Across three studies, we explored the construct of self-verification behavior in the employment interview, defined as: "sharing of unembellished self-related information that is in line with self-views." Using content analysis, Study 1 explored whether job applicants (N = 252) described self-verification behavior when they were asked which strategy they used to distinguish themselves from other applicants. Self-verification behavior was frequently mentioned in conjunction with other self-presentation tactics, such as honest impression management. In Studies 2 and 3, we surveyed job applicants (N = 92 and N = 311) immediately following an interview. We found a positive relationship between self-verification behavior and honest impression management and honesty-humility, but a near-zero relationship with interview performance. Using confirmatory factor analysis, we found that although correlated, self-verification behavior is conceptually different from honest impression management. We suggest that measuring self-verification behavior in interviews allows researchers to capture a broader range of potential interview strategies.
Previous research suggests that family dysfunction may be related to lower health-related quality of life (HRQoL) in parent caregivers, but it is unknown if this association exists in the context of child mental illness. Therefore, the objectives of this study were to compare HRQoL between parent caregivers and Canadian population norms using the Short Form 36 Health Survey (SF-36); examine associations between family functioning and parental HRQoL; and investigate whether child and parental factors moderate associations between family functioning and parental HRQoL. Cross-sectional data were collected from children receiving mental healthcare at a pediatric hospital and their parents ( n = 97). Sample mean SF-36 scores were compared to Canadian population norms using t-tests and effect sizes were calculated. Multiple regression was used to evaluate associations between family functioning and parental physical and mental HRQoL, adjusting for sociodemographic and clinical covariates. Proposed moderators, including child age, sex, and externalizing disorder, and parental psychological distress, were tested as product-term interactions. Parents had significantly lower physical and mental HRQoL versus Canadian norms in most domains of the SF-36, and in the physical and mental component summary scores. Family functioning was not associated with parental physical HRQoL. However, lower family functioning predicted lower parental mental HRQoL. Tested variables did not moderate associations between family functioning and parental HRQoL. These findings support the uptake of approaches that strive for collaboration among healthcare providers, children, and their families (i.e., family-centered care) in child psychiatry settings. Future research should explore possible mediators and moderators of these associations.
Given the stressful experiences of parenting children with mental illness, researchers and health professionals must ensure that the health-related quality of life of these vulnerable parents is measured with sufficient validity and reliability. This study examined the psychometric properties of the SF-36 in parents of children with mental illness. The data come from 99 parents whose children were currently receiving mental health services. The correlated two-factor structure of the SF-36 was replicated. Internal consistencies were robust (α > 0.80) for all but three subscales (General Health, Vitality, Mental Health). Inter-subscale and component correlations were strong. Correlations with parental psychopathology ranged from r = −0.32 to −0.60 for the physical component and r = −0.39 to −0.75 for the mental component. Parents with clinically relevant psychopathology had significantly worse SF-36 scores. SF-36 scores were inversely associated with the number of child diagnoses. The SF-36 showed evidence of validity and reliability as a measure of health-related quality of life in parents of children with mental illness and may be used as a potential outcome in the evaluation of family-centered approaches to care within child psychiatry. Given the relatively small sample size of this study, research should continue to examine its psychometric properties in more diverse samples of caregivers.
BACKGROUND Motor vehicle crashes (MVCs) are a leading cause of nonfatal injury in the United States and impose a high financial cost to the patient and the economy. For many patients, this cost may be financially devastating and contribute to worsening health outcomes after injury. We aimed to describe the population level risk of catastrophic health expenditure (CHE) and determine factors associated with risk of CHE. METHODS We performed a retrospective review using the 2014–2017 Nationwide Inpatient Sample. The study population consisted of uninsured and privately insured adults aged 26 to 64 years who were hospitalized for nonneurologic traumatic injury due to MVCs. Our measure of financial hardship was CHE, which was defined as hospital charges ≥40% of postsubsistence income. Income estimates were derived from zip-code level data using Γ distribution modeling. RESULTS Our sample included 189,000 patients, of which 149,705 had private insurance and 39,375 were uninsured. The median estimated income for the study cohort was $66,118 (interquartile range, $65,353–$66,884). The median cost of hospitalization was $53,467 (interquartile range, $29,854–$99,914). In addition, 91.5% of uninsured patients suffering from MVC are at risk for CHE, and 10.1% of privately insured patients are at risk for CHE. Among the insured, Black, Hispanic, and low income were associated with CHE. CONCLUSION Nine of 10 uninsured patients are at risk for CHE after hospitalization for MVC. Despite having insurance, 10% of patients are still at risk of CHE. Black, Hispanic, and low-income communities are at highest risk of having private insurance and still experiencing CHE. This is the first population level analysis after the implementation of the Affordable Care Act that assesses the financial burden of no insurance and underinsurance. These data are important to understand the effectiveness of insurance coverage and guide hospital and policy level interventions to prevent CHE. LEVEL OF EVIDENCE Prognostic and Epidemiological; Level III.
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