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  • 1.
    Abramsson, Marianne
    et al.
    Linköping University, Department of Social and Welfare Studies, Division Ageing and Social Change. Linköping University, Faculty of Arts and Sciences.
    Kelfve, Susanne
    Linköping University, Department of Social and Welfare Studies, Division Ageing and Social Change. Linköping University, Faculty of Arts and Sciences.
    Äldres materiella förhållanden2017In: Vem är den äldre - Äldrebilder i ett åldrande Sverige / [ed] Abramsson, Marianne; Hydén Lars-Christer & Motel Klingebiel Andreas, Stockholm: Nationell Kvalitetsplan för Äldreomsorgen , 2017Chapter in book (Other academic)
  • 2.
    Kelfve, Susanne
    Linköping University, Department of Social and Welfare Studies, Division Ageing and Social Change. Linköping University, Faculty of Arts and Sciences. Karolinska Inst, Sweden; Stockholm Univ, Sweden.
    Underestimated Health Inequalities Among Older People-A Consequence of Excluding the Most Disabled and Disadvantaged2019In: The journals of gerontology. Series B, Psychological sciences and social sciences, ISSN 1079-5014, E-ISSN 1758-5368, Vol. 74, no 8, p. E125-E134Article in journal (Refereed)
    Abstract [en]

    Objectives: The present study analyzed whether estimates of health inequalities in old age are sensitive to the exclusion of people living in institutions and nonuse of proxy interviews. Method: Pooled data from the 2004 wave (n = 1,180, aged 69-100, primarily interviewed over the phone) and the 2011 wave (n = 931, aged 76-101, primarily interviewed face-to-face) of the Swedish Panel Study of Living Conditions of the Oldest Old were used to compare absolute and relative differences in disability and mortality between people with compulsory education and people with more than compulsory education. Results: Both absolute and relative health inequalities would have been underestimated in a survey that excluded institutionalized people and proxy-interviewed community dwellers. The same patterns were found in men and women and regardless of the mode of data collection (telephone or face-to-face interview). The degree of underestimation was lower in those 85 years and older than in those 69 to 84 years. Discussion: A survey that only includes people who live in the community and can participate without the help of a proxy might give the impression that those with low levels of education have less extensive health disadvantages than they actually have.

  • 3.
    Kelfve, Susanne
    et al.
    Linköping University, Department of Social and Welfare Studies, Division Ageing and Social Change. Linköping University, Faculty of Arts and Sciences. Univ Stockholm, Sweden.
    Fors, Stefan
    Univ Stockholm, Sweden.
    Lennartsson, Carin
    Univ Stockholm, Sweden.
    Getting better all the time? Selective attrition and compositional changes in longitudinal and life course studies2017In: Longitudinal and life course studies, ISSN 1124-9064, E-ISSN 1757-9597, Vol. 8, no 1, p. 104-119Article in journal (Refereed)
    Abstract [en]

    Longitudinal surveys are valuable tools for investigating health and social outcomes across the life course. In such studies, selective mortality leads to changes in the social composition of the sample, but little is known about how selective survey participation affects the sample composition, in addition to the selective mortality. In the present paper, we followed a Swedish cohort sample over six waves 1968-2011. For each wave we recalculated the distribution of baseline characteristics in the sample among i) the sample still alive and ii) the sample still alive and with complete follow-up. The results show that the majority of the compositional changes in the cohort were modest and driven mainly by mortality. However, for some characteristics, class in particular, the selection was considerable and in addition, was substantially compounded by survey non-participation. We suggest that sample selections should be taken into account when interpreting the results of longitudinal studies, in particular when researching social inequalities.

  • 4.
    Kelfve, Susanne
    et al.
    Linköping University, Department of Social and Welfare Studies, Division Ageing and Social Change. Linköping University, Faculty of Arts and Sciences. Karolinska Inst, Sweden; Stockholm Univ, Sweden.
    Wastesson, Jonas
    Karolinska Inst, Sweden; Stockholm Univ, Sweden.
    Fors, Stefan
    Karolinska Inst, Sweden; Stockholm Univ, Sweden; Karolinska Inst, Sweden.
    Johnell, Kristina
    Karolinska Inst, Sweden; Stockholm Univ, Sweden.
    Morin, Lucas
    Karolinska Inst, Sweden; Stockholm Univ, Sweden.
    Is the level of education associated with transitions between care settings in older adults near the end of life? A nationwide, retrospective cohort study2018In: Palliative Medicine: A Multiprofessional Journal, ISSN 0269-2163, E-ISSN 1477-030X, Vol. 32, no 2, p. 366-375Article in journal (Refereed)
    Abstract [en]

    Background: End-of-life transitions between care settings can be burdensome for older adults and their relatives. Aim: To analyze the association between the level of education of older adults and their likelihood to experience care transitions during the final months before death. Design: Nationwide, retrospective cohort study using register data. Setting/participants: Older adults (65 years) who died in Sweden in 2013 (n = 75,722). Place of death was the primary outcome. Institutionalization and multiple hospital admissions during the final months of life were defined as secondary outcomes. The decedents level of education (primary, secondary, or tertiary education) was considered as the main exposure. Multivariable analyses were stratified by living arrangement and adjusted for sex, age at time of death, illness trajectory, and number of chronic diseases. Results: Among community-dwellers, older adults with tertiary education were more likely to die in hospitals than those with primary education (55.6% vs 49.9%; odds ratio (OR) = 1.21, 95% confidence interval (CI) = 1.14-1.28), but less likely to be institutionalized during the final month before death (OR = 0.83, 95% CI = 0.76-0.91). Decedents with higher education had greater odds of remaining hospitalized continuously during their final 2 weeks of life (OR = 1.12, 95% CI = 1.02-1.22). Among older adults living in nursing homes, we found no association between the decedents level of education and their likelihood to be hospitalized or to die in hospitals. Conclusion: Compared with those who completed only primary education, individuals with higher educational attainment were more likely to live at home until the end of life, but also more likely to be hospitalized and die in hospitals.

  • 5.
    Marcusson, Jan
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Local Health Care Services in Central Östergötland, Department of Acute Internal Medicine and Geriatrics.
    Nord, Magnus
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences.
    Johansson, Maria
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Local Health Care Services in Central Östergötland, Department of Activity and Health.
    Alwin, Jenny
    Linköping University, Department of Medical and Health Sciences, Division of Health Care Analysis. Linköping University, Faculty of Medicine and Health Sciences.
    Levin, Lars-Åke
    Linköping University, Department of Medical and Health Sciences, Division of Health Care Analysis. Linköping University, Faculty of Medicine and Health Sciences.
    Dannapfel, Petra
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences.
    Thomas, Kristin
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Poksinska, Bozena
    Linköping University, Department of Management and Engineering, Logistics & Quality Management. Linköping University, Faculty of Science & Engineering.
    Sverker, Annette M.
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Region Östergötland, Local Health Care Services in Central Östergötland, Department of Activity and Health.
    Olaison, Anna
    Linköping University, Department of Social and Welfare Studies, Social Work. Linköping University, Faculty of Arts and Sciences.
    Cedersund, Elisabet
    Linköping University, Department of Social and Welfare Studies, Division Ageing and Social Change. Linköping University, Faculty of Arts and Sciences.
    Kelfve, Susanne
    Linköping University, Department of Social and Welfare Studies, Division Ageing and Social Change. Linköping University, Faculty of Arts and Sciences.
    Motel-Klingebiel, Andreas
    Linköping University, Department of Social and Welfare Studies, Division Ageing and Social Change. Linköping University, Faculty of Arts and Sciences.
    Hellstrom, Ingrid
    Norrkoping Univ, Sweden.
    Kullberg, Agneta
    Linköping University, Department of Social and Welfare Studies, Social Work. Linköping University, Faculty of Arts and Sciences.
    Böttiger, Ylva
    Linköping University, Department of Medical and Health Sciences, Division of Drug Research. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Clinical Pharmacology.
    Dong, Huan-Ji
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Pain and Rehabilitation Center.
    Peolsson, Anneli
    Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences.
    Wass, Malin
    Linköping University, Department of Behavioural Sciences and Learning, Education, Teaching and Learning. Linköping University, Faculty of Arts and Sciences. Linköping University, The Swedish Institute for Disability Research.
    Lyth, Johan
    Linköping University, Department of Medical and Health Sciences, Division of Health Care Analysis. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Operations management Region Östergötland, Research and Development Unit.
    Andersson, Agneta
    Linköping University, Department of Medical and Health Sciences, Division of Health Care Analysis. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Operations management Region Östergötland, Research and Development Unit.
    Proactive healthcare for frail elderly persons: study protocol for a prospective controlled primary care intervention in Sweden2019In: BMJ Open, ISSN 2044-6055, E-ISSN 2044-6055, Vol. 9, no 5, article id e027847Article in journal (Refereed)
    Abstract [en]

    Introduction The provision of healthcare services is not dedicated to promoting maintenance of function and does not target frail older persons at high risk of the main causes of morbidity and mortality. The aim of this study is to evaluate the effects of a proactive medical and social intervention in comparison with conventional care on a group of persons aged 75 and older selected by statistical prediction.

    Methods and analysis In a pragmatic multicentre primary care setting (n=1600), a prediction model to find elderly (75+) persons at high risk of complex medical care or hospitalisation is used, followed by proactive medical and social care, in comparison with usual care. The study started in April 2017 with a run-in period until December 2017, followed by a 2-year continued intervention phase that will continue until the end of December 2019. The intervention includes several tools (multiprofessional team for rehabilitation, social support, medical care home visits and telephone support). Primary outcome measures are healthcare cost, number of hospital care episodes, hospital care days and mortality. Secondary outcome measures are number of outpatient visits, cost of social care and informal care, number of prescribed drugs, health-related quality of life, cost-effectiveness, sense of security, functional status and ability. We also study the care of elderly persons in a broader sense, by covering the perspectives of the patients, the professional staff and the management, and on a political level, by using semistructured interviews, qualitative methods and a questionnaire.

    Ethics and dissemination Approved by the regional ethical review board in Linköping (Dnr 2016/347-31). The results will be presented in scientific journals and scientific meetings during 2019–2022 and are planned to be used for the development of future care models.

  • 6.
    Poli, Arianna
    et al.
    Linköping University, Department of Social and Welfare Studies, Division Ageing and Social Change. Linköping University, Faculty of Arts and Sciences.
    Kelfve, Susanne
    Linköping University, Department of Social and Welfare Studies, Social Work. Linköping University, Faculty of Arts and Sciences. Karolinska Inst, Sweden; Stockholm Univ, Sweden.
    Motel-Klingebiel, Andreas
    Linköping University, Department of Social and Welfare Studies, Division Ageing and Social Change. Linköping University, Faculty of Arts and Sciences.
    A research tool for measuring non-participation of older people in research on digital health2019In: BMC Public Health, ISSN 1471-2458, E-ISSN 1471-2458, BMC PUBLIC HEALTH, Vol. 19, no 1, article id 1487Article in journal (Refereed)
    Abstract [en]

    Background

    Healthcare services are being increasingly digitalised in European countries. However, in studies evaluating digital health technology, some people are less likely to participate than others, e.g. those who are older, those with a lower level of education and those with poorer digital skills. Such non-participation in research – deriving from the processes of non-recruitment of targeted individuals and self-selection – can be a driver of old-age exclusion from new digital health technologies. We aim to introduce, discuss and test an instrument to measure non-participation in digital health studies, in particular, the process of self-selection.

    Methods

    Based on a review of the relevant literature, we designed an instrument – the NPART survey questionnaire – for the analysis of self-selection, covering five thematic areas: socioeconomic factors, self-rated health and subjective overall quality of life, social participation, time resources, and digital skills and use of technology. The instrument was piloted on 70 older study persons in Sweden, approached during the recruitment process for a trial study.

    Results

    Results indicated that participants, as compared to decliners, were on average slightly younger and more educated, and reported better memory, higher social participation, and higher familiarity with and greater use of digital technologies. Overall, the survey questionnaire was able to discriminate between participants and decliners on the key aspects investigated, along the lines of the relevant literature.

    Conclusions

    The NPART survey questionnaire can be applied to characterise non-participation in digital health research, in particular, the process of self-selection. It helps to identify underrepresented groups and their needs. Data generated from such an investigation, combined with hospital registry data on non-recruitment, allows for the implementation of improved sampling strategies, e.g. focused recruitment of underrepresented groups, and for the post hoc adjustment of results generated from biased samples, e.g. weighting procedures.

1 - 6 of 6
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