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To explore self-care and needs and preferences towards tailored self-care support of patients with rheumatoid arthritis at the outpatient clinic.
A sequential explanatory mixed method design.
The Self-Care of Chronic Illness Inventory questionnaire, two focus groups and six semi-structured interviews were conducted between November 2021 and April 2023. Questionnaires of 107 patients were descriptively analysed. Subsequently, 11 patients and 2 healthcare professionals participated in the focus groups and 6 patients in the interviews, which were thematically analysed.
Quantitative and qualitative data corresponded and showed that patients perform various self-care activities at an adequate level and have strategies to exert control and reduce symptoms. One key theme emerged: ‘Not only being the person with rheumatoid arthritis’ (RA) as patients primarily aim to get on with their lives. Nine subthemes covered self-care activities for maintaining health including staying physically active, finding the right medication and dose and adapting their diet. Patients differed in how they self-monitored their symptoms. Recognizing symptoms and finding strategies to manage symptoms included the process of body listening in which patient seek and try different strategies to find what works for them and incorporate routines. Patients experienced positive effects of a warm or cold environment. Patients felt the need for practical and emotional support from others and preferred having credible information.
Patients perform adequate self-care including a diversity of self-care activities to get on with their lives and have strategies to reduce and control the symptoms and impact of RA.
Tailoring self-care support to patients' individual needs and preferences is necessary to help patients cope with the erratic nature of the disease and maintain their quality of life. Healthcare providers need to provide practical and emotional support and use credible information to allow patients to make self-care decisions to manage their lives.
Quantitative finding are reported according to the STROBE guidelines and qualitative finding are reported according to the COREQ guidelines.
Patients perform various self-care activities at an adequate level and have strategies to exert control and reduce symptoms. Patients primarily aim to continue their lives and not being seen as the person with rheumatoid arthritis. Healthcare professionals need to provide practical and emotional support and use credible information to inform patients' self-care decision-making.
No patient or public contribution.
by Tjasa Kunavar, Xiaoxiao Cheng, David W. Franklin, Etienne Burdet, Jan Babič
Error based motor learning can be driven by both sensory prediction error and reward prediction error. Learning based on sensory prediction error is termed sensorimotor adaptation, while learning based on reward prediction error is termed reward learning. To investigate the characteristics and differences between sensorimotor adaptation and reward learning, we adapted a visuomotor paradigm where subjects performed arm movements while presented with either the sensory prediction error, signed end-point error, or binary reward. Before each trial, perturbation indicators in the form of visual cues were presented to inform the subjects of the presence and direction of the perturbation. To analyse the interconnection between sensorimotor adaptation and reward learning, we designed a computational model that distinguishes between the two prediction errors. Our results indicate that subjects adapted to novel perturbations irrespective of the type of prediction error they received during learning, and they converged towards the same movement patterns. Sensorimotor adaptations led to a pronounced aftereffect, while adaptation based on reward consequences produced smaller aftereffects suggesting that reward learning does not alter the internal model to the same degree as sensorimotor adaptation. Even though all subjects had learned to counteract two different perturbations separately, only those who relied on explicit learning using reward prediction error could timely adapt to the randomly changing perturbation. The results from the computational model suggest that sensorimotor and reward learning operate through distinct adaptation processes and that only sensorimotor adaptation changes the internal model, whereas reward learning employs explicit strategies that do not result in aftereffects. Additionally, we demonstrate that when humans learn motor tasks, they utilize both learning processes to successfully adapt to the new environments.
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