We investigated the classification accuracy of the Inventory of Problems − 29 (IOP-29), its newly developed memory module (IOP-M) and the Fifteen Item Test (FIT) in an Australian community sample (...

An Australian study on feigned mTBI using the Inventory of Problems - 29 (IOP-29), its Memory Module (IOP-M), and the Rey Fifteen Item Test (FIT).

While the psychometric equivalence of computerized versus paper-and-pencil administration formats has been documented for some tests, so far very few studies have focused on the comparability and validity of test scores obtained via in-person versus remote administrations, and none of them have researched a symptom validity test (SVT). To contribute to fill this gap in the literature, we investigated the scores of the Inventory of Problems-29 (IOP-29) generated by various administration formats. More specifically, Study 1 evaluated the equivalence of scores from nonclinical individuals administered the IOP-29 remotely (n = 146) versus in-person via computer (n = 140) versus in-person via paper-and-pencil format (n = 140). Study 2 reviewed published IOP-29 studies conducted using remote/online versus in-person, paper-and-pencil test administrations to determine if remote testing could adversely influence the validity of IOP-29 test results. Taken together, our findings suggest that the effectiveness of the IOP-29 is preserved when alternating between face-to-face and online/remote formats.

/pdf/comparability-and-validity-of-the-online-and-in-person-iw28dopuwl.pdf

Comparability and Validity of the Online and In-Person Administrations of the Inventory of Problems-29.

Assessing Negative Response Bias with the Inventory of Problems-29 (IOP-29): a Quantitative Literature Review

ABSTRACT This study was designed to examine alternative validity cutoffs on the Boston Naming Test (BNT). Archival data were collected from 206 adults assessed in a medicolegal setting following a motor vehicle collision. Classification accuracy was evaluated against three criterion PVTs. The first cutoff to achieve minimum specificity (.87-.88) was T ≤ 35, at .33-.45 sensitivity. T ≤ 33 improved specificity (.92-.93) at .24-.34 sensitivity. BNT validity cutoffs correctly classified 67–85% of the sample. Failing the BNT was unrelated to self-reported emotional distress. Although constrained by its low sensitivity, the BNT remains a useful embedded PVT.

Failing Performance Validity Cutoffs on the Boston Naming Test (BNT) Is Specific, but Insensitive to Non-Credible Responding

This systematic review was performed to summarize existing research on the symptom validity scales within the Trauma Symptom Inventory–Second Edition (TSI-2), a relatively new self-report measure designed to assess the psychological sequelae of trauma. The TSI-2 has built-in symptom validity scales to monitor response bias and alert the assessor of non-credible symptom profiles. The Atypical Response scale (ATR) was designed to identify symptom exaggeration or fabrication. Proposed cutoffs on the ATR vary from ≥ 7 to ≥ 15, depending on the assessment context. The limited evidence available suggests that ATR has the potential to serve as measure of symptom validity, although its classification accuracy is generally inferior compared to well-established scales. While the ATR seems sufficiently sensitive to symptom over-reporting, significant concerns about its specificity persist. Therefore, it is proposed that the TSI-2 should not be used in isolation to determine the validity of the symptom presentation. More research is needed for development of evidence-based guidelines about the interpretation of ATR scores.

/pdf/detecting-negative-response-bias-within-the-trauma-symptom-39ad8l090m.pdf

Detecting Negative Response Bias Within the Trauma Symptom Inventory–2 (TSI-2): a Review of the Literature

A growing literature indicates that to evaluate the credibility of a clinical presentation it would be optimal to rely on multiple sources of information, and use both symptom validity tests (SVTs) and performance validity tests (PVTs) whenever possible In this paper, we present the development and initial validation of a PVT module designed to be used in combination with a free-standing SVT Named Inventory of Problems – Memory (IOP-M), this new PVT module is given to the examinee immediately after completing the Inventory of Problems – 29 (IOP-29) It consists of a 34-item, two-alternative, forced-choice, implicit recognition test Results from 360 nonclinical volunteers – 192 instructed to respond honestly (honest controls) and 168 instructed to feign mental illness (experimental simulators) – suggest that the IOP-M has the potential to yield incremental validity over using the IOP-29 alone In fact, a series of hierarchical logistic regressions using group as criterion variable (0 = honest control; 1 = experimental simulator) and the IOP-29 and IOP-M as predictors showed that the models including both measures significantly improved classification accuracy over those including the IOP-29 only, Δχ2 ≥ 191, p < 01 When considering the optimal cut scores for each measure, only 6 of the 168 simulators (ie, less than 4%) passed both the IOP-29 and IOP-M, and only 3 of the 192 honest responders (ie, less than 2%) failed both A closer examination of false positive classifications, however, revealed that the IOP-M could be prone to false positive errors in examinees with moderate to severe cognitive impairment

SVT Meets PVT: Development and Initial Validation of the Inventory of Problems – Memory (IOP-M)

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Anna Maffei

Author Tools

Chat about Author

Papers

SVT Meets PVT: Development and Initial Validation of the Inventory of Problems – Memory (IOP-M)