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Anna Ugalde BA PhD Victoria White BA MA PhD Nicole M. Rankin BA MSc PhD Christine Paul BA PhD Catherine Segan BA PhD Sanchia Aranda RN BAppSci MN PhD Anna Wong Shee BSc BAppSc PhD Alison M. Hutchinson RN BApp Sci MBioth PhD Patricia M. Livingston BA PhD 《CA: a cancer journal for clinicians》2022,72(3):266-286
Smoking cessation reduces the risk of death, improves recovery, and reduces the risk of hospital readmission. Evidence and policy support hospital admission as an ideal time to deliver smoking-cessation interventions. However, this is not well implemented in practice. In this systematic review, the authors summarize the literature on smoking-cessation implementation strategies and evaluate their success to guide the implementation of best-practice smoking interventions into hospital settings. The CINAHL Complete, Embase, MEDLINE Complete, and PsycInfo databases were searched using terms associated with the following topics: smoking cessation, hospitals, and implementation. In total, 14,287 original records were identified and screened, resulting in 63 eligible articles from 56 studies. Data were extracted on the study characteristics, implementation strategies, and implementation outcomes. Implementation outcomes were guided by Proctor and colleagues' framework and included acceptability, adoption, appropriateness, cost, feasibility, fidelity, penetration, and sustainability. The findings demonstrate that studies predominantly focused on the training of staff to achieve implementation. Brief implementation approaches using a small number of implementation strategies were less successful and poorly sustained compared with well resourced and multicomponent approaches. Although brief implementation approaches may be viewed as advantageous because they are less resource-intensive, their capacity to change practice in a sustained way lacks evidence. Attempts to change clinician behavior or introduce new models of care are challenging in a short time frame, and implementation efforts should be designed for long-term success. There is a need to embrace strategic, well planned implementation approaches to embed smoking-cessation interventions into hospitals and to reap and sustain the benefits for people who smoke. 相似文献
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Matthias Knefel PhD Elisabeth L. Zeilinger PhD Simone Lubowitzki PhD Katharina Krammer MSc Matthias Unseld MD Rupert Bartsch MD Thorsten Fuereder MD Ulrich Jäger MD Barbara Kiesewetter MD Maria Krauth MD Markus Raderer MD Philipp B. Staber MD Peter Valent MD Alexander Gaiger MD 《Cancer》2023,129(21):3466-3475
Background
Survival in cancer patients is associated with a multitude of biological, social, and psychological factors. Although it is well established that all these factors add to overall mortality, it is not well understood how the predictive power of these parameters changes in a comprehensive model and over time.Methods
Patients who attended the authors’ outpatient clinic were invited to participate. The authors followed 5180 mixed cancer patients (51.1% female; mean age, 59.1 years [SD = 13.8]) for up to 16 years and analyzed biological (age, sex, cancer site, anemia), psychological (anxiety, depression), and social variables (marital status, education, employment status) potentially predicting overall survival in a Cox proportional hazards model.Results
The median survival time for the entire sample was 4.3 years (95% confidence interval, 4.0–4.7). The overall survival probabilities for 1 and 10 years were 76.8% and 38.0%, respectively. Following an empirical approach, the authors split the time interval into five periods: acute, subacute, short-term, medium-term, and long-term. A complex pattern of variables predicted overall survival differently in the five periods. Biological parameters were important throughout most of the time, social parameters were either time-independent predictors or tended to be more important in the longer term. Of the psychological parameters, only depression was a significant predictor and lost its predictive power in the long-term.Conclusions
The findings of this study allow the development of comprehensive patient-specific models of risk and resilience factors addressing biopsychosocial needs of cancer patients, paving the way for a personalized treatment plan that goes beyond biomedical cancer care. 相似文献7.
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Rosdali Y. Diaz Coronado MD Martin Mynarek MD Christian Koelsche MD Pamela Mora Alferez MD Sandro Casavilca Zambrano MD Antonio Wachtel Aptowitzer MD Felix Sahm MD Andreas von Deimling MD Ulrich Schüller MD Michael Spohn MSc Dominik Sturm MD Stefan M. Pfister MD Andres Morales La Madrid MD Raymundo Sernaque Quintana MD Gustavo Sarria Bardales MD Tatiana Negreiros Chinchihuara MD Luis Ojeda Medina MD Pamela Garcia-Corrochano Medina MD Danny A. Campos Sanchez MD Jimena Ponce Farfan MD Stefan Rutkowski MD Juan L. Garcia Leon MD 《Cancer》2022,128(4):697-707