Assessment of response bias in personality disorder research.

Abstract

Most research on personality disorders (PDs) relies upon self-reported information, commonly collected via standardized self-report inventories or structured interviews. Such data might, for instance, be culled from archival records from applied evaluative contexts or collected as part of dedicated anonymized research studies. Many factors-such as disengagement, distractibility, or motivation to appear in a certain manner-may influence whether self-reported information accurately reflects an examinee's genuine personality characteristics. Despite resultant risks to the validity of collected data, very few measures used in PD research include embedded indicators of response validity. In this article, we review the need for validity measures and strategies that exist to identify invalid self-report data, and we offer several suggestions for PD researchers to consider in order to detect invalid self-reported information and improve the quality of their data.

Check and report: The state of data validity detection in personality disorder science.

“…However, the state of invalid data detection in both PD science and the larger field of clinical psychology offers ample room for improvement. We conclude our review by adding to a growing chorus of voices offering recommendations for improving data validity (e.g., Burchett et al, 2022) as well as calling for PD science to adopt standardized practices for reporting the methods and outcomes of invalid data detection.…”

“…CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) remains a first line of defense against automated responding. Another technique is to disallow multiple responses from the same IP address (Burchett et al, 2022). Online survey platforms such as MTurk and Prolific also include reputation tools, which allow researchers to narrow their recruitment pool to individuals with a history of providing high-quality responses (Peer et al, 2014).…”

“…Although studies have examined the rate of invalid responding on the MMPI across a variety of sample types (e.g., Gu et al, 2017), we are unaware of any large-scale systematic evaluations of invalidity rates among forensic or clinical samples using open-source methods of detection 2 . This omission is particularly striking in the PD literature due to the hypothesis that high levels of specific maladaptive traits might contribute to response bias (Burchett et al, 2022; cf., Ray et al, 2013; Sleep et al, 2017). Although Maniaci & Rogge (2014) cautioned against overinterpretation of small (but robust) negative associations between attention and traits of Conscientiousness, Agreeableness, and Openness, the impact of these trends might warrant some intervention or examination when moving beyond the normative range of personality function.…”

“…Embedded Validity Scales. Burchett et al (2022) reviewed the empirical evidence for the utility of embedded validity scales in several lengthy, commercial personality assessment instruments. Research using the MMPI-3, PAI, Revised NEO Personality Inventory, or Psychopathic Personality Inventory-Revised (Lilienfeld & Widows, 2005) appears well positioned to identify both content-dependent and content -independent invalid responding.…”

The Structure of Pathological Personality Traits and Temperament in a Persian Community Sample

“…To address concerns with validity of self-reported personality pathology (Burchett et al, 2023;Sharpe et al, 2023), we screened for inconsistent responding by examining discrepancies between 20 PID-5 item pairs (Keeley et al, 2016). Possible inconsistency scores range from 0 (perfectly consistent) to 60 (perfectly inconsistent); 45 of our participants (5%) had scores above the suggested cutoff of 20 and were excluded from all ESEM analyses (Figure S2 shows a histogram of inconsistency scores).…”