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Mapping patterns of complementary and alternative medicine use in cancer: an explorative cross-sectional study of individuals with reported positive "exceptional" experiences.

Hök J, Tishelman C, Ploner A, Forss A, Falkenberg T - BMC Complement Altern Med (2008)

Bottom Line: However, a significant number of CAM therapies were not consistent with this categorization (n = 50); consequently, we introduced two additional categories: Spiritual/health literature and Treatment centers.We found considerable heterogeneity in patterns of CAM use.Beyond variations in users' reports of CAM, our findings indicate some patterns in CAM usage related to number of therapies used and preference for different CAM categories.

View Article: PubMed Central - HTML - PubMed

Affiliation: Karolinska Institutet, Dept of Neurobiology, Care Sciences and Society, Division of Nursing, Unit for Studies of Integrative Care, 23 300, SE-141 83 Huddinge, Sweden. johanna.hok@ki.se

ABSTRACT

Background: While the use of complementary and alternative medicine (CAM) among cancer patients is common and widespread, levels of commitment to CAM vary. "Committed" CAM use is important to investigate, as it may be associated with elevated risks and benefits, and may affect use of biomedically-oriented health care (BHC). Multiple methodological approaches were used to explore and map patterns of CAM use among individuals postulated to be committed users, voluntarily reporting exceptional experiences associated with CAM use after cancer diagnosis.

Method: The verbatim transcripts of thirty-eight unstructured interviews were analyzed in two steps. First, manifest content analysis was used to elucidate and map participants' use of CAM, based on the National Center for Complementary Medicine (NCCAM)'s classification system. Second, patterns of CAM use were explored statistically using principal component analysis.

Findings: The 38 participants reported using a total of 274 specific CAM (median = 4) consisting of 148 different therapeutic modalities. Most reported therapies could be categorized using the NCCAM taxonomy (n = 224). However, a significant number of CAM therapies were not consistent with this categorization (n = 50); consequently, we introduced two additional categories: Spiritual/health literature and Treatment centers. The two factors explaining the largest proportion of variation in CAM usage patterns were a) number of CAM modalities used and b) a category preference for Energy therapies over the categories Alternative Medical Systems and Treatment centers or vice versa.

Discussion: We found considerable heterogeneity in patterns of CAM use. By analyzing users' own descriptions of CAM in relation to the most commonly used predefined professional taxonomy, this study highlights discrepancies between user and professional conceptualizations of CAM not previously addressed. Beyond variations in users' reports of CAM, our findings indicate some patterns in CAM usage related to number of therapies used and preference for different CAM categories.

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Related in: MedlinePlus

Scree plot showing the proportion of variance explained by consecutive principal components (PCs). Bootstrapped 95% confidence intervals are shown as vertical lines. The dotted horizontal reference line indicates the proportion of variance explained by one of the underlying variables (i.e. category counts).
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Figure 1: Scree plot showing the proportion of variance explained by consecutive principal components (PCs). Bootstrapped 95% confidence intervals are shown as vertical lines. The dotted horizontal reference line indicates the proportion of variance explained by one of the underlying variables (i.e. category counts).

Mentions: In the explorative PC analysis we found that PC1 to PC3 accounted for 42%, 22% and 14%, respectively, of the underlying data. We interpreted the curve of percentages as steep between PC1 and PC2, and as flattening out after PC2 (as shown in Figure 1). This motivated retaining PC1 and PC2 [18], which together explained over 63% of the variability of the scaled usage counts.


Mapping patterns of complementary and alternative medicine use in cancer: an explorative cross-sectional study of individuals with reported positive "exceptional" experiences.

Hök J, Tishelman C, Ploner A, Forss A, Falkenberg T - BMC Complement Altern Med (2008)

Scree plot showing the proportion of variance explained by consecutive principal components (PCs). Bootstrapped 95% confidence intervals are shown as vertical lines. The dotted horizontal reference line indicates the proportion of variance explained by one of the underlying variables (i.e. category counts).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2538498&req=5

Figure 1: Scree plot showing the proportion of variance explained by consecutive principal components (PCs). Bootstrapped 95% confidence intervals are shown as vertical lines. The dotted horizontal reference line indicates the proportion of variance explained by one of the underlying variables (i.e. category counts).
Mentions: In the explorative PC analysis we found that PC1 to PC3 accounted for 42%, 22% and 14%, respectively, of the underlying data. We interpreted the curve of percentages as steep between PC1 and PC2, and as flattening out after PC2 (as shown in Figure 1). This motivated retaining PC1 and PC2 [18], which together explained over 63% of the variability of the scaled usage counts.

Bottom Line: However, a significant number of CAM therapies were not consistent with this categorization (n = 50); consequently, we introduced two additional categories: Spiritual/health literature and Treatment centers.We found considerable heterogeneity in patterns of CAM use.Beyond variations in users' reports of CAM, our findings indicate some patterns in CAM usage related to number of therapies used and preference for different CAM categories.

View Article: PubMed Central - HTML - PubMed

Affiliation: Karolinska Institutet, Dept of Neurobiology, Care Sciences and Society, Division of Nursing, Unit for Studies of Integrative Care, 23 300, SE-141 83 Huddinge, Sweden. johanna.hok@ki.se

ABSTRACT

Background: While the use of complementary and alternative medicine (CAM) among cancer patients is common and widespread, levels of commitment to CAM vary. "Committed" CAM use is important to investigate, as it may be associated with elevated risks and benefits, and may affect use of biomedically-oriented health care (BHC). Multiple methodological approaches were used to explore and map patterns of CAM use among individuals postulated to be committed users, voluntarily reporting exceptional experiences associated with CAM use after cancer diagnosis.

Method: The verbatim transcripts of thirty-eight unstructured interviews were analyzed in two steps. First, manifest content analysis was used to elucidate and map participants' use of CAM, based on the National Center for Complementary Medicine (NCCAM)'s classification system. Second, patterns of CAM use were explored statistically using principal component analysis.

Findings: The 38 participants reported using a total of 274 specific CAM (median = 4) consisting of 148 different therapeutic modalities. Most reported therapies could be categorized using the NCCAM taxonomy (n = 224). However, a significant number of CAM therapies were not consistent with this categorization (n = 50); consequently, we introduced two additional categories: Spiritual/health literature and Treatment centers. The two factors explaining the largest proportion of variation in CAM usage patterns were a) number of CAM modalities used and b) a category preference for Energy therapies over the categories Alternative Medical Systems and Treatment centers or vice versa.

Discussion: We found considerable heterogeneity in patterns of CAM use. By analyzing users' own descriptions of CAM in relation to the most commonly used predefined professional taxonomy, this study highlights discrepancies between user and professional conceptualizations of CAM not previously addressed. Beyond variations in users' reports of CAM, our findings indicate some patterns in CAM usage related to number of therapies used and preference for different CAM categories.

Show MeSH
Related in: MedlinePlus