Introduction
Falls represent a significant risk for hospitalised patients, particularly those with neurological conditions such as stroke and neuro-oncology diagnoses, where cognitive and motor deficits can heighten vulnerability. The Morse Fall Scale (MFS), a widely used tool for assessing fall risk, offers a structured approach to identifying at-risk individuals in clinical settings (Morse, 2008). However, its generic design may not fully account for the unique challenges faced by patients with specific neurological impairments. Tailoring the MFS to address cognitive and motor deficits in stroke and neuro-oncology patients could enhance its predictive accuracy and clinical utility. This essay proposes a research framework to modify the MFS, aligning with the APA Research Proposal Guidelines for literature reviews, and adapts the statement of the problem using the PICO format and the methodology using PRISMA checklist headings. The purpose is to explore how the MFS can be customised to improve patient safety, while critically engaging with existing evidence and outlining a clear research plan. Key areas of focus include the problem definition, literature synthesis, and a structured methodological approach, culminating in a discussion of implications for nursing practice.
Statement of the Problem: PICO Framework
The problem underpinning this research proposal can be articulated using the PICO framework, which structures clinical questions by defining Population, Intervention, Comparison, and Outcome. In this context, the question is: Among hospitalised stroke and neuro-oncology patients (P), does a tailored version of the Morse Fall Scale that accounts for cognitive and motor deficits (I), compared to the standard MFS (C), improve the accuracy of fall risk prediction and reduce fall incidence (O)? This question arises from the recognition that stroke and neuro-oncology patients often exhibit unique impairments—such as hemiparesis, ataxia, or cognitive processing delays—that may not be adequately captured by the generic MFS criteria, which focus on broader risk factors like history of falls, gait, and mental status (Morse, 2008). The lack of specificity in the MFS for these populations may lead to underestimation or overestimation of fall risk, potentially compromising patient safety. Addressing this gap is critical, as falls in hospital settings are associated with increased morbidity, prolonged recovery, and higher healthcare costs (NHS Improvement, 2017). This PICO-framed problem highlights the need for a modified assessment tool and provides a focused basis for the proposed research.
Literature Review: APA Guidelines Synthesis
Following APA Research Proposal Guidelines, this literature review synthesises existing evidence on fall risk assessment, with a focus on the MFS and its application to neurological populations. The MFS, developed by Janice Morse, is a validated tool that scores patients across six domains, including gait and mental status, to predict fall risk with a sensitivity of approximately 78% in general populations (Morse, 2008). However, studies suggest its predictive validity is reduced in patients with specific neurological conditions. For instance, Breisinger et al. (2014) found that the MFS underestimated fall risk in stroke patients, as it failed to account for fluctuating motor impairments post-rehabilitation. Similarly, in neuro-oncology contexts, cognitive deficits and treatment-related fatigue—often exacerbated by chemotherapy or radiotherapy—may skew MFS scores, as noted by Lovely et al. (2012). These findings indicate a clear limitation in the tool’s applicability to these groups.
Moreover, alternative tools, such as the Berg Balance Scale, have been explored for stroke patients, showing higher specificity for motor deficits (Maeda et al., 2009). Yet, these tools lack the simplicity and broad clinical acceptance of the MFS, underscoring the value of adapting rather than replacing it. Critically, there is a paucity of research on tailoring fall risk assessments specifically for neuro-oncology patients, representing a gap that this proposal seeks to address. The literature thus reveals both the potential of the MFS as a foundation and its shortcomings in capturing nuanced deficits, necessitating a targeted modification informed by clinical evidence and patient-specific factors.
Methodology: PRISMA Checklist Adaptation
To ensure rigour in modifying the MFS, the methodology for this research proposal is structured using key headings from the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist, adapted to suit the development of an assessment tool rather than a traditional systematic review. This framework provides a systematic approach to evidence synthesis and intervention design.
Eligibility Criteria
Studies and clinical guidelines relevant to fall risk assessment in stroke and neuro-oncology patients will be included, focusing on peer-reviewed articles published between 2010 and 2023. Inclusion criteria prioritise research addressing cognitive and motor impairments, MFS validation, and fall prevention strategies in hospital settings. Non-English publications and studies lacking methodological clarity will be excluded.
Information Sources
Databases such as PubMed, CINAHL, and the Cochrane Library will be searched for relevant literature. Additionally, grey literature, including NHS reports and WHO guidelines on patient safety, will be reviewed to contextualise clinical best practices. Search terms will include “Morse Fall Scale,” “stroke fall risk,” “neuro-oncology falls,” and “cognitive motor deficits.”
Study Selection
A two-stage screening process will be employed: initial title and abstract reviews to identify relevant studies, followed by full-text assessments against eligibility criteria. This dual approach ensures a comprehensive yet focused dataset for informing MFS modifications, with selection decisions documented for transparency.
Data Collection Process
Data will be extracted using a standardised template, capturing study design, population characteristics, MFS performance metrics (e.g., sensitivity, specificity), and identified limitations in neurological contexts. This will guide the identification of additional assessment parameters for cognitive and motor deficits, such as reaction time or visuospatial awareness tests.
Intervention Development
Drawing on synthesised data, the MFS will be modified by integrating supplementary scoring items tailored to stroke and neuro-oncology patients. For example, a subscale for motor asymmetry (common in stroke) or fatigue (prevalent in neuro-oncology) could be proposed, with pilot testing planned in a hospital setting to assess feasibility and predictive accuracy against fall incidence.
This methodology, while adhering to PRISMA’s systematic principles, is adapted to the practical aim of tool development. It acknowledges the complexity of the task and the need for iterative refinement based on clinical feedback, thereby addressing key aspects of the research problem with a structured yet flexible approach.
Conclusion
In summary, this essay has outlined a research proposal to tailor the Morse Fall Scale for stroke and neuro-oncology patients, focusing on their unique cognitive and motor deficits. Using the PICO framework, the problem was clearly defined, highlighting the inadequacy of the generic MFS for these populations and the consequent risk to patient safety. The literature review, aligned with APA guidelines, revealed critical gaps in the MFS’s applicability, supported by evidence of its variable performance in neurological contexts. The methodology, structured under PRISMA-inspired headings, proposed a systematic process for evidence synthesis and tool modification, ensuring rigour and relevance. The implications of this research are significant for nursing practice, as a tailored MFS could enhance fall risk prediction, inform personalised care plans, and ultimately reduce fall-related harm in vulnerable patients. Furthermore, this proposal underscores the importance of adapting generic tools to specific clinical populations, a principle that could extend to other assessment frameworks in healthcare. Future research should prioritise pilot testing and longitudinal evaluation to validate the modified MFS, ensuring it meets the complex needs of stroke and neuro-oncology patients in diverse settings.
References
- Breisinger, T. P., Skidmore, E. R., Niyonkuru, C., Terhorst, L., & Campbell, G. B. (2014) The Stroke Assessment of Fall Risk (SAFR): Predictive validity in inpatient stroke rehabilitation. Clinical Rehabilitation, 28(12), 1218-1224.
- Lovely, M. P., Miaskowski, C., & Dodd, M. (2012) Relationship between fatigue and quality of life in patients with glioblastoma multiforme. Oncology Nursing Forum, 39(2), E159-E165.
- Maeda, N., Kato, J., & Shimada, T. (2009) Predicting the probability for fall incidence in stroke patients using the Berg Balance Scale. Journal of International Medical Research, 37(3), 697-704.
- Morse, J. M. (2008) Preventing Patient Falls. Springer Publishing Company.
- NHS Improvement (2017) The incidence and costs of inpatient falls in hospitals. NHS Improvement Report.
