Patient activation, self-efficacy and usage of complementary and alternative medicine in cancer patients.
Jutta HübnerSaskia WelterGianluca CiarloLukas KäsmannEmadaldin AhmadiChristian KeinkiPublished in: Medical oncology (Northwood, London, England) (2022)
Complementary and alternative medicine (CAM) is used by many cancer patients by themselves. Therefore, we conducted a survey regarding the association between CAM, self-efficacy, and patient activation in adult cancer patients. A standardized questionnaire, consisted of the ASKU, the PAM 13-D, and a structured questionnaire on CAM usage from our own working group, was distributed to 880 potential participants. Six hundred and thirty-nine (639) patients (male 32.9%, female 63.2%; gynecological cancer 41%, gastrointestinal 19.2%, urogenital 15.6%) took part. 60% of all patients used CAM in the last 3 months (biological 73%, holistic 63%, mind-body methods 62%). Higher self-efficacy was associated with higher interest in CAM (p = 0.03), but not usage of CAM, compared to patients with lower self-efficacy (p = 0.099). Higher patient activation was associated with higher interest in CAM (p = 0.004) and usage of CAM (p = 0.012). Patients with higher activation significantly more often used homeopathy (p = 0.007), prayer (p = 0.002), yoga, etc. (p = 0.032), meditation (p = 0.002), low carb or ketogenic diets (p < 0.001) (but not vegan or other cancer diets). Higher patient activation is associated with higher usage of CAM. Focusing on patient activation as a goal in patient-physician relationship will help patients to adhere to a healthy lifestyle and to actively participate in the whole treatment process.
Keyphrases
- end stage renal disease
- case report
- ejection fraction
- newly diagnosed
- chronic kidney disease
- peritoneal dialysis
- emergency department
- cardiovascular disease
- primary care
- squamous cell carcinoma
- metabolic syndrome
- patient reported outcomes
- risk assessment
- patient reported
- squamous cell
- combination therapy
- childhood cancer
- neural network