The Effect of Human Care Model-Based Nursing Interventions on Psychosocial Adjustment in Patients With Cardioverter Defibrillator
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 64
- 试验地点
- 2
- 主要终点
- Increasing the patient's psychosocial adjustment with ICD
研究概览
简要总结
The aim of the randomized controlled interventional study was to to evaluate the effect of human care model-based nursing interventions on psychosocial adaptation in patients with cardioverter defibrillator. A study was carried out on a sample of 64 patients who had been implanted with a defibrillator. The intervention group participants underwent six interviews at two-week intervals, during which a hybrid and structured nursing intervention was administered.
详细描述
Aim: The aim of this research was to investigate the impact of nursing interventions that were Watson's Human Care Model- based nursing interventions on the psychosocial adjustment of patients who have undergone implantable cardioverter defibrillator (ICD) implantation.
Design: The present study employs a randomized controlled design with a pretest-posttest control group, conducted over a period spanning from March 2020 to July 2022.
Methods: The research was carried out utilizing an implantable cardioverter on individuals who met the inclusion criteria and provided consent to participate in the study at an adult cardiology outpatient unit located within a university hospital. A study was carried out on a sample of 64 patients who had been implanted with a defibrillator. The intervention group participants underwent six interviews at two-week intervals, during which a hybrid and structured nursing intervention was administered. The data were gathered utilizing an introductory information form and the Psychosocial Adjustment to Illness-Self-Report Scale (PAIS-SR). The statistical methods employed in the data analysis included the chi-square test, t test for independent groups, Mann-Whitney U test, t test for dependent groups, and Wilcoxon signed-rank test.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Supportive Care
- 盲法
- Single (Participant)
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •the patient must be of legal age
- •the patient must have undergone ICD implantation at least one month prior
- •the patient must possess the ability to comprehend and communicate in Turkish
- •the patient must not exhibit any hearing or speech impairments
- •the patient must not have received a medical diagnosis of a neurological or psychiatric condition that may impact cognitive function, such as Alzheimer's or schizophrenia
- •the patient must possess the capability to operate a computer, telephone, and internet
排除标准
- •the patient is less than 18 years old
- •the patient has hearing and speech problems
- •the patient must have received a medical diagnosis of a neurological or psychiatric condition that may impact cognitive function, such as Alzheimer's or schizophrenia
- •the patient must not possess the capability to operate a computer, telephone, and internet
- •the patient's refusal to participate in the study
结局指标
主要结局
Increasing the patient's psychosocial adjustment with ICD
时间窗: 10 week later
Psychosocial Adjustment to Illness Scale -Self Report (PAIS-SR) scale was used. This scale is a multidimensional scale that evaluates psychosocial adjustment to the disease. There are 7 different subscales of the scale that enable the determination of psychosocial adjustment, and the scale consists of a total of 46 items. These subscales are as follows; Orientation to Healthcare, Vocational Environment, Domestic Environment, Sexual Relationships, Extended family Relationships, Social Environment and Psychological distress. The minimum and maximum scores obtained from the scale are between 0-138. The higher the score, the worse the fit. Scores below 35 from the scale indicate good psychosocial adjustment, scores between 35-51 indicate moderately good psychosocial adjustment, and scores above 51 indicate poor adjustment.
次要结局
未报告次要终点
研究者
Ozgur Demir Gayretli
Principal Investigator
Ege University