Domain-specific Factors Research Articles

Financial Capability, Financial Well-Being, and Life Satisfaction of Women in an Emerging Economy

Life satisfaction depends on several life aspects, such as relationships, achievements, health, and work satisfaction. Theorists and experts contend that domain-specific factors and behaviors predict domain-specific satisfaction. Our study examines life satisfaction from the standpoint of behavior finance indicators by incorporating financial capability factors such as financial literacy, financial management behavior, and financial self-efficacy as antecedents to financial satisfaction and financial stress. Financial satisfaction and financial stress are further assumed to predict life satisfaction. Data are collected from 308 working women using a self-administered questionnaire in three different waves in Pakistan. By examining the fitness of the measurement model, we proceeded toward path analysis of the structural equation model. All the hypothesized relationships are supported except the paths between financial literacy to financial stress and financial management behavior to financial satisfaction. The results and implications are presented based on the findings of the study.

Academic grit scale for Chinese middle- and upper-grade primary school students: testing its factor structure and measurement invariance

The Academic Grit Scale (AGS) is a novel measure of academic-specific grit. However, its factor structure and measurement invariance have yet to be thoroughly supported. The present study tested the factor structure and measurement invariance of the AGS with a large sample of early adolescents (aged 9–14 years) from China (N = 1,894). The bifactor model showed that the AGS was predominately accounted for by the general factor rather than the domain-specific factors; the parallel model from the AGS’s one-factor model showed good fit indices; thus, the AGS should be described as a univocal solution and reported as the total score. Gender and grade measurement invariance were supported at a scalar level, warranting further mean difference comparisons. In addition, academic grit was significantly associated with positive academic emotions and academic achievement, yielding evidence of good criteria-related validity. The current study contributes additional evidence to the construct validity of the Chinese version of the AGS among middle- and upper-grade primary school students in China.

Unscrambling creativity measurement: An invitation to better formalize the domain generality-specificity of creativity with psychometric modeling

A key question in creativity research concerns whether creativity is best understood as domain-specific or domain-general (Baer & Kaufman, 2005). Yet, the literature is plagued with insufficiently defined notions of domain specificity and generality of creativity. For example, researchers have alternatively discussed domain-generality as either a positive manifold (i.e., positive interdomain correlations), or as a unidimensional factor model (e.g., Ivcevic, 2007), without acknowledging the difference or providing a justification for their particular choice. We argue that there are diverse ways to conceptualize domain generality and specificity, with different implications (Kan et al., 2019). We propose to unscramble confusions in the literature by defining taxonomy of models that imply a general factor, domain specific factors, both, or neither. We review statistical frameworks used to test and compare them, examine their implications, and invite creativity researchers to clarify how they conceptualize and formalize generality and specificity in their research. Statement of educational relevanceA clear representation of how creativity is structured across domains is fundamental to the understanding of how creativity is to be learned and trained. Notably, the existence of a general creativity implies that creativity might be learned and trained in general (i.e., across multiple domains), while domain specificity implies that it might be learned primarily at the domain (or subdomain) level. Beyond the traditional framing of this question as a dichotomy or continuum of generality-specificity, we argue that there are in fact many types of conceptual and statistical models for understanding the structure of creativity across domains, which have different implications.

Construct validity of the German version of the Emotion Reactivity Scale

BackgroundEmotional reactivity is an important construct to consider when studying mental disorders. This study was conducted to translate and assess the factor structure, construct validity and internal consistency of a German version of the Emotion Reactivity Scale (ERS), which is an originally English questionnaire assessing three components of emotional reactivity: sensitivity, intensity and persistence of emotions.MethodsThe German ERS and a range of questionnaires used to assess convergent and discriminant validity were completed by 334 German speaking Swiss participants.ResultsConfirmatory factor analysis showed strong support for a bi-factor model, with evaluation indices pointing to a unidimensional construct rather than to domain specific factors. The questionnaire showed good reliability and the factor structure was similar across gender. The ERS showed convergent validity with general psychopathology, behavioral inhibition, negative affect, orienting sensitivity, depressive symptoms and symptoms of disordered eating, and discriminant validity with behavioral activation and alcohol consumption.ConclusionsFindings support the construct validity of the German ERS and suggest that it assesses a unidimensional construct with high internal consistency. Accounting for the unidimensional nature of the scale and aiming for efficient assessment tools, future research could, based on these findings, develop and evaluate the psychometric properties of a short version of the ERS.

The Development of a Short Version of the Internet Addiction Test: The IAT-7

AbstractUsing a valid and reliable scale to measure problems associated with excessive internet use is a key element of research on internet addiction (IA). The main goal of the current study was to develop a brief version of the Internet Addiction Test (IAT), the most widely used measure for assessing IA. In Study 1 (N = 463), we combined strict analytic techniques for item reduction with an evaluation of item content, and we compared several CFA and ESEM Models. In Study 2 (N = 374), we applied a Latent Variable Model (LMV) to examine the associations between our proposed short scale and some related variables. Our findings suggested a 7-item version (named IAT-7), with an ESEM structure and two domain-specific factors (F1: Interpersonal, Emotional and Obsessive Conflict; F2: Online Time Management). The IAT-7 showed excellent fit-indices [χ2 = 13.373; df = 8; CFI = .994; TLI = .983; RMSEA = .030 (.000–.073); SRMR = .016; AIC = 9,276.944; BIC = 9,388.662; aBIC = 9,302.971] and an adequate level of internal consistency (alpha and omega > .752). Interpersonal, Emotional and Obsessive Conflict mainly predicted loneliness and depression, whereas Online Time Management was primarily associated with stress, followed by depression. The IAT-7 shows promising psychometric properties and could be used as a screening tool for evaluating IA. Its small number of items makes it more attractive when a large battery of assessment scales is used.

Ruminative response scale for eating disorders: bifactor model and measurement invariance in a Portuguese community sample

ABSTRACT The Ruminative Response Scale for Eating Disorders (RRS-ED) measures ruminative thought content specifically related to eating disordered themes, assessing two domains of rumination, brooding and reflection. This study aims to examine the factor structure of the RRS-ED in a Portuguese community sample, using correlated two-factor models, unifactorial and bifactor models and test for invariance across sex. A sample of 535 adults (179 male; 356 female) filled out the RRS-ED. A subsample (n=347) answered additional measures of repetitive negative thinking and eating psychopathology. The bifactor model of the RRS-ED provided the best fit, demonstrating a reliable general rumination factor. Also, the bifactor model of the RRS-ED was invariant across sex. RRS-ED showed moderate to strong correlations with negative perseverative thinking and eating psychopathology. Both domain-specific factors of RRS-ED were associated with higher levels of eating psychopathology. Findings indicate that RRS-ED is a reliable and valid measure to assess the ruminative response from the general population in Portugal, showing initial evidence that supports the use of a total score of RRS-ED as an overall measure of rumination, while specific factor scores should be reported with caution. Future studies are needed to replicate the findings and further corroborate the unidimensionality of the RRS-ED.

Examining the Impacts of Technology and Trust on I-Voting Acceptance in the COVID-19 Aftermath

This article presents an empirical study of influence of the domain-specific factors of trust in the electoral system and administration, trust in technology, citizens' attitudes toward voting, and COVID-19 conditions on the intention to use i-voting. The study examines and assesses the relationships and effects of the various factors that influence the intention to use i-voting. Survey data from 633 adult Slovenian citizens were collected in 2022, when voters were still burdened by the pandemic and needed to visit the polling place at least five times to participate in all scheduled voting. Structural equation modeling was used to analyze the data and develop the model. The study provides important findings, such as (1) trust in the voting system has a significant impact on voters' intention to use i-voting, (2) fear of COVID-19 does not persuade people to use i-voting, and (3) previous attitudes toward voting do not have a significant impact on voter intention to use i-voting.

Systematic review of the performance evaluation of clinicians with or without the aid of machine learning clinical decision support system.

For the adoption of machine learning clinical decision support systems (ML-CDSS) it is critical to understand the performance aid of the ML-CDSS. However, it is not trivial, how the performance aid should be evaluated. To design reliable performance evaluation study, both the knowledge from the practical framework of experimental study design and the understanding of domain specific design factors are required. The aim of this review study was to form a practical framework and identify key design factors for experimental design in evaluating the performance of clinicians with or without the aid of ML-CDSS. The study was based on published ML-CDSS performance evaluation studies. We systematically searched articles published between January 2016 and December 2022. From the articles we collected a set of design factors. Only the articles comparing the performance of clinicians with or without the aid of ML-CDSS using experimental study methods were considered. The identified key design factors for the practical framework of ML-CDSS experimental study design were performance measures, user interface, ground truth data and the selection of samples and participants. In addition, we identified the importance of randomization, crossover design and training and practice rounds. Previous studies had shortcomings in the rationale and documentation of choices regarding the number of participants and the duration of the experiment. The design factors of ML-CDSS experimental study are interdependent and all factors must be considered in individual choices. The online version contains supplementary material available at 10.1007/s12553-023-00763-1.

A prospective examination of the role of psychological (in)flexibility in posttraumatic stress: A cross-lagged panel design

Functional contextualist models of psychopathology suggest that psychological inflexibility and psychological flexibility are of central importance for understanding the development and maintenance of posttraumatic stress (PTS) symptomatology. To our knowledge, these two constructs and their domain-specific factors (e.g., cognitive fusion, experiential avoidance) have not been assessed in their entirety and examined in relation to PTS symptoms using a longitudinal study design. As such, the primary aim of the present study was to use cross-lagged panel analysis, an analytic approach that allows stronger causal inferences to be made regarding the nature of temporal relations among study variables, to determine the directional relations among PTS symptoms and psychological flexibility and inflexibility over an eight-month time period. Trauma-exposed adults (N = 810), recruited online via Amazon’s Mechanical Turk (MTurk), completed a battery of self-report measures via a secure online platform at three time points, spanning eight months. Results suggest that the relationship between psychological inflexibility and PTS symptoms is bidirectional and mutually reinforcing. In contrast, significant prospective relations were not observed between psychological flexibility and PTS symptoms. Results of a follow-up exploratory path analysis showed that cognitive fusion was the only psychological inflexibility subfactor that partially mediated the relationship between PTS symptoms from baseline to the eight-month follow-up assessment. Taken together, these results suggest that psychological inflexibility, and primarily the domain of cognitive fusion, maintains PTS symptoms following trauma exposure. As such, it may important to integrate cognitive defusion techniques into evidence-based treatments for Posttraumatic Stress Disorder (PTSD).

Abstract P228: Accelerometer-Derived Daily Steps, Cognition, and Cognitive Impairment in U.S. Community-Dwelling Older Adults: The Atherosclerosis Risk in Communities Study

Introduction: Higher physical activity levels have been shown to preserve cognitive function and prevent cognitive impairment (CI). Whether daily steps, an easily interpretable physical activity metric, is associated with measures of brain health has not been widely studied. Hypothesis: Higher daily step count is associated with better cognitive function and lower odds of CI. Methods: Cross-sectional analysis of ARIC participants (mean age: 78 years, 41% male, 19% Black) who wore an accelerometer (ActiGraph GT3X) on the waist for ≥10 hours on ≥3 days between 2016-17. Daily steps were derived and examined continuously and by quartiles. Global and domain-specific (memory, language, executive function) factor scores were estimated from a battery of cognitive tests. Participants were classified as having CI if they had an adjudicated diagnosis of mild CI or dementia. Hypotheses were tested using linear and logistic regression models, adjusted for age, sex, race, education, and accelerometer wear time. Results: Among 454 participants, 88 (19.4%) had CI. The mean number of daily steps was 3,501 (SD=1,974). In adjusted models, a higher daily step count was associated with better global cognition and executive function factor scores (e.g., those in the 4 th daily-step quartile [≥4,499 steps] vs. 1 st [<2074 steps] had a 0.43 [95% confidence interval: 0.24 to 0.61] higher executive function score). Associations of step count with memory or language scores were not supported. The odds of CI were lower for participants who had a higher daily steps count (e.g., those in the 4 th daily-step quartile vs. 1 st had 62% [odds ratio (OR)=0.38, 95% confidence interval: 0.16 to 0.90] lower odds of CI. The OR of CI for continuous daily steps shown in the Figure. Conclusions: Higher daily steps were associated with better cognitive function and may be a helpful marker in identifying participants with CI. Prospective studies of accelerometer-measured physical activity and cognitive outcomes are needed to understand the direction of these associations.

The Anti-Racism Behavioral Inventory: A Validation Study

The current study extends the initial creation and validation of the Anti-Racism Behavioral Inventory (ARBI; Pieterse, Utsey & Miller, 2016), a measure designed to assess anti-racism awareness and behavior among Whites Americans. Given that the original measure was developed with a sample of graduate students in counseling psychology, the current study extends validation to a sample of White individuals who identify as anti-racism activists (N=153). Findings support the original bifactor factor model of the Anti-Racism Behavioral inventory (one general anti-racism behavior factor and three domain-specific factors: individual advocacy, awareness of racism, and institutional advocacy). Additional evidence for validity was supported through negative associations with measures of the color-blind racial attitudes, as well as positive associations with scores on the White Privilege Awareness Inventory. Implications of the findings for training and future research are discussed.

Learning Domain Invariant Representations for Generalizable Person Re-Identification.

Generalizable person Re-Identification (ReID) aims to learn ready-to-use cross-domain representations for direct cross-data evaluation, which has attracted growing attention in the recent computer vision (CV) community. In this work, we construct a structural causal model (SCM) among identity labels, identity-specific factors (clothing/shoes color etc.), and domain-specific factors (background, viewpoints etc.). According to the causal analysis, we propose a novel Domain Invariant Representation Learning for generalizable person Re-Identification (DIR-ReID) framework. Specifically, we propose to disentangle the identity-specific and domain-specific factors into two independent feature spaces, based on which an effective backdoor adjustment approximate implementation is proposed for serving as a causal intervention towards the SCM. Extensive experiments have been conducted, showing that DIR-ReID outperforms state-of-the-art (SOTA) methods on large-scale domain generalization (DG) ReID benchmarks.

Effects of prefrontal and parietal neuromodulation on magnitude processing and integration.

Numerical cognition is an essential skill for survival, which includes the processing of discrete and continuous quantities, involving a mainly right fronto-parietal network. However, the neurocognitive systems underlying the processing and integration of discrete and continuous quantities are currently under debate. Noninvasive brain stimulation techniques have been used in the study of the neural basis of numerical cognition with a spatial, temporal and functional resolution superior to other neuroimaging techniques. The present randomized sham-controlled single-blinded trial addresses the involvement of the right dorsolateral prefrontal cortex and the right intraparietal sulcus in magnitude processing and integration. Multifocal anodal transcranial direct current stimulation was applied online during the execution of magnitude comparison tasks in three conditions: right prefrontal, right parietal and sham stimulation. The results show that prefrontal stimulation produced a moderated decrease in response times in all magnitude processing and integration tasks compared to sham condition. While parietal stimulation had no significant effect on any of the tasks. The effect found is interpreted as a generalized improvement in processing speed and magnitude integration due to right prefrontal neuromodulation, which may be attributable to domain-general or domain-specific factors.

Health systems strengthening through policy-level integration of community health worker programs into national health systems for improved health outcomes - scorecard metrics validation: A bifactor structural equation model approach.

Subsequent to the demonstrated potential of community health workers (CHWs) in strengthening health systems to improve health outcomes, recent literature has defined context and guidelines for integrating CHW programs into mainstream health systems. However, quantitative measures for assessing the extent of CHW program integration into national health systems need to be developed. The purpose of this study was to validate a newly developed scale, Community Health Worker Program Integration Scorecard Metrics (CHWP-ISM), for assessing the degree of integration of CHW programs into national health systems in Sub-Saharan Africa (SSA). Data obtained through a pilot study involving a purposively selected sample of 41 participants selected from populations involved in CHW programs work in selected countries of SSA formed the basis of a 31-item bifactor model. Data were collected between June and December 2019. By applying a latent variable approach implemented with structural equation modeling, data analysis was mainly done using the R statistical environment, applying factor analysis procedures. Dimensionality, construct validity, and the CHWP-ISM scale's internal consistency were assessed. Confirmatory factor analysis of the CHW-ISM bifactor model supported a co-occurring CHW integration general factor and six unique domain-specific factors. Both the comparative fit index (CFI) and Tucker-Lewis Index (TLI) fit indices were above 0.9, while the root mean square of the residuals (RMSR) was 0.02. Cronbach's alpha (α), Guttman 6 (Lambda 6), and Omega total (ωt) were above 0.8, indicating good scale reliability. Statistical significance of the bifactor model suggests that CHW integration has to be examined using factors that reflect a single common underlying integration construct, as well as factors that reflect unique variances for the identified six subject-specific domains. The validated CHWP-ISM could be useful to inform policy advisers, health systems, donors, non-governmental organizations, and other CHW program stakeholders with guidance on how to quantitatively assess the integration status of different components of CHW programs into respective critical functions of the health system. Improved integration could increase CHW program functionality, which could in turn strengthen the healthcare systems to improve health outcomes in the region.

Coupling of sensorimotor and cognitive functions in middle- and late adulthood.

The present study explored age effects and the coupling of sensorimotor and cognitive functions in a stratified sample of 96 middle-aged and older adults (age 45-86 years) with no indication of mild cognitive decline. In our sensorimotor tasks, we had an emphasis on listening in noise and postural control, but we also assessed functional mobility and tactile sensitivity. Our cognitive measures comprised processing speed and assessments of core cognitive control processes (executive functions), notably inhibition, task switching, and working memory updating. We explored whether our measures of sensorimotor functioning mediated age differences in cognitive variables and compared their effect to processing speed. Subsequently, we examined whether individuals who had poorer (or better) than median cognitive performance for their age group also performed relatively poorer (or better) on sensorimotor tasks. Moreover, we examined whether the link between cognitive and sensorimotor functions becomes more pronounced in older age groups. Except for tactile sensitivity, we observed substantial age-related differences in all sensorimotor and cognitive variables from middle age onward. Processing speed and functional mobility were reliable mediators of age in task switching and inhibitory control. Regarding coupling between sensorimotor and cognition, we observed that individuals with poor cognitive control do not necessarily have poor listening in noise skills or poor postural control. As most conditions do not show an interdependency between sensorimotor and cognitive performance, other domain-specific factors that were not accounted for must also play a role. These need to be researched in order to gain a better understanding of how rehabilitation may impact cognitive functioning in aging persons.

Reassessing the smartphone addiction scale: Support for unidimensionality and a shortened scale from an American sample

This study examined the multidimension assumption of the often-used 33-item, six-factor Smartphone Addiction Scale (SAS) by employing four confirmatory factor models (i.e., one-factor, first-order six-factor, second-order six-factor, and bifactor). Survey data were collected from 1155 undergraduate students in a US public university. Findings showed that the bifactor model was the best fitting model and SAS is a unidimensional instrument. The composite scores made for the six domain-specific factors, often seen in the literature, were not reliable measures for the construct of smartphone addiction and can result in misleading or even incorrect inferential test results. The most reliable and contributing items identified by the bifactor model were selected to form a short, more efficient version of SAS. A Rasch model was performed to test the psychometric properties of the shortened SAS. The new shortened SAS contains 10 items (SAS-10) and had good reliability, construct validity, and no presence of bias towards students in different gender or academic achievement groups. Additional evidence suggests a 4-category rating scale is enough to capture the construct of smartphone addiction. Finally, SAS-10 correlated to numerous external criterion variables similarly to how the extant literature would predict. SAS-10 is provided in appendix C.

Psychometric evaluation of the depression anxiety stress scale 8-items (DASS-8)/DASS-12/DASS-21 among family caregivers of patients with dementia.

Patients with dementia express a set of problematic and deteriorating symptoms, along with self-care dependency. Over time, the mental health of family caregivers of persons with dementia may be affected, putting them at a high risk for psychopathology, which may be associated with endangered wellbeing of people with dementia. This cross-sectional instrumental design study examined the psychometric properties of the Depression Anxiety Stress Scale 8-items (DASS-8), DASS-12, and DASS-21 in a convenient sample of 571 caregivers from northern Italy and southern Switzerland (mean age = 53 years, SD = 12, range = 24-89 years). A bifactor structure of the three measures had the best fit; some items of the DASS-12/DASS-21 failed to load on their domain-specific factors. The three-factor structure was invariant across various groups (e.g., gender and education), expressed adequate reliability and convergent validity, and had strong positive correlation with the three-item UCLA Loneliness Scale (UCLALS3). Distress scores did not differ among carers of different types of dementia (Alzheimer's disease vs. other types, e.g., vascular dementia). However, distress scores were significantly high among female individuals, adult children caregivers, those caring for dependent patients, and those who received help with care. For 54.9 and 38.8% of the latter, care was provided by relatives and health professionals, respectively. Since the DASS-8 expresses adequate psychometrics comparable with the DASS-21, it may be used as a brief measure of distress in this population.

Multilayer Exponential Family Factor models for integrative analysis and learning disease progression.

Current diagnosis of neurological disorders often relies on late-stage clinical symptoms, which poses barriers to developing effective interventions at the premanifest stage. Recent research suggests that biomarkers and subtle changes in clinical markers may occur in a time-ordered fashion and can be used as indicators of early disease. In this article, we tackle the challenges to leverage multidomain markers to learn early disease progression of neurological disorders. We propose to integrate heterogeneous types of measures from multiple domains (e.g., discrete clinical symptoms, ordinal cognitive markers, continuous neuroimaging, and blood biomarkers) using a hierarchical Multilayer Exponential Family Factor (MEFF) model, where the observations follow exponential family distributions with lower-dimensional latent factors. The latent factors are decomposed into shared factors across multiple domains and domain-specific factors, where the shared factors provide robust information to perform extensive phenotyping and partition patients into clinically meaningful and biologically homogeneous subgroups. Domain-specific factors capture remaining unique variations for each domain. The MEFF model also captures nonlinear trajectory of disease progression and orders critical events of neurodegeneration measured by each marker. To overcome computational challenges, we fit our model by approximate inference techniques for large-scale data. We apply the developed method to Parkinson's Progression Markers Initiative data to integrate biological, clinical, and cognitive markers arising from heterogeneous distributions. The model learns lower-dimensional representations of Parkinson's disease (PD) and the temporal ordering of the neurodegeneration of PD.

The Psychometric Properties of the Chinese Version of the Encouragement Character Strength Scale in Selected Undergraduate Students and Teachers

The Encouragement Character Strength Scale (ECSS) is a self-report measure of encouragement, which refers to a tendency to enjoy and perceive oneself as being accomplished in communicating affirmations to motivate others. Although it is theoretically assumed as an overarching construct consisting of two domain-specific factors (i.e., perceived ability and enjoyment), there is inconclusive evidence regarding the most optimal factor structure of the encouragement construct. This study evaluated the factor structure, measurement invariance, and criterion-related validity of the Chinese version of the ECSS among teachers and undergraduate students in mainland China. Results showed that the bifactor model of encouragement demonstrated the best fit among undergraduate students and teachers. There was evidence supporting the measurement invariance of this factor structure across type of samples (i.e., teachers and undergraduate students) and gender. Ancillary bifactor indices indicate the superiority of using the ECSS’s overall or general factor over subscale scores. The ECSS total score also showed internal consistency and temporal stability. A review of correlations between encouragement and criterion variables (i.e., kindness, hope, agreeableness, and extraversion) indicates that effect sizes ranged from moderate to large. Furthermore, the encouragement general factor was positively correlated with both psychological well-being and work engagement after controlling for the aforementioned criterion variables and demographic covariates.

Examining the Factor Structure and Incremental Utility of the Contrast Avoidance Questionnaires via Bifactor Analysis

The negative emotional contrast avoidance model posits that pathological worry is maintained by the avoidance of negative emotional shifts. The Contrast Avoidance Questionnaires (CAQ–Worry and CAQ–General Emotion) aim to assess contrast avoidance beliefs and behaviors. Questions remain around the factor structures of the CAQs, whether such structures replicate in nonundergraduate samples, and whether their domain-specific factors are valid for independent use. This study used bifactor analysis in a large community sample (N = 827) to address these gaps in the literature. Results supported bifactor models of both measures. Complementary analyses supported the multidimensionality of the CAQ–Worry, including its strong general factor and independent use of two domain-specific factors, rather than the original three domain-specific factors. The CAQ–General Emotion’s general factor was strong, but the merits of the Discomfort domain-specific factor require more exploration, and use of the Avoidance domain-specific factor is discouraged.