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© 2002 American Public Health Association
RESEARCH AND PRACTICE |
George T. Lewith is with the Complementary Medicine Research Unit, University of Southampton, Southampton, England. Michael E. Hyland is with the Department of Health Psychology, University of Plymouth, Plymouth, England. Stephen Shaw is with the Department of Statistics, University of Plymouth.
Correspondence: Requests for reprints should be sent to George T. Lewith, Complementary Medicine Research Unit, Mail Point OPH, Royal South Hants Hospital, Brintons Terrace, Off St. Mary’s Rd, Southampton SO14 0YG, England (e-mail: gl3{at}soton.ac.uk).
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INTRODUCTION |
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 TOP INTRODUCTION METHODSRESULTSDISCUSSIONReferences |
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Many patients seek help from practitioners of complementary and alternative medicine (CAM). Patients’ prior knowledge of CAM and desire for egalitarian relationships with medical practitioners have been shown to increase CAM use,1,2 as have higher scores on the Absorption scale (a measure of anxiety and "self-absorption").3 Other personality scales do not predict CAM use.4
Although users of CAM might not agree, a common view among scientists is that CAM outcomes are mediated through a placebo effect5,6; that is, patients improve because they expect to do so. Our aims in the study described here were to assess the validity of the Attitudes toward Alternative Medicine Scale (AAMS) and to determine whether asthmatic patients who had positive attitudes toward and beliefs about CAM showed greater positive changes in outcomes.
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METHODS |
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TOPINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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During 1996 through 1998, we conducted a randomized, double-blind, placebocontrolled trial among 327 patients allergic to house dust mites. The study, which took place in the counties of Hampshire and Dorset in England, was designed to evaluate the effects of a homeopathic dilution of this allergen.7 Patients completed the AAMS and the Positive and Negative Affect Scales (PANAS) on 2 occasions: 4 weeks before and 16 weeks after study randomization. Higher scores on the AAMS indicate more positive attitudes toward CAM.8,9 Higher scores on the 2 subscales of the PANAS indicate higher levels of the variable assessed (i.e., positive or negative affect).10
Spirometry and a measure of quality of life (the Asthma Bother Profile [ABP]11) were completed at baseline and at 6, 12, and 16 weeks. Patient diaries were completed on alternate weeks throughout the 20-week study; these diaries included information on diurnal peak expiratory flow, among other outcomes.7 Spirometry, peak expiratory flow, and ABP scores were the primary outcomes assessed.
The AAMS has received only limited validation, so we carried out a factor analysis. Correlations of baseline AAMS scores with all other baseline values were computed to determine whether personality factors or asthma severity determined attitudes toward CAM. To test whether beliefs or other baseline factors predicted outcomes, we calculated spirometry, ABP, and peak expiratory flow change scores (final scores minus baseline scores). Three multiple regression analyses were conducted with each of the 3 change variables in turn as the dependent variable; all baseline variables were considered independent.
Pearson correlations for the 2 AAMS scores (prerandomization and postrandomization) were calculated to examine AAMS score changes. Changes in AAMS scores were correlated with changes in peak expiratory flow, spirometry, and ABP scores. An analysis of variance compared baseline and posttreatment assessments, allowing evaluation of whether patients who believed that they had received active treatment improved more than those who believed that they had received a placebo.
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RESULTS |
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TOPINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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Results revealed significant improvements in forced expiratory volume in 1 second (FEV1; P = .006), predicted FEV1 (P = .007), and ABP scores (P = .016) but no improvements in peak expiratory flow. Table 1
shows the factor analysis of the AAMS. This analysis revealed that loadings from the first factor formed an unrotated principal axis; 12 of the 14 items had significant factor loadings (> .3). A screen test suggested a 2-factor solution (the first 5 eigenvalues were 4.2, 2.0, 1.2, 1.0, and 0.9). We obtained a good description of the data through use of a 2-factor solution with an oblimin rotation. The pattern matrix (Table 1) suggested that the correlated factors were attitudes toward CAM and a belief that the body varies in terms of "a healthy balance."
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The correlation between the prerandomization and postrandomization AAMS scores (i.e., test–retest reliability) was significant (r = 0.76, P < .001). There were no significant correlations between AAMS scores and any of the other baseline variables. Patients with more severe asthma at study entry experienced greater improvement over the course of the study (Table 2
). Those with more negative mood scores at study entry showed smaller improvements in ABP scores, and lower quality-of-life scores predicted greater improvements in scores. Variables predicting improvement in lung function and quality of life were themselves correlated; multiple regressions involving FEV1 (P < .001), predicted FEV1 (P < .001), ABP scores (P < .001), and peak expiratory flow (P < .001) confirmed that poorer lung function at study entry predicted significant improvement.
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AAMS scores did not correlate with significant changes in outcomes. The analyses of variance comparing outcomes among patients who believed that they were receiving active treatment and among those who believed that they were receiving a placebo were not significant in regard to any of the outcomes. There was no significant interaction with treatment.
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DISCUSSION |
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TOPINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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The test–retest reliability of the AAMS was acceptable, although 1 item had weak loadings on the first factor, and another item had very weak loadings on that factor. We found evidence of 2 correlated factors, indicating that attitudes toward CAM are hierarchically arranged, composed of positivity/negativity toward CAM practice as well as beliefs about the nature of health and how CAM operates.
There was no evidence that positive beliefs about CAM were associated with positive or negative affect, quality of life, or respiratory functioning. Owens et al. suggested that overall positive affect (as measured with the PANAS) is associated with greater CAM use.3 We cannot confirm this suggestion, but we employed a measure of attitude toward CAM use in a randomized study, whereas Owens et al. employed a measure of reported CAM use in clinical practice. We failed to find evidence that either belief that CAM was being received or variations in attitudes toward CAM predicted degree of patient improvement. In addition, we found no evidence that expectancy predicted ABP scores and no evidence of any overall changes in AAMS scores during the study.
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Acknowledgments |
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Support for this study was obtained from Smith’s Charity, the National Health Service Executive South and West Research and Development Directorate, and Boiron. G. T. Lewith was supported by a grant from the Maurice Laing Foundation.
Human Participant Protection
Ethical approval for this study was obtained from the Southampton local ethics committee (Hampshire) and from the Bournemouth ethics committee (Dorset).
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Footnotes |
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G. T. Lewith conceived, developed, and managed the study. M. E. Hyland provided advice at the protocol and analysis stages in respect to health psychology input, and S. Shaw provided statistical support and contributed to the data analysis.
Accepted for publication May 23, 2002.
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References |
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TOPINTRODUCTIONMETHODSRESULTSDISCUSSIONReferences |
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1. Vincent C, Furnham A. Complementary Medicine: A Research Perspective. New York, NY: John Wiley & Sons Inc; 1997:40–44.
2. Bhopal RS. The inter-relationship of folk, traditional and Western medicine with an Asian community in Britain. Soc Sci Med. 1986;22:99–105.
3. Owens JE, Taylor AG, Degood D. Complementary and alternative medicine and psychologic factors: toward an individual differences model of complementary and alternative medicine use and outcomes. J Altern Complementary Med. 1999;5:529–541.[Medline]
4. Mitzdorf U, Beck K, Horton-Hausknecht H, et al. Why do patients seek treatment in hospitals of complementary medicine? J Altern Complementary Med. 1999;5:463–473.[Medline]
5. Kirsch I. Changing Expectancies: A Key to Effective Psychotherapy. Pacific Grove, Calif: Brooks/Cole Publishers; 1990.
6. Kirsch I, ed. How Expectancies Shape Experience. Washington, DC: American Psychological Association; 1999.
7. Lewith GT, Watkins AD, Hyland ME, et al. Use of ultramolecular potencies of allergen to treat asthmatic people allergic to house dust mite: double blind randomised, controlled clinical trial. BMJ. 2002;324:520–523.
8. Finnigan MD. Complementary medicine: attitudes and expectations, a scale for evaluation. Complementary Med Res. 1991;5:79–82.
9. Finnigan MD. The Centre for the Study of Complementary Medicine: an attempt to understand its popularity through psychological, demographic and operational criteria. Complementary Med Res. 1991;5:83–87.
10. Watson D, Clark LA. Development and validation of brief measures of positive and negative affect: the PANAS scales. J Pers Soc Psychol. 1988;54:1063–1070.[Medline]
11. Hyland ME, Ley A, Fisher DW, Woodward V. Measurement of psychological distress in asthma: an asthma management programme. Br J Clin Psychol. 1995;34:601–611.
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