A qualitative study of culturally embedded factors in complementary and alternative medicine use

Abstract Background Within the intercultural milieu of medical pluralism, a nexus of worldviews espousing distinct explanatory models of illness, our research aims at exploring factors leading to complementary and alternative medicine (CAM) use with special attention to their cultural context. Methods The results are based on medical anthropological fieldwork (participant observation and in-depth interviews) spanning a period from January 2015 to May 2017 at four clinics of Traditional Chinese Medicine in Budapest, Hungary. Participant observation involved 105 patients (males N = 42); in-depth interviews were conducted with patients (N = 9) and practitioners (N = 9). The interviews were coded with Interpretative Phenomenological Analysis; all information was aggregated employing Atlas.ti software. Results In order to avoid the dichotomization of “push and pull factors,” results obtained from the fieldwork and interviews were structured along milestones of the patient journey. These points of reference include orientation among sources of information, biomedical diagnosis, patient expectations and the physician-patient relationship, the biomedical treatment trajectory and reasons for non-adherence, philosophical congruence, and alternate routes of entry into the world of CAM. All discussed points which are a departure from the strictly western therapy, entail an underlying socio-cultural disposition and must be scrutinized in this context. Conclusions The influence of one’s culturally determined explanatory model is ubiquitous from the onset of the patient journey and exhibits a reciprocal relationship with subjective experience. Firsthand experience (or that of the Other) signifies the most reliable source of information in matters of illness and choice of therapy. Furthermore, the theme of (building and losing) trust is present throughout the patient journey, a determining factor in patient decision-making and dispositions toward both CAM and biomedicine

An epistemic network analysis of patient decision-making regarding choice of therapy

Patient decision-making concerning therapy choice has been thoroughly investigated in the Push/Pull framework: factors pushing the patient away from biomedicine and those pulling them towards Complementary and Alternative Medicine (CAM). Others have examined lay etiology as a potential factor in CAM use. We conducted semi-structured interviews with patients employing only biomedicine and those using CAM. The coded and segmented data was quantified and modelled using epistemic network analysis (ENA) to explore what effects push/pull factors and etiology had on the decision-making processes.There was a marked difference between our two subsamples concerning push factors: although both groups exhibited similar scaled relative code frequencies, the CAM network models were more interconnected, indicating that CAM users expressed dissatisfaction with a wider array of phenomena. Among pull factors, a preference for natural therapies accounted for differences between groups but did not retain a strong connection to rejecting conventional treatments. Etiology, particularly adherence to vitalism, was also a critical factor in both choice of therapy and rejection of biomedical treatments. Push factors had a crucial influence on decision-making, not as individual entities, but as a constellation of experienced phenomena. Belief in vitalism affects the patient’s explanatory model of illness, changing the interpretation of other etiological factors and illness itself. Scrutinizing individual push/pull factors or etiology does not explain therapeutic choices; it is from their interplay that decisions arise. Our unified, qualitative-andquantitative methodological approach offers novel insight into decision-making by displaying connections among codes within patient narratives.</p

The Mathematical Foundations of Epistemic Network Analysis

Epistemic network analysis (ENA) has been used in more than 300 published studies to date. However, there is no work in publication that describes the transformations that constitute ENA in formal mathematical terms. This paper provides such a description, focusing on the mathematical formulations that lead to two key affordances of ENA that are not present in other network analysis tools or multivariate analyses: (1) summary statistics that can be used to compare the differences in the content rather than the structure of networks and (2) network visualizations that provide information that is mathematically consistent with those statistics. Specifically, we describe the mathematical transformations by which ENA constructs matrix representations of discourse data, uses those representations to generate networks for units of analysis, places those networks into a metric space, identifies meaningful dimensions in the space, and positions the nodes of network graphs within that space so as to enable interpretation of those dimensions in terms of the content of the networks. We conclude with a discussion of how the mathematical formalisms of ENA can be used to model networks more generally