Objectives: Determine whether there are different longitudinal patterns of treatment burden in people living with multiple chronic conditions (MCC) and, if so, explore predictors that might reveal potential routes of intervention.
Methods: We analyzed data from a prospective mailed survey study of 396 adults living with MCC in southeastern Minnesota, USA. Participants completed a measure of treatment burden, the Patient Experience with Treatment and Self-management (PETS), and valid measures of health-related and psycho-social concepts at baseline, 6, 12, and 24 months. Latent class growth mixture modeling (LCGM) determined trajectories of treatment burden in two summary index scores of the PETS: Workload and Impact. Multivariable logistic regressions were used to identify independent predictors of the trajectories.
Results: LCGM supported a 2-class model for PETS Workload, including a group of consistently high workload (N = 69) and a group of consistently low workload (N = 311) over time. A 3-class model was supported for PETS Impact, including groups of consistently high impact (N = 62), consistently low impact (N = 278), and increasing impact (N = 51) over time. Logistic regression analyses showed that the following factors were associated with patterns of consistently high or increasing treatment burden over time: lower health literacy, lower self-efficacy, more interpersonal challenges with others, and worse subjective reports of physical and mental health (all p < .05).
Conclusions: Different longitudinal patterns of treatment burden exist among people with MCC. Raising health literacy, enhancing self-efficacy, and lessening the effects of negative social interactions might help reduce treatment burden.
Keywords: Burden of treatment; latent class growth model; multimorbidity; social determinants.
© The Author(s) 2022.