Carly E. McCord

With persistent racial inequities, cultural adaptations of health programs can promote equitable maternal mental health. Despite the intersecting identities of Black mothers with preterm birth combined with racial discrimination, previous mental health programs in the neonatal intensive care unit (NICU) are void of the sociocultural context that perpetuates racially motivated care. This study uses a two-round Delphi process to gather knowledge on the cultural appropriateness and content validity of the adapted Mothers and Babies Online Course, a United States Prevention Service Task Force-recommended intervention for managing mental health symptoms in pregnant and new mothers for Black mothers with preterm birth. The Black feminist theory and cultural adaptation strategies were used to conceptualize the adaptation process. Opinions were solicited from Black mothers and professionals based on predetermined criteria. Eleven participants, comprising eight mothers and three professionals, participated in Round One. Of these, only one professional did not participate in Round Two, totaling 10 participants who participated in Round Two. The participants rated the adapted program—eMB 4 Blackmamas, positively, and four themes emerged, substantiating the importance of culturally responsive mental health. The themes also offered additional feedback related to improving the program delivery. Including diverse stakeholders in mental health research offers unique and balanced insights into designing culturally appropriate programs to promote and protect Black maternal mental health in the NICU.

The use of technology in health service delivery (e.g., telehealth) and subsequently in training and education in preparation for health service careers (e.g., telesupervision) provides both challenges and opportunities. Embracing the opportunities afforded by telehealth and telesupervision will help equip the next generation of health professionals for the realities of the healthcare system of the future as well as promote greater equity for trainees and patients. To ensure maximum gain and minimal negative impact, training programs, researchers, and policymakers must work together. The field can move forward through application of innovative use cases, thoughtful design and implementation of evaluation, and the development of constructive policies. This column aims to inform these different stakeholders by providing applied examples of telesupervision in a telehealth training clinic, discussing the evaluation of telesupervision programs and competencies, and discussing policy implications for telesupervision.

Background: The COVID-19 pandemic triggered widespread adjustments across the US health care system. Telehealth use showed a substantial increase in mental health conditions and services due to acute public health emergency (PHE) behavioral health needs on top of long-standing gaps in access to behavioral health services. How health systems that were already providing behavioral telehealth services adjusted services and staffing during this period has not been well documented, particularly in rural areas with chronic shortages of behavioral health providers and services. Objective: This study investigates patient and treatment characteristic changes from before the COVID-19 PHE to during the PHE within both telehealth and in-person behavioral health services provided in 95 rural communities across the United States. Methods: We used a nonrandomized, prospective, multisite research design involving 2 active treatment groups. The telehealth cohort included all patients who initiated telehealth treatment regimens during the data collection period. A comparison group included a cohort of patients who initiated in-person treatment regimen. Patient enrollment occurred on a rolling basis, and data collection was extended for 3 months after treatment initiation for each patient. Chi-square tests compared changes from pre-PHE to PHE time periods within telehealth and in-person treatment cohorts. The dependent measures included patient diagnosis, clinicians providing treatment services, and type of treatment services provided at each encounter. The 4780 patients in the telehealth cohort and the 6457 patients in the in-person cohort had an average of 3.5 encounters during the 3-month follow-up period. Results: The encounters involving anxiety, dissociative, and stress-related disorders in the telehealth cohort increased from 30% (698/2352) in the pre-PHE period to 35% (4632/12,853) in the PHE period (P<.001), and encounters involving substance use disorders in the in-person cohort increased from 11% (468/4249) in the pre-PHE period to 18% (3048/17,047) in the PHE period (P<.001). The encounters involving treatment service codes for alcohol, drug, and medication-assisted therapy in the telehealth cohort increased from 1% (22/2352) in the pre-PHE period to 11% (1470/13,387) in the PHE period (P<.001); likewise, encounters for this type of service in the in-person cohort increased from 0% (0/4249) in the pre-PHE period to 16% (2687/17,047) in the PHE period (P<.001). From the pre-PHE to the PHE period, encounters involving 60-minute psychotherapy in the telehealth cohort increased from 8% (190/2352) to 14% (1802/13,387; P<.001), while encounters involving group therapy in the in-person cohort decreased from 12% (502/4249) to 4% (739/17,047; P<.001). Conclusions: The COVID-19 pandemic challenged health service providers, and they adjusted the way both telehealth and in-person behavioral therapy services were delivered. Looking forward, future research is needed to explicate the interaction of patient, provider, setting, and intervention factors that influenced the patterns observed as a result of the COVID-19 pandemic.

BACKGROUND The COVID-19 pandemic triggered widespread adjustments across the US health care system. Telehealth use showed a substantial increase in mental health conditions and services due to acute public health emergency (PHE) behavioral health needs on top of long-standing gaps in access to behavioral health services. How health systems that were already providing behavioral telehealth services adjusted services and staffing during this period has not been well documented, particularly in rural areas with chronic shortages of behavioral health providers and services. OBJECTIVE This study investigates patient and treatment characteristic changes from before the COVID-19 PHE to during the PHE within both telehealth and in-person behavioral health services provided in 95 rural communities across the United States. METHODS We used a nonrandomized, prospective, multisite research design involving 2 active treatment groups. The telehealth cohort included all patients who initiated telehealth treatment regimens during the data collection period. A comparison group included a cohort of patients who initiated in-person treatment regimen. Patient enrollment occurred on a rolling basis, and data collection was extended for 3 months after treatment initiation for each patient. Chi-square tests compared changes from pre-PHE to PHE time periods within telehealth and in-person treatment cohorts. The dependent measures included patient diagnosis, clinicians providing treatment services, and type of treatment services provided at each encounter. The 4780 patients in the telehealth cohort and the 6457 patients in the in-person cohort had an average of 3.5 encounters during the 3-month follow-up period. RESULTS The encounters involving anxiety, dissociative, and stress-related disorders in the telehealth cohort increased from 30% (698/2352) in the pre-PHE period to 35% (4632/12,853) in the PHE period (P<.001), and encounters involving substance use disorders in the in-person cohort increased from 11% (468/4249) in the pre-PHE period to 18% (3048/17,047) in the PHE period (P<.001). The encounters involving treatment service codes for alcohol, drug, and medication-assisted therapy in the telehealth cohort increased from 1% (22/2352) in the pre-PHE period to 11% (1470/13,387) in the PHE period (P<.001); likewise, encounters for this type of service in the in-person cohort increased from 0% (0/4249) in the pre-PHE period to 16% (2687/17,047) in the PHE period (P<.001). From the pre-PHE to the PHE period, encounters involving 60-minute psychotherapy in the telehealth cohort increased from 8% (190/2352) to 14% (1802/13,387; P<.001), while encounters involving group therapy in the in-person cohort decreased from 12% (502/4249) to 4% (739/17,047; P<.001). CONCLUSIONS The COVID-19 pandemic challenged health service providers, and they adjusted the way both telehealth and in-person behavioral therapy services were delivered. Looking forward, future research is needed to explicate the interaction of patient, provider, setting, and intervention factors that influenced the patterns observed as a result of the COVID-19 pandemic. CLINICALTRIAL

Background: This study investigates outcomes from two federal grant programs: the Evidence-Based Tele-Behavioral Health Network Program (EB THNP) funded from September 2018 to August 2021 and the Substance Abuse Treatment Telehealth Network Grant Program (SAT TNGP) funded from September 2017 to August 2020. As part of the health services implementation program, the aims of this study were to evaluate outcomes in patient symptoms of depression and anxiety across the programs’ 17 grantees and 95 associated sites, with each grantee having data from telehealth patients and from an in-person comparison group. Methods: The research design is a prospective multi-site observational study. Each grantee provided data on a nonrandomized convenience sample of telehealth patients and an in-person comparison group from sites with similar rural characteristics and during the same time period. Patient characteristics were collected at treatment initiation, and clinical outcome measures were collected at baseline and monthly. The validated clinical outcome measure instruments included the Patient Health Questionnaire-9 (PHQ-9) for depression symptoms and the Generalized Anxiety Disorder-7 (GAD-7) scale for anxiety-related symptoms. Linear mixed models, with grantee as the random effect, were used to determine the association of behavioral health delivery (telehealth versus in-person) on the one-month change in PHQ-9 and GAD-7 while adjusting for covariates. Results: Across a total of 1,514 patients, one-month change scores were improved indicating that PHQ-9 and GAD-7 scores decreased from baseline to the one-month follow-up at similar rates in both the in-person and telehealth groups. Reduction in scores averaged 2.8 for the telehealth treatment group and 2.9 for the in-person treatment group in the PHQ-9 subsample and 2.0 for the telehealth treatment group and 2.4 for the in-person treatment group in the GAD-7 subsample. There was no statistically significant association between the modality of care (telehealth treatment group versus in-person comparison group) and the one-month change scores for either PHQ-9 or GAD-7. Individuals with higher baseline scores demonstrated the greatest decrease in scores for both measures. Upon adjusting for baseline scores and grantee program, patient demographics were not found to be significantly associated with change in anxiety or depression symptoms. Conclusion: In our very large pragmatic study comparing behavioral health treatment delivered to a population of patients in rural, underserved communities, we found no clinical or statistical differences in improvements in depression or anxiety symptoms as measured by the PHQ-9 and GAD-7 between patients treated via telehealth or in-person.

Objective: The purpose of this study was to explore physicians’ attitudes toward different strategies for supporting pain management and opioid prescribing and to identify factors related to their attitudes toward the support strategies. Design/setting/participants/measures: This preliminary cross-sectional study collected and analyzed online survey responses from physicians in Texas and Minnesota (N = 69) between December 2017 and February 2018. Primary outcomes were physicians’ interest in online continuing medical education (CME), mHealth patient monitoring system, and short, non-CME YouTube informational briefs about pain management and opioid prescribing. Multiple logistic regression models were used to examine the associations between physicians’ characteristics, attitudes, training, experience, practice setting, and their interest in three different support strategies. Results: About 51-58 percent of physicians indicated moderate-to-extreme interest in online CME (54 percent), mHealth monitoring (58 percent), and short, non-CME YouTube informational briefs (51 percent). Physicians, who practiced in a medium or large practice setting, were less likely to be interested in online CME or short, non-CME YouTube informational briefs. Physicians who prescribed a small number of Schedule II opioids were more likely to be interested in short, non-CME YouTube informational briefs and mHealth monitoring. Conclusions: Findings suggest that physicians may have different preferences in strategies for supporting their pain management and opioid prescribing practices. Future studies are needed to better understand the mechanisms underlying physicians’ interest in different support strategies.  

Mental illness significantly impacts agricultural producers, whose occupation puts them at increased risk for compromised mental health and related disorders. Help-seeking intention, which can be mediated by variables such as social identity, social capital, and self-stigma, can lead to improved mental health outcomes. This cross-sectional study aimed to describe the intention of agricultural producers to seek mental health assistance and determine whether these three variables are associated with help-seeking intention. Researchers administered a cross-sectional survey of agricultural producers from two regions in 32 Texas counties. Researchers surveyed a sample of Texas agricultural producers (n = 429) to understand their social identity, social capital, and degree of self-stigma, and their intent to seek help for personal or emotional problems and for suicide ideation. Researchers identified a relationship between social identity and social capital, which indicated that social identity is moderately associated with greater levels of social capital. The multiple linear regression analyses confirmed that social capital and self-stigma are significant predictors of producers’ help-seeking intention for both help-seeking types. These results signify the importance of efforts to increase social capital, increase mental health literacy and tailor training to address self-stigma and enhance positive help-seeking behavior among agricultural producers.

Background This study investigates outcomes from two federal grant programs: the Evidence-Based Tele-Behavioral Health Network Program (EB THNP) funded from September 2018 to August 2021 and the Substance Abuse Treatment Telehealth Network Grant Program (SAT TNGP) funded from September 2017 to August 2020. As part of the health services implementation program, the aims of this study were to evaluate outcomes in patient symptoms of depression and anxiety across the programs’ 17 grantees and 95 associated sites, with each program having data from telehealth patients and from an in-person comparison group. The evaluation compares outcomes between the group of patients seen in-person and the group of patients seen viatelehealth. Methods The study design is a nonrandomized convenience sample across telehealth and in-person groups from sites with similar rural characteristics and during the same time period. Patient characteristics were to be collected at treatment initiation, and clinical outcome measures were to be collected at baseline and monthly on patients where clinically appropriate. The validated clinical outcome measure instruments included the Patient Health Questionnaire-9 (PHQ-9) for depression symptoms and the Generalized Anxiety Disorder-7 (GAD-7) scale for anxiety-related symptoms. Results Across a total of 1,514 patients, one-month change scores were improved indicating that PHQ-9 and GAD-7 scores decreased from baseline to the one month follow-up at similar rates in both the in-person and telehealth groups. Reduction in scores averaged 2.8 for the telehealth treatment group and 2.9 for the in-person treatment group in the PHQ-9 subsample and 2.0 for the telehealth treatment group and 2.4 for the in-person treatment group in the GAD-7 subsample. There was no statistically significant association between the modality of care (telehealth treatment group versus in-person comparison group) and the one-month change scores for either PHQ-9 or GAD-7. Individuals with higher baseline scores demonstrated the greatest decrease in scores for both measures. Upon adjusting for baseline scores and clustering within grantee program, patient demographics were not found to be significantly associated with change in anxiety or depression symptoms. Conclusions In our very large pragmatic study comparing behavioral health treatment delivered to a population of patients in rural, underserved communities, we found no clinical or statistical differences in improvements in depression or anxiety symptoms as measured by the PHQ-9 and GAD-7 between patients treated via telehealth or in-person.