MMPI-2-RF Profiles in Child Custody Litigants

Feasibility of Predicting In-Season Mental Health Problems in College Student-Athletes From Pre-season Assessment

OBJECTIVE

To examine whether pre-season assessment using a validated assessment tool, the Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF), could predict college student-athletes identified as experiencing in-season mental health (MH) problems.

DESIGN

A prospective study of athletes who completed a pre-season evaluation in August 2018.

SETTING AND PARTICIPANTS

A total of 195 National Collegiate Athletic Association Division 1 student-athletes from a large midwestern university in northeast Ohio.

INDEPENDENT VARIABLE

The MMPI-2-RF, a 338-item self-report measure of constructs relevant to the assessment of psychopathology and personality.

MAIN OUTCOME MEASURE

Mental health problems of student-athletes tracked throughout the competitive season (August 2018-May 2019) by a team of athletic department personnel who met weekly with a licensed clinical psychologist.

RESULTS

In pre-season assessment, 71.8% of athletes clinically elevated at least one MMPI-2-RF scale and underreporting was higher in student-athletes than normative controls. Pre-season levels of internalizing psychopathology, diffuse physical symptoms, and unusual thoughts predicted increased likelihood of experiencing MH problems during the competitive season.

CONCLUSIONS

The current findings suggest that the MMPI-2-RF may be a promising tool for identifying student-athletes at risk for MH concerns.

Detecting faking-good response style in personality questionnaires with four choice alternatives

Deliberate attempts to portray oneself in an unrealistic manner are commonly encountered in the administration of personality questionnaires. The main aim of the present study was to explore whether mouse tracking temporal indicators and machine learning models could improve the detection of subjects implementing a faking-good response style when answering personality inventories with four choice alternatives, with and without time pressure. A total of 120 volunteers were randomly assigned to one of four experimental groups and asked to respond to the Virtuous Responding (VR) validity scale of the PPI-R and the Positive Impression Management (PIM) validity scale of the PAI via a computer mouse. A mixed design was implemented, and predictive models were calculated. The results showed that, on the PIM scale, faking-good participants were significantly slower in responding than honest respondents. Relative to VR items, PIM items are shorter in length and feature no negations. Accordingly, the PIM scale was found to be more sensitive in distinguishing between honest and faking-good respondents, demonstrating high classification accuracy (80–83%).

The Development of a Short Version of the SIMS Using Machine Learning to Detect Feigning in Forensic Assessment

In the present study, we applied machine learning techniques to evaluate whether the Structured Inventory of Malingered Symptomatology (SIMS) can be reduced in length yet maintain accurate discrimination between consistent participants (i.e., presumed truth tellers) and symptom producers. We applied machine learning item selection techniques on data from Mazza et al. (2019c) to identify the minimum number of original SIMS items that could accurately distinguish between consistent participants, symptom accentuators, and symptom producers in real personal injury cases. Subjects were personal injury claimants who had undergone forensic assessment, which is known to incentivize malingering and symptom accentuation. Item selection yielded short versions of the scale with as few as 8 items (to differentiate between consistent participants and symptom producers) and as many as 10 items (to differentiate between consistent and inconsistent participants). The scales had higher classification accuracy than the original SIMS and did not show the bias that was originally reported between false positives and false negatives.

How Personality Relates to Distress in Parents during the Covid-19 Lockdown: The Mediating Role of Child's Emotional and Behavioral Difficulties and the Moderating Effect of Living with Other People

Since the initiation of the COVID-19 lockdown, Italian parents have been forced to manage their children at home. The present study aimed at investigating the psychological distress of parents during the lockdown, identifying contributing factors. An online survey was administered to 833 participants from 3 to 15 April 2020. Mediation and moderated mediation models were run to explore the association between parent neuroticism and parent distress, mediated by child hyperactivity–inattention and child emotional symptoms, and the moderating effect of living only with child(ren) on the direct and indirect effects of parent neuroticism on parent distress. For parents living only with child(ren), high levels of psychological distress depended exclusively on their levels of neuroticism. For parents living with at least one other person in addition to child(ren), distress levels were also mediated by child behavioral and emotional difficulties. Motherhood emerged as a significant factor contributing to greater distress. Furthermore, parent psychological distress decreased in line with increased child age. The results confirm that neuroticism is an important risk factor for mental health. Preventive measures should be primarily target multicomponent families with younger children and directed towards parents who are already known to present emotional instability and to parents of children who have received local mental health assistance for behavioral and/or emotional difficulties.

Use of mouse-tracking software to detect faking-good behavior on personality questionnaires: an explorative study

The aim of the present study was to explore whether kinematic indicators could improve the detection of subjects demonstrating faking-good behaviour when responding to personality questionnaires. One hundred and twenty volunteers were randomly assigned to one of four experimental groups (honest unspeeded, faking-good unspeeded, honest speeded, and faking-good speeded). Participants were asked to respond to the MMPI-2 underreporting scales (L, K, S) and the PPI-R Virtuous Responding (VR) scale using a computer mouse. The collected data included T-point scores on the L, K, S, and VR scales; response times on these scales; and several temporal and spatial mouse parameters. These data were used to investigate the presence of significant differences between the two manipulated variables (honest vs. faking-good; speeded vs. unspeeded). The results demonstrated that T-scores were significantly higher in the faking-good condition relative to the honest condition; however, faking-good and honest respondents showed no statistically significant differences between the speeded and unspeeded conditions. Concerning temporal and spatial kinematic parameters, we observed mixed results for different scales and further investigations are required. The most consistent finding, albeit with small observed effects, regards the L scale, in which faking-good respondents took longer to respond to stimuli and outlined wider mouse trajectories to arrive at the given response.

Indicators to distinguish symptom accentuators from symptom producers in individuals with a diagnosed adjustment disorder: A pilot study on inconsistency subtypes using SIMS and MMPI-2-RF

In the context of legal damage evaluations, evaluees may exaggerate or simulate symptoms in an attempt to obtain greater economic compensation. To date, practitioners and researchers have focused on detecting malingering behavior as an exclusively unitary construct. However, we argue that there are two types of inconsistent behavior that speak to possible malingering-accentuating (i.e., exaggerating symptoms that are actually experienced) and simulating (i.e., fabricating symptoms entirely)-each with its own unique attributes; thus, it is necessary to distinguish between them. The aim of the present study was to identify objective indicators to differentiate symptom accentuators from symptom producers and consistent participants. We analyzed the Structured Inventory of Malingered Symptomatology scales and the Minnesota Multiphasic Personality Inventory-2 Restructured Form validity scales of 132 individuals with a diagnosed adjustment disorder with mixed anxiety and depressed mood who had undergone assessment for psychiatric/psychological damage. The results indicated that the SIMS Total Score, Neurologic Impairment and Low Intelligence scales and the MMPI-2-RF Infrequent Responses (F-r) and Response Bias (RBS) scales successfully discriminated among symptom accentuators, symptom producers, and consistent participants. Machine learning analysis was used to identify the most efficient parameter for classifying these three groups, recognizing the SIMS Total Score as the best indicator.