JAMA Psychiatry最新文献

Importance: Medical debt is common in the US and may hinder timely access to care for mental disorders.

Objective: To estimate the prevalence of medical debt among US adults with depression and anxiety and its association with delayed and forgone mental health care.

Design, setting, and participants: Cross-sectional, nationally representative survey study of US adult participants in the 2022 National Health Interview Survey who had current or lifetime diagnoses of depression or anxiety.

Exposures: Self-reported lifetime clinical diagnoses of depression and anxiety; moderate to severe symptoms of current depression (Patient Health Questionnaire-8 score ≥10) and anxiety (Generalized Anxiety Disorder-7 score ≥10) irrespective of lifetime diagnoses; and past-year medical debt.

Main outcomes and measures: Self-reported delaying and forgoing mental health care because of cost in the past year.

Results: Among 27 651 adults (15 050 [54.4%] female; mean [SD] age, 52.9 [18.4] years), 5186 (18.2%) reported lifetime depression, 1948 (7.3%) reported current depression, 4834 (17.7%) reported lifetime anxiety, and 1689 (6.6%) reported current anxiety. Medical debt was more common among adults with lifetime depression (19.9% vs 8.6%; adjusted prevalence ratio [aPR], 1.97; 95% CI, 1.96-1.98), lifetime anxiety (19.4% vs 8.8%; aPR, 1.91; 95% CI, 1.91-1.92), current depression (27.3% vs 9.4%; aPR, 2.34; 95% CI, 2.34-2.36), and current anxiety (26.2% vs 9.6%; aPR, 2.24; 95% CI, 2.24-2.26) compared with adults without the respective mental disorders. Medical debt was associated with delayed health care among adults with lifetime depression (29.0% vs 11.6%; aPR, 2.68; 95% CI, 2.62-2.74), lifetime anxiety (28.0% vs 11.5%; aPR, 2.45; 95% CI, 2.40-2.50), current depression (36.9% vs 17.4%; aPR, 2.25; 95% CI, 2.13-2.38), and current anxiety (38.4% vs 16.9%; aPR, 2.48; 95% CI, 2.35-2.66) compared with those without these diagnoses. Medical debt was associated with forgone health care among adults with lifetime depression (29.4% vs 10.6%; aPR, 2.66; 95% CI, 2.61-2.71), lifetime anxiety (28.2% vs 10.7%; aPR, 2.63; 95% CI, 2.57-2.68), current depression (38.0% vs 17.2%; aPR, 2.35; 95% CI, 2.23-2.48), and current anxiety (40.8% vs 17.1%; aPR, 2.57; 95% CI, 2.43-2.75) compared with those without the diagnoses.

Conclusions and relevance: Medical debt is prevalent among adults with depression and anxiety and may contribute to the mental health treatment gap. In the absence of structural reform, new policies are warranted to protect against this financial barrier to mental health care.

Importance: Supporting healthy aging is a US public health priority, and gratitude is a potentially modifiable psychological factor that may enhance health and well-being in older adults. However, the association between gratitude and mortality has not been studied.

Objective: To examine the association of gratitude with all-cause and cause-specific mortality in later life.

Design, setting, and participants: This population-based prospective cohort study used data from self-reported questionnaires and medical records of 49 275 US older female registered nurses who participated in the Nurses' Health Study (2016 questionnaire wave to December 2019). Cox proportional hazards regression models estimated the hazard ratio (HR) of deaths by self-reported levels of gratitude at baseline. These models adjusted for baseline sociodemographic characteristics, social participation, physical health, lifestyle factors, cognitive function, and mental health. Data analysis was conducted from December 2022 to April 2024.

Exposure: Gratitude was assessed with the 6-item Gratitude Questionnaire, a validated and widely used measure of one's tendency to experience grateful affect.

Main outcomes and measures: Deaths were identified from the National Death Index, state statistics records, reports by next of kin, and the postal system. Causes of death were ascertained by physicians through reviewing death certificates and medical records.

Results: Among the 49 275 participants (all female; mean [SD] age at baseline, 79 [6.16] years), 4608 incident deaths were identified over 151 496 person-years of follow-up. Greater gratitude at baseline was associated with a lower hazard of mortality in a monotonic fashion. For instance, the highest tertile of gratitude, compared with the lowest tertile, was associated with a lower hazard of all-cause deaths (HR, 0.91; 95% CI, 0.84-0.99) after adjusting for baseline sociodemographic characteristics, social participation, religious involvement, physical health, lifestyle factors, cognitive function, and mental health. When considering cause-specific deaths, death from cardiovascular disease was inversely associated with gratitude (HR, 0.85; 95% CI, 0.73-0.995).

Conclusions and relevance: This study provides the first empirical evidence suggesting that experiencing grateful affect is associated with increased longevity among older adults. The findings will need to be replicated in future studies with more representative samples.

Importance: Subjective cognitive decline (SCD) is recognized to be in the Alzheimer disease (AD) cognitive continuum. The SCD Initiative International Working Group recently proposed SCD-plus (SCD+) features that increase risk for future objective cognitive decline but that have not been assessed in a large community-based setting.

Objective: To assess SCD risk for mild cognitive impairment (MCI), AD, and all-cause dementia, using SCD+ criteria among cognitively normal adults.

Design, setting, and participants: The Framingham Heart Study, a community-based prospective cohort study, assessed SCD between 2005 and 2019, with up to 12 years of follow-up. Participants 60 years and older with normal cognition at analytic baseline were included. Cox proportional hazards (CPH) models were adjusted for baseline age, sex, education, APOE ε4 status, and tertiles of AD polygenic risk score (PRS), excluding the APOE region. Data were analyzed from May 2021 to November 2023.

Exposure: SCD was assessed longitudinally using a single question and considered present if endorsed at the last cognitively normal visit. It was treated as a time-varying variable, beginning at the first of consecutive, cognitively normal visits, including the last, at which it was endorsed.

Main outcomes and measures: Consensus-diagnosed MCI, AD, and all-cause dementia.

Results: This study included 3585 participants (mean [SD] baseline age, 68.0 [7.7] years; 1975 female [55.1%]). A total of 1596 participants (44.5%) had SCD, and 770 (21.5%) were carriers of APOE ε4. APOE ε4 and tertiles of AD PRS status did not significantly differ between the SCD and non-SCD groups. MCI, AD, and all-cause dementia were diagnosed in 236 participants (6.6%), 73 participants (2.0%), and 89 participants (2.5%), respectively, during follow-up. On average, SCD preceded MCI by 4.4 years, AD by 6.8 years, and all-cause dementia by 6.9 years. SCD was significantly associated with survival time to MCI (hazard ratio [HR], 1.57; 95% CI, 1.22-2.03; P <.001), AD (HR, 2.98; 95% CI, 1.89-4.70; P <.001), and all-cause dementia (HR, 2.14; 95% CI, 1.44-3.18; P <.001). After adjustment for APOE and AD PRS, the hazards of SCD were largely unchanged.

Conclusions and relevance: Results of this cohort study suggest that in a community setting, SCD reflecting SCD+ features was associated with an increased risk of future MCI, AD, and all-cause dementia with similar hazards estimated in clinic-based settings. SCD may be an independent risk factor for AD and other dementias beyond the risk incurred by APOE ε4 and AD PRS.

Importance: While abundant work has examined patient-level differences in antidepressant treatment outcomes, little is known about the extent of clinician-level differences. Understanding these differences may be important in the development of risk models, precision treatment strategies, and more efficient systems of care.

Objective: To characterize differences between outpatient clinicians in treatment selection and outcomes for their patients diagnosed with major depressive disorder across academic medical centers, community hospitals, and affiliated clinics.

Design, setting, and participants: This was a longitudinal cohort study using data derived from electronic health records at 2 large academic medical centers and 6 community hospitals, and their affiliated outpatient networks, in eastern Massachusetts. Participants were deidentified clinicians who billed at least 10 International Classification of Diseases, Ninth Revision (ICD-9) or Tenth Revision (ICD-10) diagnoses of major depressive disorder per year between 2008 and 2022. Data analysis occurred between September 2023 and January 2024.

Main outcomes and measures: Heterogeneity of prescribing, defined as the number of distinct antidepressants accounting for 75% of prescriptions by a given clinician; proportion of patients who did not return for follow-up after an index prescription; and proportion of patients receiving stable, ongoing antidepressant treatment.

Results: Among 11 934 clinicians treating major depressive disorder, unsupervised learning identified 10 distinct clusters on the basis of ICD codes, corresponding to outpatient psychiatry as well as oncology, obstetrics, and primary care. Between these clusters, substantial variability was identified in the proportion of selective serotonin reuptake inhibitors, selective norepinephrine reuptake inhibitors, and tricyclic antidepressants prescribed, as well as in the number of distinct antidepressants prescribed. Variability was also detected between clinician clusters in loss to follow-up and achievement of stable treatment, with the former ranging from 27% to 69% and the latter from 22% to 42%. Clinician clusters were significantly associated with treatment outcomes.

Conclusions and relevance: Groups of clinicians treating individuals diagnosed with major depressive disorder exhibit marked differences in prescribing patterns as well as longitudinal patient outcomes defined by electronic health records. Incorporating these group identifiers yielded similar prediction to more complex models incorporating individual codes, suggesting the importance of considering treatment context in efforts at risk stratification.