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BackgroundPhysician responsiveness to patient preferences for depression treatment may improve treatment adherence and clinical outcomes.ObjectiveTo examine associations of patient treatment preferences with types of depression treatment received and treatment adherence among Veterans initiating depression treatment.DesignPatient self-report surveys at treatment initiation linked to medical records.SettingVeterans Health Administration (VA) clinics nationally, 2018-2020.ParticipantsA total of 2582 patients (76.7% male, mean age 48.7 years, 62.3% Non-Hispanic White) MAIN MEASURES: Patient self-reported preferences for medication and psychotherapy on 0-10 self-anchoring visual analog scales (0="completely unwilling"; 10="completely willing"). Treatment receipt and adherence (refilling medications; attending 3+ psychotherapy sessions) over 3 months. Logistic regression models controlled for socio-demographics and geographic variables.Key resultsMore patients reported strong preferences (10/10) for psychotherapy than medication (51.2% versus 36.7%, McNemar χ21=175.3, p

BackgroundPhysician responsiveness to patient preferences for depression treatment may improve treatment adherence and clinical outcomes.ObjectiveTo examine associations of patient treatment preferences with types of depression treatment received and treatment adherence among Veterans initiating depression treatment.DesignPatient self-report surveys at treatment initiation linked to medical records.SettingVeterans Health Administration (VA) clinics nationally, 2018-2020.ParticipantsA total of 2582 patients (76.7% male, mean age 48.7 years, 62.3% Non-Hispanic White) MAIN MEASURES: Patient self-reported preferences for medication and psychotherapy on 0-10 self-anchoring visual analog scales (0="completely unwilling"; 10="completely willing"). Treatment receipt and adherence (refilling medications; attending 3+ psychotherapy sessions) over 3 months. Logistic regression models controlled for socio-demographics and geographic variables.Key resultsMore patients reported strong preferences (10/10) for psychotherapy than medication (51.2% versus 36.7%, McNemar χ21=175.3, p

BackgroundPsychiatric comorbidities may complicate depression treatment by being associated with increased role impairments. However, depression symptom severity might account for these associations. Understanding the independent associations of depression severity and comorbidity with impairments could help in treatment planning. This is especially true for depressed Veterans, who have high psychiatric comorbidity rates.Methods2,610 Veterans beginning major depression treatment at the Veterans Health Administration (VHA) were administered a baseline self-report survey that screened for diverse psychiatric comorbidities and assessed depression severity and role impairments. Logistic and generalized linear regression models estimated univariable and multivariable associations of depression severity and comorbidities with impairments. Population attributable risk proportions (PARPs) estimated the relative importance of depression severity and comorbidities in accounting for role impairments.ResultsNearly all patients (97.8%) screened positive for at least one comorbidity and half (49.8%) for 4+ comorbidities. The most common positive screens were for generalized anxiety disorder (80.2%), posttraumatic stress disorder (77.9%), and panic/phobia (77.4%). Depression severity and comorbidities were significantly and additively associated with impairments in multivariable models. Associations were attenuated much less for depression severity than for comorbidities in multivariable versus univariable models. PARPs indicated that 15-60% of role impairments were attributable to depression severity and 5-32% to comorbidities.LimitationsThe screening scales could have over-estimated comorbidity prevalence. The cross-sectional observational design cannot determine either temporal or causal priorities.ConclusionsAlthough positive screens for psychiatric comorbidity are pervasive among depressed VHA patients, depression severity accounts for most of the associations of these comorbidities with role impairments.

IntroductionThe Veterans Health Administration (VHA) supports the nation's largest primary care-mental health integration (PC-MHI) collaborative care model to increase treatment of mild to moderate common mental disorders in primary care (PC) and refer more severe-complex cases to specialty mental health (SMH) settings. It is unclear how this treatment assignment works in practice.MethodsPatients (n = 2610) who sought incident episode VHA treatment for depression completed a baseline self-report questionnaire about depression severity-complexity. Administrative data were used to determine settings and types of treatment during the next 30 days.ResultsThirty-four percent (34.2%) of depressed patients received treatment in PC settings, 65.8% in SMH settings. PC patients had less severe and fewer comorbid depressive episodes. Patients with lowest severity and/or complexity were most likely to receive PC antidepressant medication treatment; those with highest severity and/or complexity were most likely to receive combined treatment in SMH settings. Assignment of patients across settings and types of treatment was stronger than found in previous civilian studies but less pronounced than expected (cross-validated AUC = 0.50-0.68).DiscussionBy expanding access to evidence-based treatments, VHA's PC-MHI increases consistency of treatment assignment. Reasons for assignment being less pronounced than expected and implications for treatment response will require continued study.

BackgroundEarly diagnosis and treatment of chronic obstructive pulmonary disease (COPD) can slow disease progression. The Department of Veterans Affairs (VA)/Department of Defense Clinical Practice Guidelines (CPG), established to improve patient outcomes, recommend the use of spirometry in the COPD diagnostic process. The aims of this study were to assess VA health care providers' performance related to CPG-recommended spirometry administration in the evaluation of newly diagnosed COPD among veterans, determine the patient characteristics that may influence the adherence rate, and compare VA concordance rates to those of other health plans.MethodsAdministrative health care data related to Operations Enduring Freedom/Iraqi Freedom/New Dawn (OEF/OIF/OND) veterans was used to identify newly diagnosed COPD cases and the proportion of cases receiving spirometry. Cases were defined as veterans who had their first medical encounter with a coded diagnosis of COPD ≥ 6 months after their initial VA health care evaluation. The relationship between prediagnostic and comorbid conditions and the administration of CPG-concordant spirometry was examined using regression analyses.FindingsAmong the 923,646 OEF/OIF/OND veterans receiving VA health care between January 2002 and December 2014, 32,076 (3%) had a coded diagnosis of COPD. Among those, 22,156 (69%) were identified as newly diagnosed COPD cases; only 6,827 (31%) had CPG-concordant spirometry. Concordant spirometry was more likely to occur in veterans aged ≥40. A pre-existing tobacco use disorder marginally changed the concordance rate.DiscussionVA provider adherence to CPG-concordant spirometry would decrease the prevalence of false-positive COPD cases and lead to more targeted disease treatment. Future research should focus on such cases by assessing the association between COPD diagnosis and bronchodilator responsiveness.

Background: Communication campaigns offer a viable mechanism to promote suicide prevention and reinforce mental health for U.S. veterans in midlife, a group with a high suicide burden. However, little empirical investigation of this type of messaging has been conducted, with formative campaign research conspicuously missing from the limited literature. Aims: Using the theory of planned behavior as a guide, formative research was conducted to inform the design of suicide prevention messaging by (a) describing and measuring several theoretical constructs among our audience and (b) modeling associations between constructs and intentions to seek help for suicidal behaviors and mental health more broadly. Methods: Telephone-based cross-sectional surveys were collected between 2014 and 2016 from a nationally representative sample of veterans with analyses restricted to those aged between 44 and 65 years (n = 809). Multiple logistic regression was used to identify significant factors associated with intentions to seek help for either suicidal behaviors or mental health. Results. Perceived behavioral control was one of the largest predictors of intentions to seek help for both suicidal behaviors and mental health concerns. Descriptive norms were also significantly associated with suicide-related intentions. Data further suggest several types of attitudes (i.e., discordant beliefs, stereotypes) to consider when designing messages for this group. Discussion: This study represents one of the first efforts to document and describe theoretical constructs and their influence on intentions among veterans in midlife to contribute to the development of evidence-based messaging for veterans informed by a conceptual framework. Conclusion: Findings have important implications as the use of communication strategies for suicide prevention grows increasingly popular.

Public stigma is a significant deterrent to mental health service use for U.S. veterans. Media campaigns are often used to dispel stigmatizing beliefs and actions. Segmentation is an evidence-based practice for their effective use; however, little data has been published on veteran segments to target with anti-stigma messages. This article aims to identify and describe initial typologies of stigmatizing attitudes within a group of U.S. military veterans. Telephone-based cross-sectional surveys were conducted with a national random sample of veterans from 2014 to 2016 (N = 2142). Stigma outcomes were measured using a brief, validated instrument used in population-based surveys of public perceptions toward people with mental illness. Cluster analysis was conducted to identify specific groupings along multiple dimensions. A final four-cluster solution was identified among veterans with distinct patterns of attitudes toward mental illness and include: 1) the undecided, 2) the influencer, 3) the ambivalent, and 4) the potential ally. Several strategies were also identified for designing anti-stigma messaging toward these segments. This research demonstrates veterans can be segmented by attitudes to target with anti-stigma campaign messages. [ABSTRACT FROM AUTHOR]

Key Points: Question: Can development of an individualized treatment rule identify patients presenting to emergency departments/urgent care with suicidal ideation or suicide attempts who are likely to benefit from psychiatric hospitalization? Findings: A decision analytic model found that hospitalization was associated with reduced suicide attempt risk among patients who attempted suicide in the past day but not among others with suicidality. Accounting for heterogeneity, suicide attempt risk was found to increase with hospitalization in 24% of patients and decrease in 28%. Meaning: Results of this study suggest that implementing an individualized treatment rule could identify many additional patients who may benefit from or be harmed by hospitalization. Importance: Psychiatric hospitalization is the standard of care for patients presenting to an emergency department (ED) or urgent care (UC) with high suicide risk. However, the effect of hospitalization in reducing subsequent suicidal behaviors is poorly understood and likely heterogeneous. Objectives: To estimate the association of psychiatric hospitalization with subsequent suicidal behaviors using observational data and develop a preliminary predictive analytics individualized treatment rule accounting for heterogeneity in this association across patients. Design, Setting, and Participants: A machine learning analysis of retrospective data was conducted. All veterans presenting with suicidal ideation (SI) or suicide attempt (SA) from January 1, 2010, to December 31, 2015, were included. Data were analyzed from September 1, 2022, to March 10, 2023. Subgroups were defined by primary psychiatric diagnosis (nonaffective psychosis, bipolar disorder, major depressive disorder, and other) and suicidality (SI only, SA in past 2-7 days, and SA in past day). Models were trained in 70.0% of the training samples and tested in the remaining 30.0%. Exposures: Psychiatric hospitalization vs nonhospitalization. Main Outcomes and Measures: Fatal and nonfatal SAs within 12 months of ED/UC visits were identified in administrative records and the National Death Index. Baseline covariates were drawn from electronic health records and geospatial databases. Results: Of 196 610 visits (90.3% men; median [IQR] age, 53 [41-59] years), 71.5% resulted in hospitalization. The 12-month SA risk was 11.9% with hospitalization and 12.0% with nonhospitalization (difference, −0.1%; 95% CI, −0.4% to 0.2%). In patients with SI only or SA in the past 2 to 7 days, most hospitalization was not associated with subsequent SAs. For patients with SA in the past day, hospitalization was associated with risk reductions ranging from −6.9% to −9.6% across diagnoses. Accounting for heterogeneity, hospitalization was associated with reduced risk of subsequent SAs in 28.1% of the patients and increased risk in 24.0%. An individualized treatment rule based on these associations may reduce SAs by 16.0% and hospitalizations by 13.0% compared with current rates. Conclusions and Relevance: The findings of this study suggest that psychiatric hospitalization is associated with reduced average SA risk in the immediate aftermath of an SA but not after other recent SAs or SI only. Substantial heterogeneity exists in these associations across patients. An individualized treatment rule accounting for this heterogeneity could both reduce SAs and avert hospitalizations. This predictive analytics model develops a preliminary individualized treatment rule to estimate the association between psychiatric hospitalization and subsequent suicidal behaviors in patients at risk for suicide. [ABSTRACT FROM AUTHOR]

Objectives: Using a sample of student service members/veterans, the current study aimed to examine the prevalence of psychiatric diagnoses and suicide-related outcomes and the association of hazardous duty with mental health. Participants: Data are from the Fall 2011 National College Health Assessment (N = 27,774). Methods: Logistic regression was used to examine (1) the association of student service member/veteran status with mental health outcomes and (2) the association of hazardous duty with mental health outcomes among student service members/veterans (n = 706). Results: Student service members/veterans had higher odds of self-harm than students without military experience. Among student service members/veterans, hazardous duty was positively associated (odds ratio [OR] = 2.00, 95% confidence interval [CI] [1.30, 3.07]) with having a psychiatric diagnosis but negatively associated (OR = 0.41, 95% CI [0.20, 0.85]) with suicidal ideation. Conclusions: Self-harm may be a unique phenomenon among service members/veterans. Suicide prevention with this population should include information about self-harm, and future research should explore whether suicidal intent underlies self-harm.

Background: Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the feasibility of creating a baseline model to determine which of these would be among patients beginning ADM treatment in the US Veterans Health Administration (VHA). Methods: A 2018–2020 national sample of n = 660 VHA patients receiving ADM treatment for MDD completed an extensive baseline self-report assessment near the beginning of treatment and a 3-month self-report follow-up assessment. Using baseline self-report data along with administrative and geospatial data, an ensemble machine learning method was used to develop a model for 3-month treatment response defined by the Quick Inventory of Depression Symptomatology Self-Report and a modified Sheehan Disability Scale. The model was developed in a 70% training sample and tested in the remaining 30% test sample. Results: In total, 35.7% of patients responded to treatment. The prediction model had an area under the ROC curve (s.e.) of 0.66 (0.04) in the test sample. A strong gradient in probability (s.e.) of treatment response was found across three subsamples of the test sample using training sample thresholds for high [45.6% (5.5)], intermediate [34.5% (7.6)], and low [11.1% (4.9)] probabilities of response. Baseline symptom severity, comorbidity, treatment characteristics (expectations, history, and aspects of current treatment), and protective/resilience factors were the most important predictors. Conclusions: Although these results are promising, parallel models to predict response to alternative treatments based on data collected before initiating treatment would be needed for such models to help guide treatment selection. [ABSTRACT FROM AUTHOR]

Background: Fewer than half of patients with major depressive disorder (MDD) respond to psychotherapy. Pre-emptively informing patients of their likelihood of responding could be useful as part of a patient-centered treatment decision-support plan. Methods: This prospective observational study examined a national sample of 807 patients beginning psychotherapy for MDD at the Veterans Health Administration. Patients completed a self-report survey at baseline and 3-months follow-up (data collected 2018–2020). We developed a machine learning (ML) model to predict psychotherapy response at 3 months using baseline survey, administrative, and geospatial variables in a 70% training sample. Model performance was then evaluated in the 30% test sample. Results: 32.0% of patients responded to treatment after 3 months. The best ML model had an AUC (SE) of 0.652 (0.038) in the test sample. Among the one-third of patients ranked by the model as most likely to respond, 50.0% in the test sample responded to psychotherapy. In comparison, among the remaining two-thirds of patients, <25% responded to psychotherapy. The model selected 43 predictors, of which nearly all were self-report variables. Conclusions: Patients with MDD could pre-emptively be informed of their likelihood of responding to psychotherapy using a prediction tool based on self-report data. This tool could meaningfully help patients and providers in shared decision-making, although parallel information about the likelihood of responding to alternative treatments would be needed to inform decision-making across multiple treatments. [ABSTRACT FROM AUTHOR]

In the United States, an estimated three million men are victims of sexual violence each year, yet the majority of existing studies have evaluated the consequences and characteristics of victimization among women alone. The result has been a gap in the existing literature examining the physical and psychological consequences of sexual assault among men. The main objective of this study was to identify health outcomes, risk behaviors, and perpetrator/victim relationship characteristics among men who have experienced an attempted or completed sexual assault using data from the sexual violence module of the Behavioral Risk Factor Surveillance System survey. A total of 59,511 male respondents participated in the sexual violence module, and the majority of participants were White (73.7%), between the ages of 35 to 44 years (19.8%), married (69.0%), graduated from college (34.6%), and had an annual household income of more than US$50,000 (49.9%). Stratified multivariate logistic regression models were conducted to test the associations between victimization and health outcomes and risk behaviors controlling for age, marital status, race/ethnicity, income, education, and other potential confounders. Results of these analyses suggest important associations between health and sexual violence victimization. Specifically, men who reported unwanted attempted intercourse and attempted and completed intercourse were more likely to report poor mental health, poor life satisfaction, activity limitations, and lower emotional and social support. The current study extends knowledge of consequences of male sexual violence by considering characteristics of sexual assault and by identifying associations between victimization and a broad range of health indicators. (Contains 5 tables.)

Background: Problems related to gangs have been noted in large cities and in many schools across the United States. This study examined the patterns of alcohol, drug use, and related exposures among male and female high school students who were gang members. Methods: Analyses were based on the Youth Violence Survey, conducted in 2004, and administered to over 80% of eligible public school students in grades 7, 9, 11, and 12 (N = 4131) in a high-risk, urban school district. The self-administered survey, completed during a class period, included measures of alcohol and drug use and related exposures. Tests of associations were determined using chi-square tests and logistic regression analyses. Results: In this study, 8.8% of students reported gang membership. Students who initiated alcohol use prior to age 13 (OR = 4.90; 95% CI: 3.65-6.58), who drank alcohol 3 or more times per week (OR = 9.57; 95% CI: 6.09-15.03) and who used drugs 3 or more times per week (OR = 6.51; 95% CI: 4.59-9.25) were more likely to report gang membership than students who did not report alcohol or drug use. Boys were more likely than girls to report alcohol-related fighting and drug selling. Discussion: Gang members were significantly more likely than non-gang members to have initiated alcohol early, to have reported a high prevalence of alcohol use, to have engaged in alcohol-related physical fighting, peer drinking, drug use, drug selling, peer drug selling, and having seen drug deals in their neighborhood. Schools may serve as a critically important source for intervention and prevention efforts for gang members, especially those in 7th grade, who still attend school. (Contains 3 tables.)

Background: Involvement in interpersonal violence or suicidal behaviors can have a significant impact on an adolescent's physical health. Similarly, previous research has suggested that lived experiences, more than the presence or absence of physical ailments, can significantly influence self-assessed health status among adolescents. The purpose of this study was to examine the cross-sectional associations between involvement in violence and poor or fair self-reported health among US high school students. Methods: Data were obtained from the 2005 national Youth Risk Behavior Survey (n = 13,953). Logistic regression analyses were conducted to determine the associations between violence-related measures and self-reported health while controlling for demographic characteristics and potential confounders. Analyses are presented for students overall and stratified by sex and race/ethnicity. Results: Overall, 7.2% of students reported fair or poor self-rated health. Having been in a physical fight, having been injured in a physical fight, having attempted suicide, and having not gone to school because of safety concerns were significantly associated with fair or poor self-rated health after controlling for demographic characteristics and other potential confounders. Differences associated with race/ethnicity and sex are identified. Conclusions: Four of the 5 violence-related measures included in these analyses were significantly associated with fair or poor self-rated health. Future studies should consider the impact of involvement in violent behaviors and perceptions of both physical and mental well-being. (Contains 3 tables.)

To understand the co-occurrence of multiple types of violence, the authors developed a behavioral typology based on self-reports of suicidal behaviors, physical violence, and psychological abuse. Using a sample of dating adolescents from a high-risk school district, they identified five clusters of behaviors among the 1,653 students who reported being abusive or violent in the past year. Victimization and perpetration with same-sex peers and dating partners clustered together among the students who reported the highest levels of abusive (n = 357) or violent behavior (n = 146). These students also reported high levels of suicidal behavior. There were few significant demographic differences across clusters. The implications of the results for the need to design and evaluate efforts to prevent multiple types of violence are discussed. (Contains 4 tables and 1 note.)