Identifying latent classes about the changing trajectories of child maltreatment by child developmental period

2017 ◽  
Vol 59 ◽  
pp. 183-208
Author(s):  
Ji-hyeon Han ◽  
Ok-chae Choi
Author(s):  
Carmen García-Alba

This study is part of a larger research study (doctoral dissertation), in which a comparative study with adolescent samples is done: 50 anorexic restricting patients (ANP), 50 patients diagnosed with depression (DP) and 50 non patients (NP). The proposed objective is two-fold: 1) To try to clarify the existing relationship between Anorexia (AN) and Depression (D), investigated from diverse disciplines but without conclusive results. 2) To detect in the ANP personality different traits from those of other groups, which should, if possible, allow to detect them at an early stage for an adequate prognosis. The current article presents the Rorschach findings in relation to the cognitive functioning of the ANP. In them, the following has been detected: (1) An information processing similar to that of the other groups, even with a more complete (L ≤ .99), more complex (DQ+↑) and better discriminated (Zd↑) grasp of the stimulus; (2) Mediating processes very similar to those of the other groups, sharing with them the perceptive maladjustments (X–%↑) and an excessive individualism (Xu%↑); (3) A clearly differentiating ideation disorder. Definitely, the ANP use predominantly ideation (M↑), but their thought, usually well-adjusted (MQo↑), presents eventual operations of delusional type (MQnone↑). Above that, their thinking is marked by a great passivity (Mp↑), which makes them more vulnerable to accept ideas without criticizing them and it results in a very inefficient thinking, which spins around these concepts without finding solutions, entering into a sort of ruminating which is completely unproductive. The differences toward the obsessive pathology are established. The discriminant analysis conducted with all the Rorschach variables that resulted as significant throughout the research, provides quite a consistent function which discriminates the ANP: MQnone↑, Mp↑, FD↓, Ma↑, MQo↑, AdjD↑, Sum H↑, (H)↑. Based on this we can understand that these adolescents, being in a developmental period of big changes and disorientations in relation with their own image, confronted with life events, and possibly starting off with some biologic vulnerability: (1) Due to the alterations of their ideation, accept without criticism (Mp) irrational ideas dominating in our culture, in which slimness appears as the only model, synthesis of intelligence, beauty and success; remaining captured in this type of mental activity (MQnone), which they cannot escape nor criticize (Mp), despite they reason adequately on other topics (MQo); (2) Their alterations of self-perception [(H)] make them hide themselves in a fantasized image, which is the axis of their interests and the only thing that really matters to them; (3) The resources they have to decide on behaviors and to finish these deliberately (AdjD), and their scarce tendency to the introspection (FD) lead to their decision of not eating, based on distorted and passively accepted thinking, which has great power and thus, so difficult to modify. Finally, based on the Rorschach data obtained, the hypothesis of a personality disorder as underlying pathology is pointed out.


Methodology ◽  
2014 ◽  
Vol 10 (3) ◽  
pp. 100-107 ◽  
Author(s):  
Jürgen Groß ◽  
Ann Cathrice George

When a psychometric test has been completed by a number of examinees, an afterward analysis of required skills or attributes may improve the extraction of diagnostic information. Relying upon the retrospectively specified item-by-attribute matrix, such an investigation may be carried out by classifying examinees into latent classes, consisting of subsets of required attributes. Specifically, various cognitive diagnosis models may be applied to serve this purpose. In this article it is shown that the permission of all possible attribute combinations as latent classes can have an undesired effect in the classification process, and it is demonstrated how an appropriate elimination of specific classes may improve the classification results. As an easy example, the popular deterministic input, noisy “and” gate (DINA) model is applied to Tatsuoka’s famous fraction subtraction data, and results are compared to current discussions in the literature.


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