OBJECTIVE: To identify trajectories of cognitive-affective depressive symptoms among acutely hospitalized older patients and whether trajectories are related to prognostic baseline factors and three-month outcomes such as functional decline, falls, unplanned readmissions, and mortality.METHODS: Prospective multicenter cohort of acutely hospitalized patients aged ≥ 70. Depressive trajectories were based on Group Based Trajectory Modeling, using the Geriatric Depression Scale-15. Outcomes were functional decline, falls, unplanned readmission, and mortality within three months post-discharge.RESULTS: The analytic sample included 398 patients (mean age = 79.6 years; SD = 6.6). Three distinct depressive symptoms trajectories were identified: minimal (63.6%), mild persistent (25.4%), and severe persistent (11.0%). Unadjusted results showed that, compared to the minimal symptoms group, the mild and severe persistent groups showed a significantly higher risk of functional decline (mild: OR = 3.9, p < .001; severe: OR = 3.0, p = .04), falls (mild: OR = 2.0, p = .02; severe: OR = 6.0, p < .001), and mortality (mild: OR = 2.2, p = .05; severe: OR = 3.4, p = .009). Patients with mild or severe persistent symptoms were more malnourished, anxious, and functionally limited and had more medical comorbidities at admission.CONCLUSION: Nearly 40% of the acutely hospitalized older adults exhibited mild to severe levels of cognitive-affective depressive symptoms. In light of the substantially elevated risk of serious complications and the fact that elevated depressive symptoms was not a transient phenomenon identification of these patients is needed. This further emphasizes the need for acute care hospitals, as a point of engagement with older adults, to develop discharge or screening procedures for managing cognitive-affective depressive symptoms.
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Longitudinal criminological studies greatly improved our understanding of the longitudinal patterns of criminality. These studies, however, focused almost exclusively on traditional types of offending and it is therefore unclear whether results are generalizable to online types of offending. This study attempted to identify the developmental trajectories of active hackers who perform web defacements. The data for this study consisted of 2,745,311 attacks performed by 66,553 hackers and reported to Zone-H between January 2010 and March 2017. Semi-parametric group-based trajectory models were used to distinguish six different groups of hackers based on the timing and frequency of their defacements. The results demonstrated some common relationships to traditional types of crime, as a small population of defacers accounted for the majority of defacements against websites. Additionally, the methods and targeting practices of defacers differed based on the frequency with which they performed defacements generally.
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In deze studie onderzoeken we de ontwikkelingstrajecten van hackers, op basis van zelfgerapporteerde web defacements. Tijdens een web defacement wordt ongewenst de inhoud van een website aangepast. In totaal hebben we 50.330 defacements van websites met een Nederlandse extensie (.nl websites) geanalyseerd, die door 3640 verschillende defacers zijn uitgevoerd tussen januari 2010 en maart 2017. Met behulp van trajectory-modellen kunnen er zes groepen defacers worden onderscheiden in de analyses: twee groepen chronische daders en vier groepen daders die slechts gedurende een korte periode defacements uitvoerden. Deze groepen verschillen ook van elkaar in hun motivaties en modus operandi. De groep hoogfrequente chronische daders bestaat uit minder dan 2% van de daders, maar is verantwoordelijk voor meer dan de helft van alle defacements. Het zou dan ook het meest efficiënt zijn wanneer toekomstige interventies zich met name richten op deze kleine groep chronische daders. Voor vervolgonderzoek zou het interessant zijn om de inhoudelijke boodschap van de web defacements te onderzoeken.
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