The psychometric properties of the Norwegian version of FSS were satisfactory. To avoid over-diagnosing people for high level of fatigue, the threshold for high fatigue probably should be 5 on the FSS scale instead of 4 as had been suggested originally, but further validation of the cut-off point is needed.

Person-centredness as a concept is becoming more prominent and increasingly central within some research literature, approaches to practice and as a guiding principle within some health and social care policy. Despite the increasing body of literature into person-centred nursing (PCN), there continues to be a 'siloed' approach to its study, with few studies integrating perspectives from across nursing specialties. The purpose of this paper is to present the results of a study undertaken to explore if the secondary analysis of findings from four different and unrelated research studies (that did not have the main aim of researching person-centredness) could inform our understanding of person-centred nursing. A qualitative meta-synthesis was undertaken of the data derived from the four unrelated research studies undertaken with different client groups with long-term health conditions. A hermeneutic and interpretative approach was used to guide the analysis of data and framed within a particular person-centred nursing framework. Findings suggest 'professional competence' (where competence is understood more broadly than technical competence) and knowing 'self' are important prerequisites for person-centred nursing. Characteristics of the care environment were also found to be critical. Despite the existence of expressed person-centred values, care processes largely remained routinised, ritualistic and affording few opportunities for the formation of meaningful relationships. Person-centred nursing needs to be understood in a broader context than the immediate nurse-patient/family relationship. The person-centred nursing framework has utility in helping to understand the dynamics of the components of person-centredness and overcoming the siloed nature of many current perspectives.

These findings suggest that chronic pain is a significant problem in the general Norwegian population, and that gender, education, being frequently ill, or having a chronic illness are important variables in predicting pain group membership.

Although fatigue is a common complaint after stroke, relatively little is known about how poststroke fatigue is experienced and what its related factors are. An in-depth understanding is necessary to develop effective and patient-centered poststroke rehabilitation programs. This review was undertaken to provide a comprehensive synthesis of knowledge from the literature concerning the description, definition, and measurement of fatigue and its relationship to sociodemographic and clinical factors. A search in PubMed, CINAHL, EMBASE, and PsychInfo was performed using "stroke" or "cerebrovascular accident" as medical subject headings in combination with "fatigue" as a key word. Descriptions of fatigue revealed multiple dimensions of the phenomenon. Although no specific theoretical definition of fatigue as a poststroke condition was found, a case definition has recently been published to be used as a tool to determine the presence of fatigue in poststroke patients. Poststroke fatigue is most frequently measured by using the general fatigue scales such as the Fatigue Severity Scale and a Fatigue Visual Analogue Scale, as there is no scale developed to measure poststroke fatigue specifically. Age, sex, living conditions, and personality were associated with poststroke fatigue, albeit with some conflicting findings. Conflicting results also were found in the relationships between fatigue and stroke-related characteristics such as stroke location/type, the number of strokes, and neurological deficits. There is an indication that prestroke and poststroke fatigue are related. Possible antecedent components identified are personal factors, biomarkers, stroke characteristics, prestroke fatigue, and comorbidity. As knowledge regarding poststroke fatigue remains limited, there is a need to continue empirical research with various theoretical orientations.

Pre-stroke fatigue and fatigue during the acute phase needs to be assessed in relation to physical functioning and depression during recovery and the rehabilitation process.

We sought to identify clinical characteristics and socio-demographic variables associated with longitudinal patterns of fatigue in MS patients.A questionnaire including the Fatigue Severity Scale (FSS) was mailed to a community sample of 502 MS patients three times one year apart. Three patterns of fatigue were defined: persistent fatigue (PF) (mean FSS-score ≥5 at all time-points), sporadic fatigue (SF) (mean FSS-score ≥5 at one or two time-points) and no fatigue (mean FSS-score <5 at all time-points).Among the 267 (53%) patients who responded at all time points, 101 (38%, 95%CI 32-44) had persistent, 98 (37%, 95CI 31-43) sporadic and 68 (25%, 95%CI 20-31) no fatigue. Persistent and sporadic fatigue were more common in patients with, increased neurological impairment (p<0.001), primary progressive MS (p=0.01), insomnia (p<0.001), heat sensitivity (p<0.001), sudden-onset fatigue (p<0.001) or mood disturbance (p<0.001) compared to patients without fatigue. Multivariable analysis showed that depression (PF p=0.02, SF p<0.001), heat sensitivity (PF p=0.04, SF p=0.02), and physical impairment (PF p=0.004, SF p=0.01) were associated with both sporadic and persistent fatigue.

The main aim of the present study was to derive norms or reference values from the general Norwegian population for the Norwegian version of the Quality of Life Scale (QOLS-N). In addition, associations between socio-demographic and health variables on the level of quality of life were examined. The sample consisted of 1893 subjects from a total of 4000 randomly selected Norwegian citizens representative of the entire Norwegian population, aged 19-81. The subjects received a mailed questionnaire containing the QOLS-N. Results show that the mean quality of life score was 84.1 (SD 12.5). Women reported a higher quality of life than men. People with higher levels of education reported a higher quality of life. Those who were married or cohabitating reported the highest quality of life and those who were unemployed reported a lower quality of life than those who worked. In addition, people reporting long-term diseases or health problems scored significantly lower on quality of life. These results could serve as reference values for the level of quality of life, as measured by the QOLS-N in the Norwegian population.

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