Today, technology has become an integral part of nursing care and its significance to addressing topical and acute health concerns should not be underestimated. To illustrate, the professionals in the field pay specific attention to nursing informatics. This discipline is an opportunity to generate the knowledge in order to utilize the relevant and efficient updates into the practice, namely, the underpinning of clinical information systems and their appropriateness to provide high-quality and up-to-date care to the patients (Nelson & Staggers, 2015). In this respect, informatics is at the core of instant upgrading the practical domain with the recent evidence of improvements in care through the relevant research data. Therefore, the purpose of this paper is to summarize the four-step process of the data, information, knowledge, and wisdom continuum (DIKW) as it applies to major depression.

Clinical Question

Major depressive disorder is a complex worldwide phenomenon, while the prevalence of the condition varies per countries. For instance, the percentage of people who are affected by the disorder at one point in their life varies from 7% in Japan to 21% in France, with higher rates among females (Kessler & Bromet, 2013). In addition, the complexity of the problem relates to the fact that it can negatively affect person’s family, work or school life, sleeping or eating habits, and general health among other issues (American Psychiatric Association [APA], 2013). Moreover, depression correlates with complications related to existing patients’ disease and suicide thinking and attempts (APA, 2013). At the same time, around two-thirds of those who suffer from depression do not recognize its severity and tend to ignore their condition. Hence, depression is a significant healthcare problem that requires attention of healthcare specialists due to its complicated character and disease burden, including direct medical costs, suicide-related cost linked to mortality, and the loss from patients’ non-productivity. Nevertheless, a universal approach to treating the condition with long-term implications is yet to be developed.

For this reason, reference to a PICO approach is to develop answerable clinical questions that will help to develop the keywords for search terms in the scope of conducting the research. Specifically, it is reasonable to clarify whether in patients with depression, group therapy is more effective as compared with standard intervention (e.g. antidepressants) (over the 2 months).

FREE extras
  • Cover page
  • Table of contents
  • Revision (during 48 hours)
  • Outline (on demand)
  • Plagiarism report (on demand)
We Guarantee
  • On-time delivery
  • Supreme quality products
  • No hidden charges
  • 24/7 customer support
  • No-plagiarism guarantee

DIKW Continuum

Nowadays, nurses and physicians are seeking the way of gaining the wisdom and applying this wisdom in their daily practice. In this context, application of DIKW framework is more than relevant. With the developed PICO question, the primary databases used for the research include PubMed, Cochrane Database of Systemic Reviews, as well as CINAHL & MEDLINE Simultaneous Search. Some of the keywords formulated during the search process are “major depression and group therapy,” “[major] depression and standard treatment,” “[major] depression treatment.” All the databases provided the scholarly articles on depression-related topics according to the searched terms that were organized with respect to the 5-year period of datedness to ensure that I consider the most recent evidence on the topic. For instance, Cochrane Library showed 34 reviews for “[major] depression and standard treatment” query. On the other hand, PubMed identified 1,449 articles published within the last 5 years “major depression and group therapy”, including clinical trials and reviews, though there was a need to filter the obtained results for relevance of the content. Similarly, the other search results required sorting the articles per relevance, especially due to narrow-specific research focus, such as handling depression after stroke, because of terminal disease (e.g. cancer), or based on smoking cessation, to list a few. 


Drawing upon the rationale by Nelson and Staggers (2015), data entails objective summary of discrete entities described without interpretation. In this regard, the data concerned with major depression were related to statistical scale and significance of the problem embodied in numerical representation of its context. Based on the search, some articles showed that among around 350 million people suffering from depression globally, the prevalence and burden of disease comprises approximately 50% higher for women than men. Moreover, behavior activation, as a form of cognitive behavioral therapy, is a popular approach to address the disease that attracts sufficient practitioners’ interest nowadays. In addition, some scholars pay great attention to application of new or ‘well-tested old’ antidepressants, e.g. fluoxetine. Such data serve as the basic for clarifying further information. In any case, the data evidenced that the problem exists and it is of crucial importance for patient quality life and care.


However, the data cannot provide the full picture of the illness as one has to transform the raw discrete entities into the information, namely, interpreted, organized and structured data (Nelson & Staggers, 2015). For example, with respect to the previously provided examples of the search results, the obtained data about the multiple aspects of major depression and the approaches to its treatment, which are of particular interest in the scope of the PICO question, were categorized and organized. In this way, a more complete view regarding the researched phenomenon could be drawn through structuring the information.


In the data-information-knowledge-wisdom system, understanding, interpreting and integrating of information facilitate the transitioning of applied information, which is knowledge (Nelson & Staggers, 2015). Specifically, the information synthesized on the verge of the collected sources allowed distinguishing the risk factors for acquiring depression, such as gender or particular disease or disability, along with most recent findings concerned with treatment of the disorder and its verified efficacy. At the same time, the search-based inquiry demonstrated the unambiguous character of pharmacologic therapy, which enables to reveal the need for interprofessional collaboration in the treatment of depression due to uncertain results of a standard approach.


Future strategic decisions require the proper utilization of knowledge that focuses on the application of knowledge in order to establish solutions and management protocols to complex patient issues and needs (American Nurses Association [ANA], 2015). The issue is more than evident with a focus on the research problem. Undoubtedly, the DIKW process showed the complexity of the disorder and medical considerations over its elimination. Thus, each particular case within the clinical environment should be well-reasoned, with individual approach to each patient because of potential risk factors, existing comorbidities, and relevance of treatment methods among others.  


This paper examined major depression through the formulating of clinical questions and relating them to the four-step process of data, information, knowledge, and wisdom (DIKW). The analysis revealed the notable mediating role of nursing informatics as an opportunity for acquiring wisdom for development of solutions to address major depression in a holistic manner. The step-by-step analysis clearly showed that all the elements of the DIKW system are inextricably linked. Moreover, reference to informatics resources was valuable to understand that it is crucial for follow each stage of the framework gradually, in sequence, and in a well-thought-out manner to gain wisdom in order to enhance the approach to treating depression effectively.  

Price Quote


Special price: 00.00 $10.99

Save 15% OFF on your 1st order


Related essays

  1. Innovative Nursing
  2. Rule of Data Mining In Healthcare
  3. Congestive Heart Failure
  4. Deaf, Dumb and Disabled People