Background: The use of patient-reported outcomes to improve burn care increases. Little is known on burn patients’ views on what outcomes are most important, and about preferences regarding online Patient Reported Outcome Measures (PROMs). Therefore, this study assessed what outcomes matter most to patients, and gained insights into patient preferences towards the use of online PROMs. Methods: Adult patients (≥18 years old), 3–36 months after injury completed a survey measuring importance of outcomes, separately for three time periods: during admission, short-term (< 6 months) and long-term (6–24 months) after burn injury. Both open and closed-ended questions were used. Furthermore, preferences regarding the use of patient-reported outcome measures in burn care were queried. Results: A total of 140 patients were included (response rate: 27%). ‘Not having pain’ and ‘good wound healing’ were identified as very important outcomes. Also, ‘physical functioning at pre-injury level’, ‘being independent’ and ‘taking care of yourself’ were considered very important outcomes. The top-ten of most important outcomes largely overlapped in all three time periods. Most patients (84%) had no problems with online questionnaires, and many (67%) indicated that it should take up to 15 minutes. Patients’ opinions differed widely on the preferred frequency of follow-up. Conclusions: Not having pain and good wound healing were considered very important during the whole recovery of burns; in addition, physical functioning at pre-injury level, being independent, and taking care of yourself were deemed very important in the short and long-term. These outcomes are recommended to be used in burn care and research, although careful selection of outcomes remains crucial as patients prefer online questionnaires up to 15 minutes.
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Dynamic body feedback is used in dance movement therapy (DMT), with the aim to facilitate emotional expression and a change of emotional state through movement and dance for individuals with psychosocial or psychiatric complaints. It has been demonstrated that moving in a specific way can evoke and regulate related emotions. The current study aimed to investigate the effects of executing a unique set of kinetic movement elements on an individual mover’s experience of happiness. A specific sequence consisting of movement elements that recent studies have related to the feeling of happiness was created and used in a series of conditions. To achieve a more realistic reflection of DMT practice, the study incorporated the interpersonal dimension between the dance movement therapist (DMTh) and the client, and the impact of this interbodily feedback on the emotional state of the client. This quantitative study was conducted in a within-subject design. Five male and 20 female participants (mean age = 20.72) participated in three conditions: a solo executed movement sequence, a movement sequence executed with a DMTh who attuned and mirrored the movements, and a solo executed movement sequence not associated with feelings of happiness. Participants were only informed about the movements and not the feelings that may be provoked by these movements. The effects on individuals were measured using the Positive and Negative Affect Schedule and visual analog scales. Results showed that a specific movement sequence based on movement elements associated with happiness executed with a DMTh can significantly enhance the corresponding affective state. An additional finding of this study indicated that facilitating expressed emotion through movement elements that are not associated with happiness can enhance feelings such as empowerment, pride, and determination, which are experienced as part of positive affect. The results show the impact of specific fullbody movement elements on the emotional state and the support outcome of DMT on emotion regulation.
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Live programming is a style of development characterized by incremental change and immediate feedback. Instead of long edit-compile cycles, developers modify a running program by changing its source code, receiving immediate feedback as it instantly adapts in response. In this paper, we propose an approach to bridge the gap between running programs and textual domain-specific languages (DSLs). The first step of our approach consists of applying a novel model differencing algorithm, tmdiff, to the textual DSL code. By leveraging ordinary text differencing and origin tracking, tmdiff produces deltas defined in terms of the metamodel of a language. In the second step of our approach, the model deltas are applied at run time to update a running system, without having to restart it. Since the model deltas are derived from the static source code of the program, they are unaware of any run-time state maintained during model execution. We therefore propose a generic, dynamic patch architecture, rmpatch, which can be customized to cater for domain-specific state migration. We illustrate rmpatch in a case study of a live programming environment for a simple DSL implemented in Rascal for simultaneously defining and executing state machines.
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