Journal of personality assessment最新文献

Emerging research highlights the significant role of happiness orientations (i.e., preferred and prioritized ways of pursuing happiness) in well-being and psychosocial functioning. Despite the increasing use of the Hedonic, Eudaimonic, and Extrinsic Motives for Activities (HEEMA) scale to measure happiness orientations across diverse populations, evidence is lacking regarding its measurement invariance, which leaves the validity of group comparisons in happiness orientation uncertain. Thus, we tested the measurement invariance of the HEEMA scale using data from 1,182 U.S. participants (ages 18-86) and 1,531 Chinese participants (ages 18-75). Results showed that the configural and metric invariance of the scale with four factors (i.e., pleasure, comfort, eudaimonic, and extrinsic orientations) was maintained across countries, age groups, and sex groups. Partial scalar invariance was established across countries, and full scalar invariance was established across age and sex groups. Among the invariant models, we found group differences in the levels of pleasure, comfort, eudaimonic, and extrinsic orientations. Moreover, these happiness orientations had differential associations with two criterion indicators: mental illness and proenvironmental behaviors. Our findings support the use of the HEEMA scale in U.S. and Chinese contexts and in different sex and age groups, and also demonstrate the distinction among four orientations.

The primary goal of this study was to develop a concise, theoretically grounded tool -the Holistic Wellbeing Measure (HWM)- that captures both hedonic and eudaimonic facets of wellbeing. Items for the HWM were generated through a careful review of existing wellbeing scales and literature, followed by expert consultation, pilot testing, and iterative refinement to ensure conceptual coverage, clarity, and face validity. Data were collected from three distinct samples: adolescents (n = 453), young adults (n = 361), and adults (n = 358). Exploratory and confirmatory factor analyses supported a two-factor structure, with 12 items reflecting independent but related hedonic and eudaimonic wellbeing dimensions. The measure demonstrated strong internal reliability and evidence of convergent, discriminant, and concurrent validity across all age groups. Regression analyses further indicated that the HWM contributed unique variance to the prediction of general health indicators (physical, social, and mental health) and psychological problems (depression, anxiety, and somatization), above the effects of gender, age, and psychological wellbeing. These results suggest that the HWM is a valid and reliable measure for assessing both aspects of wellbeing across age groups and can support strategies aimed at promoting overall mental health.

The Big Five Inventory-2 (BFI-2; Soto & John, 2017a) was developed to improve on the limitations of the original BFI by balancing the number of positively and negatively worded items and establishing a hierarchical structure for the Big Five traits. However, as the BFI-2 employs a Likert format with agree-disagree options, it suffers from common problems of the Likert format, including acquiescence bias and method effects due to the negatively worded items. In this research, we converted the BFI-2 into three alternative formats: Expanded, Item-Specific-Full, and Item-Specific-Light. These formats have tailored response options for each item and avoid the use of negatively worded items, thereby addressing the issues associated with the Likert format. Across two studies (N = 1,335 and N = 1,451), we randomly assigned Canadian undergraduate students to complete the BFI-2 in the original Likert format or one of the three alternative formats. Results showed that the Likert and alternative formats exhibit similar predictive validity. However, the alternative formats-particularly the Expanded format-showed better psychometric properties, including enhanced factor structure, increased reliability, and possibly reduced careless responding. We recommend that researchers consider adopting the BFI-2 in these alternative formats and adapting other Likert scales to these alternative formats.

The Fear of Failure as Motivation Scale (FOFAMS) addresses the motivational role of fear of failure, which existing measures typically overlook in favor of its negative effects. FOFAMS was developed using a rational-theoretical approach to fill this gap, offering a new tool for examining this aspect in achievement contexts. Two studies examined the scale's psychometric properties. Study 1 involved item development and an exploratory factor analysis, refining the scale by removing conceptually and psychometrically weaker items. Study 2, with samples of students (N = 385) and sports participants (N = 382), supported the unidimensional structure through confirmatory factor analysis and contributed evidence supporting the scale's construct validity. FOFAMS showed significant correlations with other constructs hypothesized to relate to fear of failure as motivation. This questionnaire provides a unique perspective, enhancing the understanding of fear of failure's positive influences on goal pursuit and achievement, and contributing to the broader nomological network of this construct.

Since its inception, the European Social Survey (ESS) has recognized the importance of studying human values because of their potential to contribute to our understanding of individuals and societies. All ESS rounds have included a shortened 21-item version of the Portrait Value Questionnaire (PVQ21) for measuring the 10 values of Schwartz's original theory and the underlying 4 higher-order dimensions. This scale has seen widespread use in value studies, not limited to those based on the ESS. In 2012, Schwartz and colleagues proposed a refinement of the theory that identified 19 narrower values derived from the original 10. This theory has been cited in thousands of studies. The present research explores whether single items of the PVQ21 can be used to properly measure the 19 values of Schwartz's refined theory. A sample of 645 Italian adults (56.1% females, M_age=34.66) completed the PVQ21 and the PVQ-RR, an instrument developed to measure the refined values. We examined the correspondence between each PVQ21 item and the refined values on both theoretical and empirical grounds. Results suggested that the PVQ21 allows researchers to effectively capture most refined values. We discuss findings regarding their implications, possibilities, and limitations for measuring the refined values in the ESS.

This paper presents five studies conducted on 3,644 participants to examine a questionnaire assessing stable individual differences in approach and avoidance motivation. In Study 1, we developed a gender-invariant measure of a multidimensional model of approach and avoidance motivation. In Study 2, we confirmed the factor structure and gender-invariant solution of the instrument and established its relationship with the Big Five Inventory 2 (BFI-2). In Study 3, we provided evidence of the convergent and divergent validity of the new questionnaire by comparing it with several established measures of approach and avoidance motivation. In Study 4, we demonstrated the incremental validity of the QAAM Anxiety scale over BFI Neuroticism and the Behavioral Inhibition System scale from the BIS/BAS Scales in predicting stress-related psychophysiological responses. In Study 5, the questionnaire was shown to be useful in predicting behavioral outcomes in an overearning experimental paradigm. Overall, the new instrument possesses adequate psychometric properties. With its theoretical framework based on a multidimensional model of approach and avoidance motivation, it has the potential to facilitate more experimental studies on the underlying processes of personality traits.

Psychological assessment remains a core competency in clinical psychology, yet its role in graduate training has become marginalized, with programs prioritizing brief test administration and rapid initiation of therapy over a comprehensive, integrative assessment designed to inform treatment planning. Despite calls to reestablish assessment as a cornerstone of clinical competence, few studies have examined the feasibility and clinical utility of structured, multimethod assessment models in university training clinics. This study evaluated a simplified, feasibility-oriented adaptation of Therapeutic Assessment-the Therapeutic Model of Assessment (TMA)-implemented in a university psychology clinic. A total of 194 adult patients (M = 29.5 years, 63% female) treated under the TMA model were compared with 52 patients (M = 27.8 years, 65% female) seen before its implementation. Patients in the TMA group showed significant reductions in depressive, anxious, and overall distress symptoms from the initial assessment to the feedback session. Dropout rates decreased from 37% to 16.5%, reflecting improved engagement and treatment retention. Among patients with personality pathology, dropout risk was significantly lower when TMA was implemented. Findings support the clinical utility of brief, multimethod assessment in training-clinic settings and its potential to enhance patient outcomes while reinforcing the relevance of assessment within psychology training.

Implicit motives have a clear relation to observed behavior but are time-consuming to measure. Automating the content coding of implicit motives has been a pursuit since the 1960s, but has not been widely adopted due to limitations with the marker-word approach that underpinned those automation attempts. More recent attempts use a machine-learning-based approach to automating implicit motive coding. In this paper, we report on a new transformer model, in which machine-predicted scores of the Winter (1994) training manual benchmark dataset achieve over or near .85 correlation with hand-coded scores, as measured by both Pearson and intraclass correlation coefficients. We additionally provide evidence of the convergent, divergent, causal, and criterion validity of the machine-predicted motive scores from our model, and make the model freely available for research via a web-based API.¹ Finally, we compare performance between our model and two recent transformer-based models. We hope that triangulation of evidence from independent, parallel automation efforts will kindle greater advancement in this emerging field of "motivational computing", in which computers are used to detect and study motives in real time.

Handling item wording effects within Likert-style, self-report questionnaires has long been a challenge when measuring psychological traits. When testing models for such traits, wording effects are commonly addressed by correlating uniquenesses for negatively and positively phrased items or including separate uncorrelated method factors for each effect. However, the magnitude of wording effects is rarely considered in such analyses or distinguished from effects of multiple sources of measurement error. In this article, we demonstrate how generalizability theory-based structural equation model designs are well suited for such purposes using results from all subscales within the Self-Description Questionnaire-III taken by a large sample of college students (n = 1,796) on two occasions. Results emphasized the importance of separating construct, item wording, and measurement error (specific-factor, transient, and random-response) effects for each individual subscale and the effectiveness of generalizability theory-based techniques in doing so. Within the most complete designs, average proportions of explained observed score variance were highest for targeted constructs, followed respectively by random-response error, transient error, specific-factor error, and item wording. We provide code in R for analyzing both generalizability theory and parallel conventional congeneric structural equation models to estimate construct, wording, and measurement error effects using both single- and multiple-occasion designs.