Telehealth Self-Management Coaching Sessions to Improve Quality of Life in Pancreatic Cancer Survivors and Their Family Care Givers

Patient reported quality of life will be assessed by the Functional Assessment of Cancer Therapy- Hepatobiliary (FACT-Hep) quality of life score. The primary analysis will be a treatment group comparison of the QOL at 3 months via linear regression model, with adjustment for baseline FACT-Hep score and stratification factors. Robust standard errors will be estimated via generalized estimating equations to adjust for correlation between repeated outcome measures. The dependent variables will be transformed to approximate normality as appropriate.

Feasibility of the intervention will be defined as at least 60% of eligible participants enrolling. Descriptive statistics will be used to summarize the feasibility of the intervention. Reasons for non-participation will be recorded and used to make needed modifications for improvement in future studies.

Feasibility of the intervention will be defined as at least 60% of participants completing ≥ 80% of the intervention (4 of 6 sessions). Descriptive statistics will be used to summarize the feasibility of the intervention. Reasons for attrition will be recorded and used to make needed modifications for improvement in future studies.

Feasibility of the intervention will be defined as at least 60% of participants completing any follow-up assessments after randomization. Descriptive statistics will be used to summarize the feasibility of the intervention. Reasons for attrition will be recorded and used to make needed modifications for improvement in future studies.

Participant experiences with the intervention will be explored through qualitative data (structured exit interviews) from participants randomized to the intervention group and analyzed using content analysis approach. Interviews will be transcribed and data analyzed. Transcripts will be imported for the development of analytic categories, data coding, and review of coded data. Codes will be sorted into themes based on links and relationship.

Treatment group comparisons will be assessed via repeated measures linear regression models with adjustment for baseline value of the outcome including sex and age and stratification factors. Robust standard errors will be estimated via generalized estimating equations to adjust for correlation between repeated outcome measures. The dependent variables will be transformed to approximate normality as appropriate.

Patient reported psychological distress will be measured using the National Comprehensive Cancer Network (NCCN) Distress Thermometer (DT). Treatment group comparisons will be assessed via repeated measures linear regression models with adjustment for baseline value of the outcome including sex and age and stratification factors. Robust standard errors will be estimated via generalized estimating equations to adjust for correlation between repeated outcome measures. The dependent variables will be transformed to approximate normality as appropriate.

FCG reported psychological distress will be measured using the NCCN DT. Treatment group comparisons will be assessed via repeated measures linear regression models with adjustment for baseline value of the outcome including sex and age and stratification factors. Robust standard errors will be estimated via generalized estimating equations to adjust for correlation between repeated outcome measures. The dependent variables will be transformed to approximate normality as appropriate.

FCG caregiving burden will be measured using the Montgomery Borgatta Caregiver Burden Scale. Treatment group comparisons will be assessed via repeated measures linear regression models with adjustment for baseline value of the outcome including sex and age and stratification factors. Robust standard errors will be estimated via generalized estimating equations to adjust for correlation between repeated outcome measures. The dependent variables will be transformed to approximate normality as appropriate.

FCG QOL will be measured using City of Hope Quality of Life-Family questionnaire. Treatment group comparisons will be assessed via repeated measures linear regression models with adjustment for baseline value of the outcome including sex and age and stratification factors. Robust standard errors will be estimated via generalized estimating equations to adjust for correlation between repeated outcome measures. The dependent variables will be transformed to approximate normality as appropriate.