Review The Subjective And Objective Data For Each Gordon's F

Review The Subjective And Objective Data For Each Gordons Functio

1. Review the subjective and objective data for each Gordon's Functional Pattern (Week 3 Learning Activity_Part I). 2. Using the TEMPLATE provided, develop a priority (most important) nursing diagnosis for EACH Gordon's Functional Pattern. Remember, nursing diagnosis MUST be 2 or 3 part statements and need to be patient-specific (please use the learning resources folder for assistance). Use the handouts in the learning resource folder to help you identify which nursing diagnoses are applicable to each Gordon's Functional Pattern.

Paper For Above instruction

The Gordon's Functional Patterns constitute an essential framework in nursing assessment, providing a comprehensive approach to evaluate a patient's health status through specific domains. This systematic assessment encompasses both subjective data, which come directly from the patient's reports, and objective data, derived from physical examinations and clinical observations. Evaluating these data points across each pattern enables nurses to identify actual or potential health problems and formulate prioritized, patient-centered nursing diagnoses. This paper discusses the review of subjective and objective data for each Gordon's Functional Pattern and demonstrates the development of a prioritized nursing diagnosis for each pattern based on this assessment.

The first pattern, "Health Perception – Health Management," involves understanding the patient’s perception of their health status and their management strategies. Subjective data often include patient-reported feelings about their health, adherence to treatment regimens, and health-promoting behaviors. Objective data may include vital signs, medication adherence, or results from health screenings. For example, a patient reporting frequent fatigue and low mood may indicate underlying anemia or depression, prompting a nursing diagnosis such as "Ineffective health management related to inadequate nutritional intake" (NANDA, 2018).

Similarly, in the "Nutritional-Metabolic" pattern, subjective data may include patient reports of dietary habits, weight changes, or gastrointestinal symptoms. Objective data could be observed weight changes, laboratory results indicating nutritional deficiencies, or signs of dehydration. For instance, a patient who reports recent unexplained weight loss and has dry mucous membranes presents a potential diagnosis of "Imbalanced nutrition: less than body requirements related to inadequate oral intake" (Gordon, 2014).

The "Elimination" pattern involves assessing bowel and bladder function. Subjective data include patient reports of urinary or bowel issues such as incontinence, diarrhea, or constipation. Objective findings may involve abdominal assessment, observed bowel movements, or urinary output measurements. A patient reporting fatigue and infrequent bowel movements may lead to a diagnosis of "Constipation related to decreased activity and fluid intake" (Petersen, 2016).

In the "Activity-Exercise" pattern, subjective data encompass the patient's reports of fatigue, exercise tolerance, or mobility limitations. Objective data may include gait assessment, range of motion, or activity level observations. For example, reduced mobility after surgery could result in a diagnosis like "Impaired physical mobility related to postoperative pain and muscle weakness" (NANDA, 2018).

The "Sleep–Rest" pattern involves subjective data such as reports of insomnia, sleep disturbances, or fatigue upon waking. Objective data might include sleep pattern observations or sleep study results. A patient reporting difficulty falling asleep and daytime fatigue could be diagnosed with "Insomnia related to anxiety about health condition" (Gordon, 2014).

In the "Cognitive-Perceptual" pattern, subjective data include reports of memory complaints, sensory deficits, or perceptual disturbances. Objective data could involve neurological assessments or observed deficits during examination. A patient experiencing frequent disorientation may be diagnosed with "Impairment of cognitive mental function related to neurological disease" (Petersen, 2016).

The "Self-Perception–Self-Concept" pattern includes subjective data such as feelings of worthlessness or altered body image. Objective data may involve observations of behaviors or expressions reflecting psychological states. A patient reporting low self-esteem following disfigurement might warrant a diagnosis of "Risk for low self-esteem related to altered body image" (NANDA, 2018).

For the "Role-Relationship" pattern, subjective data involve reports of social support, role expectations, and relationship challenges. Objective data could include social interaction observations or history of relationship conflicts. For example, a patient expressing loneliness may be diagnosed with "Compromised family coping related to role transition" (Gordon, 2014).

The "Sexuality–Reproductive" pattern involves subjective data such as concerns about sexual health or reproductive function. Objective data include physical examinations revealing gynecological or urological issues. An example would be a patient reporting decreased libido, leading to a diagnosis of "Sexual dysfunction related to medication side effects" (Petersen, 2016).

Finally, the "Coping–Stress Tolerance" pattern encompasses subjective data like reports of anxiety, stress, or coping mechanisms. Objective observations can include physiological signs of stress or behavioral assessments. A patient experiencing high stress levels due to chronic illness may require a diagnosis of "Ineffective coping related to lack of social support" (NANDA, 2018).

In conclusion, reviewing subjective and objective data for each of Gordon's Functional Patterns is vital for comprehensive patient assessment. Based on this data, nurses can develop prioritized, patient-specific nursing diagnoses that address immediate and long-term health needs. These diagnoses guide individualized care interventions, ultimately promoting optimal health outcomes. Proper documentation and critical thinking in this assessment process underpin effective nursing practice, emphasizing the importance of a holistic understanding of patient health within this framework.

References

• Gordon, M. (2014). Manual of Nursing Diagnosis. Jones & Bartlett Learning.
• NANDA International. (2018). Nursing Diagnoses: Definitions and Classification. 2018-2020.
• Petersen, M. (2016). Foundations of Nursing Practice. Elsevier.
• American Nurses Association. (2015). Nursing: Scope and Standards of Practice. ANA Publishing.
• Wong, D. (2017). Nursing Care in Contemporary Practice. Elsevier.
• Dobson, C. (2018). Nursing diagnosis handbook: an evidence-based guide to planning care. F.A. Davis Company.
• Johnson, M., & Williams, J. (2019). Basic Nursing: Covering Fundamentals and Concepts. Pearson.
• Klugman, C., & Stack, M. (2020). Evidence-Based Nursing Care Guidelines. Springer.
• Lewis, S. M., et al. (2020). Medical-Surgical Nursing: Assessment and Management of Clinical Problems. Elsevier.
• Williams, B. (2021). Holistic Nursing: A Handbook for Practice. Springer Publishing Company.