing data in a valid and meaningful way. A good and appropriate measure is important not only for data but also for statistical methods used for hypothesis testing. For continuous data, testing of normality is very important because based on the normality status, measures of central tendency, dispersion, and selection of parametric/nonparametric test are decided. Although there are various methods for normality testing but for small sample size (n <50), Shapiro–Wilk test should be used as it has more power to detect the nonnormality and this is the most popular and widely used method. When our sample size (n) is at least 50, any other methods (Kolmogorov–Smirnov test, skewness, kurtosis, z value of the skewness and kurtosis, histogram, box plot, P–P Plot, Q–Q Plot, and SD with respect to mean) can be used to test of the normality of continuous data.

Acknowledgment

The authors would like to express their deep and sincere gratitude to Dr. Prabhat Tiwari, Professor, Department of Anaesthesiology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, for his critical comments and useful suggestions that was very much useful to improve the quality of this manuscript.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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Correspondence Address:
Anshul Gupta
Department of Haematology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow - 226 014, Uttar Pradesh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/aca.ACA_157_18

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17 Eco-friendly design of Warm mix asphalt (WMA) with recycled concrete aggregate (RCA): A case study from a developing country
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19 Understanding thermal comfort in vernacular dwellings in Alentejo, Portugal: A mixed-methods adaptive comfort approach
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20 First report of perfluoroalkyl acids (PFAAs) in the Indus Drainage System: Occurrence, source and environmental risk
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21 Ultra-fine transformation of data for normality
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22 Zeolite increases grain yield and potassium balance in paddy fields
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23 Cumulative glucocorticoid exposure in patients receiving epidural steroid injections: a single-centre retrospective evaluation on 581 procedures against existing clinical recommendations
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24 Regulation of NLRP3 inflammasome by zinc supplementation in Behçet's disease patients: A double-blind, randomized placebo-controlled clinical trial
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25 Exploring the links between variations in snow cover area and climatic variables in a Himalayan catchment using earth observations and CMIP6 climate change scenarios
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26 A Cartoon Version of Braden Scale to Assess the Risk of Pressure Injury: Content Validity and Interrater Reliability Study
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27 Feasibility Assessment for E-Commerce: A Data Collection from Developing Country (Ethiopia)
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28 Short inertial sensor-based gait tests reflect perceived state fatigue in multiple sclerosis
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29 Cognitive reserve and coping strategies predict the level of perceived stress during COVID-19 pandemic: A cross-sectional study
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30 Assessing the digital maturity of micro and small enterprises: a focus on an emerging market
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31 Physical, chemical, and microbial feedbacks controlling brine geochemistry and lake morphology in polyextreme salar environments
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32 Myocarditis following mRNA Covid-19 vaccination: A pooled analysis
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33 Aboriginal children and family connections to primary health care whilst homeless and in high housing mobility: observations from a Nurse Practitioner-led service
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34 Development of the Assessment of Student Knowledge of Green Chemistry Principles (ASK-GCP)
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35 Impact of tourist arrivals on environmental quality: a way towards environmental sustainability targets
Tomiwa Sunday Adebayo, Seyi Saint Akadiri, Obioma Chinenyenwa Asuzu, Nanfa Hamisu Pennap, Yetunde Sadiq-Bamgbopa
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36 The Effectiveness Of Socialization Toward Students Understanding Of Tectonic Activities Disaster
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37 Offline vs online problem-based learning: a case study of student engagement and learning outcomes
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38 The evolution of privacy in contemporary houses in Iran using space syntax techniques: a case study of Kerman
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39 Segmentation and Recognition Model for Complex Action Sequences
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40 An Investigation of Edge Bead Removal Width Variability, Effects and Process Control in Photolithographic Manufacturing
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41 The Use of Concrete Examples Enhances the Learning of Abstract Concepts; A Replication Study
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42 Testing the role of economic complexity on the ecological footprint in China: a nonparametric causality-in-quantiles approach
Seyi Saint Akadiri, Tomiwa Sunday Adebayo, Obioma Chinenyenwa Asuzu, Ijeoma Christina Onuogu, Izuchukwu Oji-Okoro
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43 Describing Death Acceptance Among Thai Buddhists With Cancer
Kanoklekha Suwannapong, Sureeporn Thanasilp, Dawn Liam Doutrich, Lanchasak Akkayagorn, Nguyen Hoang Long, Janya Chimluang, Noppamat Pudtong, Ratchaneekorn Upasen
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44 Cold Water Immersion Directly and Mediated by Alleviated Pain to Promote Quality of Life in Indonesian with Gout Arthritis: A Community-based Randomized Controlled Trial
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45 Examining the Benefits of Digitally Selectable Meals Called “À La Carte Digital-Select” in Cancer Chemotherapy Patients
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46 Association between perfectionism and life satisfaction among a sample of the Lebanese population: The indirect role of social phobia and validation of the Arabic version of the Social Phobia Inventory
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47 Presence of a psychiatric patient at home and work fatigue in family caregivers: The moderating effect of spirituality
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48 Knowledge, attitude and practice of Lebanese parents towards childhood overweight/obesity: the role of parent-physician communication
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49 Factors of body dissatisfaction among lebanese adolescents: the indirect effect of self-esteem between mental health and body dissatisfaction
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50 Eating disorders and their relationship with menopausal phases among a sample of middle-aged Lebanese women
Joe Khalil, Sarah Boutros, Nelly Kheir, Maha Kassem, Pascale Salameh, Hala Sacre, Marwan Akel, Sahar Obeid, Souheil Hallit
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51 Analysis of different domains of physical activity with health-related quality of life in adults: 2-year cohort
Catarina Covolo Scarabottolo, William Rodrigues Tebar, Luis Alberto Gobbo, David Ohara, Aline Duarte Ferreira, Daniel da Silva Canhin, Diego Giulliano Destro Christofaro
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52 Couple’s Satisfaction among Lebanese adults: validation of the Toronto Alexithymia Scale and Couple Satisfaction Index-4 scales, association with attachment styles and mediating role of alexithymia
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53 Feeling the burn in the era of COVID-19: cross-cultural adaptation and validation of the Arabic version of the Copenhagen Burnout Inventory among community pharmacists
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54 The impact of clinical pharmacist-led health education on the disease course of non-alcoholic fatty liver disease patients: an interventional study
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55 Personality characteristics and competitive anxiety in individual and team athletes
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56 The Effect of Cooperative Problem-Solving Method on Students’ Motivation Towards Learning Algebra
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57 Dilemma in Health During Pandemic in OECD Countries: Increasing Health Expenditures for Preventing Against the Pandemic Will Cause a Crowding-out in Increasing the Employment in Nursing Service or not?
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58 The effect of the researchers, research and development expenditure as innovation inputs on patent grants and high-tech exports as innovation outputs in OECD and emerging countries especially in BRIICS
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59 Enhancing Meaning in Life and Psychological Well-Being Among a European Cohort of Young Adults via a Gratitude Intervention
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60 Dysfunctional Attitudes Mediate the Relationship Between Childhood Emotional Neglect and Anhedonia in Young Adult Major Depression Patients
Peilin Wang, Nan Zhang, Simeng Ma, Lijun Kang, Wei Wang, Xiaofen Zong, Hanping Bai, Ruiting Li, Zhongchun Liu
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61 The Symmetric and Asymmetric Effect of Defense Expenditures, Financial Liberalization, Health Expenditures on Sustainable Development
Li Meiling, Nigar Taspinar, Farzan Yahya, Muhammad Hussain, Muhammad Waqas
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62 GELECEGIN SAGLIK ÇALISANLARINDA SAGLIK OKURYAZARLIK DÜZEYININ SAGLIK ALGISI ÜZERINDEKI ETKISI
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63 Effect of Rapid Weight Loss on Hydration Status and Performance in Elite Judo Athletes
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64 Autologous Blood Doping Induced Changes in Red Blood Cell Rheologic Parameters, RBC Age Distribution, and Performance
Marijke Grau, Emily Zollmann, Janina Bros, Benedikt Seeger, Thomas Dietz, Javier Antonio Noriega Ureña, Andreas Grolle, Jonas Zacher, Hannah L. Notbohm, Garnet Suck, Wilhelm Bloch, Moritz Schumann
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65 Effect of Architectural Building Design Parameters on Thermal Comfort and Energy Consumption in Higher Education Buildings
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66 Extracellular Vesicles Derived from Bone Marrow in an Early Stage of Ionizing Radiation Damage Are Able to Induce Bystander Responses in the Bone Marrow
Dávid Kis, Ilona Barbara Csordás, Eszter Persa, Bálint Jezsó, Rita Hargitai, Tünde Szatmári, Nikolett Sándor, Eniko Kis, Katalin Balázs, Géza Sáfrány, Katalin Lumniczky
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67 Price Index Modeling and Risk Prediction of Sharia Stocks in Indonesia
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68 The Cardiorespiratory Demands of Treadmill Walking with and without the Use of Ekso GT™ within Able-Bodied Participants: A Feasibility Study
Damien Duddy, Rónán Doherty, James Connolly, Johnny Loughrey, Joan Condell, David Hassan, Maria Faulkner
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69 Feasibility and Acceptability of a Dietary Intervention to Reduce Salt Intake and Increase High-Nitrate Vegetable Consumption in Malaysian Middle-Aged and Older Adults with Elevated Blood Pressure: Findings from the DePEC-Nutrition Trial
Siew Siew Lee, Andrea McGrattan, Yee Chang Soh, Mawada Alawad, Tin Tin Su, Uma Devi Palanisamy, Azizah Mat Hussin, Zaid bin Kassim, Ahmad Nizal bin Mohd Ghazali, Blossom Christa Maree Stephan, Pascale Allotey, Daniel D. Reidpath, Louise Robinson, Devi Mohan, Mario Siervo
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70 A Quality Control Methodology for Heterogeneous Vehicular Data Streams
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71 Statistical Analysis and Kinematic Assessment of Upper Limb Reaching Task in Parkinson’s Disease
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72 Fundamentos Para La Elaboración De Artículos Científicos En Trauma Y Cuidado Agudo De Emergencias (Parte 5-A): Bases Y Fundamentaciones De Metodología Estadística
Angelica Clavijo, Diana M Sánchez Parra, Juan P Ávila, Diana Urrego, Andrés M. Rubiano
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73 Methods for testing statistical differences between groups in medical research: statistical standard and guideline of life cycle committee
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74 Long short-term memory prediction for COVID19 time series
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75 Evaluating Starting a Business Indicators Innovation in the World
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76 Protection against Brain histopathological damage in experimental Cerebral malaria models after exposure to hyperbaric oxigent
Prawesty Diah Utami, Usman Hadi, Yoes Prijatna Dachlan, Guritno Suryokusumo, R. Loeki Enggar Fitri, Varidianto Yudo
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77 Can intelligent agents improve data quality in online questiosnnaires? A pilot study
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78 Cover Crop Residue Effects on Soil and Corn Performance in Ex-Nickel Mining Soils
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79 Cost and Treatment Characteristics of Sport-Related Knee Injuries Managed by Athletic Trainers: A Report From the Athletic Training Practice-Based Research Network
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80 In-depth investigation of turn-around time of full blood count tests requested from a clinical haematology outpatient department in Cape Town, South Africa
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81 Impact of Scientific Calculators in Mathematics among Low- Achieving Students in a Secondary School in Kajang, Selangor
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82 Association between Self-Reported and Accelerometer-Based Estimates of Physical Activity in Portuguese Older Adults
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83 Prediction of Solid Waste Generation Rates in Urban Region of Laos Using Socio-Demographic and Economic Parameters with a Multi Linear Regression Approach
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84 Adult Education: A Sustainable Model for the Reduction of Psychosocial and Educational Risks Caused by COVID-19
Manuel-Jesús Perea-Rodríguez, Juan-Agustín Morón-Marchena, María-Carmen Muñoz-Díaz, David Cobos-Sanchiz
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85 Shadow of Your Former Self: Exploring Project Leaders’ Post-Failure Behaviors (Resilience, Self-Esteem and Self-Efficacy) in High-Tech Startup Projects
Umer Zaman, Laura Florez-Perez, Pablo Farías, Saba Abbasi, Muddasar Ghani Khwaja, Tri Indra Wijaksana
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86 Self-Assessment Adaptive Capacity Indicators of Health Risks from Air Pollution
Nawhath Thanvisitthpon, Jarasphol Rintra, Phakkharawat Sittiprapaporn, Akkarach Bumrungpert, Phaisit Trakulkongsmut
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87 High Olfactory Receptor-Rich 11q11 Copy Number in Girls and African American Children
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88 Processing Cycle Efficiency to Monitor the Performance of an Intelligent Tube Preparation System for Phlebotomy Services
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89 Short-Term Effectiveness of the Youth Gambling Prevention Program “Who Really Wins?”—Results from the First National Implementation
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90 How Does Food Addiction Relate to Obesity? Patterns of Psychological Distress, Eating Behaviors and Physical Activity in a Sample of Lebanese Adults: The MATEO Study
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91 The Response of Social Crime Prevention Police to Cyberbullying Perpetrated by Youth in Rural Areas of South Africa
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92 Increase of Agribusiness in the Brazilian Amazon: Development or Inequality?
Rosana Cavalcante de Oliveira, Rogério Diogne de Souza e Silva
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93 Effects of environmental factors on health risks by using machine learning
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94 Evaluación de marcadores antropométricos de riesgo cardiometabólico en adultos de una comunidad de la región Cañada de Oaxaca, México.
Jacob Jonatan Cruz Sánchez, Remedios Jiménez Pineda, Nelly Victoria Gutiérrez Moguel, Zaydi Anaí Acosta Chí, Citlalli Regalado Santiago, Patricia González Cano
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95 Exploring the Gaze Behavior of Tennis Players with Different Skill Levels When Receiving Serves through Eye Movement Information
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96 Free-Living Physical Activity Measured With a Wearable Device Is Associated With Larger Hippocampus Volume and Greater Functional Connectivity in Healthy Older Adults: An Observational, Cross-Sectional Study in Northern Portugal
Célia Domingos, Maria Picó-Pérez, Ricardo Magalhães, Mariana Moreira, Nuno Sousa, José Miguel Pêgo, Nadine Correia Santos
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97 Age-Related Exosomal and Endogenous Expression Patterns of miR-1, miR-133a, miR-133b, and miR-206 in Skeletal Muscles
Chrystalla Mytidou, Andrie Koutsoulidou, Margarita Zachariou, Marianna Prokopi, Konstantinos Kapnisis, George M. Spyrou, Andreas Anayiotos, Leonidas A. Phylactou
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98 Feasibility of Reducing and Breaking Up University Students' Sedentary Behaviour: Pilot Trial and Process Evaluation
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99 Bedtime Smart Phone Usage and Its Effects on Work-Related Behaviour at Workplace
Abida Ellahi, Yasir Javed, Samina Begum, Rabia Mushtaq, Mobashar Rehman, Hafiz Mudassir Rehman
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100 Reducing Loneliness Among Aging Adults: The Roles of Personal Voice Assistants and Anthropomorphic Interactions
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101 Effects of Difficult Coworkers on Employees’ Responses in Macao’s Public Organizations—The Mediating Role of Perceived Stress
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102 Determination of Polycyclic Aromatic Hydrocarbons in Batman River by Liquid-liquid and Solid-phase Extractions and the Statistical Comparison of the Two Extraction Techniques
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103 Psychological Effects of Heart Rate and Physical Vibration on the Operation of Construction Machines: Experimental Study
Nobuki Hashiguchi, Jianfei Cao, Yeongjoo Lim, Shinichi Kuroishi, Yasuhiro Miyazaki, Shigeo Kitahara, Shintaro Sengoku, Katsushi Matsubayashi, Kota Kodama
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104 Age- and Gender-Related Changes in Physical Function in Community-Dwelling Brazilian Adults Aged 50 to 102 Years
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105 Clock hours of food and nutrition education in curricula of undergraduate nutrition programs: a two-country comparison
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106 Greek population’s perceptions of nonpharmacological interventions towards the first wave of COVID-19 pandemic mitigation: A regressionbased association analysis
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107 REVEALING THE EFFECTS OF TEACHERS STIMULATING TECHNOLOGICAL INCLUSION ON UNIVERSITY STUDENTS EDUCATIONAL GAINS: A COMPARATIVE STUDY
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108 Lightpath QoT computation in optical networks assisted by transfer learning
Ihtesham Khan, Muhammad Bilal, M. Umar Masood, Andrea D’Amico, Vittorio Curri
Journal of Optical Communications and Networking. 2021; 13(4): B72
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109 DNAku Consumers Profile: One of The First Direct to Customer Genetics Testing in Indonesia
Deby Erina Parung, Kians Azizatikarna, Dian Amirulloh, Erlin Listiyaningsih, Bharuno Mahesworo, Arif Budiarto, Simon, Bens Pardamean
IOP Conference Series: Earth and Environmental Science. 2021; 794(1): 012117
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110 Efficient neural spike sorting using data subdivision and unification
Masood Ul Hassan, Rakesh Veerabhadrappa, Asim Bhatti, Alexandros Iosifidis
PLOS ONE. 2021; 16(2): e0245589
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111 Does curve pattern impact on the effects of physiotherapeutic scoliosis specific exercises on Cobb angles of participants with adolescent idiopathic scoliosis: A prospective clinical trial with two years follow-up
Yunli Fan, Michael K. T. To, Eric H. K. Yeung, Jianbin Wu, Rong He, Zhuoman Xu, Ruiwen Zhang, Guangshuo Li, Kenneth M. C. Cheung, Jason P. Y. Cheung, Alison Rushton
PLOS ONE. 2021; 16(1): e0245829
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112 Comparison of the disinfecting effect of sodium hypochlorite aqueous solution and surfactant on hospital kitchen hygiene using adenosine triphosphate swab testing
Takashi Aoyama, Tomoko Kudo, Hans-Uwe Dahms
PLOS ONE. 2021; 16(4): e0249796
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113 Orthorexia nervosa and disordered eating attitudes among Lebanese adults: Assessing psychometric proprieties of the ORTO-R in a population-based sample
Souheil Hallit, Anna Brytek-Matera, Sahar Obeid, Claudio Imperatori
PLOS ONE. 2021; 16(8): e0254948
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114 The role of access to finance from different finance providers in production risks of horticulture in Indonesia
Eliana Wulandari, Miranda P. M. Meuwissen, Maman H. Karmana, Alfons G. J. M. Oude Lansink, László Vasa
PLOS ONE. 2021; 16(9): e0257812
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115 Exploring safety culture in the Finnish ambulance service with Emergency Medical Services Safety Attitudes Questionnaire
Anu Venesoja, Veronica Lindström, Pasi Aronen, Maaret Castrén, Susanna Tella
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine. 2021; 29(1)
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116 Evaluation of a mosquito home system for controlling Aedes aegypti
Ahmad Mohiddin Mohd Ngesom, Anis Ahmad Razi, Nur Syahirah Azizan, Nazni Wasi Ahmad, Asmalia Md Lasim, Yanfeng Liang, David Greenhalgh, Jasmine Chia Siew Min, Mazrura Sahani, Rozita Hod, Hidayatulfathi Othman
Parasites & Vectors. 2021; 14(1)
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117 Validation of the Arabic version of the Dusseldorf Orthorexia Scale (DOS) among Lebanese adolescents
Radoslaw Rogoza, Souheil Hallit, Michel Soufia, Friederike Barthels, Sahar Obeid
Journal of Eating Disorders. 2021; 9(1)
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118 Phubbing and temperaments among young Lebanese adults: the mediating effect of self-esteem and emotional intelligence
Zeinab Bitar, Souheil Hallit, Wael Khansa, Sahar Obeid
BMC Psychology. 2021; 9(1)
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119 Problematic smartphone use and affective temperaments among Lebanese young adults: scale validation and mediating role of self-esteem
Joanne Zeidan, Souheil Hallit, Marwan Akel, Ismail Louragli, Sahar Obeid
BMC Psychology. 2021; 9(1)
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120 Cyberchondria severity and quality of life among Lebanese adults: the mediating role of fear of COVID-19, depression, anxiety, stress and obsessive–compulsive behavior—a structural equation model approach
Clara Rahme, Marwan Akel, Sahar Obeid, Souheil Hallit
BMC Psychology. 2021; 9(1)
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121 Premenstrual dysphoric disorder and childhood maltreatment, adulthood stressful life events and depression among Lebanese university students: a structural equation modeling approach
Yorgo Younes, Souheil Hallit, Sahar Obeid
BMC Psychiatry. 2021; 21(1)
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122 Association between impulsivity and orthorexia nervosa / healthy orthorexia: any mediating effect of depression, anxiety, and stress?
Emmanuelle Awad, Pascale Salameh, Hala Sacre, Diana Malaeb, Souheil Hallit, Sahar Obeid
BMC Psychiatry. 2021; 21(1)
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123 Association between cumulative cigarette and Waterpipe smoking and symptoms of dependence in Lebanese adults
Diana Malaeb, Marwan Akel, Hala Sacre, Chadia Haddad, Sahar Obeid, Souheil Hallit, Pascale Salameh
BMC Public Health. 2021; 21(1)
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124 Clinical and genetic factors associated with anxiety and depression in breast cancer patients: a cross-sectional study
Aline HAJJ, Roula HACHEM, Rita KHOURY, Souheil HALLIT, Bashar ElJEBBAWI, Fady NASR, Fadi EL KARAK, Georges CHAHINE, Joseph KATTAN, Lydia RABBAA KHABBAZ
BMC Cancer. 2021; 21(1)
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125 Restrained eating in Lebanese adolescents: scale validation and correlates
Tracy Boulos Nakhoul, Anthony Mina, Michel Soufia, Sahar Obeid, Souheil Hallit
BMC Pediatrics. 2021; 21(1)
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126 Sleep disorders in a sample of Lebanese children: the role of parental mental health and child nutrition and activity
Elsa Sfeir, Chadia Haddad, Marwan Akel, Souheil Hallit, Sahar Obeid
BMC Pediatrics. 2021; 21(1)
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127 Caregiver burden of families of children with corrosive esophageal injuries
Nazife G Özer Özlü, Fatma Vural
Journal of Child Health Care. 2021; : 1367493521
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128 Exploring the Elements Influencing the Behavioral Adoption of E-Commerce by Chinese Small and Medium Enterprises (SMEs)
Isaac Kofi Mensah, Rui Wang, Lin Gui, Jinxuan Wang
Information Development. 2021; : 0266666921
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129 Height Prediction Using the Knee Height Measurement Among Indonesian Children
Fernando Rumapea, Eddy Fadlyana, Meita Dhamayanti, Rodman Tarigan, Rahmayani Rahmayani, Kusnandi Rusmil
Food and Nutrition Bulletin. 2021; 42(2): 247
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130 Peritoneal dialysis in very low and extremely low birthweight infants: A pooled analysis
Ioannis Bellos, Vasilios Karageorgiou
Peritoneal Dialysis International: Journal of the International Society for Peritoneal Dialysis. 2021; : 0896860821
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131 Radiographic assessment of carpal conformation in the horse: Technique development and validation of the consistency of measurements
Timothy A. O. Olusa, Sa'ad M. Y. Ismail, Christina M. Murray, Helen M. S. Davies
Anatomia, Histologia, Embryologia. 2021; 50(2): 284
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132 Development of a novel risk score for the prediction of critical illness amongst COVID-19 patients
Ioannis Bellos, Panagiota Lourida, Aikaterini Argyraki, Eleni Korompoki, Christina Zirou, Ioanna Kokkinaki, Angelos Pefanis
International Journal of Clinical Practice. 2021; 75(4)
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133 Nomophobia and temperaments in Lebanon: Results of a national study
Clara Rahme, Rabih Hallit, Marwan Akel, Clarissa Chalhoub, Maria Hachem, Souheil Hallit, Sahar Obeid
Perspectives in Psychiatric Care. 2021;
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134 AC and Lightning Impulse Breakdown Voltages of Natural Ester Based Fullerene Nanofluids
A. Beroual, H. Duzkaya
IEEE Transactions on Dielectrics and Electrical Insulation. 2021; 28(6): 1996
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135 Impact of Educational Coaching Programs and Mentoring Services on Users’ Perception and Preferences: A Qualitative and Quantitative Approach
Kingsley Okoye, Samira Hosseini, Arturo Arrona-Palacios, Jose Escamilla
IEEE Access. 2021; 9: 48105
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136 Entrepreneurial alertness and social entrepreneurial venture creation: the mediating role of personal initiative
Isa Nsereko, Juma Wasswa Balunywa, Lawrence Musiitwa Kyazze, Hamidah Babirye Nsereko, Jamidah Nakato
Journal of Enterprising Communities: People and Places in the Global Economy. 2021; ahead-of-p(ahead-of-p)
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137 Conditional resource and social entrepreneurial action: the mediating role of social entrepreneurial intent
Isa Nsereko
Journal of Entrepreneurship in Emerging Economies. 2021; 13(5): 1057
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138 Treating top management team conflicts through employee voice for reducing intentions to quit: moderating role of union instrumentality
Naveed Iqbal Chaudhry, Muhammad Azam Roomi, Marium Eugien, Javed Iqbal Chaudhry
International Journal of Conflict Management. 2021; ahead-of-p(ahead-of-p)
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139 Synchronous online flip learning with formative gamification quiz: instruction during COVID-19
Zamzami Zainuddin, Ratna Farida, Cut Muftia Keumala, Rudi Kurniawan, Hadi Iskandar
Interactive Technology and Smart Education. 2021; ahead-of-p(ahead-of-p)
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140 Optimization of the rapid carbapenem inactivation method for use with AmpC hyperproducers
Madalina Maria Muntean, Andrei-Alexandru Muntean, François Guerin, Vincent Cattoir, Elodie Creton, Garance Cotellon, Saoussen Oueslati, Mircea Ioan Popa, Delphine Girlich, Bogdan I. Iorga, Rémy A. Bonnin, Thierry Naas
Journal of Antimicrobial Chemotherapy. 2021; 76(9): 2294
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141 Knowledge, Attitudes, and Practices on the Use of Household Insecticide Products: Is the Awareness in Place?
Taib Azratul-Hizayu, Chee Dhang Chen, Noor Azrizal-Wahid, Mohd Sofian-Azirun, Fong Peng Chew, Van Lun Low, Andrea Joyce
Journal of Integrated Pest Management. 2021; 12(1)
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142 Changes in young adult substance use during COVID-19 as a function of ACEs, depression, prior substance use and resilience
Katelyn F. Romm, Brooke Patterson, Natalie D. Crawford, Heather Posner, Carly D. West, DeEnna Wedding, Kimberly Horn, Carla J. Berg
Substance Abuse. 2021; : 1
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143 Letter to Editor ‘Effect of moving cupping therapy on hip and knee range of movement and knee flexion power: a preliminary investigation’
Diksha Bains, Adarsh Kumar Srivastav
Journal of Manual & Manipulative Therapy. 2021; 29(3): 196
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144 Analysing Gray Cast Iron Data using a New Shapiro-Wilks test for Normality under Indeterminacy
Muhammad Aslam
International Journal of Cast Metals Research. 2021; 34(1): 1
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145 Trends in COSI responses associated with age and degree of hearing loss
Richard Windle
International Journal of Audiology. 2021; : 1
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146 Dehydration and Rapid Weight Gain Between Weigh-in and Competition in Judo Athletes: The Differences between Women and Men
Bayram Ceylan, Sukru Serdar Balci
Research in Sports Medicine. 2021; : 1
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147 Cogstate Brief Battery: Cognition and the feigning of cognitive impairment in chronic pain
Tamar Lupu, Yoram Braw, Yaron Sacher, Motti Ratmansky
Applied Neuropsychology: Adult. 2021; : 1
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148 Understanding mediators and moderators of the effect of customer satisfaction on loyalty
Lovemore Chikazhe, Charles Makanyeza, Blessing Chigunhah, Morteza Akbari
Cogent Business & Management. 2021; 8(1): 1922127
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149 The effects of feeding and starvation on antioxidant defence, fatty acid composition and lipid peroxidation in reared Oncorhynchus mykiss fry
Hatayi Zengin
Scientific Reports. 2021; 11(1)
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150 Evaluating the interchangeability of infrared and digital devices with the traditional mercury thermometer in hospitalized pediatric patients: an observational study
Angelo Dante, Elona Gaxhja, Vittorio Masotta, Carmen La Cerra, Valeria Caponnetto, Cristina Petrucci, Loreto Lancia
Scientific Reports. 2021; 11(1)
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151 Financial stability in response to climate change in a northern temperate economy
Kayla Stan, Graham A. Watt, Arturo Sanchez-Azofeifa
Nature Communications. 2021; 12(1)
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152 Misinterpretations of Null Hypothesis Significance Testing Results Near the P-Value Threshold: An Estimation of the Prevalence of Such a Statistical Error in the Neurosurgical Literature
Najib E. El Tecle, Jorge F. Urquiaga, Samuel T. Griffin, Georgios Alexopoulos, Tarek Y. El Ahamadieh, Salah G. Aoun, Tobias A. Mattei
World Neurosurgery. 2021;
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153 Predicting the physical activity of new parents who participated in a physical activity intervention
Ryan E. Rhodes, Mark R. Beauchamp, Alison Quinlan, Danielle Symons Downs, Darren E.R. Warburton, Chris M. Blanchard
Social Science & Medicine. 2021; 284: 114221
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154 Chest CT severity score and radiological patterns as predictors of disease severity, ICU admission, and viral positivity in COVID-19 patients
Ioannis Bellos, Kyriaki Tavernaraki, Konstantinos Stefanidis, Olympia Michalopoulou, Giota Lourida, Eleni Korompoki, Ioanna Thanou, Loukas Thanos, Angelos Pefanis, Aikaterini Argyraki
Respiratory Investigation. 2021; 59(4): 436
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155 Letter to the editor “Effect of a brief progressive resistance training program in hospital porters on pain, work ability and physical function”
Prachi Maheshwari, Shilpasree Saha, Hina Vaish
Musculoskeletal Science and Practice. 2021; 51: 102263
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156 Características y tendencias de la mortalidad por cáncer de ojo y anexos en Chile
Blas Vargas
Revista Médica Clínica Las Condes. 2021; 32(4): 511
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157 Item analysis of multiple choice questions: A quality assurance test for an assessment tool
Dharmendra Kumar, Raksha Jaipurkar, Atul Shekhar, Gaurav Sikri, V. Srinivas
Medical Journal Armed Forces India. 2021; 77: S85
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158 Effect of customer involvement on co-creation of services: A moderated mediation model
Millissa F.Y. Cheung, W.M. To
Journal of Retailing and Consumer Services. 2021; 63: 102660
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159 Kidney biopsy findings in vancomycin-induced acute kidney injury: a pooled analysis
Ioannis Bellos, Vasilios Pergialiotis, Despina N. Perrea
International Urology and Nephrology. 2021;
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160 Evidence of declining trees resilience under long term heavy metal stress combined with climate change heating
Constantin Nechita, Andreea Maria Iordache, Karel Lemr, Tom Levanic, Tomas Pluhacek
Journal of Cleaner Production. 2021; 317: 128428
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161 Testing the reliability and effectiveness of a new tool for assessing urban blue spaces: The BlueHealth environmental assessment tool (BEAT)
Himansu Sekhar Mishra, Simon Bell, James Grellier, Mathew P. White
Health & Place. 2021; 68: 102526
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162 Moderating effects of personal innovativeness and driving experience on factors influencing adoption of BEVs in Malaysia: An integrated SEM–BSEM approach
Hamed Khazaei, Mohammad Ali Tareq
Heliyon. 2021; 7(9): e08072
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163 The motivations of visiting upscale restaurants during the COVID-19 pandemic: The role of risk perception and trust in government
Bekir Bora Dedeoglu, Erhan Bogan
International Journal of Hospitality Management. 2021; 95: 102905
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164 Development and validation of a predictive model of exclusive breastfeeding at hospital discharge: Retrospective cohort study
Ana Ballesta-Castillejos, Juan Gómez-Salgado, Julián Rodríguez-Almagro, Antonio Hernández-Martínez
International Journal of Nursing Studies. 2021; 117: 103898
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165 Comment on gallbladder polyps: Correlation of size and clinicopathologic characteristics based on updated definitions
Sami Akbulut, Tevfik Tolga Sahin
International Journal of Surgery Case Reports. 2021; 83: 105947
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166 Drivers of food waste reduction behaviour in the household context
Saman Attiq, Muhammad Danish Habib, Puneet Kaur, Muhammad Junaid Shahid Hasni, Amandeep Dhir
Food Quality and Preference. 2021; 94: 104300
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167 Microbial dynamics in rearing trials of Hermetia illucens larvae fed coffee silverskin and microalgae
Andrea Osimani, Ilario Ferrocino, Maria Rita Corvaglia, Andrea Roncolini, Vesna Milanovic, Cristiana Garofalo, Lucia Aquilanti, Paola Riolo, Sara Ruschioni, Elham Jamshidi, Nunzio Isidoro, Matteo Zarantoniello, Luca Cocolin, Ike Olivotto, Francesca Clementi
Food Research International. 2021; 140: 110028
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168 Development of shiny dashboard application for “genome-wide association study on analysis of SNPs injected in Homo sapiens genome (snips-HsG)”
Balamurugan Sivaprakasam, Prasanna Sadagopan
Gene Reports. 2021; 23: 101033
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169 Promoting critical thinking in an online, project-based course
Catalina Cortázar, Miguel Nussbaum, Jorge Harcha, Danilo Alvares, Felipe López, Julián Goñi, Verónica Cabezas
Computers in Human Behavior. 2021; 119: 106705
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170 Energy consumption prediction by using machine learning for smart building: Case study in Malaysia
Mel Keytingan M. Shapi, Nor Azuana Ramli, Lilik J. Awalin
Developments in the Built Environment. 2021; 5: 100037
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171 Maternal and perinatal outcomes in pregnant women infected by SARS-CoV-2: A meta-analysis
Ioannis Bellos, Aakash Pandita, Raffaella Panza
European Journal of Obstetrics & Gynecology and Reproductive Biology. 2021; 256: 194
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172 Three-dimensional geotechnical-layer mapping in Seoul using borehole database and deep neural network-based model
Han-Saem Kim, Yoonsoo Ji
Engineering Geology. 2021; : 106489
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173 Work-related stress, psychophysiological strain, and recovery among on-site construction personnel
Janet M. Nwaogu, Albert P.C. Chan
Automation in Construction. 2021; 125: 103629
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174 Hydrological alteration induced changes on macrophyte community composition in sub-tropical floodplain wetlands of Nepal
Tika Regmi, Deep Narayan Shah, Tanya M. Doody, Susan M. Cuddy, Ram Devi Tachamo Shah
Aquatic Botany. 2021; 173: 103413
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175 Statistical Methods in Experimental Pathology
Douglas A. Mata, Danny A. Milner
The American Journal of Pathology. 2021; 191(5): 784
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176 Political marketing and social media influence on young voters in Ghana
Justice Boateng Dankwah, Kobby Mensah
SN Social Sciences. 2021; 1(6)
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177 Deciphering the non-linear impact of Al on chemical durability of silicate glass
Kamalesh Damodaran, Jean-Marc Delaye, Andrey G. Kalinichev, Stephane Gin
Acta Materialia. 2021; : 117478
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178 Basics of Statistical Comparisons
Amir Maroof Khan, Ashish Goel
Indian Pediatrics. 2021; 58(10): 987
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179 Drunkorexia behaviors and motives, eating attitudes and mental health in Lebanese alcohol drinkers: a path analysis model
Diana Malaeb, Dora Bianchi, Sara Pompili, Jana Berro, Fiorenzo Laghi, Vanessa Azzi, Marwan Akel, Sahar Obeid, Souheil Hallit
Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity. 2021;
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180 Jaws of Platynereis dumerilii: Miniature Biogenic Structures with Hardness Properties Similar to Those of Crystalline Metals
Luis Zelaya-Lainez, Giuseppe Balduzzi, Olaf Lahayne, Kyojiro N. Ikeda, Florian Raible, Christopher Herzig, Winfried Nischkauer, Andreas Limbeck, Christian Hellmich
JOM. 2021; 73(8): 2390
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181 Industrial growth and CO2 emissions in Vietnam: the key role of financial development and fossil fuel consumption
Kishwar Ali, Satar Bakhsh, Saif Ullah, Atta Ullah, Sami Ullah
Environmental Science and Pollution Research. 2021; 28(6): 7515
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182 Study of cobalt doping control via various routes in thoroughbred horses
Young Beom Kwak, Jundong Yu, Eo Jin Im, Bok Son Jeong, Hye Hyun Yoo
Drug Testing and Analysis. 2021;
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183 Obesity and long-term outcomes after incident stroke: a prospective population-based cohort study
Ralph K. Akyea, Wolfram Doehner, Barbara Iyen, Stephen F. Weng, Nadeem Qureshi, George Ntaios
Journal of Cachexia, Sarcopenia and Muscle. 2021;
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184 Statistics decrypted—a comprehensive review and smartphone-assisted five-step approach for good statistical practice
Laura C. Guglielmetti, Fabio Faber-Castell, Lukas Fink, Raphael N. Vuille-dit-Bille
Langenbeck's Archives of Surgery. 2021;
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185 New evidence from hyperspectral imaging analysis on the effect of photobiomodulation therapy on normal skin oxygenation
Mihaela Antonina Calin, Adrian Macovei, Roxana Savastru, Adriana Sarah Nica, Sorin Viorel Parasca
Lasers in Medical Science. 2021;
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186 Measurement Properties of the Work Ability Score in Sick-Listed Workers with Chronic Musculoskeletal Pain
M. Stienstra, M. J. A. Edelaar, B. Fritz, M. F. Reneman
Journal of Occupational Rehabilitation. 2021;
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187 Pregnancy status and thyroid function in semi-intensive-kept Marecha she-camels (Camelus dromedarius): managerial implications
Asim Faraz, Carlos Iglesias Pastrana, Annamaria Passantino, Ayman Balla Mustafa, Abdul Waheed, Nasir Ali Tauqir, Muhammad Shahid Nabeel
Tropical Animal Health and Production. 2020; 52(6): 3387
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188 Spatial and temporal distributions of terrestrial and marine organic matter in the surface sediments of the Yangtze River estuary
Shanshan Zhang, Cui Liang, Weiwei Xian
Continental Shelf Research. 2020; 203: 104158
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189 Unleashing ß-catenin with a new anti-Alzheimer drug for bone tissue regeneration
Marianne Comeau-Gauthier, Magdalena Tarchala, Jose Luis Ramirez-Garcia Luna, Edward Harvey, Geraldine Merle
Injury. 2020; 51(11): 2449
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190 Multiparametric qMTI Assessment and Monitoring of Normal Appearing White Matter and Classified T1 Hypointense Lesions in Relapsing-Remitting Multiple Sclerosis
M. Fooladi, N. Riyahi Alam, H. Sharini, K. Firouznia, M. Shakiba, M.H. Harirchian
IRBM. 2020; 41(3): 151
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191 Corticospinal activity during a single-leg stance in people with chronic ankle instability
Masafumi Terada, Kyle B. Kosik, Ryan S. McCann, Colin Drinkard, Phillip A. Gribble
Journal of Sport and Health Science. 2020;
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192 Exploring the vulnerability of frontline nurses to COVID-19 and its impact on perceived stress
Eddieson Pasay-an
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193 Mental Health Outcomes of the COVID-19 Pandemic and a Collapsing Economy: Perspectives from a Developing Country
Pascale SALAMEH, Aline HAJJ, Danielle A BADRO, Carla ABOU?SELWAN, Randa AOUN, Hala SACRE
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194 Letter to the Editor regarding: Does pectoralis minor stretching provide additional benefit over an exercise program in participants with subacromial pain syndrome? A randomized controlled trial
Saumya Kothiyal, Manu Goyal
Musculoskeletal Science and Practice. 2020; 46: 102126
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195 Letter to editor “Effectiveness of additional deep-water running for disability, lumbar pain intensity, and functional capacity in patients with chronic low back pain: A randomised controlled trial with 3-month follow-up"
Gurjant Singh, Saumya Kothiyal
Musculoskeletal Science and Practice. 2020; 50: 102227
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196 Ecuadorian mothers of preschool children with and without intellectual disabilities: Individual and family dimensions
Carmita E. Villavicencio, Silvia López-Larrosa
Research in Developmental Disabilities. 2020; 105: 103735
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197 Prolonged bedrest reduces plasma high-density lipoprotein levels linked to markedly suppressed cholesterol efflux capacity
Athina Trakaki, Hubert Scharnagl, Markus Trieb, Michael Holzer, Helmut Hinghofer-Szalkay, Nandu Goswami, Gunther Marsche
Scientific Reports. 2020; 10(1)
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198 Psychological outcomes of MRSA isolation in spinal cord injury rehabilitation
Jenna L. Gillett, Jane Duff, Rebecca Eaton, Katherine Finlay
Spinal Cord Series and Cases. 2020; 6(1)
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199 Differential microRNAs expression in acute graft-versus-host disease as potential diagnostic biomarkers
Jamshid Motaei, Marjan Yaghmaie, Hossein Pashaiefar, Seyed Asadollah Mousavi, Ardeshir Ghavamzadeh, Mohammad Ahmadvand, Mohammad Amin Kerachian
Bone Marrow Transplantation. 2020; 55(12): 2339
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200 Impact of Mobile Augmented Reality System on Cognitive Behavior and Performance during Rebar Inspection Tasks
Ali Abbas, JoonOh Seo, MinKoo Kim
Journal of Computing in Civil Engineering. 2020; 34(6): 04020050
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201 The effectiveness of instructional media based on lectora inspire towards student’s achievement
N V Saputro, Masturi, Supriyadi
Journal of Physics: Conference Series. 2020; 1567(2): 022063
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202 Gender differences in the prevalence of vitamin D deficiency in a southern Latin American country: a pilot study
M. S. Vallejo, J. E. Blümel, E. Arteaga, S. Aedo, V. Tapia, A. Araos, C. Sciaraffia, C. Castelo-Branco
Climacteric. 2020; 23(4): 410
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203 Infertility and perceived stress: the role of identity concern in treatment-seeking men and women
Paul Grunberg, Skye Miner, Phyllis Zelkowitz
Human Fertility. 2020; : 1
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204 The impact of sensory activity schedule (SAS) intervention on classroom task performance in students with autism – a pilot randomised controlled trial
Caroline Jennifer Mills, Christine Chapparo, Joanne Hinitt
Advances in Autism. 2020; 6(3): 179
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205 Associations of obstetrical characteristics and dietary intakes with iron status among pregnant women in Selangor and Kuala Lumpur
Meng Lee Tan, Yit Siew Chin, Poh Ying Lim, Salma Faeza Ahmad Fuzi
British Food Journal. 2020; 122(10): 3115
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206 Impact of Workforce Diversity Management on Employees’ Outcomes: Testing the Mediating Role of a person’s Job Match
Wenjing Li, Xuhui Wang, Md Jamirul Haque, Muhammad Noman Shafique, Muhammad Zahid Nawaz
SAGE Open. 2020; 10(1): 2158244020
[Pubmed] | [DOI]
207 Previous Intestinal Resection Is Associated with Postoperative Complications in Crohn’s Disease: A Cohort Study
Yantao Duan, Yifan Liu, Yousheng Li
Gastroenterology Research and Practice. 2020; 2020: 1
[Pubmed] | [DOI]
208 Suicidal ideation among Lebanese adolescents: scale validation, prevalence and correlates
Melissa Chahine, Pascale Salameh, Chadia Haddad, Hala Sacre, Michel Soufia, Marwan Akel, Sahar Obeid, Rabih Hallit, Souheil Hallit
BMC Psychiatry. 2020; 20(1)
[Pubmed] | [DOI]
209 The impact of social distancing policy on small and medium-sized enterprises (SMEs) in Indonesia
Muhtar Lutfi, Pricylia Chintya Dewi Buntuang, Yoberth Kornelius, Erdiyansyah, Bakri Hasanuddin
Problems and Perspectives in Management. 2020; 18(3): 492
[Pubmed] | [DOI]
210 A Quality of Experience assessment of haptic and augmented reality feedback modalities in a gait analysis system
Thiago Braga Rodrigues, Ciarán Ó Catháin, Noel E. O’Connor, Niall Murray, Bijan Najafi
PLOS ONE. 2020; 15(3): e0230570
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211 An interdisciplinary intensive outpatient pain program is associated with improved patient activation and key outcomes
Barbara K Bujak, Christine E Blake, Paul F Beattie, Shana Harrington, Courtney M Monroe, David Wilkie, Mary E Earwood
Pain Management. 2020; 10(5): 307
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212 Role of Virtual Reality in Balance Training in Patients with Spinal Cord Injury: A Prospective Comparative Pre–Post Study
Shilpasree Saha
Asian Spine Journal. 2020; 14(2): 264
[Pubmed] | [DOI]
213 Response to: Role of Virtual Reality in Balance Training in Patients with Spinal Cord Injury: A Prospective Comparative Pre–Post Study
Dhritiman Chakrabarti, Anupam Gupta
Asian Spine Journal. 2020; 14(2): 266
[Pubmed] | [DOI]
214 Letter to the Editor: “Sarcopenia and Back Muscle Degeneration as Risk Factors for Back Pain: A Comparative Study”
Hina Vaish
Asian Spine Journal. 2020; 14(4): 581
[Pubmed] | [DOI]
215 Response to: “Sarcopenia and Back Muscle Degeneration as Risk Factors for Back Pain: A Comparative Study”
Whoan Jeang Kim, Kap Jung Kim, Dae Geon Song, Jong Shin Lee, Kun Young Park, Jae Won Lee, Shann Haw Chang, Won Sik Choy
Asian Spine Journal. 2020; 14(4): 583
[Pubmed] | [DOI]
216 Selection of Immature Cat Oocytes with Brilliant Cresyl Blue Stain Improves In Vitro Embryo Production during Non-Breeding Season
Anna Rita Piras, Federica Ariu, Maria-Teresa Zedda, Maria-Teresa Paramio, Luisa Bogliolo
Animals. 2020; 10(9): 1496
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217 The Effect of a Physiotherapy Intervention on Thoracolumbar Posture in Horses
Amy Shakeshaft, Gillian Tabor
Animals. 2020; 10(11): 1977
[Pubmed] | [DOI]
218 Impact of Alcohol on Occupational Health and Safety in the Construction Industry at Workplaces with Scaffoldings
Marek Sawicki, Mariusz Szóstak
Applied Sciences. 2020; 10(19): 6690
[Pubmed] | [DOI]
219 Improved Photoacoustic Imaging of Numerical Bone Model Based on Attention Block U-Net Deep Learning Network
Panpan Chen, Chengcheng Liu, Ting Feng, Yong Li, Dean Ta
Applied Sciences. 2020; 10(22): 8089
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220 SPOR BILIMLERI ALANINDA YAYINLANAN MAKALELERDE KULLANILAN ISTATISTIKSEL YÖNTEMLERIN INCELENMESI
Yetkin Utku KAMUK
Ankara Üniversitesi Beden Egitimi ve Spor Yüksekokulu SPORMETRE Beden Egitimi ve Spor Bilimleri Dergisi. 2020; 18(3): 73
[Pubmed] | [DOI]
221 ??? ???? ???? ????? ?? ???? ???????? ????????? ???????? ?????? ??? ????? ??????? ???? ?????? ?? ????- ????
Messaoud Harikeche, Mokhtar Hadid
Dirassat Journal Economic Issue. 2020; 11(2): 305
[Pubmed] | [DOI]
222 Assessment of the Natural Radioactivity of Polish and Foreign Granites Used for Road and Lapidary Constructions in Poland
Tomasz Drzymala, Aneta Lukaszek-Chmielewska, Sylwia Lewicka, Joanna Stec, Barbara Piotrowska, Krzysztof Isajenko, Pawel Lipinski
Materials. 2020; 13(12): 2824
[Pubmed] | [DOI]
223 Application of Ecological Indices using Macroinvertebrate Assemblages in Relation to Aquaculture Activities in Rawang Sub-basin, Selangor River, Malaysia
Nadeesha Dilani Hettige, Rohasliney Binti Hashim, Ahmad Bin Abas Kutty, Nor Rohaizah Binti Jamil, Zulfa Hanan Binti Ash’aari
Pertanika Journal of Science and Technology. 2020; 28(S2)
[Pubmed] | [DOI]
224 Adoption of Road Water Harvesting Practices and Their Impacts: Evidence from a Semi-Arid Region of Ethiopia
Kebede Manjur Gebru, Kifle Woldearegay, Frank van Steenbergen, Aregawi Beyene, Letty Fajardo Vera, Kidane Tesfay Gebreegziabher, Taye Alemayhu
Sustainability. 2020; 12(21): 8914
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225 The effects of “Fangcang, Huoshenshan, and Leishenshan” hospitals and environmental factors on the mortality of COVID-19
Yuwen Cai, Tianlun Huang, Xin Liu, Gaosi Xu
PeerJ. 2020; 8: e9578
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226 Clinical Severity as a Predictor of Nursing Workload in Pediatric Intensive Care Units: A Cross-Sectional Study
Alexandra-Stavroula Nieri, Eleni Spithouraki, Petros Galanis, Daphne Kaitelidou, Vasiliki Matziou, Margarita Giannakopoulou
Connect: The World of Critical Care Nursing. 2019; 13(4): 175
[Pubmed] | [DOI]
227 Comparison of the recruitment of transverse abdominis through drawing-in and bracing in different core stability training positions
Navid Moghadam, Maryam Selk Ghaffari, Pardis Noormohammadpour, Mohsen Rostam, Mohammad Zarei, Mersad Moosavi, Ramin Kordi
Journal of Exercise Rehabilitation. 2019; 15(6): 819
[Pubmed] | [DOI]



 
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