Introduction Although supported self-management has been defined theoretically at end of life (Johnston et al., 2014), and has empirically been demonstrated to be beneficial within long-term condition management, it is not known how it plays out in the realities of end of life care.
Aim To use empirical data to describe supportive self-management within end of life in relation to the specific context of analgesia and related treatments
Methods A qualitative approach was taken using semi-structured focus groups and interviews with healthcare professionals and patients/carers. The data were coded in NVivo 11 utilising Framework Analysis.
Results The sample comprised 38 participants recruited via two geographical regions in Northern and Southern England. The patient/carer and healthcare professional samples had 19 participants each.
Supportive self-management was enacted on a far-reaching continuum from:
Expertise and mastery, with full responsibility chosen by the individual, and acceptance of the possibility of risk and the requirements of complex decision-making, through to
Reduced capabilities and engagement in self-management behaviours, negatively affected by uncontrolled pain, the side-effects of opioids, clinical depression and memory loss, with responsibilities transferred to another (the carer and/or palliative care clinical nurse specialist)
Conclusion Supported self-management of analgesia and related treatments at end of life was an ever-changing process affected by the complexity of end of life itself and opioid related fears. The complexity of end of life with continual disease progression, frequent changes in symptoms and side-effects, resulted in fluctuating self-management capabilities of the patient, and in turn fluctuating supportive behaviours of the carer.
This work was part of a larger study (SMART) funded by the NIHR’s HTA programme.
Johnston B, Rogerson L, Macijauskiene J, Blazeviciene A, Cholewka P.An exploration of self-management support in the context of palliative nursing: a modified concept analysis. BMC Nurs 2014;13:21
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