© 2019 Kseniya GERASIMOVA
2019 – № 2 (18)
Kseniya Georgievna Gerasimova, Cand. Sc. in Sociology, is an Associate Professor at the Department of Methodology of Sociological and Marketing Research, Samara State University.
Keywords:medical choice, therapeutic decisions, factors of medical choice, situation of choice, chronic illness, self- treatment, biomedicine, nonconventional medicine, classification trees, CHAID analysis
Abstract: The article presents the results of a sociological study of the influence of various factors on the logic of therapeutic choice at various stages of the development of the chronic disease. The results of a survey of 510 chronic patients are the continuation of a large-scale study of the characteristics of medical choice, carried out by sociologists of Samara University. CHAID analysis allowed to elicit the features of making therapeutic decisions at the disease’s debut and chronicity stages. With financial accessibility as the main factor in decision-making, the importance of relevant experience and self-knowledge was revealed, as well as the importance of general trust-distrust to medical knowledge and medical institutions.
The article presents the results of a sociological study on the influence of various factors on the logic behind therapeutic choice at different stages of development of the chronic disease. The results of a poll among 510 chronically ill people are a continuation of wide-scale research of characteristics of medical choice conducted by sociologists from Samara University. Using CHAID-analysis, they exposed specifics of therapeutic decision-making at the stage of disease’s debut and at the stage of its chronicalization.
The set of factors varied for each situation and included generalized indices based on respondents’ agreement or disagreement with proposed judgments. I. e. they were subjective evaluations of reasons behind patients’ behavior in studied situations.
The therapeutic decisions themselves (as a dependant variable) could manifest themselves in four variations (for either situation): 1. addressing official medicine only; 2. mixture of biomedical choice and self-treatment; 3. self-treatment only; 4. other variations (including choice of alternative medical help, in particular, folk healing, Indian Ayurveda, traditional Chinese medicine, homeopathy).
The resulting trees of solutions allowed to find solutions where various factors combinations secured a maximal probability of a certain therapeutic choice.
For situation 1 (“Disease Debut”), out of the eight regarded factors these three were included in the Solutions Tree as essential ones: financial availability, communication channels, and trust or mistrust to medical institutions.
Based on the model, it was revealed that most likely to take independent decisions in regards to the disease at its debut stage are the patients for whom financial availability is not a crucial factor (28.4 %). Most likely to address traditional medicine (91.2 %) are those who take financial availability into account but disregard, while taking decisions, the knowledge received via communication channels, or the aspect of trust in medical institutions. The share of patients using a mixture of variations of addressing biomedicine and autonomous actions is highest among the respondents for whom financial availability is not critical, while communication factors, vice versa, are taken into account in the decision-making process (29.7 %).
In regards to Situation 3 (“Disease Chronicalication”), factors defining branching of Solutions Tree are financial availability, knowledge about oneself, and trust or mistrust to medical institutions and science.
It has been identified that the highest probability of taking exclusively independent therapeutic decisions (78.9 %) is among patients who are guided by the factors of financial availability and knowledge of oneself while considering the aspect of trust or mistrust to medical institutions as part of the decision-making scheme. Supporters of traditional biomedicine are also widely guided by the factor of financial availability and knowledge of oneself but, in the end, their decision is defined by the question of trust to medical science (80 %). A combination of self-treatment and addressing official medicine is most likely if the patient is guided by financial availability and knowledge of oneself.
Classification trees as a mathematical method allow us to successfully solve the substantive task of subject choice and, in particular, the therapeutic choice of a chronically ill patient. To a large extent, this modeling experience is complicated by the dominance of conventional medical choice, although its weakening during the development of disease allowed to expand reference frames of the factor space and to evaluate peculiarities of therapeutic decision-making by chronic patients.
Aronson, P.YA. (2006) Utrata institucional’nogo doveriya v rossijskom zdravoohranenii [Loss of institutional trust in Russian healthcare], Zhurnal sociologii i social’noj antropologii [The Journal of Sociology and Social Anthropology], Vol.9. No.2, pp.120–131.
Bova, A. (2002) Derev’ya reshenij kak tekhnika dobychi dannyh [Decision trees as a data mining technique], Sociologiya: teoriya, metody, marketing [Sociology: theory, methods, marketing], No 1, pp.128–136.
Gruzdev, A. (2016) Prognoznoe modelirovanie v IBM SPSS Statistics i R. Metod derev’ev reshenij [Predictive modeling in IBM SPSS Statistics and R. Decision tree method], Moscow: DMK Press.
Dembitskyi, S. (2019) Rozrobka socіologіchnih testіv: metodologіja і praktiki її zastosuvannja[Development of Sociological Tests: Methodology and Practices of Its Application], Kiev: Іnstitut socіologії NAN Ukraїni publ.
Dorner, K. (2006) Horoshij doktor [Good doctor], Moscow: Alitejya.
Zhuchkova, S. V., Rotmistrov, A. N. (2019) Poisk mnogomernoj svyazi kategorial’nyh priznakov: sravnenie CHAID, loglinejnogo analiza i mnozhestvennogo analiza sootvetstvij [In search of multivariate associations: comparison of CHAID, log-linear analysis, and multiple correspondence analysis], Monitoring obshchestvennogo mneniya: ekonomicheskie i social’nye peremeny [Monitoring of Public Opinion: economic and Social Changes], No 2, pp. 32–53.
Zdravomyslova E., Tyomkina А. (2009) «Vracham ya ne doveryayu, no… » Preodolenie nedoveriya k reproduktivnoj medicine [“I don’t trust doctors, but …” Overcoming mistrust in reproductive medicine] Zdravomyslova E., Tyomkina А. (eds.), Zdorov’e i doverie: gendernyj podkhod k reproduktivnoj meditsine [Health and trust: a gender approach to reproductive medicine], SPb.: Izdatel’stvo Evropejskogo universiteta v Sankt-Peterburge, pp. 179–210.
Lekhtsier, V.L. (2018) Bolezn’: Opyt, Narrative, Nadezhda. Ocherk social’nyh i gumanitarnyh issledovaniĭ mediciny [Disease: Experience, Narrative, Hope. Essay on the social and humanities research of medicine]. Vilnius: Logvino literatūros namai.
Lekhtsier, V.L., Gotlib, А.S. (2017) Meditsinskij vybor khronicheskikh bol’nykh v krupnom rossijskom gorode: opyt kachestvennogo analiza [Medical choice of chronic patients in a large Russian city: experience of qualitative analysis] Lishaev S.S. (eds.) Mixturaverborum’ 2017: chelovek i vremya: filosofskij ezhegodnik [Mixturaverborum’ 2017: Man and time. Philosophical Yearbook], pp. 108–136.
Lekhtsier, V.L., Gotlib, A.S., Finkelshtein, I.E. (2019) Medicinskij vybor hronicheskih bol’nyh v krupnom rossijskom gorode: situacii, praktiki, faktory [Medical choice of chronic patients in a large Russian сity: Situations, practices, factors], Sociologicheskij zhurnal [Sociological Journal], Vol. 25, No. 2, pp. 78–98.
Mastikova, N. S. (2019) Vospriyatie social’noj spravedlivosti rossiyanami na osnove dannyh evropejskogo issledovaniya [Perception of social justice by Russians based on data from a European study], Nauchnyj rezul’tat. Sociologiya i upravlenie [The scientific result. sociology and management], Vol.5, No 1, pp. 39–51.
Sadykov, R.A. (2012) Status gomeopatii v prostranstve rossijskogo zdravoohraneniya: avtonomiya ili integraciya ? [The status of homeopathy in the Russian healthcare space: autonomy or integration?], Zhurnal issledovanij social’noj politiki [Journal of Social Policy Studies], Vol. 10, No 1, pp. 109–126.
Samarskaya, T.A., Teper, G.A. (2007) Al’ternativnaya medicina rossijskoj provincii [Alternative medicine of the Russian province], Zhurnal issledovanij social’noj politiki [Journal of Social Policy Studies], Vol. 5, No 1, pp. 87–103.
Saponov, D.I. (2013) Opyt konkurentnoj bor’by kak faktor akademicheskoj uspevaemosti [Competition experience as a factor of academic performance], Monitoring obshchestvennogo mneniya: ekonomicheskie i social’nye peremeny [Monitoring of Public Opinion: Economic and Social Changes Journal], No 5, pp.113–126.
Tenisheva, K. A., Savel’eva, S. S., Aleksandro,v D. A. (2018) Primenenie metoda uslovnyh derev’ev reshenij k modelirovaniyu vybora roditelyami shkoly [Application of the method of conditional decision trees to modeling the choice of school parents], Sociologiya: metodologiya, metody, matematicheskoe modelirovanie (4M) [Sociology: Methodology, Methods, Mathematical Modeling], Vol.46, pp.44–84.
Tolstova, YU.N. (2000) Analiz sociologicheskih dannyh. Metodologiya, deskriptivnaya statistika, izuchenie svyazej mezhdu nominal’nymi priznakami [Analysis of sociological data. Methodology, descriptive statistics, the study of the relationship between nominal features], Moscow: Nauchnyj mir.
Finkelshtein, I. E. (2018) Model’ prinyatiya terapevticheskih reshenij v kognitivnoj medicinskoj antropologii Lindy Garro [Model of decision-making in medical anthropology L. Garro], Vestnik Sankt-Peterburgskogo universiteta. Sociologiya [Vestnik of Saint Petersburg University. Sociology], Vol. 11, issue 1, pp. 79–93.
Castellani, B., Castellani, J. (2003) Data Mining: Qualitative Analysis with Health Informatics Data, Qualitative Health Research, 13(7), pp. 1005–1018.
Garro, L. C. (1998a) On the Rationality of Decision-Making Studies: Part 1: Decision Models of Treatment Choice, Medical Anthropology Quarterly, 12(3), pp.319–340.
Garro, L. C. (1998b) On the Rationality of Decision-Making Studies: Part 2: Divergent Rationalities, Medical Anthropology Quarterly, Vol. 12(3), pp. 341–355.
Milanović, M., Stamenković, M. (2016) CHAID decision tree: methodological frame and application, Economic Themes, Vol. 54(4), pp. 563–586.
Parsons, Т. (1951) The social system, N.Y.: The Free Press.
Šulc, Z., Stecenková, M., Vild, J. (2015) Two-Step Classification of Unemployed People in the Czech Republic, Statistica, Vol. 95 (1), pp. 38–46.
Young, J. C., Garro, L. (1994) Medical Choice in a Mexican Village. Prospect Heights, Illinois: Waveland Press.
Gerasimova K. G. (2019). Therapeutic Decision of Chronic Patients: Decision-making Models in the Mirror of CHAID-analysis [Terapevticheskij vybor hronicheskih bol’nyh: modeli prinjatija reshenij v zerkale CHAID-analiza]. Medical Anthropology and Bioethics [Medicinskaja antropologija i biojetika], 2 (18).