背景:高强度父母纠纷(HIPD)是一种普遍现象,对二元和家族细胞产生严重影响,在研究中受到相当多的关注,公共和专业话语。然而,系统在这一现象中的密集参与之间存在显著差距,以及他们表征和衡量定义它的基本概念的能力。
目的:本研究的目的是研究HIPD文献中认可的指标如何在参与该领域的社会工作者的实践中表现出来。更具体地说,将审查对参与HIPD的家庭进行评估的三个维度:争议强度,父子关系,儿童功能。
方法:样本包括199份由社会工作者撰写的关于被法院认为参与HIPD的家庭的书面报告。首先,使用演绎内容分析开发了每个维度的编码系统。第二,我们检查了指标的频率,并使用潜在类别分析(LCA)或潜在概况分析(LPA)确定了每个维度内质量不同的亚组.
结果:这些发现揭示了参与HIPD的夫妇的两个显著不同的群体,并揭示了亲子关系和儿童功能的共同特征。
结论:研究结果表明,没有单一的特征可以准确描述HIPD家庭生活的不同维度,相反,应该期望出现具有不同行为的子组。因此,研究结果强调了使用系统测量进行识别和评估的重要性,这可能有助于微调干预措施和优化资源分配。
High Intensity Parental Dispute (HIPD) is a universal phenomenon that has grave ramifications on the dyadic and familial cells, which are receiving considerable attention in the research, public and professional discourses. However, a significant gap exists between the intensive involvement of systems in this phenomenon, and their ability to characterize and measure cardinal concepts defining it.
The goal of the present study is to examine how indicators that are recognized in literature on HIPD are manifested in the practice of social workers involved in this sphere. More specifically, three dimensions included in evaluations on families involved in HIPD will be examined: dispute intensity, parent-child relationships, and child functioning.
The sample included 199 written
reports by social workers on families deemed by the court to be involved in HIPD. First, encoding systems for each dimension were developed using deductive content analysis. Second, the frequency of the indicators was examined and qualitatively different subgroups within each dimension were identified using Latent Class Analysis (LCA) or Latent Profile Analysis (LPA).
The findings uncovered two significantly different groups for couples involved in HIPD and revealed the common profiles for parent-child relationships and for child functioning.
The findings illustrate that there is no single characterization that can accurately describe different dimensions in the lives of families with HIPD, rather that subgroups with different behaviors should be expected to emerge. Thus, the findings emphasize the importance of using systematic measurements for identification and evaluation that could assist in fine tuning interventions and optimized resource allocation.