scholarly journals Implementation of Medicine Take-back Concept at Community Level in Nepal: a Feasibility Study

2020 ◽  
Author(s):  
Binaya Sapkota ◽  
Anil Giri ◽  
Bigyan Bhatta ◽  
Krishna Awasthi ◽  
Kiran Bhurtyal ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Significant Relationship ◽  
Multinomial Logistic Regression ◽  
Health Hazards ◽  
P Value ◽  
Multinomial Logistic Regression Analysis ◽  
Take Back ◽  
Relationship Of

Abstract Background: Medications are not always completely consumed as purchased from pharmacy due to lack of awareness, forgetfulness. So, most households may have leftover, unwanted, unused and expired (UUE) medicines. They may lead to health hazards and environment pollution. The present study was aimed to analyze feasibility of implementation of medicine take-back in select communities of Nepal.Methods: Exploratory study was conducted among adults (total 400) in Kathmandu, Lalitpur, Kaski, Kanchanpur and Kailali districts from July 2017 to January 2018. Study sites and participants were selected by simple random sampling and respondents were interviewed about their awareness about medicine disposal techniques, possible hazards and their willingness to support take-back program using semi-structured questionnaire. Multinomial logistic regression analysis was applied to explore the relationship of various take-back related outcomes with the predictors. The p-value less than 0.05 was statistically significant at 95% confidence level. Results: The multinomial logistic regression analysis showed that there was significant relationship of health hazards (rashes and diarrhea) among the farmers, engineers, nurse and lawyers (p value <0.01 in each). Land pollution and effect on health of children was significantly related with the inappropriate disposal of medicines such as site of disposal (p value <0.01), river (p value 0.02), garbage (p value 0.04), and dumping site (p value 0.01). The analysis of the willingness to follow take-back program with the techniques of support showed significant relationship with the establishment of collection center and participation on seminar (p value <0.01). Conclusions: Most participants kept UUE medicines in home, disposed with household rubbish and flushed down the sink. They were interested to support take-back, if implemented in their community but the main constraint was the budget. Hence, take-back concept could be initiated and implemented on government funding or other external sources.

scholarly journals Implementation of Medicine Take-back Concept at Community Level in Nepal: A Feasibility Study

2020 ◽  
Author(s):  
Binaya Sapkota ◽  
Anil Giri ◽  
Bigyan Bhatta ◽  
Krishna Awasthi ◽  
Kiran Bhurtyal ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Significant Relationship ◽  
Multinomial Logistic Regression ◽  
Health Hazards ◽  
P Value ◽  
Multinomial Logistic Regression Analysis ◽  
Take Back ◽  
Relationship Of

Abstract Background: Medications are not always completely consumed as purchased from pharmacy due to lack of awareness, forgetfulness. So, most households may have leftover, unwanted, unused and expired (UUE) medicines. They may lead to health hazards and environment pollution. The present study was aimed to analyze feasibility of implementation of medicine take-back in select communities of Nepal.Methods: Exploratory study was conducted among adults (total 400) in Kathmandu, Lalitpur, Kaski, Kanchanpur and Kailali districts from July 2017 to January 2018. Study sites and participants were selected by simple random sampling and respondents were interviewed about their awareness about medicine disposal techniques, possible hazards and their willingness to support take-back program using semi-structured questionnaire. Multinomial logistic regression analysis was applied to explore the relationship of various take-back related outcomes with the predictors. The p-value less than 0.05 was statistically significant at 95% confidence level. Results: The multinomial logistic regression analysis showed that there was significant relationship of health hazards (rashes and diarrhea) among the farmers, engineers, nurse and lawyers (p value <0.01 in each). Land pollution and effect on health of children was significantly related with the inappropriate disposal of medicines such as site of disposal (p value <0.01), river (p value 0.02), garbage (p value 0.04), and dumping site (p value 0.01). The analysis of the willingness to follow take-back program with the techniques of support showed significant relationship with the establishment of collection center and participation on seminar (p value <0.01). Conclusions: Most participants kept UUE medicines in home, disposed with household rubbish and flushed down the sink. They were interested to support take-back, if implemented in their community but the main constraint was the budget. Hence, take-back concept could be initiated and implemented on government funding or other external sources.

scholarly journals PERBANDINGAN REGRESI LOGISTIK MULTINOMINAL DAN ANALISIS DISKRIMINAN

2021 ◽  
Vol 1 (2) ◽  
pp. 135-150
Author(s):  
Rifda Nabila ◽  
Risdiana Himmati ◽  
Rendra Erdkhadifa
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Discriminant Analysis ◽  
Logistic Regression Analysis ◽  
Multinomial Logistic Regression ◽  
Regression Method ◽  
Destination Image ◽  
Tourism Destination ◽  
Multinomial Logistic Regression Analysis ◽  
Logistic Regression Method

Abstrak: Tujuan dari penelitian ini adalah untuk membandingkan analisis regresi logistik multinomial dan analisis diskriminan untuk mengelompokkan keputusan kunjungan wisata halal di Jawa Tengah berdasarkan ketepatan pengelompokan. Analisis statistik yang digunakan adalah regresi logistik multinomial dan analisis diskriminan. Kedua analisis tersebut dapat digunakan sebagai metode pengelompokan objek, sehingga keduanya dapat dibandingkan berdasarkan ketepatan pengelompokkannya. Penelitian ini membandingkan analisis regresi logistik multinomial dan analisis diskriminan dalam pengelompokan keputusan kunjungan wisata halal. Data yang digunakan adalah worship facilities, halalness, general Islamic mortality, dan tourism destination image. Hasil analisis menggunakan metode regresi logistik multinomial menunjukkan faktor-faktor yang secara signifikan mempengaruhi pengelompokan keputusan kunjungan wisata halal adalah variabel tourism destination image, variabel halalness, dan variabel general Islamic morality. Sedangkan dengan analisis diskriminan menunjukkan bahwa semua variabel prediktor yakni worship facilities, halalness, general Islamic mortality, dan tourism destination image memberikan pengaruh secara signifikan terhadap pengklasifikasian keputusan mengunjungi destinasi wisata halal. Penelitian ini menunjukkan bahwa metode regresi logistik multinomial lebih baik untuk pengelompokkan keputusan kunjungan wisata halal dibandingan metode analisis diskriminan, dengan presetnase ketepatan pengelompokkan pada metode regresi logit multinomial sebesar 59,5%  dan analisis diskriminan sebesar 53,5%. Analisis regresi logistik multinominal lebih mudah digunakan dalam proses pengelompokan keputusan kunjuangan wisata halal karena tidak mempertimbangkan asumsi yang harus dipenuhi. Kata Kunci: Analisis Diskriminan; Regresi Logistik Multinominal; Keputusan Mengunjungi   Abstract: The purpose of this study is to compare multinomial logistic regression analysis and discriminant analysis to classify decisions on halal tourism visits in Central Java based on grouping accuracy. Statistical analysis used is multinomial logistic regression and discriminant analysis. The two analyzes can be used as a method of grouping objects, so that they can be compared based on the accuracy of the grouping. This study compares multinomial logistic regression analysis and discriminant analysis in grouping decisions for halal tourism visits. The data used are worship facilities, halalness, general Islamic mortality, and tourism destination image. The results of the analysis using the multinomial logistic regression method show that the factors that significantly influence the grouping of decisions for halal tourism visits are the tourism destination image variable, the halalness variable, and the general Islamic morality variable. Meanwhile, discriminant analysis shows that all predictor variables namely worship facilities, halalness, general Islamic mortality, and tourism destination image have a significant influence on the classification of decisions to visit halal tourist destinations. This study shows that the multinomial logistic regression method is better for grouping decisions on halal tourist visits than the discriminant analysis method, with a preset percentage of grouping accuracy in the multinomial logit regression method of 59.5% and discriminant analysis of 53.5%. Multinominal logistic regression analysis is easier to use in the process of grouping halal tourism travel decisions because it does not consider the assumptions that must be met. Keywords: Discriminant Analysis; Multinomial Logistic Regression; Visiting decision.

scholarly journals Comparative analysis of the elements of attack and defence in men’s and women’s games in the Estonian volleyball highest league

2016 ◽  
Vol 25 (1) ◽  
pp. 37 ◽  
Author(s):  
Raini Stamm ◽  
Meelis Stamm ◽  
Doris Torilo ◽  
Kaivo Thomson ◽  
Alexander Jairus
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Comparative Analysis ◽  
Logistic Regression Analysis ◽  
Multinomial Logistic Regression ◽  
Block Type ◽  
Multinomial Logistic Regression Analysis ◽  
Expert Assessments ◽  
Attack Type

The aim of this study was to analyse the differences between men’s and women’s teams of the Estonian highest league in attack, serve, block, defence and serve reception. The sample consisted of 5 men’s and 5 women’s teams of the Estonian volleyball highest league in the 2014/2015 season. To collect data, two game videos of each team were watched; from them tempo of attack, type of attack, block and serve, and the results of defence and cover were registered. In addition, statistics created by the Data Volley and Volleysoft 6–3 programs on the basis of expert assessments were used to estimate the efficiency of volleyball elements and results of reception. SPSS Statistics 23 version for Windows was used to construct frequency tables and multinomial logistic regression analysis was applied to find the probable frequencies of the activities analysed. The results revealed that in Estonian men’s highest league games quick tempo 1 attacks were used statistically significantly more often than in women’s games. Men were more proficient at attack and used a vigorous spike more often than women. For both genders, double block was the most often used block type. Broken double block was more common to men than to women. The serve type most often used by men was the power jump serve, followed by the tactical float serve. Women most often used the standing serve and, as second, the jump float serve. Men made more serve errors than women did. The percentage of ace serves was also higher in women than in men.In defence, the percentage of the ball remaining in play was higher in women than in men, and women’s defence cover was more efficient than men’s. As a result of attack cover, the ball remained in play nearly by half more frequently in women’s than in men’s games. Nonetheless, women scored fewer points as a result of attack cover. Serve reception in the Estonian highest league was better in men, and men made statistically significantly fewer errors in reception than women did.

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