Araştırma Makalesi
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Nitel ve Nicel Araştırma Tasarımı Uygulamasıyla Etanol Kullanımını ve Etkilerinin Anlaşılması

Yıl 2021, Sayı: 32, 40 - 49, 31.12.2021
https://doi.org/10.31590/ejosat.1039621

Öz

İnsan türünün alkole olan ilgisi uzun yıllardır bilinmektedir. Fermantasyon ve damıtma tekniklerinin keşfedilmesi ve geliştirilmesine paralel olarak İnsanlar, farklı coğrafyalar, ülkeler ve kültürlerde alkolü kullandılar. Birçok davranış kalıbının analizinde görüldüğü gibi, alkol içmeye ve bu tür davranışların ortaya çıkmasına yol açan çeşitli faktörlerin ve öncüllerin olduğuna inanılmaktadır.

Günümüzde özellikle 21. yüzyılda alkol kullanımı, çeşitli şekillerde önemli bir davranış biçimi haline gelmiş, birçok sosyal ve kültürel ortamlarda popülerlik kazanmıştır. Toplum ve iş ortamındaki değişiklikler yardımıyla birçok organizasyonel ortamda sosyal ve bireysel formlarda yer buldu. İnsanoğlunun alkole olan ilgisi onlarca yıldır bilinmekte ve bunun devam etmesi beklenmektedir. Ancak farklı normlar, gelenekler. değerler. düzenleyici çerçeveler. çevre, grup etkisi, çeşitli mikro ve makro düzeydeki değişkenler doğrudan veya dolaylı olarak alkol tüketimini etkilemektedir. Birçok nesildeki ve yaşam tarsi tercihindeki popülaritesine ragmen, aşırı alkol tüketimi insan sağlığı için çeşitli riskler ve tehlikeler oluşturmaktadır. Literatürde alkol tüketiminin kısa vadeli, uzun vadeli ve aşırı tüketimi ile ilgili çeşitli çalışmalar vardır.Bunları bazı olası faydaları, riskleri ve tehlikeleri içermektedir. Bu çalışmada alkol tüketimi ile ilişkili bazı faktörler derinlemesine görüşmelerden oluşan nitel ve nicel araştırma metodolojilerinin üçgenleme(triangulation) yaklaşımıyla, derinlemesine mülakat, gözlemleme, güdümlü ve güdümsüz makine öğrenmesi gibi veri madenciliği yöntemleri yardımı ile kalitatif ve kantitatif araştırma yöntemleri kullanılarak ilgilili phenomenanın anlaşılması ve uzun vadede karşılaşılabilecek risklerin ve tehditlerin altının çizilmesi maksadıyla uygulanmıştır.

Kaynakça

  • https://www.hsph.harvard.edu/nutritionsource/healthy-drinks/drinks-to-consume-in-moderation/alcohol-full-story/
  • Renaud S. de Lorgeril M. Wine. alcohol. platelets. and the French paradox for coronary heart disease. Lancet. 1992 Jun 20;339(8808):1523-6.
  • Burr ML.. Explaining the French paradox. J R Soc Health. 1995 Aug;115(4):217-9.
  • Constant J.. Alcohol. ischemic heart disease. and the French paradox. Coron Artery Dis. 1997 Oct;8(10):645-9.
  • Isabela Maria MONTEIRO VIEIRA. Alcohol and Health: Standards of Consumption. Benefits and Harm – a Review. Czech J. Food Sci.. 36. 2018 (6): 427–440
  • Haseeb S. Alexander B. Baranchuk A. Wine and Cardiovascular Health: A Comprehensive Review. Circulation. 2017 Oct 10;136(15
  • Carvalho AF. Heilig M. Perez A. Probst C. Rehm J. Alcohol use disorders. Lancet. 2019 Aug 31;394(10200):781-792.
  • Mathurin P. Lucey MR. Liver transplantation in patients with alcohol-related liver disease: current status and future directions. Lancet Gastroenterol Hepatol. 2020 May;5(5):507-514.
  • Rehm J. Taylor B. Mohapatra S. Irving H. Baliunas D. Patra J. Roerecke M. Alcohol as a risk factor for liver cirrhosis: a systematic review and meta-analysis. Drug Alcohol Rev. 2010 Jul;29(4):437-45.
  • https://www.hopkinsmedicine.org/health/wellness-and-prevention/detoxing-your-liver-fact-versus-fiction
  • https://www.health.harvard.edu/blog/sorting-out-the-health-effects-of-alcohol-2018080614427
  • https://www.archivesofmedicalscience.com/The-role-of-curcumin-in-liver-diseases.78816.0.2.html
  • https://medipol.com.tr/kurumsal/haberler/medyada-medipol/karacigeriniz-icin-detokstan-medet-ummayin
  • https://www.sommerwhitemd.com/eat-these-foods-to-increase-glutathione/
  • https://www.hpa.org.nz/sites/default/files/documents/HealthEffects.pdf
  • Blais E. Maurice P. Toward improved evaluations of laws against drink-driving. Lancet. 2019 Jan 26;393(10169):297-298.
  • White A. Hingson R. The burden of alcohol use: excessive alcohol consumption and related consequences among college students.
  • Antonio Riccardo Buonomo . The role of curcumin in liver diseases. Arch Med Sci 2019; 15 (6): 1608–1620
  • https://www.encyclopedia.com/education/applied-and-social-sciences-magazines/alcohol-history-drinking
  • https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-021-10991-7
  • SWOT Analysis: Discover New Opportunities. Manage and Eliminate Threats". www.mindtools.com. 2016. Retrieved 24 February 2018.
  • Sammut-Bonnici. Tanya & Galea. David. (2015). SWOT Analysis. 10.1002/9781118785317.weom120103.
  • Satoshi Nakamoto. Bitcoin: A Peer-to-Peer Electronic Cash System.2008
  • Águila. R.D.M.. Ramírez. G.A.. 2013. Series: basic statistics for busy clinicians. Allergol Immunopathol. 42 (5). pp. 485-492.
  • Blackmore. K.. Bossomaier. T.. 2002. Comparison of See5 and J48.PART algorithms for missing persons profiling. International Conference on Information Technology and Applications
  • Frank E. and Witten I.H. (1998). Generating Accurate Rule Sets Without Global Optimization. In Shavlik. J.. ed.. Machine Learning: Proceedings of the Fifteenth International Conference. Morgan Kaufmann Publishers.
  • Frank E. and Witten I.H. (2000). Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann Publishers: San Francisco. CA.
  • Lemeshow S.. Hosmer D.W.. Klar J. & Lwanga S.K.. 1990. Adequacy of sample size in health studies. Chichester: John Wiley and Sons.
  • Ramchoun. H. r.. Idrissi. M. m.. Ghanou. Y. y.. & Ettaouil. M. m. (2017). New Modeling of Multilayer Perceptron Architecture Optimization with Regularization: An Application to Pattern Classification. IAENG International Journal of Computer Science. 44(3). 261-269.
  • Rosenblatt. F.. & Cornell Aeronautical Laboratory. (1958). The perceptron: A theory of statistical separability in cognitive systems (Project Para). Buffalo. N.Y: Cornell Aeronautical Laboratory.
  • Shearer. C.. 2000 The CRISP-DM model: the new blueprint for data mining. Journal of Data Warehousing. 5. 13-22.
  • Simoudis. E. (1996). Reality Check for Data Mining. IEEE EXPERT. 11(5). pp.26-33
  • Cohen. W. (1995). Fast effective rule induction. In A. Prieditis and S. Russell (eds.). Proceedings of the 12th International Conference on Machine Learning. Lake Tahoe. CA. pp.115-123.
  • Saravanan. N.. Gayathri V.. 2018. Performance and classification evaluation of J48 algorithm and Kendall's based J48 algorithm (KNJ48). International Journal of Computer Trends and Technology
  • Sasaki M.. Kita K.. 1998. Rule based text categorization using hierarchical categories. IEEE
  • Edmondson. Amy C.. and Tiona Zuzul. "Quantitative and Qualitative Methods in Organizational Research." In The Palgrave Encyclopedia of Strategic Management. Continuously updated edition. edited by Mie Augier and David J. Teece. Palgrave Macmillan. 2017. Electronic. (Pre-published. October 2013.)
  • Taniguchi M.. Haft M.. Hollm´en J.. and Tresp V. (1998). Fraud detection in communications networks using neural and probabilistic methods. In Proceedings of the 1998 IEEE International Conference on Acoustics. Speech and Signal Processing (ICASSP'98). Volume II. pp. 1241-1244.
  • Venkatesan. E. V.. 2015. Performance Analysis of Decision Tree Algorithms for Breast Cancer Classification. Indian Journal of Science and Technology.
  • Yavuz Ö.. 2019. A data mining approach for desire and intention to participate in virtual communities. International Journal of Electrical and Computer Engineering. 9(5).
  • Ławrynowicz. A.. Tresp. V.. 2014. Introducing Machine Learning. Perspectives on Ontology Learning. AKA Heidelberg /IOS Press.
  • Thomas. M.. 2012. Root Mean Square Error Compared to. and Contrasted with. Standard Deviation. Surveying and Land Information Science. 72.
  • Ławrynowicz. A.. Tresp. V.. 2014. Introducing Machine Learning. Perspectives on Ontology Learning. AKA Heidelberg /IOS Press.
  • Thomas. M.. 2012. Root Mean Square Error Compared to. and Contrasted with. Standard Deviation. Surveying and Land Information Science. 72.
  • Karahoca D.. Karahoca A.. Yavuz Ö.. 2013. An early warning system approach for the identification of currency crises with data mining techniques. Neural Computing and Applications. 23(7-8)
  • Rasmussen. C. E.; Williams. C. K. I. Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning); The MIT Press: 2005.
  • Malhotra. Naresh K. Marketing Research: An Applied Orientation. Upper Saddle River. NJ: Pearson/Prentice Hall. 2007.
  • Anil Rajput. 2011 J48 and JRIP Rules for E-Governance Data. International Journal of Computer Science and Security (IJCSS). 5(2)
  • Conkright. Todd. (2015). Using the Four Functions of Management for Sustainable Employee Engagement. Performance Improvement. 54. 10.1002/pfi.21506.
  • Ajzen. I. & Fishbein. M.. 1980. Understanding attitudes and predicting social behaviour. Englewood Cliffs. NJ: Prentice Hall.
  • Kotler. Philip. Principles of Marketing. Englewood Cliffs. N.J. :Prentice Hall. 1991.
  • Kotler. Philip. Marketing Management. Upper Saddle River. N.J. :Prentice Hall. 2000.
  • Yavuz. Ö.. 2018. Marketing Implications Of Participative Behavior In Virtual Communities. Bahcesehir University Graduate School of Social Sciences. Management-Marketing Program. Istanbul
  • Yavuz. Ö.. 2009. An early warning system approach for the identification of currency crises. Bahcesehir University Graduate School of Sciences. Computer Engineering Graduate Program. Istanbul
  • Yavuz. Ö. (2021). A Public Perceptions Analysis With Data Mining Algorithms. 2. International “Başkent” Congress On Physical. Social and Health Sciences. Ankara
  • Yavuz. Ö. (2021). A Data Mining Analysis of Coronavirus Cases and Vaccinations in The City of London. Astana. Ankara.
  • Halldórsdóttir. S. (2000). The Vancouver School of doing Phenomenology. In: Fridlund. B. and Hildingh. C. (eds.) Qualitative research methods in the service of health. Lund: Studentlitteratur. pp. 47-84.
  • Smith. J.D.. (2012). Single-Case Experimental Designs: A Systematic Review of Published Research and Current Standards. Psychological Methods. 10.1037/a0029312.
  • Tate. Robyn & Perdices. Michael. (2020). Research Note: Single-case experimental designs. Journal of Physiotherapy. 66. 10.1016/j.jphys.2020.06.004.
  • Khan. Shahid. (2014). Qualitative Research Method - Phenomenology. Asian Social Science. 10. 298-310. 10.5539/ass.v10n21p298.
  • Neubauer. B.E.. Witkop. C.T. & Varpio. L. How phenomenology can help us learn from the experiences of others. Perspect Med Educ 8. 90–97 (2019).
  • Olsen. Wendy. (2004). Triangulation in social research: Qualitative and quantitative methods can really be mixed. Developments in sociology. 20. 103–118.
  • Kelle. Udo & Kühberger. Christoph & Bernhard. Roland. (2019). How to Use Mixed-methods and Triangulation Designs: an Introduction to History Education Research. History Education Research Journal. 16. 5-23. 10.18546/HERJ.16.1.02.
  • Todd D. Jick. 1979. Mixing Qualitative and Quantitative Methods: Triangulation in Action. Administrative Science Quarterly
  • Cropley. Arthur. (2015). Introduction to Qualitative Research Methods. 10.13140/RG.2.1.3095.6888/1.
  • van den Brandt PA. Brandts L. Alcohol consumption in later life and reaching longevity: the Netherlands Cohort Study. Age Ageing. 2020 Apr 27;49(3)
  • Joseph A. Samant H. Jaundice. [Updated 2021 Aug 11]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing;
  • Brandt. Piet & Brandts. Lloyd. (2020). Alcohol consumption in later life and reaching longevity: the Netherlands Cohort Study. Age and ageing. 49. 10.1093/ageing/afaa003.
  • Bryman. A. (2008). Social Research Methods. New York: Oxford University Press.

Understanding Ethanol Usage and Its Influences by Applying a Qualitative and Quantitative Research Design

Yıl 2021, Sayı: 32, 40 - 49, 31.12.2021
https://doi.org/10.31590/ejosat.1039621

Öz

Human kind’s interest on alcohol has been known for many decades. People used alcohol in different geographies. countries and cultures in parallel to the discovery and development of fermentation and distillation techniques. As seen in the analysis of many behavioural patterns it is believed to be several factors and antecedents that lead to engaging drinking alcohol and such behavior to occur.
Today especially in 21st century alcohol usage became an important behavioral pattern in various contexts and settings and gained popularity in many social and cultural settings. With the help of transitions of the society and business landscape it found place in many organizational settings and landscapes in a more social and individualistic way. Interest of human to alcohol known for many decades and expected to remain. However different norms. traditions. values. approach of regulatory frameworks. environment. group influence have impact on alcohol consumption with several micro and macro level variables directly or indirecatly in a moderating nature. Despite its popularity in many generations. life styles and preferences excessive levels of alcohol consumption constitutes several hazarding risks and dangerous to human health. There are several studies associated with alcohol consumption and its benefits. dangers and risks associated with its short term. long term and excessive usage in literature. In this study some of the factors associated with alcohol consumption is investigated with the triangulation approach of qualitative and quantitative research methodologies composed of in depth interviews. observation and supervised and supervised forms of data ming with the aim of having an comprehensive understanding of the phenomena and highlighting the risks and dangers associated with long term. excessive usage.

Kaynakça

  • https://www.hsph.harvard.edu/nutritionsource/healthy-drinks/drinks-to-consume-in-moderation/alcohol-full-story/
  • Renaud S. de Lorgeril M. Wine. alcohol. platelets. and the French paradox for coronary heart disease. Lancet. 1992 Jun 20;339(8808):1523-6.
  • Burr ML.. Explaining the French paradox. J R Soc Health. 1995 Aug;115(4):217-9.
  • Constant J.. Alcohol. ischemic heart disease. and the French paradox. Coron Artery Dis. 1997 Oct;8(10):645-9.
  • Isabela Maria MONTEIRO VIEIRA. Alcohol and Health: Standards of Consumption. Benefits and Harm – a Review. Czech J. Food Sci.. 36. 2018 (6): 427–440
  • Haseeb S. Alexander B. Baranchuk A. Wine and Cardiovascular Health: A Comprehensive Review. Circulation. 2017 Oct 10;136(15
  • Carvalho AF. Heilig M. Perez A. Probst C. Rehm J. Alcohol use disorders. Lancet. 2019 Aug 31;394(10200):781-792.
  • Mathurin P. Lucey MR. Liver transplantation in patients with alcohol-related liver disease: current status and future directions. Lancet Gastroenterol Hepatol. 2020 May;5(5):507-514.
  • Rehm J. Taylor B. Mohapatra S. Irving H. Baliunas D. Patra J. Roerecke M. Alcohol as a risk factor for liver cirrhosis: a systematic review and meta-analysis. Drug Alcohol Rev. 2010 Jul;29(4):437-45.
  • https://www.hopkinsmedicine.org/health/wellness-and-prevention/detoxing-your-liver-fact-versus-fiction
  • https://www.health.harvard.edu/blog/sorting-out-the-health-effects-of-alcohol-2018080614427
  • https://www.archivesofmedicalscience.com/The-role-of-curcumin-in-liver-diseases.78816.0.2.html
  • https://medipol.com.tr/kurumsal/haberler/medyada-medipol/karacigeriniz-icin-detokstan-medet-ummayin
  • https://www.sommerwhitemd.com/eat-these-foods-to-increase-glutathione/
  • https://www.hpa.org.nz/sites/default/files/documents/HealthEffects.pdf
  • Blais E. Maurice P. Toward improved evaluations of laws against drink-driving. Lancet. 2019 Jan 26;393(10169):297-298.
  • White A. Hingson R. The burden of alcohol use: excessive alcohol consumption and related consequences among college students.
  • Antonio Riccardo Buonomo . The role of curcumin in liver diseases. Arch Med Sci 2019; 15 (6): 1608–1620
  • https://www.encyclopedia.com/education/applied-and-social-sciences-magazines/alcohol-history-drinking
  • https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-021-10991-7
  • SWOT Analysis: Discover New Opportunities. Manage and Eliminate Threats". www.mindtools.com. 2016. Retrieved 24 February 2018.
  • Sammut-Bonnici. Tanya & Galea. David. (2015). SWOT Analysis. 10.1002/9781118785317.weom120103.
  • Satoshi Nakamoto. Bitcoin: A Peer-to-Peer Electronic Cash System.2008
  • Águila. R.D.M.. Ramírez. G.A.. 2013. Series: basic statistics for busy clinicians. Allergol Immunopathol. 42 (5). pp. 485-492.
  • Blackmore. K.. Bossomaier. T.. 2002. Comparison of See5 and J48.PART algorithms for missing persons profiling. International Conference on Information Technology and Applications
  • Frank E. and Witten I.H. (1998). Generating Accurate Rule Sets Without Global Optimization. In Shavlik. J.. ed.. Machine Learning: Proceedings of the Fifteenth International Conference. Morgan Kaufmann Publishers.
  • Frank E. and Witten I.H. (2000). Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann Publishers: San Francisco. CA.
  • Lemeshow S.. Hosmer D.W.. Klar J. & Lwanga S.K.. 1990. Adequacy of sample size in health studies. Chichester: John Wiley and Sons.
  • Ramchoun. H. r.. Idrissi. M. m.. Ghanou. Y. y.. & Ettaouil. M. m. (2017). New Modeling of Multilayer Perceptron Architecture Optimization with Regularization: An Application to Pattern Classification. IAENG International Journal of Computer Science. 44(3). 261-269.
  • Rosenblatt. F.. & Cornell Aeronautical Laboratory. (1958). The perceptron: A theory of statistical separability in cognitive systems (Project Para). Buffalo. N.Y: Cornell Aeronautical Laboratory.
  • Shearer. C.. 2000 The CRISP-DM model: the new blueprint for data mining. Journal of Data Warehousing. 5. 13-22.
  • Simoudis. E. (1996). Reality Check for Data Mining. IEEE EXPERT. 11(5). pp.26-33
  • Cohen. W. (1995). Fast effective rule induction. In A. Prieditis and S. Russell (eds.). Proceedings of the 12th International Conference on Machine Learning. Lake Tahoe. CA. pp.115-123.
  • Saravanan. N.. Gayathri V.. 2018. Performance and classification evaluation of J48 algorithm and Kendall's based J48 algorithm (KNJ48). International Journal of Computer Trends and Technology
  • Sasaki M.. Kita K.. 1998. Rule based text categorization using hierarchical categories. IEEE
  • Edmondson. Amy C.. and Tiona Zuzul. "Quantitative and Qualitative Methods in Organizational Research." In The Palgrave Encyclopedia of Strategic Management. Continuously updated edition. edited by Mie Augier and David J. Teece. Palgrave Macmillan. 2017. Electronic. (Pre-published. October 2013.)
  • Taniguchi M.. Haft M.. Hollm´en J.. and Tresp V. (1998). Fraud detection in communications networks using neural and probabilistic methods. In Proceedings of the 1998 IEEE International Conference on Acoustics. Speech and Signal Processing (ICASSP'98). Volume II. pp. 1241-1244.
  • Venkatesan. E. V.. 2015. Performance Analysis of Decision Tree Algorithms for Breast Cancer Classification. Indian Journal of Science and Technology.
  • Yavuz Ö.. 2019. A data mining approach for desire and intention to participate in virtual communities. International Journal of Electrical and Computer Engineering. 9(5).
  • Ławrynowicz. A.. Tresp. V.. 2014. Introducing Machine Learning. Perspectives on Ontology Learning. AKA Heidelberg /IOS Press.
  • Thomas. M.. 2012. Root Mean Square Error Compared to. and Contrasted with. Standard Deviation. Surveying and Land Information Science. 72.
  • Ławrynowicz. A.. Tresp. V.. 2014. Introducing Machine Learning. Perspectives on Ontology Learning. AKA Heidelberg /IOS Press.
  • Thomas. M.. 2012. Root Mean Square Error Compared to. and Contrasted with. Standard Deviation. Surveying and Land Information Science. 72.
  • Karahoca D.. Karahoca A.. Yavuz Ö.. 2013. An early warning system approach for the identification of currency crises with data mining techniques. Neural Computing and Applications. 23(7-8)
  • Rasmussen. C. E.; Williams. C. K. I. Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning); The MIT Press: 2005.
  • Malhotra. Naresh K. Marketing Research: An Applied Orientation. Upper Saddle River. NJ: Pearson/Prentice Hall. 2007.
  • Anil Rajput. 2011 J48 and JRIP Rules for E-Governance Data. International Journal of Computer Science and Security (IJCSS). 5(2)
  • Conkright. Todd. (2015). Using the Four Functions of Management for Sustainable Employee Engagement. Performance Improvement. 54. 10.1002/pfi.21506.
  • Ajzen. I. & Fishbein. M.. 1980. Understanding attitudes and predicting social behaviour. Englewood Cliffs. NJ: Prentice Hall.
  • Kotler. Philip. Principles of Marketing. Englewood Cliffs. N.J. :Prentice Hall. 1991.
  • Kotler. Philip. Marketing Management. Upper Saddle River. N.J. :Prentice Hall. 2000.
  • Yavuz. Ö.. 2018. Marketing Implications Of Participative Behavior In Virtual Communities. Bahcesehir University Graduate School of Social Sciences. Management-Marketing Program. Istanbul
  • Yavuz. Ö.. 2009. An early warning system approach for the identification of currency crises. Bahcesehir University Graduate School of Sciences. Computer Engineering Graduate Program. Istanbul
  • Yavuz. Ö. (2021). A Public Perceptions Analysis With Data Mining Algorithms. 2. International “Başkent” Congress On Physical. Social and Health Sciences. Ankara
  • Yavuz. Ö. (2021). A Data Mining Analysis of Coronavirus Cases and Vaccinations in The City of London. Astana. Ankara.
  • Halldórsdóttir. S. (2000). The Vancouver School of doing Phenomenology. In: Fridlund. B. and Hildingh. C. (eds.) Qualitative research methods in the service of health. Lund: Studentlitteratur. pp. 47-84.
  • Smith. J.D.. (2012). Single-Case Experimental Designs: A Systematic Review of Published Research and Current Standards. Psychological Methods. 10.1037/a0029312.
  • Tate. Robyn & Perdices. Michael. (2020). Research Note: Single-case experimental designs. Journal of Physiotherapy. 66. 10.1016/j.jphys.2020.06.004.
  • Khan. Shahid. (2014). Qualitative Research Method - Phenomenology. Asian Social Science. 10. 298-310. 10.5539/ass.v10n21p298.
  • Neubauer. B.E.. Witkop. C.T. & Varpio. L. How phenomenology can help us learn from the experiences of others. Perspect Med Educ 8. 90–97 (2019).
  • Olsen. Wendy. (2004). Triangulation in social research: Qualitative and quantitative methods can really be mixed. Developments in sociology. 20. 103–118.
  • Kelle. Udo & Kühberger. Christoph & Bernhard. Roland. (2019). How to Use Mixed-methods and Triangulation Designs: an Introduction to History Education Research. History Education Research Journal. 16. 5-23. 10.18546/HERJ.16.1.02.
  • Todd D. Jick. 1979. Mixing Qualitative and Quantitative Methods: Triangulation in Action. Administrative Science Quarterly
  • Cropley. Arthur. (2015). Introduction to Qualitative Research Methods. 10.13140/RG.2.1.3095.6888/1.
  • van den Brandt PA. Brandts L. Alcohol consumption in later life and reaching longevity: the Netherlands Cohort Study. Age Ageing. 2020 Apr 27;49(3)
  • Joseph A. Samant H. Jaundice. [Updated 2021 Aug 11]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing;
  • Brandt. Piet & Brandts. Lloyd. (2020). Alcohol consumption in later life and reaching longevity: the Netherlands Cohort Study. Age and ageing. 49. 10.1093/ageing/afaa003.
  • Bryman. A. (2008). Social Research Methods. New York: Oxford University Press.
Toplam 68 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Özerk Yavuz 0000-0002-1371-688X

Yayımlanma Tarihi 31 Aralık 2021
Yayımlandığı Sayı Yıl 2021 Sayı: 32

Kaynak Göster

APA Yavuz, Ö. (2021). Nitel ve Nicel Araştırma Tasarımı Uygulamasıyla Etanol Kullanımını ve Etkilerinin Anlaşılması. Avrupa Bilim Ve Teknoloji Dergisi(32), 40-49. https://doi.org/10.31590/ejosat.1039621