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5 results on '"Roer, O."'

2. Halogene

Author

Sabetay, S., Bléger, J., Slawjanow, J. N., Hahn, Fr. L., Tomíček, O., Jánsky, A. J., Szancer, H., Remington, R. E., Mc Clendon, J. F., Kolnitz, H. v., Culp, F. B., Roer, O., Schuster, F., Sontag, D., Pavolini, T., and Palfray, L.

Published
1931
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3. Quality of life of elderly persons with newly diagnosed cancer

Author

Esbensen, B A, Osterlind, K, Roer, O, Hallberg, I R, Esbensen, B A, Osterlind, K, Roer, O, and Hallberg, I R

Abstract

The aim was to investigate quality of life (QoL) in elderly persons newly diagnosed with cancer (65+ years) in relation to age, contact with the health-care system, ability to perform activities of daily living (ADL), hope, social network and support, and to identify which factors were associated with low QoL. The sample consisted of 101 patients (75 women and 26 men) newly diagnosed with cancer. EORTC QLQ-C30, Nowotny's Hope Scale, Katz ADL and the Interview Schedule for Social Interaction (ISSI) were used. The analysis was carried out in four age groups and revealed no significant differences in QoL. Compared with the other age groups, those of a high age (80+ years) more often lived alone, used more home-help service and had a smaller social network. Factors associated with low QoL were 'no other incomes than retirement pension', 'low level of hope' and 'lung cancer'. In addition, 'being told that the cancer disease has not come to an end', 'needing more help in activities of daily living', 'getting help from grown-up children' and 'needing help with PADL' were associated with low QoL. Those at risk of inferior QoL, that is, having poor economy, low level of hope and lung cancer need special attendance and specific interventions to improve QoL.

Published
2004

4. Quality of life of elderly persons with newly diagnosed cancer.

Author

Esbensen, Bente Appel, Osterlind, K, Roer, O, Hallberg, I R, Esbensen, Bente Appel, Osterlind, K, Roer, O, and Hallberg, I R

Abstract

The aim was to investigate quality of life (QoL) in elderly persons newly diagnosed with cancer (65+ years) in relation to age, contact with the health-care system, ability to perform activities of daily living (ADL), hope, social network and support, and to identify which factors were associated with low QoL. The sample consisted of 101 patients (75 women and 26 men) newly diagnosed with cancer. EORTC QLQ-C30, Nowotny's Hope Scale, Katz ADL and the Interview Schedule for Social Interaction (ISSI) were used. The analysis was carried out in four age groups and revealed no significant differences in QoL. Compared with the other age groups, those of a high age (80+ years) more often lived alone, used more home-help service and had a smaller social network. Factors associated with low QoL were 'no other incomes than retirement pension', 'low level of hope' and 'lung cancer'. In addition, 'being told that the cancer disease has not come to an end', 'needing more help in activities of daily living', 'getting help from grown-up children' and 'needing help with PADL' were associated with low QoL. Those at risk of inferior QoL, that is, having poor economy, low level of hope and lung cancer need special attendance and specific interventions to improve QoL.

Published
2004

5. Identifying and correcting spatial bias in opportunistic citizen science data for wild ungulates in Norway.

Author

Cretois B, Simmonds EG, Linnell JDC, van Moorter B, Rolandsen CM, Solberg EJ, Strand O, Gundersen V, Roer O, and Rød JK

Abstract

Many publications make use of opportunistic data, such as citizen science observation data, to infer large-scale properties of species' distributions. However, the few publications that use opportunistic citizen science data to study animal ecology at a habitat level do so without accounting for spatial biases in opportunistic records or using methods that are difficult to generalize. In this study, we explore the biases that exist in opportunistic observations and suggest an approach to correct for them. We first examined the extent of the biases in opportunistic citizen science observations of three wild ungulate species in Norway by comparing them to data from GPS telemetry. We then quantified the extent of the biases by specifying a model of the biases. From the bias model, we sampled available locations within the species' home range. Along with opportunistic observations, we used the corrected availability locations to estimate a resource selection function (RSF). We tested this method with simulations and empirical datasets for the three species. We compared the results of our correction method to RSFs obtained using opportunistic observations without correction and to RSFs using GPS-telemetry data. Finally, we compared habitat suitability maps obtained using each of these models. Opportunistic observations are more affected by human access and visibility than locations derived from GPS telemetry. This has consequences for drawing inferences about species' ecology. Models naïvely using opportunistic observations in habitat-use studies can result in spurious inferences. However, sampling availability locations based on the spatial biases in opportunistic data improves the estimation of the species' RSFs and predicted habitat suitability maps in some cases. This study highlights the challenges and opportunities of using opportunistic observations in habitat-use studies. While our method is not foolproof it is a first step toward unlocking the potential of opportunistic citizen science data for habitat-use studies., Competing Interests: The authors declare no conflict of interest., (© 2021 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Published
2021
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