Conceptual and operational definitions of the defining characteristics of the nursing diagnosis Disturbed Sleep Pattern

Manzoli, Juliana Prado Biani; Correia, Marisa Dibbern Lopes; Duran, Érika Christiane Marocco

doi:10.1590/1518-8345.2582.3105

Cited by 4 publications

(4 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…3 Conceptual definitions make reference to the theoretical meaning of DCs, and operational definitions should be able to elucidate how a given concept can be applied, giving practical meaning to conceptual definitions, specifying what procedures should be performed to evaluate such DCs. 5,24 This review was performed following recommended criteria and, in addition to helping to determine the conceptual and operational definitions of the Disturbed Sleep Pattern ND (00198), 25 also provided support for the introduction of two additional DCs, namely daytime sleepiness and sleep deprivation.…”

Section: Methodsmentioning

confidence: 99%

Disturbed Sleep Pattern (000198): Content Analysis in Patients With Acute Coronary Syndrome

Manzoli

Montanari

Carvalho

et al. 2020

Texto contexto - enferm.

Self Cite

View full text Add to dashboard Cite

Objective: to analyze the content of the defining characteristics of the Disturbed Sleep Pattern Nursing Diagnosis (00198) in patients with Acute Coronary Syndrome. Method: content analysis performed by specialists who achieved a score equal to or greater than five, according to established criteria: clinical experience, teaching and/or research; participation in research groups; doctorate degree; master's degree; specialization and/or residency in cardiology and/or sleep and/or nursing classifications. Eight defining characteristics were evaluated for their relationship to population, relevance, clarity and accuracy. Descriptive statistics were performed to characterize the sample, binomial statistical test to establish if there is agreement between the experts and chi-square and Fisher's exact to establish associations between the evaluated items and the experts' variables. Results: 54 experts participated in the study. The defining characteristics validated by the experts were the following: dissatisfaction with sleep, feeling unrested, sleep deprivation, alteration in sleep pattern, unintentional awakening, difficulty initiating sleep and daytime sleepiness. There was a statistically significant association between evaluated items and the variables time of training, time of operation and punctuation. Conclusion: seven of the eight defining characteristics were considered valid after the application of binomial test. This study will contribute to the refinement of the Disturbed Sleep Pattern Nursing Diagnosis (000198) and may enable the improvement of the quality of care of patients hospitalized with Acute Coronary Syndrome regarding changes in sleep pattern. The content analysis stage will support the next stage of the validation process of the present diagnosis, the clinical validation.

show abstract

Section: Methodsmentioning

confidence: 99%

Disturbed Sleep Pattern (000198): Content Analysis in Patients With Acute Coronary Syndrome

Manzoli

Montanari

Carvalho

et al. 2020

Texto contexto - enferm.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Good sleep health with the right quality and quantity is recognized as an indicator of vitality, mental, emotional and physical health that leads to a good quality of life. Meanwhile, persistent lack of sleep can cause changes in physical health, leading to more serious conditions and even death [2].…”

Section: Introductionmentioning

confidence: 99%

The Prevalence and Association of Stress with Sleep Quality during the COVID-19 Pandemic among Medical Students at Airlangga University

Nugraha

Fidiana

Khairina

et al. 2023

International Journal of Advanced Health Science and Technology

View full text Add to dashboard Cite

The COVID-19 pandemic requires students to adapt to circumstances and cause various kinds of psychological problems during a pandemic outbreak. Some may experience stress, insomnia or hypersomnia. There are many factors causing poor sleep quality in students, including psychological problems such as stress which can worsen the quality of student’s sleep during the COVID-19 pandemic. This study aims to prove that there is a relationship between stress and the sleep quality of medical students at Airlangga University during the COVID-19 pandemic. This study is an observational analytic study using the cross-sectional design to assess the relationship between stress and sleep quality of respondents using the Pittsburgh Sleep Quality Index (PSQI) and Depression, Anxiety, Stress Scale - 42 (DASS-42) questionnaires. The research subjects were active pre-clinical students in the medical study program, Faculty of Medicine, Airlangga University, totaling 280 students who were divided into 3 batches, namely Class of 2019, Class of 2020, and Class of 2021. From the results of the study, it was found that 84.7% of students experienced poor sleep quality and a normal stress level of 55.5%. Sleep quality and stress levels are related to each other. This is proven by the Spearman rank analysis, which shows sleep quality is related to the stress level with a p-value = 0.000 and rho = 0.230. Based on these results, it was concluded that sleep quality and stress level have a positive correlation.

show abstract

“…Esta fase caracteriza-se pela presença de sonhos e movimentos corporais. Enquanto o sono NREM, que ocupa cerca de 75% do ciclo do sono, é divido em três estágios (N1, N2 e N3), sendo o último estágio o mais profundo (Santos et al, 2014, Manzoli et al, 2018.…”

Section: Introductionunclassified

Avaliação dos Distúrbios do Sono de pacientes submetidos à Polissonografia

Barbosa

Souza

Müller

et al. 2021

RSD

View full text Add to dashboard Cite

Objetivo: caracterizar os distúrbios do sono dos pacientes submetidos à polissonografia e identificar suas associações com variáveis epidemiológicas. Métodos: estudo transversal, observacional, conduzido com análise de dados dos prontuários de 101 pacientes submetidos a polissonografia no Laboratório de Medicina do Sono do HUMAP, Campo Grande, MS. Os dados utilizados foram os laudos da polissonografia e escalas padronizadas (escala de sonolência de Epworth e Questionário de Berlim). Resultados: O alto risco para Síndrome da Apneia Obstrutiva do Sono (SAOS) foi identificado em 83% dos avaliados. Quanto ao perfil polissonográfico, 77% foram diagnosticados com SAOS, sendo a maioria representada pelo sexo feminino. Dos pacientes com SAOS, 95,5% apresentava obesidade ou sobrepeso. A Sonolência Excessiva Diurna foi identificada em 51,2% dos pacientes com diagnóstico de SAOS. Conclusão: A prevalência de distúrbios do sono foi elevada, sendo que os pacientes com diagnóstico de SAOS, maioria sexo feminino, apresentaram com maior frequência SED, sobrepeso ou obesidade e Hipertensão Arterial Sistêmica, fatores de risco importantes para a síndrome respiratória.

show abstract

Conceptual and operational definitions of the defining characteristics of the nursing diagnosis Disturbed Sleep Pattern

Cited by 4 publications

References 29 publications

Disturbed Sleep Pattern (000198): Content Analysis in Patients With Acute Coronary Syndrome

Disturbed Sleep Pattern (000198): Content Analysis in Patients With Acute Coronary Syndrome

The Prevalence and Association of Stress with Sleep Quality during the COVID-19 Pandemic among Medical Students at Airlangga University

Avaliação dos Distúrbios do Sono de pacientes submetidos à Polissonografia

Contact Info

Product

Resources

About