在老年护理工作人员中,对领导和管理清单II的探索性和确认性因素分析
Bernice Skytt1, Hans Högberg2, Maria Engström3
1Faculty of Health and Occupational Studies, University of Gävle, Gävle, Sweden and Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden.
Leadership in health services (Bradford, England)
|November 14, 2023
概括
领导力和管理库存 (LaMI) 证明了在评估瑞典老年护理人员领导力和管理绩效时的强有力的构造有效性和内部一致性. 这种经过验证的工具有助于确定管理发展的领域.
科学领域:
- 老年学是一门学科.
- 医疗保健管理的管理
- 组织心理学 组织心理学
背景情况:
- 在老年护理机构中,有效的领导和管理至关重要.
- 从员工的角度评估经理的绩效对于质量提高至关重要.
- 领导和管理清单 (LaMI) 是一个在这种情况下使用的工具.
研究的目的:
- 调查LaMI的构造有效性和内部一致性.
- 评估LaMI对瑞典老年护理工作人员的适用性.
- 确认LaMI在衡量领导和管理方面的可靠性.
主要方法:
- 利用来自老年护理人员的纵向问卷数据.
- 采用探索性因子分析 (n=1,149) 进行初始规模开发.
- 进行了确认因素分析 (n=1,061) 来验证结构.
主要成果:
- 探索性因子分析产生了两因素解决方案,解释了70.2%的差异.
- 确认因素分析支持在项目遗漏后改进的两因素模型.
- 最终的模型证明了可接受的合适性,证实了LaMI的结构.
结论:
- 拉米有效地衡量领导力和管理绩效.
- 该工具适用于持续评估管理人员的绩效.
- 调查结果支持使用LaMI来确定老年护理人员发展需求.
相关概念视频
Self-Report Tests of Personality
359
Self-report inventories are objective personality assessments that use multiple-choice items or numbered scales, typically ranging from 1 (strongly disagree) to 5 (strongly agree). They are often called Likert scales after Rensis Likert. These inventories are widely used due to their ease of administration and cost-effectiveness. One of the most prominent examples is the Minnesota Multiphasic Personality Inventory (MMPI), initially developed in the 1940s to assess abnormal personality traits.
359
Factorial Design
13.0K
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
13.0K
Longitudinal Research
12.0K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
12.0K
Obedience
32.9K
According to obedience research, we may harm others under the forceful pressures of an authority figure (Milgram, 1974). How about if the inappropriate orders were delivered with less force? The increasing interdependence between nurses and physicians compelled Hofling and his colleagues to explore nurses’ reactions to a potentially harmful medical request made by the perceived authority figure, the doctor (Hofling, Brotzman, Dalrymple, Graves, & Pierce, 1966). In this situation,...
32.9K
Nursing Evaluation
3.3K
The evaluation stage signals the end of the nursing process. The nurse gathers evaluative data to assess whether or not the patient has attained the expected results. Whereas the nurse collects data in the nursing assessment to identify the patient's health concerns, the evaluation stage data determines if the indicated health issues are resolved. Evaluative data collection includes two sections: the data acquired to evaluate patient outcomes and the time criteria for data collection.
3.3K
Two-Way ANOVA
2.6K
The two-way ANOVA is an extension of the one-way ANOVA. It is a statistical test performed on three or more samples categorized by two factors - a row factor and a column factor. Ronald Fischer mentioned it in 1925 in his book 'Statistical Methods for Researchers.'
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
2.6K


