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transcultural psychiatry March 2004 BRIEF REPORT

Knowledge Structures in Illness Narratives: Development and Reliability of a Coding Scheme LARA STERN & LAURENCE J. KIRMAYER McGill University Abstract Illness narratives reflect patients’ underlying illness schemas or models of illness as well as efforts to position themselves vis-à-vis a specific interlocutor and social context. Although the literature on illness narratives in medical anthropology has been dominated by the explanatory model perspective, people may use other types of knowledge structures to frame and construct their conceptions of symptoms. For this study, we developed operational definitions and a coding manual for three types of putative knowledge schemas: prototypes, chain complexes, and explanatory accounts. The operationalized definitions were then applied to coding a sample of illness narratives collected in a study of help-seeking in an urban community population. It was found that all three knowledge structures could be reliably identified in these narratives. This method of analysis provides a way to test hypotheses regarding the role of knowledge structures in illness narratives. Key words attribution, • discourse analysis • explanatory models • measures • symptom schemas

In recent years the notion of explanatory models has become a popular way to approach the analysis of illness narratives. Building on Kleinman’s earlier work (1980), Weiss (1997) developed the Explanatory Model Interview Catalog (EMIC), a flexible method of collecting, coding and analyzing illness narratives for the key features of explanatory models, Vol 41(1): 130–142 DOI: 10.1177/1363461504041358 Copyright © 2004 McGill University

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Stern & Kirmayer: Knowledge Structures in Illness Narratives

including notions of etiology, onset, pathophysiology, course, and treatment of illness. The EMIC has been applied to studies of a wide range of problems including depression, somatoform disorders, schizophrenia, and deliberate self-harm (Weiss, 1997, 2001). The explanatory model perspective assumes that patients habitually construct and can access such cause-and-effect models of their symptoms. However, the type of logical reasoning that guides such structures may not be the only mode of reasoning available to people. Based on his analysis of Ethiopian patients’ illness narratives, Young (1981, 1982) argued that people use multiple cognitive models to reason about illness. He suggested that the explanatory model perspective imposes a false coherence on complex narratives that may contain internal contradictions due to the different types of reasoning at play. If Young’s critique is correct, then an exclusive focus on explanatory models may ignore other forms of reasoning that shape patients’ conceptions of and responses to their illnesses including their coping, help-seeking, and treatment adherence (Edman & Kameoka, 1997; Kirmayer, Young, & Robbins, 1994). Young (1982) proposed three specific types of knowledge structures that may govern people’s accounts of their symptoms: (1) explanatory models, (2) prototypes, and (3) chain complexes. Explanatory models refer to symptoms or illness schemas organized in terms of cause-and-effect relationships, referring to ideas about etiology, pathophysiology, course and treatment. This type of representation parallels the structure of physicians’ biomedical knowledge. Prototypes involve salient past episodes or events, which serve as exemplars of a particular type of illness experience. The person reasons analogically from the prototype to his or her current instance of illness to understand its meaning and implications. Prototypes are based on images or events from one’s own past illness experience or that of someone with whom the individual identifies in some way, and can serve as models to anticipate future events and outcomes. However, they are not organized in terms of explicit causal process (Young, 1982). Based on the work of Vygotsky (Vygotsky, Cole, John-Steiner, Scribner, & Souberman, 1978; see also Wertsch, 1985), Young (1981) described a third type of knowledge structure, chain complexes, a form of ‘transductive’ reasoning which uses the meaningful linking together of salient events and sensations based on temporal contiguity. Chain complexes involve a sequence of events, drawn from memory, which led up to the current symptom or illness. In chain complexes, people reason about their symptoms in terms of this sequence but do not invoke a causal link. Young (1982) claimed that prototypes and chain complexes may be as prevalent as explanatory models in illness narratives. He stressed that the various knowledge structures are not mutually exclusive but commonly 131

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Transcultural Psychiatry 41(1)

co-exist and may be used to differing degrees by different people. Both the content of illness schemas and the use of specific knowledge structures may vary with cultural group and educational level (Edman & Kameoka, 1997). Use of different knowledge structures may also depend on the respondent’s relationship with the interlocutor and may serve to negotiate social contexts and position. Young’s formulation of patients’ illness narratives was based on theoretical considerations and the qualitative evaluation of a corpus of ethnographic material. Although much work in cognitive science makes his claims plausible, there has been no empirical test of his theory. The present study aimed to operationalize definitions and develop a coding scheme for explanatory models, prototypes and chain complexes, to see whether, using these definitions, all three types of knowledge structure could be identified and to test inter-rater reliability in identifying these structures in illness narratives collected from a community sample.

Method Sample This study examined illness narratives collected as part of a larger study by Kirmayer, Young, Galbaud du Fort, Weinfeld, and Lasry (1996) of helpseeking and healthcare utilization among immigrant groups in an urban multicultural milieu. A total of 120 ethnographic interviews were collected from samples of five ethnocultural groups. The analysis presented here used transcripts of ethnographic interviews of the seven Filipino respondents who had experienced medically undiagnosed symptoms in the previous year. The sample consists of four men and three women, all employed, with an average age of 31 years, who had arrived in Canada between 2 and 15 years earlier.

Procedure Structured telephone interviews administered to a random community sample of 2400 respondents obtained socio-demographic data and migration history and asked about psychological distress, somatic complaints, and medically unexplained symptoms. A subsample of 120 respondents was selected for ethnographic interviews on the basis of ethnicity and recent history of multiple somatic symptoms. All respondents gave implicit consent on the telephone and signed consent at the time of the meeting for the face-to-face ethnographic interview. Interviews lasted 1–3 hours and were held in the respondent’s home or an office in a community hospital. 132

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The discussion of symptoms in the ethnographic interviews was initiated by questions regarding the medically unexplained symptoms that the respondents had reported in the first two interviews. In addition, the interviewers asked about any other physical complaints mentioned in the subject’s previous interviews. The ethnographic interviews were conducted using protocols previously designed by Young and Kirmayer (1996) to elicit the three types of illness representations described above. On the assumption that once an explanatory model is evoked, people may tend to give accounts of their illness experience that conform to that model, the sequence of questions in the interview was designed to insulate chain complexes and prototypes from the structuring effect of discussions of explanatory models. Hence, subjects were questioned first about the sequence of events before the development of symptoms to elicit chain complexes. Next, to identify prototypes, they were asked whether they or anyone they knew of had ever experienced similar symptoms or problems. Finally, they were asked explicit questions about symptoms, diagnosis, etiology, risk factors, and treatment to elicit explanatory models. Interviews were tape-recorded and transcribed in accordance with standard conventions (Mishler, 1984). Transcripts of these interviews were analyzed in terms of the use, frequencies, and co-occurrences of the three types of knowledge structures. To this end, operational definitions and a coding manual for three knowledge structures, Chain Complexes, Prototypes and Explanatory Accounts, were developed through discussion between the authors. Initial attempts to code interviews revealed that the three categories were not sufficient because there was much text that discussed symptoms in terms of chain complexes but made explicit generalizations about the temporal pattern or sequence, implying that the symptom is always related to that particular chain of events in that same way. These accounts were felt to be intermediate between chain complexes and prototypes and were termed Generalized Chain Complexes. This fourth category was operationalized and added to the coding scheme, which then permitted for coding of all the narratives, leaving no new unclassifiable text. We also identified three subtypes of Explanatory Accounts based on whether they involved discussion of symptoms simply in terms of causal factors, discussion of the causal process as well, or use of a diagnostic label. We included these subcategories in our coding scheme. The final coding scheme included the following categories: 1.

Simple Chain Complex. Refers to a single example of events or occurrences presented as temporally contiguous with the development of the symptom. Description is experience-based and does not provide an explicit explanation for the occurrence of the symptom. 133

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2.

3.

4.

(e.g. ‘I took those pills, contraceptive pills, and then it starts I got that pain.’) Generalized Chain Complex. Extension of the concept of chain complexes to present a repeating pattern of factors seen as often or always temporally contiguous with the symptom. (This is a type of prototype as it refers to previous experiences. However, the text coded here is not coded as a Prototype unless there is an explicit mention of a specific previous experience.) (e.g. ‘Sometimes I have nose bleeding, so I feel – first of all I feel it’s too hot, sometimes in my back. Then after that I have nose bleeding. I don’t know what the problem is.’) Prototype. Description of the symptom in terms of a previous experience of something similar by the respondent or someone else. (e.g. ‘My nephew he always has nose bleeding too . . . we have the same thing . . . And my nephew is even worse . . .’) Explanatory Account. Explanation for the nature of the symptom or its occurrence. Some notion of causality is made explicit or clearly implied by discussion of causal factors or processes, diagnostic labels, or models regarding course or treatment. Explanatory accounts can be subdivided into the following subcategories (which may co-occur) according to the type of explanation offered: a. Causal factors. Specifying or implying a causal relationship between the factors described and the symptom, without reference to any specific process. (e.g. ‘Probably it’s the food that I eat sometimes or the drink that I drink that cause pain.’) b. Causal Process. Description of causal factors as well as causal process or mechanism. (e.g. ‘I went through a little burnout . . . because of my work before, there is a lot of pressure and sometimes it’s hard for me to get to sleep at night. And also I feel I’m very tired always.’) c. Nominal. Description of symptoms through the use of a specific diagnostic label which may imply the existence of an explanatory model. (e.g. ‘Way back home they told me that I have a peptic ulcer.’)

Transcripts of the seven narratives were coded according to this scheme using NuDist, a computer-based qualitative data analysis program (Richards & Richards, 1994). Within the narrative text, paragraphs or conversational turns (i.e. changes in speaker or topic) were used as the units of text for coding; these are the smallest differentiated units of text to be counted in the course of our coding. Given the variable length of paragraphs and conversational turns, however, this text unit only roughly 134

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reflects the actual amount of text. All text units referring to physical symptoms in any detail were coded for types of representation. Because use of the final coding scheme left no new unclassifiable text units, all the narratives were coded according to these expanded categories. After coding was completed, the NuDist software was used to analyze frequencies and co-occurrences of the different categories of knowledge structures. As well, inter-rater reliability of the coding scheme was assessed by comparing the coding of a random sample of text units by three separate raters using the coding manual. A coefficient of agreement (Cohen’s Kappa) was calculated for each pair of raters.

Results Characteristics of the seven respondents whose ethnographic interviews were analyzed for this article are presented in Table 1. They were all under 50 years of age and relatively new arrivals from the Philippines, most in Canada for less than 10 years. All were employed, working at least 40 hours per week and often at more than one job; their work was mostly physical labour. All respondents discussed multiple somatic symptoms in their narratives and all complained of a medically unexplained symptom within the past year. The degree to which the respondents’ symptoms were unexplained varied from accounts of medical doctors looking for but not finding explanations, ‘reassuring’ the patient that ‘it’s nothing,’ to actual explanations which the patient did not find satisfactory. There were several accounts of the latter where pain had been explained as muscular or anxiety-related and an answer was still being sought.

Coding of representations A total of 310 text units discussing somatic symptoms were identified in the transcripts for an average of 44.3 units per respondent. Table 2 shows the frequency with which the knowledge structures occurred within each respondent’s narrative. In general, 60% of these text-units contained Explanatory Accounts, 20% Prototypes, 20% Generalized Chain Complexes, and 12% Simple Chain Complexes. Some of the units were assigned simultaneously to several categories but this amounted to only 8.7% of the text units coded. The four major categories were well-represented in the majority of cases although only Generalized Chain Complexes and Explanatory Accounts appeared in all seven narratives. All respondents used at least two of the four categories of knowledge structures within their narratives and the majority made use of all four types. More than one type of knowledge 135

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Case #1

Case #2

Case #3

Case #4

Case #5

Case #6

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TABLE 1 Sociodemographic characteristics and somatic symptoms of sample Case #7

36

31

22

44

28

Gender

M

M

M

F

M

F

F

Education

undergraduate degree

some completed post-secondary elementary

completed high school

some some completed post-secondary post-secondary elementary

Occupation

skilled labour

handler

nursing aid

nanny

9

maintenance worker 5

factory worker

Years in Canada

machine operator 2

4

3

15

7

Medically unexplained symptoms

skin rashes

nose bleeding

back pain, abdominal pain, gas

frequent menses

shoulder problems

chest pain

chest pain

Other somatic symptoms

diarrhea, aches, back pain

arm/leg pain, abdominal pain, abdominal pain, arm/leg pain, abdominal pain, arm/leg pain, chest pain, gas, arm/leg pain, diarrhea, gas, gas, dizziness, arm/leg pain, chest pain, fatigue, aches, gas, dizziness, dizziness, fatigue, aches chest pain, diarrhea, gas, feeling hot, fatigue, weakness, weakness, fatigue, aches back pain, insomnia, insomnia, fatigue, aches headache aches, back back pain pain

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136

Age

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Prototype

Explanatory account

6 34 12 88 59 69 42 310

0 0 1 (8%) 19 (11%) 3 (5%) 8 (12%) 6 (14%) 37 (12%)

5 (83%) 7 (21%) 8 (67%) 7 (8%) 13 (22%) 5 (7%) 18 (43%) 63 (20%)

0 8 (24%) 0 41 (47%) 6 (10%) 2 (3%) 4 (10%) 61 (20%)

1 (17%) 24 (71%) 3 (25%) 32 (36%) 43 (73%) 61 (88%) 21 (50%) 185 (60%)

Type of explanatory account —————————————————– factors process nominal 1 0 3 21 1 3 13 42

0 20 0 0 42 51 5 118

0 14 0 11 2 19 5 51

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Simple chain complex

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Case 1 Case 2 Case 3 Case 4 Case 5 Case 6 Case 7 Total text units

Text units coded


TABLE 2 Frequencies of knowledge structures

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structure was often present in a subject’s discussion of a single symptom or problem. Explanatory Accounts were common but showed variation in the extent of their use by different respondents, both overall and for each subtype. Those who did speak in terms of Explanatory Accounts involving causal processes did so for many text units, perhaps due to the more elaborate nature of such explanations. As shown in Table 3, there was some overlap between the types of representations within the same text units. Explanatory Accounts cooccurred with each of the three other types. There was significant overlap between Prototypes and Explanatory Accounts, which occurred together in one-third of the units coded as Prototypes. There was also some overlap between Generalized Chain Complexes and Prototypes. Because the coding manual specified that all Generalized Chain Complexes are by definition Prototypes in that they draw on previous experience, we coded text units as Prototypes as well only if they explicitly mentioned a particular previous experience. Within the subcategories of Explanatory Accounts, nominal and causal process subtypes co-occurred relatively frequently while the other combinations happened only once each.

Reliability The inter-rater reliability of the coding scheme for knowledge structures was assessed using 45 passages from the interviews, taken out of context and coded independently by three separate raters using the coding manual. Cohen’s Kappa was calculated to assess agreement between each pair of raters while accounting for chance correlation (Kramer & Feinstein, 1981). The Kappa values were all acceptable, ranging from .61 to .79, indicating significant correlation between raters for the four main categories. When Kappas were calculated to include coding for the subcategories of Explanatory Accounts, they ranged from .64 to .68, indicating that reliability was still good.

Discussion This study demonstrates that it is possible to identify and reliably code multiple types of knowledge structures in illness narratives. The initial coding scheme using three categories was insufficient to code all relevant text units, but with the addition of one category intermediate between chain complex and prototype, termed ‘generalized chain complex,’ all of the units could be readily categorized. Generalized chain complexes tended to occur more frequently in text about common somatic symptoms, and may represent the process by which a chain complex becomes prototypical, 138

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Explanatory Account

0

0

6

0

0

6

0

63

5

3

3

0

0

0

5

61

22

0

7

16

6 0 0 6

3 3 0 0

22 0 7 16

185 42 118 51

42 42 1 1

118 1 118 26

51 1 26 51

Causal factors

Causal process

Nominal

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Prototype

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Generalized Chain Complex

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Simple Chain Complex Generalized Chain Complex Prototype Explanatory Account Causal factors Causal process Nominal

Simple Chain Complex


TABLE 3 Co-occurrence of knowledge structures

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i.e. generalized to the extent that it serves as a model for similar experiences, an idea alluded to by Young (1982). Consistent with Young’s (1982) claims, the study also documents diversity in the types of representations used by respondents to narrate their symptom and illness experiences. The results confirmed the wide prevalence of knowledge structures other than explanatory models in illness narratives about somatic symptoms. A major implication is that studies that simply elicit explanatory models may miss fundamental aspects of respondents’ illness experience that are encoded in terms of prototypes and chain complexes. Similarly, clinicians and researchers who seek to understand the underpinnings of patients’ illness behaviors must go beyond explanatory models to inquire about these other forms of knowledge (Groleau, 1998; Groleau & Kirmayer, in press; Kirmayer, Young, & Robbins, 1994; Sobo, 1995). The study raised several methodological issues. The text unit chosen for coding in the present study was the paragraph or conversational turn. Thus it was possible for one text unit to contain statements about several different symptoms, each of which involved different knowledge structures. However, examination of the actual text revealed that most instances of multiple coding within a text unit represented true co-occurrences of knowledge structures concerning the same symptom. Of course, the quality of the narratives collected limits the validity of subsequent analysis. Variations in how the interviewers applied the interview protocol undoubtedly influenced the types of narrative elicited. Future work should examine the effects of different types of interviews on the prevalence of specific knowledge structures, for example, comparing the EMIC (Weiss, 1997) with the interview developed for this study (Young & Kirmayer, 1996) and examining the effect of different types of questions in eliciting different representations. Although the absence of certain types of representations in respondents’ speech may reflect the ways in which they conceive of their symptoms, it may also represent choices they make regarding how to respond to a specific interlocutor and style of interviewing. Although the sample was small, it was sufficient to establish the feasibility of reliably coding narratives for underlying knowledge structures. Testing hypotheses about the relationships between ethnicity, symptom type and the prevalence of specific knowledge structures in illness narratives will require larger samples but this method provides a new way of testing such hypotheses. In future work, we plan to apply this method to explore how respondents attempt to explain medically unexplained symptoms.

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References Edman, J., & Kameoka, V. (1997). Cultural differences in illness schemas: An analysis of Filipino and American illness attributions. Journal of CrossCultural Psychology, 28(3), 252–265. Groleau, D. (1998). Déterminants culturels et l’approche écologique: le cas de la promotion de l’allaitement chez les immigrantes vietnamiennes. Unpublished Thèse de doctorat, Université de Montréal, Montréal. Groleau, D., & Kirmayer, L. J. (in press). Sociosomatic theory in Vietnamese immigrants’ narratives of distress. Anthropology & Medicine. Kirmayer, L. J., Young, A., Galbaud du Fort, G., Weinfeld, M., & Lasry, J.-C. (1996). Pathways and barriers to mental health care: A community survey and ethnographic study (Working Paper No. 6). Montreal: Culture & Mental Health Research Unit, Institute of Community & Family Psychiatry, Sir Mortimer B. Davis–Jewish General Hospital. Kirmayer, L. J., Young, A., & Robbins, J. (1994). Symptom attribution in cultural perspective. Canadian Journal of Psychiatry, 39, 584–595. Kleinman, A. (1980). Patients and healers in the context of culture: An exploration of the borderland between anthropology, medicine, and psychiatry. Berkeley: University of California Press. Kramer, M. S., & Feinstein, A. R. (1981). The biostatistics of concordance. Clinical Pharmacology and Therapeutics, 29, 111–129. Mishler, E. G. (1984). The discourse of medicine. Norwood, NJ: Ablex. Richards, L., & Richards, T. (1994). From filing cabinet to computer. In A. Bryman & R. G. Burgess (Eds.), Analyzing qualitative data (pp. 146–173). New York: Routledge. Sobo, E. (1995). Choosing unsafe sex: AIDS-risk denial among disadvantaged women. Philadelphia: University of Pennsylvania Press. Vygotsky, L. S., Cole, M., John-Steiner, V., Scribner, S., & Souberman, E. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press. Weiss, M. (1997). Explanatory Model Interview Catalogue (EMIC): Framework for comparative study of illness. Transcultural Psychiatry, 34, 235–263. Weiss, M. G. (2001). Cultural epidemiology: An introduction and overview. Anthropology and Medicine, 8(1), 5–30. Wertsch, J. V. (1985). Vygotsky and the social formation of the mind. Cambridge, MA: Harvard University Press. Young, A. (1981). When rational men fall sick: An inquiry into some assumptions made by medical anthropologists. Culture, Medicine, and Psychiatry, 5, 317–335. Young, A. (1982). Rational men and the explanatory model approach. Culture, Medicine, and Psychiatry, 6, 57–71. Young, A., & Kirmayer, L. J. (1996). Illness narrative interview protocols. Culture & Mental Health Research Unit, Department of Psychiatry, Sir Mortimer B. Davis–Jewish General Hospital, Montréal.

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Transcultural Psychiatry 41(1) LARA STERN, MD, completed her Psychiatry Residency at McGill University and is undertaking post-residency training in Autism and Developmental Disorders at the Montreal Children’s Hospital. Her research and clinical interests are in the fields of Cultural Psychiatry and Child Psychiatry. She is involved in research on cultural consultation, illness narratives, and autistic spectrum disorders and is Editorial Assistant of Transcultural Psychiatry. Address: Department of Psychiatry, Montréal Children’s Hospital, 4018 Ste. Catherine West, Montréal, Quebec H3Z 1P2, Canada. [E-mail: [email protected]] LAURENCE J. KIRMAYER, MD is James McGill Professor and Director, Division of Social and Transcultural Psychiatry, Department of Psychiatry, McGill University and Editor-in-Chief of Transcultural Psychiatry. He directs the Culture & Mental Health Research Unit at the Department of Psychiatry, Sir Mortimer B. Davis–Jewish General Hospital in Montreal where he conducts research on the mental health of Canadian Aboriginal peoples, mental health services for immigrants and refugees, consultation–liaison psychiatry, and the anthropology of psychiatry. He founded and directs the annual Summer Program and Advanced Study Institute in Social and Cultural Psychiatry at McGill and is Co-Director of the National Network for Aboriginal Mental Health Research funded by the Canadian Institutes for Health Research. Address: McGill University, 1033 Pine Avenue West, Montréal, Québec H3A 1A1, Canada. [E-mail: [email protected]]

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