Clinical Utility of the Rorschach Inkblot Method: Reframing the Debate

 

Phase		Period
1	1921- 1950s	The unbridled optimism period	This period was marked by widespread interest in the RIM, aided in part by these seminal publications of Schafer (1954)
2	1960s	Increasing skepticism period	widespread misuse of the test by clinicians (typically involving biased, impressionistic interpretation.
3	1974 onwards	The psychometrization period	Comprehensive System (CS) for RIM scoring and interpretation (subsequently revised and refined in 1986, and again in 1993). With the publication of Exner’s CS, a single overarching framework was adoptedby most (although not all) RIM users. The empirical foundation of the RIM was strengthened, and the test achieved a degree of respectability that it had not enjoyed for some time (see Meyer, 1999; Weiner, 1995, 2000a)
4	1996 onwards	Backlash period	began with Wood, Nezworski, and Stejskal’s (1996) critique of the RIM in general, and the CS in particular. Wood et al.’s challenge led to Exner’s (1996) published response in Psychological Science, and several interrelated dialogues ensued, with RIM proponents and critics exchanging sharply opposing views (e.g., Hunsley & Bailey, 1999; Viglione, 1999).   In the midst of these debates, two prominent journals published point–counterpoint exchanges specifically devoted to the RIM: the special series on “The Utility of the Rorschach for Clinical Assessment” in Psychological Assessment (Meyer, 1999), and the special section on “The Rorschach Test in Clinical Diagnosis” in the Journal of Clinical Psychology (Garfield 1947/2000; Weiner, 2000b).

Source: Clinical Utility of the Rorschach Inkblot Method: Reframing the Debate: Journal of Personality Assessment: Vol 77, No 1 (tandfonline.com)

Proposal defense

 After 4 years of sweat and tears, I have finally got through my proposal defense presentation.

Thank you, Lord, Jesus Christ and all the angels around me, I cannot do it without your grace. 

TOM as the theoretical Framework

 

TOM, weak central coherence and executive functioning difficulties are underlying cognitive features associated with Autism. These cognitive features effect the way students or children process in the environment including:

1.      Impairments recognizing the mental states (TOM) of others can result in difficulty understanding social interactions, relating to their peers and knowing what to do to fitting in.

2.    Hyper focus on the details of a lesson, piece of work or social situation (Weak central coherence) can result in difficulty understanding the big picture and coping when things change.

3.      Problems organizing and coordinating multiple tasks (Poor executive functioning) can lead to difficulty coping with the workload, prioritising and displaying flexibility in problem solving.

Rorschach Scoring system

 1. RIAP5

The unlimited-use RIAP5 generates a revised Interpretive Report that assists the clinician with scoring and interpretation. In addition, the program provides a Client Report—an abbreviated, individualized, and simplified version of the RIAP5 Interpretive Report—that is intended to be read and retained by the client.

https://www.parinc.com/Products/Pkey/361

Interpretive report: https://www.parinc.com/WebUploads/samplerpts/RIAP5IR.pdf

Client report: https://www.parinc.com/WebUploads/samplerpts/RIAP5CR.pdf

2. VIRTUAL PYSCHOLOGY

Rorschach Assistance Program (version 3.0.8) is a secured online application designed to assists professionals with the complex task of coding and interpreting the Rorschach Inkblot test in accordance with the latest theoretical and practical developments of Exner's Comprehensive System methodology. [A Rorschach Workbook for the Comprehensive System (Exner, 2001); The Rorschach: A Comprehensive System (Exner, 2003).]

 

RAP3 is a free online beta application. 

https://www.virtualpsychology.com

Free test:

https://openpsychometrics.org/tests/HEMCR/

https://psycho-tests.com/test/rorschach-inkblot

https://rorschach-inkblot-test.com/

https://quizterra.com/en/rorschach-inkblot-test

Rorschach test for ASD

Rorschach test, also called Rorschach inkblot test, projective method of psychological testing in which a person is asked to describe what he or she sees in 10 inkblots, of which some are black or gray and others have patches of colour. The test was introduced in 1921 by Swiss psychiatrist Hermann Rorschach. It attained peak popularity in the 1960s, when it was widely used to assess cognition and personality.

Rorschach test is useful with ASD patients because it doesn’t present classic problems that they usually encounter in other test, like: the tendency to interpret verbal items or written questions in a literal way; the difficulty in answering questions that are not directly related to them; the difficulty of focusing their attention on the test; the length of the test. The Rorschach test could be one of the most useful diagnostic tools to explore personality traits, eventual psychopathologic problems and the psychological functioning of the ASD patients.

Big Data analytics methods

 

SOurce: file:///C:/PHD/NOV%20DATA%20AI%20SCIENCE/Literature_Review_on_Big_Data_Analytics_Methods.pdf

1.CNN

 inspired from neural network model as a type of deep learning algorithm has a “convolutional layer” and “subsampling layer” architecture. Multi-instance data is deployed as a bag of instances in which each data point is a set of instances. CNN has been known with three features namely “local field,” “subsampling,” and “weight sharing” and comprised of three layers, which are input, hidden that consists of “convolutional layer” and “subsampling layer” and output layer. In hidden layer, each “convolutional layer” comes after “subsampling layer.” 

2. Deep neural network (DNN) 

A deep architecture in supervised data has been introduced with advances in computation algorithm and method, which is called deep neural network (DNN) [3]. It originates from shallow artificial neural networks (SANN) that are related to artificial intelligence (AI). DNN deploys a layered architecture with complex function to deal with complexity and high number of layers

3. Recurrent neural network (RNN) RNN

a network of nodes that are similar to neurons, was developed in 1980s. Each neuron-like node is interconnected with each other, and it can be divided into categories of input, hidden, and output neurons. The data will receive, transform, and generate results in this triple process.

Can we outgrow ASD?

 https://www.sciencedaily.com/releases/2019/03/190312075923.htm#:~:text=Summary%3A,require%20therapeutic%20and%20educational%20support.

Autism Spectrum Disorders in Sarawak:

 An Overview and Analysis of Educator Awareness, Training, Development Opportunities, and Challenges

https://www.tandfonline.com/doi/full/10.1080/1034912X.2020.1731433?needAccess=true

 http://scerts.com/