| Literature DB >> 21609461 |
Kah Hoong Chang1, Rachel Brodie, Mei Ann Choong, Karl J Sweeney, Michael J Kerin.
Abstract
BACKGROUND: We aimed to investigate the prevalence and predictors of Complementary and Alternative Medicine (CAM) use among cancer patients and non-cancer volunteers, and to assess the knowledge of and attitudes toward CAM use in oncology among health care professionals.Entities:
Mesh:
Year: 2011 PMID: 21609461 PMCID: PMC3123324 DOI: 10.1186/1471-2407-11-196
Source DB: PubMed Journal: BMC Cancer ISSN: 1471-2407 Impact factor: 4.430
Characteristics of patient participants
| Variables | Number of Participants | Number of CAM Users (%) | p value (χ2) |
|---|---|---|---|
| Total | 520 | 155 (29.8) | |
| Gender | <0.001 | ||
| Male | 186 | 29 (15.6) | |
| Female | 330 | 124 (37.6) | |
| Missing | 4 | 2 | |
| Age* | 52.5 ± 16.9 | 49.1 ± 15.5 | 0.004† |
| Ethnicity | 0.385 | ||
| Caucasian | 497 | 149 (30.0) | |
| Non-Caucasian | 4 | 2 | |
| Missing | 19 | 4 | |
| Educational background | <0.001 | ||
| Primary level | 97 | 11 (11.3) | |
| Secondary level | 255 | 74 (29.0) | |
| Tertiary level | 154 | 66 (42.9) | |
| Missing | 13 | 4 | |
| Annual household income | 0.001 | ||
| <€20 000 | 197 | 43 (21.8) | |
| €20 000 - €49 999 | 161 | 50 (31.1) | |
| €50 000 - €99 999 | 71 | 33 (46.5) | |
| >€100 000 | 12 | 5 (41.7) | |
| Missing | 79 | 24 | |
| Health insurance | 0.001 | ||
| None | 71 242 | 26 (36.6) 52 (21.5) | |
| Public Medical Card | |||
| Private Health Insurance | 200 | 76 (38.0%) | |
| Missing | 7 | 1 | |
| Religions | 0.001 | ||
| Christian | 486 | 138 (28.4) | |
| Non-Christian | 15 | 11 (73.3) | |
| Missing | 19 | 6 | |
| Subgroups | 0.369 | ||
| Non-cancer volunteers | 301 | 93 (30.9) | |
| Cancer patients | 219 | 62 ((28.3) | |
| Breast | 81 | 27 (33.3) | 0.667 |
| Colorectal | 23 | 4 | |
| Lymphoma | 17 | 6 | |
| Leukaemia | 13 | 3 | |
| Prostate | 12 | 3 | |
| Lung | 12 | 2 | |
| Ovarian | 12 | 5 | |
| Melanoma | 12 | 6 | |
| Head & Neck | 7 | 0 | |
| Oesophagus | 5 | 1 | |
| Kidney | 5 | 1 | |
| Brain | 4 | 1 | |
| Cervix | 3 | 1 | |
| Stomach | 3 | 0 | |
| Testicle | 2 | 0 | |
| Urinary bladder | 2 | 0 | |
| Non-melanoma skin | 2 | 1 | |
| Pancreatic | 1 | 1 | |
| Myeloma | 1 | 0 | |
| Missing | 2 | 0 | |
| HADS | |||
| High anxiety score (≥11) | 44 | 13 (29.5) | 0.350 |
| Low anxiety score (<11) | 333 | 112 (33.6) | |
| Missing | 143 | 30 | |
| High depression score (≥11) | 13 | 3 (23.1) | 0.328 |
| Low depression score (<11) | 386 | 128 (33.2) | |
| Missing | 121 | 24 | |
| Karnofsky score | 0.493 | ||
| 80 - 100 | 106 | 33 (31.1) | |
| 50 - 70 | 36 | 7 (19.4) | |
| 0 - 40 | 6 | 1 (16.7) | |
| Missing | 76 | 24 | |
* mean ± standard deviation
† student's t-test
Characteristics of health care professional participants
| Variables | Number of Participants | Number of CAM Users (%) | p value (χ2) |
|---|---|---|---|
| Total | 156 | 62 (39.7) | |
| Gender | 0.001 | ||
| Male | 38 | 7 (18.4) | |
| Female | 118 | 55 (46.6) | |
| Age* | 31.1 ± 7.3 | 33.3 ± 8.6 | 0.001† |
| Ethnicity | 0.211 | ||
| Caucasian | 136 | 56 (41.2) | |
| Non-Caucasian | 18 | 5 | |
| Missing | 1 | 1 | |
| Professions | 0.050 | ||
| Doctors | 59 | 17 (28.8) | |
| Nurses | 61 27 | 30 (49.2) | |
| Physiotherapists | 27 | 10 (37.0) | |
| Pharmacists | 5 | 4 (80.0) | |
| Occupational therapists | 2 | 0 | |
| S&L therapists | 2 | 1 | |
* mean ± standard deviation
† student's t-test
S&L therapists, speech and language therapists
Types of CAM used
| Types of CAM Used | Number of Users (%) |
|---|---|
| Natural supplements | 83 (53.9) |
| Vitamins | 78 (50.6) |
| Green tea | 62 (40.3) |
| Massage therapy | 51 (33.1) |
| Herbal remedies | 50 (30.5) |
| Acupuncture | 40 (26.1) |
| Yoga | 35 (22.7) |
| Homeopathy | 26 (16.9) |
| Chinese herbal medicine | 25 (16.2) |
| Chiropractic | 20 (13.0) |
| Meditation | 15 (9.7) |
| Energy healing | 14 (9.1) |
| Spiritual practice | 13 (8.5) |
| Music/art therapy | 12 (7.8) |
| Tai Chi | 10 (6.5) |
| Psychotherapy | 8 (5.2) |
| Hypnotherapy | 7 (4.5) |
| Biofeedback | 2 (1.3) |
| Others (Neuro Linguistic Programming) | 1 (0.6) |
Univariate and multivariate analyses of factors predictive of CAM use
| Univariate | Multivariate Binary Logistic Regression | |||
|---|---|---|---|---|
| Female gender | < 0.001 | 3.703 | 2.251-6.094 | < 0.001 |
| Younger age | 0.004 | - | NS | |
| Higher educational background | <0.001 | - | NS | |
| Higher annual household income | 0.001 | - | NS | |
| Private health insurance | 0.001 | 1.670 | 1.106-2.521 | 0.015 |
| Non-Christian | <0.001 | 10.587 | 3.000-37.359 | <0.001 |
NS, not significant.
Distribution of answers provided by health care professionals on evidence-based practices of CAM in cancer
| Numbers of Answers (%) | |||||
|---|---|---|---|---|---|
| There is evidence that acupuncture is effective in reducing first day vomiting after chemotherapy. | 128 (82.6) | 5 (3.2) | 2 (1.3) | ||
| There is evidence that Chinese herbs decrease side-effects in patients treated with chemotherapy. | 132 (85.7) | 8 (5.2) | 2 (1.3) | ||
| There is evidence to support recommending antioxidant vitamins such as α-tocopherol, beta-carotene or retinol to prevent lung cancer. | 0 | 12 (7.8) | 127 (82.5) | ||
| There is evidence to support the use of oral fish oil for the management of cancer cachexia. | 0 | 18 (11.7) | 126 (81.8) | ||
| There is evidence that ginger has a potential role as an antiemetic herbal remedy. | 109 (70.8) | 4 (2.6) | 2 (1.3) | ||
Bold fonts indicate the correct answers according to the best available evidence.