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To classify Italian home care models based on structural characteristics, process factors and stakeholder perceptions.
This is a secondary analysis of the AIDOMUS-IT multicentre cross-sectional study, conducted in Italy between July 2022 and December 2023.
Data were collected via online surveys completed by 33 Local Health Authority Nursing Directors, home care nurses and patients. Hierarchical cluster analysis was used to classify different organisational models based on structural and process-related factors. Nurses' and patients' perceptions of care were described for each identified cluster.
The analysis identified three distinct organisational home care models: The ‘multidisciplinary model’, in which nurses reported high dissatisfaction due to organisational complexity and excessive workloads. In the ‘nurse-centred model’, characterised by publicly employed nurses, strong leadership, and a supportive work environment, patients reported high levels of satisfaction. The ‘performance-based model’, which operated with a lower nurse-to-patient ratio, reduced service hours, and greater reliance on external professionals. Nurses in this model reported high job satisfaction but also a greater intention to leave, while patient satisfaction was lower.
This study underscores the importance of leadership, resource management, and a supportive work environment in influencing both job satisfaction and patient outcomes in home care settings.
Policymakers could use these findings to refine care models and improve service delivery.
Limited research has examined the organisational structures of home care services, which are important for professionals' organisational well-being, patient safety, and quality of care. This study identified three distinct organisational home care models that could be used to refine care approaches and improve service delivery.
This study respects the EQUATOR guideline for observational studies (STROBE).
This study did not include patient or public involvement in its design, conduct, or reporting.
To identify the pain assessment scales with the best psychometric properties to be used by nurses in an inpatient setting.
Umbrella review.
A comprehensive search of four databases was conducted for systematic reviews published from July 2013 to November 2024, focusing on psychometric properties of pain scales used in inpatient settings. Inclusion criteria required scales to assess subjective or behavioural pain and be nurse-administered, while reviews without detailed psychometric data were excluded. Screening, quality appraisal (JBI checklist), and data extraction were performed independently by two researchers. Data synthesis combined qualitative and quantitative approaches, with psychometric properties evaluated using the COSMIN checklist. The study was reported in accordance with the Preferred Reporting Items for Overviews of Reviews (PRIOR) statement.
Seventeen articles met the inclusion criteria, identifying 41 scales used across various patient populations, including critical care, paediatric, postoperative, cancer, cerebral palsy, disorders of consciousness, low back and neck pain, stroke and verbal communication disorders. The Paediatric Pain Profile, the Breakthrough Pain Assessment Tool and the Questionnaire on Pain caused by Spasticity demonstrated adequate psychometric properties, although the positive findings for the latter two should be confirmed by at least one additional study. Most of the scales (n = 36) require further studies to validate their use in clinical practice. For two scales, their clinical use remains questionable.
The Paediatric Pain Profile, the Breakthrough Pain Assessment Tool, and the Questionnaire on Pain caused by Spasticity can be recommended for use. Unidimensional scales should complement, rather than replace, multidimensional scales to ensure a comprehensive pain assessment. Standardising documentation with validated scales enhances clinical decision-making, care quality, research usability, and reduces documentation burden.
Crohn’s disease (CD) is a chronic inflammatory disorder of the gastrointestinal tract distinguished by progressive bowel damage with a risk of structuring and penetrating complications. It is characterised by focal or segmental transmural inflammation that disrupts intestinal mucosal integrity and favours the development of abscesses and fistulas. Perianal fistula develops in 13%–39% of patients with CD. Their care is difficult but improves with medical and surgical treatment to preserve anal continence and avoid a maximum proctectomy. Combined treatment with seton placement and concomitant anti-TNF (infliximab, adalimumab) allows wound healing in 40%–70% of cases. The currently available treatments are not curative and fail to provide a long-term resolution. The injection of adipose stromal cells is currently being evaluated in clinical studies for repair-damaged tissues in various diseases (limb ischaemia, osteoarthritis, systemic sclerosis, etc). Immunoregulatory and anti-inflammatory properties of AdMSC (adipose-derived stroma/stem cells) are responsible for accelerating healing and represent an innovative approach for treating perianal fistulas associated with CD.
This phase I/IIa study is designed to assess the treatment of complex perianal fistulas linked with CD after failure of conventional treatment by injection of AdMSC (CellReady) into the fistula. Two doses of associated AdMSC will be tested for a dose escalation (5x107 and 10x107 cells) and injected into the wall of the fistula. Those eligible for inclusion include patients with controlled luminal CD characterised by a Harvey-Bradshaw score below or equal to eight and diagnosed on clinical, endoscopic, histological and/or radiological criteria, a colonoscopy dating back less than 1 year without ulcer in the rectum and presence of complex chronic perianal fistula with a maximum of two internal ports and three external ports. All patients must have social security insurance or equivalent social protection. The aim of this study is to determine the optimal dose corresponding to maximum efficacy 6 months after injection of cells with a treatment-related adverse event rate of 20%.
The EU CT number 2024-511821-75-00 was approved by the following Ethics Committee: CPP (committee for the protection of persons in French: comité de protection des personnes) Ouest 1 – Tours #2024UEMED-18 and ANSM (French Agency for the Safety of Health and Medicinal Products in French : Agence nationale de sécurité du médicament et des produits de santé) #2024-511821-75-00 (Sponsor number RC31/13/7030, protocol V2.1). The results will be disseminated through conventional scientific channels.
The results will be disseminated through conventional scientific channels.
This paper discusses data errors and offers guidance on data cleaning techniques, with a particular focus on handling missing values and outliers in quantitative datasets.
Methodological discussion.
This paper provides an overview of various techniques for identifying and addressing data anomalies, which can arise from incomplete, noisy, and inconsistent data. These anomalies can significantly affect data quality, leading to biased model parameter estimates and evidence-based decisions. Data cleaning, particularly the appropriate handling of missing values and outliers, is essential to improving data quality before analysis. Data cleaning includes screening for anomalies, diagnosing errors, and applying appropriate corrective measures.
Proper handling of missing values and the identification and correction of outliers are crucial aspects of data cleaning in ensuring data quality and the reliability of statistical analyses. Effective data cleaning enhances the validity and accuracy of research findings for evidence-based decision making that leads to optimal patient outcomes.
The quality of study results depends on how a dataset and its complexities are processed or handled before the analysis. Nursing researchers must use a framework to identify and address important data anomalies and produce reliable results.
This paper describes data cleaning, often overlooked during the data mining process, as a crucial step before conducting data analysis. By addressing missing values and outliers, identifying and fixing data anomalies, and enhancing data quality prior to analysis, data cleaning techniques can produce precise research findings for evidence-based decision making.
In this methodological paper, no new data were generated.
No patient or public contribution.
This paper explores the methodological challenges associated with cross-cultural validation of clinical assessment measures and proposes strategies to enhance the validity and reliability of these assessments.
Methodological discussion.
Three main phases require consideration in the cross-cultural validation of assessment instruments: (1) Linguistic translation of the assessment instrument and confirmation of its equivalence, which includes conceptual, item, semantic and operational equivalence; (2) Empirical validation of the translated version's accuracy; (3) Adjusting the scores to fit the cultural context.
Achieving cross-cultural equivalence of assessment instruments is a complex and challenging process that can only be achieved through methodological rigour. It requires interdisciplinary collaboration of both linguistic and subject experts with strong statistical knowledge and a willingness to explore the nuances of the target population. By enhancing methodological rigour, we can improve the validity of clinical assessment measures across cultures, ultimately leading to better health outcomes for diverse populations.
The implications of cross-cultural validation of clinical assessment measures/tools for nursing are significant and multifaceted. Overcoming challenges to cross-cultural validation contributes to the professional growth of nurses by equipping them with greater cultural awareness and confidence in the tools' reliability for patient assessment and evaluation. This not only aids in their clinical practice but also fosters a commitment to evidence-based practice, enhancing their overall effectiveness as healthcare providers. Reliable and valid assessment tools enable nurses to confidently engage in research literature that reflects the realities of diverse populations. This can inform healthcare policies and practices, ensuring they are inclusive and equitable.
While researchers endeavour to reach a consensus on the definition of cross-cultural equivalence and how it should be determined, this practical introduction discusses challenges and proposes strategies to enhance the validity and reliability of these measures/tools.
No patient or public contribution.
Clinical research nurses work at the fulcrum of clinical trials with clearly defined roles and responsibilities. In England, the National Institute for Health Research (the main funder of health research) has broadened its scope to encompass social care research. The expectation is that clinical research nurses will expand their skill set to support these new studies, many of which will employ qualitative and mixed methods. This discussion paper explores the challenges of facilitating this clinical academic workforce development through a case study of a homeless health and social care research project. This was one of the first studies to engage clinical research nurses in this new and expanded role.
Much of what is known about the research nurse workforce has been generated through studies of clinical trials in oncology. The ‘caring-recruiting’ dichotomy has been used as a heuristic device for identifying workforce issues that can impact on study delivery such as how intense pressure to recruit study participants leads to low job satisfaction.
This case study reflects on the authors' experiences of employing a clinical research nurse in a social care research project concerned with the discharge of homeless people from hospital. The ‘caring-recruiting’ dichotomy is used to generate new information about the relationship between workforce development and the successful delivery of social care research.
The case study illuminates how social care research can generate different pressures and ethical challenges for research nurses. The time and skill it took to recruit study participants identified as ‘hard to reach’ was suggestive of the need to move beyond performance measures that prioritise recruitment metrics. The need for different types of staff supervision and training was also warranted as supporting study participants who were homeless was often distressing, leading to professional boundary issues.
This study highlights that performance management, training and supervisory arrangements must be tailored to the characteristics of each new study coming onto the portfolio to ensure research nurses are fully supported in this new and expanded role.
Postoperative pulmonary complications (PPCs) are common after cardiac surgery and are associated with significant morbidity and mortality. Lung-protective ventilation strategies have been proposed to reduce PPCs, but the optimal level of positive end-expiratory pressure (PEEP) and the use of alveolar recruitment manoeuvres (RMs) remain controversial.
In this investigator-initiated, multicentre, open, randomised, parallel-group, superiority clinical trial, elective cardiac surgery patients at risk of PPCs will be assigned to one of two intraoperative ventilation strategies: (1) an open-lung ventilation strategy with protective ventilation, moderate PEEP and RMs or (2) a standard protective ventilation with low PEEP and no RM. The primary outcome will be a composite of prolonged (>24 hour) postoperative mechanical ventilation, reintubation for any cause or hospital-acquired pneumonia within 7 days of surgery, or death within 28 days of surgery. Data will be analysed on an intention-to-treat basis.
The VACARM (impact of intraoperatiVe moderAte positive end-expiratory pressure with reCruitment mAnoeuvres versus low positive end-expiRatory pressure on major postoperative pulMonary complications and death after on-pump cardiac surgery in high-risk patients) trial has been approved by an independent ethics committee for all study centres. Recruitment began in July 2021. Results will be published in international peer-reviewed medical journals.
ClinicalTrials.gov NCT04408495.
To describe a knowledge translation capacity-building initiative and illustrate the roles of nurses in practice change using an exemplar case study.
The report uses observational methods and reflection.
The Knowledge Translation Challenge program involves a multi-component intervention across several sites. The advisory committee invited eligible teams to attend capacity-building workshops. Implementation plans were developed, and successful teams receive funding for a 2 year period. Evaluation involved collecting data on program uptake and impact on practice change. Data has been collected from five cohorts. The exemplar case study employed an action-research framework.
Four nurse-led teams have demonstrated successful implementation of their practice change. The case study on implementing a clinical toolkit for clozapine management further illustrates a thoughtful planning process, and implementation journey and learnings by a team of nurses.
The Knowledge Translation Challenge program empowers nurses to use implementation science practices to enhance the quality and effectiveness of healthcare services. Success of this initiative serves as a model for addressing the persistent gap between knowledge and practice in clinical settings and the value of activating nurses to help close this gap.
As the most trusted and numerous profession, it is vital that nurses contribute to efforts to translate research evidence into clinical practice. The Knowledge Translation Challenge program supports nurses to lead practice change.
The Knowledge Translation Challenge program successfully equips nurses and other health care providers with the knowledge, skills and resources to implement practice improvements which enhance the quality and effectiveness of healthcare services and nursing practice.
The Knowledge Translation Challenge advisory committee has three patient-public partners that support teams to develop a patient-oriented approach for their projects by providing feedback on the implementation plans. Each team was also supported to include patient-public partners on their project.
Dental caries is the most common oral disease worldwide, affecting up to 90% of children globally. It can lead to pain, infection and impaired quality of life. Early prevention is a key strategy for reducing the prevalence of dental caries in young children. Valid and reliable diagnostic or prognostic tools that enable accurate individualised prediction of current or future dental caries are essential for facilitating personalised caries prevention and early intervention. However, no efficacious tools currently exist in early childhood—the optimal period for disease prevention. We aim to develop and validate diagnostic and prognostic prediction tools for dental caries in young children, using a combination of environmental, physical, behavioural and biological early life data.
Data sources include two prospective studies, with a total sample size of approximately 600 children. These cohorts have collected detailed demographic, antenatal, perinatal and postnatal data from medical records and parent-completed questionnaires and biological samples including a dental plaque swab. Candidate predictor variables will include sociodemographic characteristics, health history, behavioural and microbiological characteristics. The outcome variable will be the presence, incidence or severity of dental caries diagnosed using the International Caries Detection and Assessment System. Statistical and machine learning approaches will be used for selection of predictor variables and model development. Internal validation will be conducted using resampling methods (i.e., bootstrapping) and nested cross-validation. Model performance will be evaluated using standard performance metrics such as accuracy, discrimination and calibration. Where feasible, external validation will be performed in an independent cohort. Model development and reporting will be guided by the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) statement and the Prediction model Risk Of Bias Assessment Tool (PROBAST) guidelines.
This study has ethical and governance approval from The Royal Children’s Hospital Melbourne Human Research Ethics Committee (HREC/111803/RCHM-2024). Results of this study will be published in peer-reviewed journals and presented at scientific conferences.
Infant2Child: ACTRN12622000205730—pre-results; MisBair: NCT01906853—post results.
There are estimated to be 3.4 million patients in the UK living after a diagnosis of cancer. We know very little about their quality of life or healthcare usage. Patient-reported outcome measures (PROMs) are tools which help to translate a patient’s quality of life into measurable categories, but how to do this at scale remains underexplored. The study employs a randomised design to assess different engagement strategies for optimising participation, data linkage and questionnaire completion in Northwest London and then nationally, with appropriate research approvals.
We have designed and implemented an online, patient-completed, randomised observational trial. We will pilot it in Northwest London before national roll-out, using initially the General Practice (GP) record of a cancer diagnosis and then exploring the use of social media. The primary objective is to explore the feasibility of recruiting participants via self-identification or contact from the primary care research network and obtaining consent to link participants’ PROMs responses to their cancer registry records. Data collection occurs through a secure platform, with participants directly responsible for data entry. There is no formal target sample size because this is a feasibility study, and we want to explore how many patients we can recruit. Analyses will be conducted using descriptive statistics, repeated measures multilevel modelling and machine learning techniques. If a substantial difference in responses between randomisation arms is detected, ineffective strategies will be removed. If no clear difference is observed, recruitment will continue with periodic reviews based on response rates and data completeness.
The Study Coordination Centre has obtained approval from the London—Surrey Research Ethics Committee and Health Research Authority. We will publish and disseminate the results in local, national and international meetings, in peer-reviewed journals, on social media and on websites.
It has been registered under ‘Investigating Digital Outcomes for Cancer Survivors in the Community’ (NCT06095024).
NCT06095024: Investigating Digital Outcomes for Cancer Survivors in the Community.
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