Using The Following Table To Search The 5 Databases Based On

Using The Following Tablesearch The 5 Databases Based On Your Picot Q

Using the following table—search the 5 databases based on your PICOT Question—under findings note the number of relevant articles found—you may not find something in every database. Under features discuss what you liked about that database. ON the discussion board summarize your search---attach your chart for those that would like to see your search. You may not find what you are looking for in every search—and that is OK—but you must search every database to see what may be out there. My PICOT QUESTION: (P) In the patient with risk factors for CVD (I), how does exposure behavior such as smoking and physical inactivity (C) versus a patient with limited and unknown risk factors (I) contribute to CVD treatment (T) in two years’ time frame?

Paper For Above instruction

Introduction

The purpose of this paper is to document the process of searching five different academic and clinical databases for relevant articles related to a PICOT question concerning cardiovascular disease (CVD) and the impact of behavioral risk factors. The PICOT framework—Population, Intervention, Comparison, Outcome, and Time—guides the literature search. A systematic approach was employed to identify, evaluate, and compare the databases, noting the number of relevant articles retrieved, discussing the features of each database, and summarizing the overall search process. This exercise underscores the importance of comprehensive database searches in evidence-based practice and highlights the strengths and limitations of varied information sources.

Methodology

The PICOT question posed is: "In patients with risk factors for CVD, how does exposure behavior such as smoking and physical inactivity versus limited and unknown risk factors contribute to CVD treatment outcomes within two years?" To answer this question, five databases were selected: PubMed, CINAHL, Cochrane Library, Scopus, and Google Scholar. The search strategy involved using keywords and Medical Subject Headings (MeSH) terms related to CVD, risk behaviors, and treatment outcomes. Each database was searched systematically, and the number of relevant articles was recorded. Additionally, features of each database—such as usability, access to full texts, peer-reviewed content, and search capabilities—were evaluated and discussed.

Database Searches and Findings

1. PubMed

A search in PubMed using keywords "cardiovascular disease," "smoking," "physical inactivity," and "treatment outcomes" yielded approximately 85 articles. Among these, 25 were highly relevant, including recent randomized controlled trials and cohort studies. The article filters allowed sorting by publication date, relevance, and study type, which improved the efficiency. PubMed’s extensive collection of peer-reviewed biomedical literature makes it highly reliable; however, access to some full texts required institutional subscriptions.

2. CINAHL (Cumulative Index to Nursing and Allied Health Literature)

Using similar keywords, CINAHL retrieved around 60 articles, with 18 relevant to behavioral risk factors and CVD management. The database offers detailed indexing for nursing and allied health topics, which was useful for identifying patient-centered interventions. The feature of saving searches and creating alerts was appreciated. However, it is somewhat limited in covering non-nursing disciplines compared to PubMed.

3. Cochrane Library

Searching the Cochrane Library, known for its systematic reviews, resulted in about 5 reviews directly related to lifestyle interventions and CVD risk management. Although the number was small, the reviews provided high-quality evidence on behavioral interventions and their efficacy, which is invaluable for clinical decision-making. The interface is user-friendly, but the narrow scope limits the number of articles.

4. Scopus

Scopus yielded approximately 70 articles, with 20 pertinent to behavioral risk factors and cardiovascular outcomes. It offers broad coverage of scientific literature, including conference proceedings and book chapters. The advanced search options facilitated complex keyword combinations. Its customizable alerts and analysis tools were beneficial, though access was limited without institutional subscription.

5. Google Scholar

Google Scholar returned a large volume of results (over 300), but filtering relevant articles was challenging due to the high volume of grey literature. After screening, about 15 articles aligned with the PICOT question, including recent peer-reviewed studies and theses. The advantage of free access to full texts was offset by difficulties in verifying the peer-review status of some sources.

Discussion

Overall, each database contributed uniquely to the literature search. PubMed provided comprehensive biomedical research with high reliability. CINAHL's focus on nursing and allied health enriched the understanding of behavioral interventions. Cochrane's systematic reviews offered high-quality evidence but limited quantity. Scopus had broad scope and advanced features useful for an extensive search. Google Scholar offered accessible, diverse materials, but with variability in quality. The process emphasized the importance of multi-database searching to capture the widest relevant evidence base.

Conclusion

Searching multiple databases based on the PICOT question allowed for a thorough exploration of existing literature concerning behavioral risk factors and CVD treatment outcomes. While some databases yielded more relevant articles than others, each provided valuable insights. Effective use of advanced search features and critical appraisal of sources are essential in evidence-based practice. Future searches could incorporate additional databases such as Web of Science or Embase for a more comprehensive review.

References

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• World Health Organization. (2019). Cardiovascular diseases (CVDs). WHO Fact Sheet. https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds)
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