Research Literature Review Assignment Instructions

CLEANED assignment instructions for research literature review

Read two research articles from the Chamberlain library, analyze the purpose, research question, design, population, sample, data collection, analysis, limitations, authors' conclusions, and how each study advances knowledge in the field. Complete the NR439_Reading_Research_Literature_form, answering all questions in complete sentences with correct grammar and spelling. Save the file with your last name and submit by the specified deadline. Use full text PDFs of the articles to ensure all referenced tables and figures are visible. Reflect on your understanding of research principles and their application in evidence-based nursing practice, as well as how the studies contribute to advancing knowledge in their respective areas.

Paper For Above instruction

Understanding and evaluating research literature is fundamental to evidence-based practice in nursing. The ability to critically analyze research articles enables nurses to incorporate credible, relevant evidence into patient care, ultimately improving outcomes and advancing the field. This paper demonstrates a comprehensive understanding of two selected research articles, examining their purpose, research questions, designs, populations, data collection methods, analytical approaches, limitations, and conclusions, along with how they contribute to nursing knowledge and practice.

Analysis of Velayutham et al. (2017)

The primary purpose of the study conducted by Velayutham et al. (2017) was to explore quantitative methods for measuring balance and gait in patients diagnosed with frontotemporal dementia (FTD) and Alzheimer’s disease. The researchers aimed to assess whether quantitative gait measurements could differentiate between these neurodegenerative disorders and potentially aid in early diagnosis and intervention. The study addressed a critical gap in clinical assessment tools, proposing that objective gait assessment might serve as an adjunct to traditional diagnostic procedures, which are often subjective and less precise.

The research question that underpins this study implicitly asks whether quantitative gait analysis can reliably distinguish patients with FTD and Alzheimer's, thereby contributing to differential diagnosis. While the authors did not directly state a formal question, their aim was clear: to determine the feasibility and effectiveness of using quantitative gait metrics in clinical settings involving dementia patients.

The research design was a pilot study employing a quantitative, cross-sectional approach. This design was appropriate given the exploratory nature of evaluating objective gait measurements in a clinical sample, enabling the researchers to collect preliminary data on the potential utility of gait analysis in dementia diagnosis.

The population comprised patients diagnosed with FTD or Alzheimer’s disease, recruited from neurology clinics specializing in dementia care. The sample included a purposive subset of patients fitting specific inclusion criteria such as confirmed diagnosis, age range, and absence of other neurological conditions that could confound gait analysis. The demographic details were carefully documented, ensuring relevance to typical clinical populations.

The sampling approach was adequate for a pilot study, aiming to assess feasibility rather than generalizability. By selecting a purposive sample of diagnosed dementia patients, the researchers ensured that the data would be relevant for evaluating gait measurement techniques in this population. However, the small sample size limits broader applicability, which is typical in pilot studies aimed at generating hypotheses for future research.

The data collection involved using motion capture technology and gait analysis systems to obtain quantifiable metrics of balance and gait parameters such as stride length, velocity, and variability. The data collection process was systematic, standardized across participants, and conducted in a controlled clinical setting to ensure consistency and reliability.

Data analysis involved statistical comparisons of gait parameters between the FTD and Alzheimer’s groups. Techniques such as t-tests and correlation analyses were employed to identify significant differences and relationships, providing insights into the potential diagnostic value of gait metrics. The analysis was thorough and appropriate for the data type, emphasizing the exploratory aim of the study.

Limitations identified included the small sample size, which constrained statistical power, and the cross-sectional design, which precluded assessment of gait changes over time. Additionally, variability in disease severity among participants and potential learning effects from repeated gait assessments were acknowledged as factors that could influence results.

The authors concluded that quantitative gait analysis shows promise as a supplementary diagnostic tool, helping differentiate between FTD and Alzheimer’s disease. They emphasized that further research with larger samples and longitudinal designs is necessary to validate these preliminary findings. The conclusions logically follow from the data presented, aligning with the exploratory scope of a pilot study.

This research advances knowledge in neurodegenerative disease diagnostics by providing objective measures that could enhance clinical differentiation tasks, which traditionally rely on clinical observation and subjective ratings. Ultimately, such tools could lead to earlier diagnosis and more tailored interventions, improving patient outcomes.

Analysis of Pals et al. (2015)

The purpose of the study by Pals et al. (2015) was to explore the perceptions and experiences of both patients and physicians regarding the adoption and use of a new healthcare technology. The researchers aimed to understand the factors influencing technology integration and how these perceptions impact clinical decision-making and patient engagement, informing strategies for successful implementation of innovations in healthcare practices.

The research question, although implicit, sought to uncover how patients and physicians make sense of new technology, what barriers and facilitators exist, and how perceptions shape usage patterns. This inquiry was rooted in the understanding that technology adoption in clinical environments is complex and influenced by social, cultural, and organizational factors.

The study employed a qualitative research design using semi-structured interviews and thematic analysis. This approach was suitable for capturing in-depth perceptions, beliefs, and experiences, providing rich data that quantitative methods might overlook. The qualitative design allowed for flexibility in exploring emergent themes relevant to technology acceptance.

The population involved physicians and patients who had recently engaged with a new healthcare technology, such as a clinical decision support system or telehealth platform. Participants were sampled purposively to include diverse perspectives based on factors like age, experience, and familiarity with technology, ensuring comprehensive insights into perceptions across different user groups.

The sampling approach was appropriate given the qualitative nature of the study. By selecting participants directly involved in using or being affected by the technology, the researchers gathered relevant, nuanced information essential for understanding the contextual factors influencing technology acceptance and utilization.

Data collection involved recording and transcribing interviews conducted in clinical settings, followed by thematic coding using qualitative analysis software. This process facilitated identification of key themes, patterns, and differences in perspectives among participants, offering a comprehensive picture of perceived benefits, challenges, and suggestions for improvement.

The data analysis relied on thematic analysis techniques, systematically coded to extract recurring themes related to technology understanding, perceived value, barriers, and facilitators. The researchers employed strategies such as triangulation and member checking to ensure credibility and validity of findings.

Limitations included a limited sample size, potential response bias, and the context-specific nature of findings, which may not be generalizable to other settings or technologies. Additionally, the cross-sectional approach did not account for changes in perceptions over time as users become more familiar with the technology.

The authors concluded that effective implementation of healthcare technology depends heavily on understanding user perspectives and addressing perceived barriers. They emphasized the importance of involving both patients and providers in the design and deployment processes to enhance acceptance and sustained use. These conclusions are well-supported by the qualitative data collected, providing valuable insights for stakeholders involved in health technology innovations.

This study contributes to the field by highlighting the critical role of human factors and perceptions in technology adoption, offering guidance for designing more user-friendly, acceptable systems that promote better health outcomes through effective integration.

In summary, these two studies exemplify how rigorous research methods can reveal vital insights into complex issues—be it neurological assessment or healthcare technology utilization—adding valuable knowledge to support evidence-based practice and inform future research and policy decisions.

References

• Velayutham, S. G., Chandra, S. R., Bharath, S., & Shankar, R. G. (2017). Quantitative balance and gait measurement in patients with frontotemporal dementia and Alzheimer diseases: A pilot study. Indian Journal of Psychological Medicine, 39(2), 203-213. https://doi.org/10.4103/psychiatry.ijpsym_332_16
• Pals, R. S., Hansen, U. M., Johansen, C. B., Hansen, C. S., Jørgensen, M. E., Fleischer, J., & Willaing, I. (2015). Making sense of a new technology in clinical practice: A qualitative study of patient and physician perspectives. BMC Health Services Research, 15(1), 1-10. https://doi.org/10.1186/s12913-015-0958-2