This pilot clinical trial studies how well psychoeducational and behavioral strategies work in reducing distress and anxiety in patients with multiple myeloma and their family caregivers. Education and walking programs, may be able to reduce distress and anxiety and improve the well-being and quality of life of patients with multiple myeloma and their family caregivers. Understanding how different forms of education and support can promote emotional wellness may help nurse researchers find ways to improve services provided to patients and family members during cancer treatment.
PRIMARY OBJECTIVES: I. Evaluate the effect of the intervention, as compared to the control group, on emotional distress, the primary outcome, measured as anxiety in patients with multiple myeloma and their caregivers at the transition. II. Evaluate the effect, including the effect size, of the intervention, as compared to the control group, on activation for self-management, fatigue, depression, and health-related quality of life (HRQOL) in both patients and caregivers. III. Assess the feasibility, acceptability, and content integrity of the intervention in patients with multiple myeloma and their family caregivers. OUTLINE: Participants are randomized to 1 of 2 arms. ARM I: Participants meet with a nurse in-person for approximately 30 minutes to receive information about strategies for cognitive self-management of distress and an individualized walking prescription to gradually increase their walking to 30 minutes per day, 5 times per week. Participants wear a pedometer for at least 3 consecutive days during weeks 1, 6, and 12. Participants are also contacted by the nurse via telephone at 1 and 3 weeks for supplemental counseling support. ARM II: Participants meet with a nurse in-person for approximately 20 minutes to receive National Cancer Institute (NCI) educational booklets and a link to the American Cancer Society (ACS) website. Participants are also contacted by the nurse via telephone at 1 and 3 weeks but the calls are primarily social in nature and do not include counseling support.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
SUPPORTIVE_CARE
Masking
NONE
Enrollment
30
Receive information about strategies for cognitive self-management of distress
Receive individualized walking prescription and wear pedometer
Receive supplemental counseling support over the phone
Receive NCI educational booklets and a link to the ACS website
Receive calls that are primarily social in nature
Ancillary studies
Ancillary studies
Case Comprehensive Cancer Center
Cleveland, Ohio, United States
Change in emotional distress in patients measured as anxiety using the Patient-Reported Outcomes Measurement Information System (PROMIS)
A linear mixed model will be used and the model parameters will be estimated by the method of restricted maximum likelihood.
Time frame: Baseline to up to 12 weeks
Change in activation for self-management in patients using the Patient Activation Measure (PAM)
A linear mixed model will be used. If there are large numbers of missing values, the parameters will be estimated by utilizing the "pattern mixture model." Should the change be non-linear, the model may be extended to allow for non-linearity. In the case of parametric model assumption violation, the generalized estimating equation approach may be used.
Time frame: Baseline to up to 12 weeks
Change in activation for self-management in caregivers using the PAM
A linear mixed model will be used. If there are large numbers of missing values, the parameters will be estimated by utilizing the "pattern mixture model." Should the change be non-linear, the model may be extended to allow for non-linearity. In the case of parametric model assumption violation, the generalized estimating equation approach may be used.
Time frame: Baseline to up to 12 weeks
Change in fatigue in patients using the PROMIS
A linear mixed model will be used. If there are large numbers of missing values, the parameters will be estimated by utilizing the "pattern mixture model." Should the change be non-linear, the model may be extended to allow for non-linearity. In the case of parametric model assumption violation, the generalized estimating equation approach may be used.
Time frame: Baseline to up to 12 weeks
Change in fatigue in caregivers using the PROMIS
A linear mixed model will be used. If there are large numbers of missing values, the parameters will be estimated by utilizing the "pattern mixture model." Should the change be non-linear, the model may be extended to allow for non-linearity. In the case of parametric model assumption violation, the generalized estimating equation approach may be used.
Time frame: Baseline to up to 12 weeks
Change in depression in patients using the PROMIS
A linear mixed model will be used. If there are large numbers of missing values, the parameters will be estimated by utilizing the "pattern mixture model." Should the change be non-linear, the model may be extended to allow for non-linearity. In the case of parametric model assumption violation, the generalized estimating equation approach may be used.
Time frame: Baseline to up to 12 weeks
Change in depression in caregivers using the PROMIS
A linear mixed model will be used. If there are large numbers of missing values, the parameters will be estimated by utilizing the "pattern mixture model." Should the change be non-linear, the model may be extended to allow for non-linearity. In the case of parametric model assumption violation, the generalized estimating equation approach may be used.
Time frame: Baseline to up to 12 weeks
Change in HRQOL in patients using the PROMIS short form, Global Health
A linear mixed model will be used. If there are large numbers of missing values, the parameters will be estimated by utilizing the "pattern mixture model." Should the change be non-linear, the model may be extended to allow for non-linearity. In the case of parametric model assumption violation, the generalized estimating equation approach may be used.
Time frame: Baseline to up to 12 weeks
Change in HRQOL in caregivers using the PROMIS short form, Global Health
A linear mixed model will be used. If there are large numbers of missing values, the parameters will be estimated by utilizing the "pattern mixture model." Should the change be non-linear, the model may be extended to allow for non-linearity. In the case of parametric model assumption violation, the generalized estimating equation approach may be used.
Time frame: Baseline to up to 12 weeks
Feasibility of the intervention, assessed via attrition rates
Time frame: Up to 12 weeks
Acceptability of the intervention, assessed via consent rates
Time frame: Up to 12 weeks
Satisfaction with the intervention assessed using an exit interview survey
Time frame: At 12 weeks
Integrity of the intervention, assessed through fidelity monitoring
Time frame: Up to 12 weeks
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.