Trust and perceived mental health access: Exploring the relationship between perceived access barriers and veteran-reported trust.
Jeffrey M PyneP Adam KellyEllen P FischerRichard R OwenMichael A CucciareChristopher J MillerSamantha L ConnollyKara A ZamoraChristopher J KoenigKaren H SealJohn C FortneyPublished in: Psychological services (2023)
The importance of patients' trust in health care is well known. However, identifying actionable access barriers to trust is challenging. The goal of these exploratory analyses is to identify actionable access barriers that correlate with and predict patients' lack of trust in providers and in the health care system. This article combines existing data from three studies regarding perceived access to mental health services to explore the relationship between provider and system trust and other access barriers. Data from the Perceived Access Inventory (PAI) were analyzed from three studies that together enrolled a total of 353 veterans who screened positive for a mental health problem and had a VA mental health encounter in the previous 12 months. The PAI includes actionable barriers to accessing VA mental health services. The data are cross-sectional, and analyses include Spearman rank correlations of PAI access barriers and provider and system trust, and linear regressions examining the effect of demographic, clinical, and PAI barriers on lack of trust in VA mental health providers and in the VA health care system. Age, depression, and anxiety symptoms and PAI items demonstrated statistically significant bivariate correlations with provider and system trust. However, in multivariate linear regressions, only PAI items remained statistically significant. The PAI items that predicted provider and system trust could be addressed in interventions to improve provider- and system-level trust. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Keyphrases
- mental health
- health information
- primary care
- healthcare
- end stage renal disease
- physical activity
- depressive symptoms
- social support
- newly diagnosed
- mental illness
- cross sectional
- ejection fraction
- chronic kidney disease
- social media
- prognostic factors
- electronic health record
- big data
- sleep quality
- health insurance
- neural network