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Item Psychological interventions for women with non-metastatic breast cancer(John Wiley & Sons, Inc., 2023-01-11) Jassim, Ghufran A.; Doherty, Sally; Whitford, David L.; Khashan, Ali S.Background: Breast cancer is the most common cancer affecting women worldwide. It is a distressing diagnosis and, as a result, considerable research has examined the psychological sequelae of being diagnosed and treated for breast cancer. Breast cancer is associated with increased rates of depression and anxiety and reduced quality of life. As a consequence, multiple studies have explored the impact of psychological interventions on the psychological distress experienced after a diagnosis of breast cancer. This review is an update of a Cochrane Review first published in 2015. Objectives: To assess the effect of psychological interventions on psychological morbidities and quality of life among women with non‐metastatic breast cancer. Search methods: We searched the Cochrane Breast Cancer Group Specialised Register, CENTRAL, MEDLINE, Embase, CINAHL, PsycINFO, the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) and ClinicalTrials.gov up to 16 March 2021. We also scanned the reference lists of relevant articles. Selection criteria: Randomised controlled trials that assessed the effectiveness of psychological interventions for women with non‐metastatic breast cancer. Data collection and analysis: Two review authors independently appraised, extracted data from eligible trials, and assessed risk of bias and certainty of the evidence using the GRADE approach. Any disagreement was resolved by discussion. Extracted data included information about participants, methods, the intervention and outcomes. Main results: We included 60 randomised controlled trials comprising 7998 participants. The most frequent reasons for exclusion were non‐randomised trials and the inclusion of women with metastatic disease. The updated review included 7998 randomised women; the original review included 3940 women. A wide range of interventions was evaluated. Most interventions were cognitive‐ or mindfulness‐based, supportive‐expressive, and educational. The interventions were mainly delivered face‐to‐face (56 studies) and in groups (50 studies) rather than individually (10 studies). Most intervention sessions were delivered on a weekly basis with an average duration of 14 hours. Follow‐up time ranged from two weeks to 24 months. Pooled standardised mean differences (SMD) from baseline indicated that the intervention may reduce depression (SMD ‐0.27, 95% confidence interval (CI) ‐0.52 to ‐0.02; P = 0.04; 27 studies, 3321 participants, I2 = 91%, low‐certainty evidence); anxiety (SMD ‐0.43, 95% CI ‐0.68 to ‐0.17; P = 0.0009; 22 studies, 2702 participants, I2 = 89%, low‐certainty evidence); mood disturbance in the intervention group (SMD ‐0.18, 95% CI ‐0.31 to ‐0.04; P = 0.009; 13 studies, 2276 participants, I2 = 56%, low‐certainty evidence); and stress (SMD ‐0.34, 95% (CI) ‐0.55 to ‐0.12; P = 0.002; 8 studies, 564 participants, I2 = 31%, low‐certainty evidence). The intervention is likely to improve quality of life in the intervention group (SMD 0.78, 95% (CI) 0.32 to 1.24; P = 0.0008; 20 studies, 1747 participants, I2 = 95%, low‐certainty evidence). Adverse events were not reported in any of the included studies. Authors' conclusions: Based on the available evidence, psychological intervention may have produced favourable effects on psychological outcomes, in particular depression, anxiety, mood disturbance and stress. There was also an improvement in quality of life in the psychological intervention group compared to control group. Overall, there was substantial variation across the studies in the range of psychological interventions used, control conditions, measures of the same outcome and timing of follow‐up.Item Knowledge translation interventions for facilitating evidence-informed decision-making amongst health policymakers(John Wiley & Sons, Inc., 2022-10-13) Toomey, Elaine; Wolfenden, Luke; Armstrong, Rebecca; Booth, Debbie; Christensen, Robin; Byrne, Molly; Dobbins, Maureen; Katikireddi, Srinivasa Vittal; Lavis, John N.; Maguire, Teresa; McHugh, Sheena; Schmidt, Bey-Marrié; Mulholland, Deirdre; Smith, Maureen; Devane, DeclanThis is a protocol for a Cochrane Review (intervention). The objectives are as follows: The aim of this review is to determine the effectiveness of knowledge translation interventions for facilitating evidence-informed decision-making amongst health policymakers.Item Grand Rounds in Methodology: a new series to contribute to continuous improvement of methodology and scientific rigour in quality and safety(BMJ Publishing Group, 2022-12-22) Marang-van de Mheen, Perla J.; Browne, John P.; Thomas, Eric J.; Franklin, Bryony Dean; National Institute for Health and Care Research; Public Health EnglandIn clinical practice, ‘grand rounds’ are well known as a method for continuing medical education. In the early 1900s, grand rounds involved bedside teaching, but teaching sessions later moved to the auditorium when they gained popularity to accommodate a larger audience.1 Nowadays, grand rounds are generally targeted to a diverse audience and include topics that will have broad appeal but may also be organised for specific specialties, for example, medical,2 surgical,3 nursing4 or diagnostic5 grand rounds. Grand rounds are a way to help doctors and other healthcare professionals keep up to date in evolving areas that may be outside their core practice. While bedside rounding with a senior physician is an important part of on-the-job training with the primary focus on immediate patient care, grand rounds are often multidisciplinary and present the ‘bigger picture’, as well as the newest research and treatments in a given area.Item Treatment effect analysis of the Frailty Care Bundle (FCB) in a cohort of patients in acute care settings(Springer, 2024) Crowe, Colum; Naughton, Corina; de Foubert, Marguerite; Cummins, Helen; McCullagh, Ruth; Skelton, Dawn A.; Dahly, Darren L.; Palmer, Brendan A.; O'Flynn, Brendan; Tedesco, Salvatore; Health Research Board; South South-West Hospital; Science Foundation IrelandPurpose: The aim of this study is to explore the feasibility of using machine learning approaches to objectively differentiate the mobilization patterns, measured via accelerometer sensors, of patients pre- and post-intervention. Methods: The intervention tested the implementation of a Frailty Care Bundle to improve mobilization, nutrition and cognition in older orthopedic patients. The study recruited 120 participants, a sub-group analysis was undertaken on 113 patients with accelerometer data (57 pre-intervention and 56 post-intervention), the median age was 78 years and the majority were female. Physical activity data from an ankle-worn accelerometer (StepWatch 4) was collected for each patient during their hospital stay. These data contained daily aggregated gait variables. Data preprocessing included the standardization of step counts and feature computation. Subsequently, a binary classification model was trained. A systematic hyperparameter optimization approach was applied, and feature selection was performed. Two classifier models, logistic regression and Random Forest, were investigated and Shapley values were used to explain model predictions. Results: The Random Forest classifier demonstrated an average balanced accuracy of 82.3% (± 1.7%) during training and 74.7% (± 8.2%) for the test set. In comparison, the logistic regression classifier achieved a training accuracy of 79.7% (± 1.9%) and a test accuracy of 77.6% (± 5.5%). The logistic regression model demonstrated less overfitting compared to the Random Forest model and better performance on the hold-out test set. Stride length was consistently chosen as a key feature in all iterations for both models, along with features related to stride velocity, gait speed, and Lyapunov exponent, indicating their significance in the classification. Conclusion: The best performing classifier was able to distinguish between patients pre- and post-intervention with greater than 75% accuracy. The intervention showed a correlation with higher gait speed and reduced stride length. However, the question of whether these alterations are part of an adaptive process that leads to improved outcomes over time remains.Item Use of participant data and biological samples is insufficiently described in participant information leaflets(Elsevier Inc., 2025-11-03) McGrath, Emer R.; Kirby, Nigel; Shiely, FrancesBackground: With greater availability of participant data and biobank repositories following clinical trial completion, adequately describing future data and biological sample reuse plans to trial participants is increasingly important. We evaluated how trial teams currently describe current and future use of participant data and biological samples in participant information leaflets (PILs). Methods: Retrospective qualitative analysis of 240 PILs (182 clinical trials) in Ireland and the UK. Descriptions of data and sample use/reuse were extracted and analyzed using a 4-stage pragmatic content analysis approach. A recommended list of questions to be addressed by trial teams when designing PILs was developed. Results: Of the 240 included PILs, 85% specifically mentioned, or directly implied, how confidentiality of participant data would be maintained; 38% were considered by the authors to adequately describe how data confidentiality would be maintained (ie, the PIL specifically mentioned data deidentification and compliance with data protection regulations); 47% reported the intended duration of data storage (mean 15; SD ± 9 years); 40% specified if data would be used in future research studies and 28% stated if data would be shared with other researchers. Of the 117 PILs stating biological samples would be collected from participants, 80% provided a reason for requesting the sample, 66% stated whether stored samples would be deidentified, 21% specified if individual-level results would be made available to participants and 70% specified whether samples may be used for future studies. Of the 73 PILs specifying planned future sample storage, 18% stated the intended duration of storage and 48% specified if samples would be shared with other researchers. A list of 8 recommended questions to be addressed by trial teams when designing PILs were identified, for example, ‘What is the intended duration of data and sample storage for the current study?’. Conclusions: PILs often provide insufficient detail regarding plans for current use and future reuse of participants’ data and their biological samples. The majority do not adequately describe plans for maintaining data confidentiality. Best practice approaches to describing data use and reuse in PILs are needed. This will require multistakeholder input, including potential trial participants to progress this.