Environmental factors that impact the eating behavior of home-living older adults.

Objective: To identify environmental factors that influence the eating behavior of home-living older adults. Design: Qualitative study with two interview methods, dyadic and in-depth individual interviews. Setting: The study was conducted in a western district of Norway. Participants: A total of 22 participants. The study sample consisted of 8 dyads for the dyadic interviews and 6 participants for the in-depth individual interviews. The dyads were composed of pairs who share a pre-existing relationship as well as pairs of strangers. Method: The qualitative study uses deductive and inductive content analysis. Results: Seven environmental factors that play a role in older adults' eating behavior were organized into three levels of influence: interpersonal influence (food habits of significant others, household composition, and social relationship), community influence (senior centers and food access), and public policy influence (health information and transportation/mobility aids). Conclusion: Various environmental factors determine the eating behavior of older adults living at home. An approach is needed to address these factors in order to bring positive change in the eating behavior of home-living older adults. The findings suggest that a social environment may be used to encourage healthy eating. Furthermore, increasing participation in a senior center, ensuring access to food, reducing ambiguity in diet and nutrition information, and increasing mobility support can help older adults maintain or develop healthy eating behavior.

Fatigue in type 1 diabetes, prevalence, predictors and comparison with the background population.

AIM: Fatigue is scarcely studied in type 1 diabetes (T1D), and the aims were to investigate its prevalence compared to the background population, potential associations, and to validate the Fatigue Questionnaire (FQ) in type 1 diabetes. METHODS: Persons with T1D were recruited from three outpatient clinics in Norway. Fatigue was measured using the FQ, and FQ data from the Norwegian background population were used for comparison. Socio-demographic and clinical variables were obtained by self-report, clinical investigation, medical records and laboratory tests. RESULTS: Of 332 eligible patients, 288 (87%) were included. Mean age was 44.65/44.95 years (SD 13.34/13.38) for females/males, respectively. Total fatigue (TF) was 15.31 (SD 5.51) compared to 12.2 (SD 4.0) in the background population (p < 0.001). HADS ≥ 8, current menstruation, increased leukocytes and sleep problems were associated with increased TF. Chronic fatigue (CF) was reported in 26.4% compared to 11% in the background population (p < 0.001). HADS ≥ 8, increased time since diagnosis and decreased sleep quality were associated with CF. The validity, internal consistency and repeatability of the FQ was confirmed. CONCLUSIONS: Fatigue was more common in T1D than in the background population, and associated with increased anxiety, depression and sleep problems. The FQ demonstrated satisfactory psychometric properties.

Psychometric testing of the Norwegian Diabetes Health Profile (DHP-18) in patients with type 1 diabetes.

OBJECTIVE: The Diabetes Health Profile-18 (DHP-18) was developed to measure disease-specific health-related quality of life. It has been translated into Norwegian but remains invalidated. The purpose of this paper was to examine the psychometric properties of the Norwegian DHP-18. RESEARCH DESIGN AND METHODS: Participants with type 1 diabetes were recruited from three outpatient clinics in Norway. Clinical and sociodemographic data were collected, and participants completed the DHP-18 and the Short-Form 36 (SF-36). Descriptive analysis, frequencies, t-tests and the chi-squared tests were used. Principal axis factoring (PAF) and confirmatory factor analysis (CFA) were used. Convergent validity was tested using Spearman's correlation between the DHP-18 and SF-36. Reliability was tested using Cronbach's alpha and intraclass correlation coefficient. RESULTS: In total, 288 patients were included. No floor and ceiling effects were found. A forced PAF analysis revealed that three questions had an eigenvalue below 0.40. In the unforced PAF analysis, one question loaded below 0.40, while three questions loaded into a fourth factor. The correlation between the DHP-18 and SF-36 dimensions was low to moderate. Problematic internal consistency was observed for the disinhibited eating dimension in the forced PAF and in the suggested fourth dimension in the unforced PAF. CFA revealed poor fit. The test-retest reliability displayed good to excellent values, but responsiveness was limited. CONCLUSIONS: Problematic issues were identified regarding factor structure, item loadings, internal consistency and responsiveness. Further evaluation of responsiveness is particularly recommended, and using a revised 14-item DHP version is suggested.

Fatigue in type 1 diabetes: A systematic review of Observational studies.

AIM: To systematically review the literature on fatigue in people with type 1 diabetes. METHODS: In the period from April to June 2015 and with an updated search in May 2016, eight electronic databases as well as the grey literature were searched. Studies of all types of design were included if they reported data on fatigue in adult people with type 1 diabetes. All studies were assessed for quality. RESULTS: Out of 4259 references (including grey literature), 10 papers were reviewed in full. Three of these papers investigated fatigue as the primary endpoint, and one was assessed to be high quality. Two papers provided a definition of fatigue. Prevalence estimates ranged from 23 to 40%, dependent on the cut-off used. Six different questionnaires were used to measure fatigue/vitality and these were only validated to a limited extent in a diabetes population. Several demographic, personal and clinical factors were associated with fatigue, but the results were conflicting. CONCLUSIONS: Few studies have been published that investigate fatigue in type 1 diabetes and there is a large variability in findings due to different measurement methods and factors investigated. There is still an unmet need to understand what contributes to fatigue in these patients through rigorous research.

Healthcare Engineering Defined: A White Paper.

Engineering has been playing an important role in serving and advancing healthcare. The term "Healthcare Engineering" has been used by professional societies, universities, scientific authors, and the healthcare industry for decades. However, the definition of "Healthcare Engineering" remains ambiguous. The purpose of this position paper is to present a definition of Healthcare Engineering as an academic discipline, an area of research, a field of specialty, and a profession. Healthcare Engineering is defined in terms of what it is, who performs it, where it is performed, and how it is performed, including its purpose, scope, topics, synergy, education/training, contributions, and prospects.