Projects

Employing a Stepped-Wedge Design to Implement an Evidence-Based Psychotherapy for PTSD in Six Large, Diverse Health Care Systems

Grant Details

Funder: PCORI

Grant Number:

Project Period: 2022 – 2025

Lead Sites:
- Yale (co-PI Joan Cook) and KPHI (co-PI Vanessa Simiola)
Participating Sites:
- Henry Ford Health System (co-I Lisa Matero)
- Kaiser Permanente Northwest (co-I Frances Lynch)
- Kaiser Permanente Georgia (co-Is Ashli Owen-Smith, Kanetha Wilson, Courtney McCracken)
- Essentia Health (co-I Melissa Harry)
- Baylor Scott & White Health (co-I Katherine Sanchez)

Brief Narrative: Written Exposure Therapy (WET) is a five-session exposure-based EBP for PTSD that was efficacious in randomized controlled trials for treating PTSD from different types of traumas. In addition to PCORI’s recognition, WET is recommended as a first-line treatment by the Department of Veteran Affairs (VA) and the Department of Defense (DoD). In two recent trials, WET was non-inferior to the more time-intensive, gold-standard EBP, Cognitive Processing Therapy. Thus, WET seems to meet the need for alternative PTSD treatments that are brief, with little dropout, and require less clinical training. Indeed, WET’s brevity and tolerability make it an ideal first-level intervention, appealing to patients who have opted not to seek out more time- and therapist-intensive EBPs. WET addresses significant barriers to other EBPs for PTSD at the patient, provider, and system levels.

The project will employ a stepped wedge design to implement WET in six, large, diverse, integrated, civilian health care systems across the United States— Kaiser Permanente (KP) Hawaii, Henry Ford Health System, Kaiser Permanente Northwest, Kaiser Permanente Georgia, Essentia Health, and Baylor Scott & White Health — with all sites receiving the intervention during the project period. The healthcare systems are members of the Mental Health Research Network (MHRN), a consortium of 14 research centers. Sites will be assigned to one of two implementation groups. Every site will receive WET training, consultation, and multi-component implementation strategies, promoting equity and advancing the field of implementation science.

The specific aims of this project are to:

Employ multi-component implementation strategies to help mental health providers implement WET for their PTSD patients in mental health settings in six health care systems.
Use Consolidated Framework for Implementation Research (CFIR) to understand the determinants and process of implementation.
Utilize RE-AIM framework to evaluate implementation outcomes for mental health providers and patients.

Improving Suicide Risk Prediction with Social Determinants Data

Grant Details

Funder: NIMH

Grant Number: R56MH125794-01A1

Grant Period: 1/1/2022 – 12/31/2022

Brief Narrative: Suicide accounted for 47,511 deaths in the United States in 2019 and the suicide rate has increased by 39% since 1999. Suicide prevention is an NIMH research priority. Recent research in estimating machine learning algorithms to predict suicide risk has been tremendously successful. The models have been implemented as part of routine prevention programs in health systems such as Kaiser Permanente Washington, HealthPartners, and the Veterans Health Administration. Despite these successes, existing models have important shortcomings. A significant proportion of suicides followed healthcare visits where the predicted risk was low (and where an intervention might have taken place otherwise). The models do not currently include any information about social determinants of suicide (e.g., living alone, financial stress) or negative life events (NLE), such as divorce, bankruptcy, and criminal arrest. Adding social determinants data and NLE data to models may improve predictive accuracy. The specific aims of this study are: (1) expand and enhance the risk prediction dataset with over 1500 date-stamped variables describing social determinants of suicide risk and NLE; (2) construct and evaluate suicide risk prediction models using social determinants and NLE data alone; (3) construct and evaluate suicide risk prediction models using social determinants, NLE and healthcare data together and estimate interaction terms between social determinants, NLE, and healthcare predictors. An example would be “depression diagnosis” interacted with “divorce filing in last 30 days”. This will be the first large scale study to incorporate individual-level, date-stamped measures of social determinants and NLE into machine learning suicide risk prediction models. Upon successful completion of this study we expect to know how much incorporating these new data contributes to the accuracy of suicide risk prediction models. This will be an important next step towards implementing better suicide prevention programs and reducing overall suicide rates.

Lead Site: KPWA (PI Rob Penfold)

Participating Sites: N/A

Current Status

We fielded the discrete choice experiment in mid-October 2022. Planned recruitment is 720.

Summary of Findings

Publications

Mindfulness-based cognitive therapy for prevention of perinatal depression

Grant Details

Funder: NIMH

Grant Number: R34MH083866

Grant Period: 9/17/2008 – 7/31/2012

Brief Narrative: This study will investigate the feasibility, safety, acceptability, and preliminary efficacy of a brief, group intervention designed to prevent perinatal depression (PD). We will develop and evaluate a behavioral preventive intervention based on Mindfulness-Based Cognitive Therapy (MBCT), which has been found to significantly reduce rates of relapse of recurrent depression among general adult samples and has high relevance to the prevention of PD. MBCT is non-pharmacological, offers an alternative to traditional one-on-one care models, and is based on a clear conceptual and empirical relationship between the specific intervention strategies and the most robust risk factor for perinatal depression, namely depressive history. The project will involve 3 phases, implemented in 2 obstetric settings: 1) conceptualizing the intervention based on theory and empirical research (MBCT for perinatal depression; MBCT-PD), 2) developing and standardizing MBCT-PD, and 3) pilot testing its efficacy in preventing relapse and recurrence among perinatal women with histories of depression. Phase 1 work is already under way. In Phase 2, we propose an open-trial to develop the MBCT-PD program (N=20). Based on an iterative process, we will finalize a participant- and expert informed manual for MBCT-PD that is sensitive and specific to the developmental factors associated with PD. In Phase 3, we propose to test MBCT-PD in a pilot randomized controlled trial comparing MBCT-PD to Treatment-as-Usual (TAU) (N=160). We will test the primary hypothesis that participants receiving MBCT-PD will experience improved depressive outcomes compared to participants receiving TAU, including testing group differences in rates of relapse/recurrence and exploring group differences in depressive symptom severity. We will also explore group differences in secondary outcomes, including anxiety and stress and obstetrical complications, and will explore potential moderators and mediators of depression outcomes. Finally, we will train and evaluate the ability of behavioral health care providers to administer the MBCT-PD program with fidelity. Given the negative and enduring consequences of untreated perinatal depression for women and their children, low rates of treatment seeking, and concerns associated with pharmacological approaches, the development and ongoing investigation of MBCT-PD may have significant benefits for women, children, and society at large

Lead Site: University of Colorado (PI Sona Dimidjian)

Participating Sites: KPCO, Emory University

Current Status

Summary of Findings

Publications

Dimidjian, Sona; Goodman, Sherryl H; Felder, Jennifer N; Gallop, Robert; Brown, Amanda P; Beck, Arne. Staying Well during Pregnancy and the Postpartum: A Pilot Randomized Trial of Mindfulness Based Cognitive Therapy for the Prevention of Depressive Relapse/Recurrence. Journal of consulting and clinical psychology 2016 Feb; 84 (2) 134-45
Dimidjian, Sona; Segal, Zindel V. Prospects for a clinical science of mindfulness-based intervention. The American psychologist 2015 Oct; 70 (7) 593-620
Dimidjian, Sona; Goodman, Sherryl H; Felder, Jennifer N; Gallop, Robert; Brown, Amanda P; Beck, Arne. An open trial of mindfulness-based cognitive therapy for the prevention of perinatal depressive relapse/recurrence. Archives of women’s mental health 2015 Feb; 18 (1) 85-94
Goodman, Sherryl H; Dimidjian, Sona. The developmental psychopathology of perinatal depression: implications for psychosocial treatment development and delivery in pregnancy. Canadian journal of psychiatry. Revue canadienne de psychiatrie 2012 Sep; 57 (9) 530-6

Trans-America Consortium of the Health Care Systems Research Network for the All of Us Research Program

Grant Details

Funder: NIH Office of the Director

Grant Number: OT2OD026550

Grant Period: 1/4/2018 – 3/31/2023

Narrative:

Lead Site: HFHS (co-PIs Christine Johnson and Brian Ahmedani)

Participating Sites:

Current Status:

Ongoing recruitment, enrollment and retention of 100,000 participants and members.

Summary of Findings:

Publications:

Cronin, R.M., Jerome, R.N., Mapes, B.M., Andrade, R., Johnston, R., Ayala, J., Schlundt, D., Bonnet, K.R., Kripalani, S., Goggins, K., Wallston, K.A., Couper, M.P., Elliott, M.R., Harris, P.A., Begale, M.A., Munoz, F.A., Lopez-Class, M., Cella, D., Condon, D.M., AuYoung, M., Mazor, K.M., Mikita, S., Manganiello, M., Borselli, N., Fowler, S.L., Rutter, J.L., Denny, J.C., Karlson, E.W., Ahmedani, B.K., O’Donnell, C.J. Vanderbilt University Medical Center Pilot Team, and the Participant Provided Information Committee. (2019). Development of the Initial Surveys for the All of Us Research Program. Epidemiology, 30(4), 597-608.. doi: 10.1097/EDE.0000000000001028. PMID: 31045611.

Ramirez AH, Sulieman L, Schlueter DJ, Halvorson A, Qian J, Ratsimbazafy F, Loperena R, Mayo K, Basford M, Deflaux N, Muthuraman KN, Natarajan K, Kho A, Xu H, Wilkins C, Anton-Culver H, Boerwinkle E, Cicek M, Clark CR, Cohn E, Ohno-Machado L, Schully SD, Ahmedani BK, Argos M, Cronin RM, O’Donnell C, Fouad M, Goldstein DB, Greenland P, Hebbring SJ, Karlson EW, Khatri P, Korf B, Smoller JW, Sodeke S, Wilbanks J, Hentges J, Mockrin S, Lunt C, Devaney SA, Gebo K, Denny JC, Carroll RJ, Glazer D, Harris PA, Hripcsak G, Philippakis A, Roden DM; All of Us Research Program. (2022). The All of Us Research Program: Data quality, utility, and diversity. Patterns (N Y); 3(8), 100570. doi: 10.1016/j.patter.2022.100570. PMID: 36033590.

Cronin, R.M., Halvorson, A.E., Springer, C., Feng, X., Sulieman, L., Loperena-Cortes, R., Mayo, K., Carroll, R.J., Chen, Q., Ahmedani, B.K., Karnes, J., Korf, B., O’Donnell, C.J., Qian, J., Ramirez, A.H., All of Us Research Program Investigators. (2021). Comparison of Family Health History in Surveys versus Electronic Health Records in the All of Us Research Program. Journal of the American Medical Informatics Association, 28(4):695-703. doi: 10.1093/jamia/ocaa315. PMID: 33404595.

Treatment Initiation for New Episodes of Depression in Pregnant Women

Grant Details

Funder: NICHHD

Grant Number: R01HD100579

Grant Period: 5/6/2021 – 3/31/2026

Narrative: Up to 12% of pregnant women have a new episode of depression, ie, an incident or recurrent depressive episode with symptom onset during pregnancy. Effects of untreated antenatal depression include unhealthy maternal behaviors (eg, diminished self-care, smoking, substance use, self-harm) and emotional and behavioral problems in offspring. Antenatal depression or elevated depression scores, identified by screening instruments, increase the risk of preterm birth (PTB), low birth weight (LBW), and small for gestational age (SGA) birth, and are associated with breastfeeding discontinuation before 3 months postpartum. In-person psychotherapy and antidepressant medication improve depression symptoms in many with depression, yet <50% of pregnant women with new episodes of depression initiate these treatments. Although some barriers to initiating antidepressants and psychotherapy are known, other factors have not been well described, especially after accounting for depression severity. Furthermore, the impact of antidepressants and psychotherapy on perinatal outcomes, including PTB, LBW, SGA, and breastfeeding continuation among pregnant women with new episodes of depression after accounting for confounding by depression severity is unknown. Given the importance of factors influencing the decision to initiate antidepressant or psychotherapy treatment during pregnancy and the need for further evidence on the perinatal risks and benefits associated with antidepressant use and psychotherapy in pregnant women, the goal of this study is to identify predictors and perinatal effects of psychotherapy and antidepressant use for new episodes of depression during pregnancy while accounting for depression severity. We will conduct this study in a racially and ethnically diverse multi- site population using electronic health data, enriched with survey data from a subset of women. Among pregnant women with new episodes of depression, we will evaluate factors that influence the propensity to initiate psychotherapy or antidepressants; accounting for these is crucial when studying treatment effects. We will describe patterns of use of alternative depression management approaches (eg, Internet- based psychotherapy, peer support groups, and complementary and alternative medicine) and will evaluate whether initiation of psychotherapy or antidepressants is associated with these practices while accounting for depression severity. We will quantify the impact of psychotherapy and antidepressants (including dose, timing, and duration of use) on PTB, LBW, SGA, and breastfeeding continuation accounting for the propensity to initiate psychotherapy or antidepressants and depression severity. We are uniquely positioned to overcome limitations of confounding and small size in prior studies given our data on depression severity and maternal comorbidity for more than 8,000 pregnant women. Our study will be informative for understanding the mental health interventions utilized by pregnant women with depression and will inform decision making on optimal depression management during pregnancy.

Lead site:
- HPI (PI Kristin Palmsten)

Participating Sites:
- HFHS
- KPHI
- KPNC
- KPSC

Current Status:

We are currently conducting the first aim of the study, which is a survey among people with new episodes of depression during pregnancy. We aim to learn about the treatments and strategies participants used to manage new episodes of depression during pregnancy, how they are supported by others, and how they feed their new babies. The survey also asks about childhood and life experiences. We completed a pilot survey at HealthPartners this spring and we are launching the survey across all sites this fall.

Summary of Findings:

None yet

Publications:

None yet

Assisted Identification and Navigation of Early Mental Health Symptoms in Youth

Grant Details

Funder: NIMH

Grant Number: R01MH124652

Grant Period: 1/18/2021 – 11/30/2024

Narrative: About 55% of children with significant mental health difficulties receive treatment and up to 80% of children with sub-clinical symptoms receive no treatment. Treatments are often not initiated until issues are significantly impacting the child and family. This study aims to conduct a pragmatic randomized trial in two non-academic health care systems to test a mental health family navigator model to promote early access to, engagement in, and coordination of needed mental health services for children. The first task of the study will focus on the implementation of a predictive model to identify symptomatic children with no diagnosed mental health disorder(s) or treatments initiated. The tool identifies patients with documentation of mental health symptoms or complaints in the free text of a progress note from a recent primary care or urgent care visit. Using this predictive algorithm, we will conduct a pragmatic randomized trial comparing intervention and usual care arm patients enrolled from Kaiser Permanente (KP) Washington and KP Northern California. The trial will enroll 200 patients per arm (n=400). Children with (1) a new mental health diagnosis but no treatment initiated; (2) a new mental health medication ordered with no mental health diagnosis; and (3) symptoms identified by the predictive model with no new mental health diagnosis or treatment initiated will be recruited. The study intervention will offer 6 months of support to the family by a mental health navigator (social worker). The navigator will perform an initial needs and barriers assessment with the family around mental health services, conduct ongoing motivational interviewing around mental health care, provide up to 4 psychotherapy sessions (when appropriate) via clinic-to-home video visits, help the family find and schedule with appropriate mental health providers in the community, and reach out ad hoc if mental health appointments or medication refills are missed. The primary outcome is the percentage of youth initiating psychotherapy. The secondary outcome is the percentage of youth with at least 4 mental health visits. We hypothesize that the intervention arm will have higher rates of psychotherapy use compared to the control arm. We will also assess initiation of psychotropic medications. All primary analyses will follow an intent-to-treat approach. A waiver of consent will be obtained to include data for all individuals offered the intervention in the analysis, regardless of the amount of intervention (“dose” of navigation) received.

Lead Site: KPWA (PI Rob Penfold)

Participating Site: KPNC

Current Status:

Recruitment is active at both KPWA and KPNC. N = 44 as of 10/25/2022.

Summary of Findings:

Publications:

STAR Caregivers – Virtual Training and Follow-up

Grant Details

Funder: NIMH

Grant Number: R01AG061926

Grant Period: 9/30/2018 – 5/31/2023

Narrative: Alzheimer’s Disease and related Dementias (ADRD) are debilitating conditions affecting more than 5 million Americans in 2014. It is projected that 8.4 million people with be diagnosed with ADRD over the next 15 years and health care costs attributable to ADRD are projected to be more than $1.2 trillion by 2050. Behavioral interventions such as STAR-Caregivers are efficacious first-line treatments for managing BPSD endorsed by the Administration on Aging. However, the programs have not been implemented widely – partly due to the intensity/cost of the programs and difficulty conducting outreach. No study has investigated CG willingness to reduce or discontinue antipsychotic use. We propose a Stage III clinical trial to ascertain the feasibility and acceptability of STAR Virtual Training and Follow-up (STAR- VTF) in which (a) training materials are delivered electronically and learning is self-directed, (b) caregivers have two in-home visits with a social worker and (c) where caregivers receive support from a social worker via secure messaging (email) within a web-based portal. We will compare outcomes in the STAR-VTF group to an attention control group (mailed material plus generic secure messages). Our specific aims are: (1) Assess the feasibility and acceptability of STAR-VTF to caregivers; (2) Assess the feasibility and acceptability of the program from the payer perspective; and (3) Test the hypotheses that (H1) caregiver participants in STAR-VTF will have lower levels of caregiver burden at 8 weeks and 6 months compared to an attention control group; and (H2) PWD participants in STAR-VTF will have lower rates of daily antipsychotic medication use at 6 months compared to attention control. We propose to recruit 100 CG-PWD dyads (50 in each arm). This will be the first study to test a low intensity, self-directed caregiver training program with secure message support from social workers. It will also be the first study to measure changes in antipsychotic medication use by PWD after CG training. The study is also innovative because it brings together leading experts in caregiver training, health information management, and care management. Third, this will be the first study to use automated data and natural language processing to identify potential caregivers in need of education/support at a time when antipsychotic medication use begins. Results of this study will inform a future multi-site trial in the Mental Health Research Network.

Lead Site: KPWA (PI Rob Penfold)

Participating Sites: N/A

Current Status

Currently enrolling person-living-with-dementia – Caregiver dyads. Recruitment will end December 2022.

Summary of Findings

none yet

Publications

Ramirez M, Duran MC, Pabiniak CJ, Hansen KE, Kelley A, Ralston JD, McCurry SM, Teri L, Penfold RB. Family Caregiver Needs and Preferences for Virtual Training to Manage Behavioral and Psychological Symptoms of Dementia: Interview Study. JMIR Aging. 2021 Feb 10;4(1):e24965. doi: 10.2196/24965. PMID: 33565984; PMCID: PMC8081155.

Trauma and PTSD in Medical Records

Grant Details:

Funder: NIMH (MHRN III Feasibility Pilot Program)

Grant Number: U19MH121738

Project Period: 7/1/2022 – 6/30/2023

Narrative:

Background: Exposure to potentially traumatic events such as physical and sexual abuse/assault, serious accidental injury, mass shootings, and terrorism, and associated PTSD are major public health concerns (Magruder, McLaughlin & Elmore Borbon, 2017). It is estimated that over 20 million Americans develop PTSD at some point in their life (Kessler, Berglund et al., 2005). Inadequate treatment of PTSD may lead to chronic impairment and disability and have long-term and widespread familial and societal consequences (e.g., domestic violence, suicide, incarceration).

Incident rates of PTSD appear strikingly low in the health care system compared to estimates derived from representative epidemiological studies of the general public. Conservative estimates suggest that up to 80% of adults will experience a traumatic event during their lifetime. In a large nationally representative epidemiological study, it was estimated that PTSD impacts 3.6% of civilians each year, with a lifetime prevalence rate of 6.8% (Kessler, Berglund et al., 2005; Kessler, Chiu et al., 2005). However, in a recent examination of PTSD in six MHRN-affiliated health care systems we found less than 1% of the patient population had a diagnosis of PTSD when using ICD diagnosis codes only, suggesting patients may be underdiagnosed or inadequately captured using this method. Further, ICD diagnosis codes are limited in their ability to capture trauma exposure type (e.g., combat exposure, motor vehicle crash, sexual abuse, elder abuse, intimate partner violence, natural disaster) and may be underutilized by providers.

This project builds on previously MHRN-funded research conducted by Negriff and colleagues (Lynch, 2022) who examined incidence of child maltreatment comparing rates of those captured by ICD diagnosis codes versus natural language processing (NLP). In their investigation, NLP identified 10 times more children with child maltreatment than just using the diagnosis code. Building on this methodology the proposed pilot project will use NLP to identify patients within one health care system (Kaiser Permanente Hawaii) who experience PTSD compared to those identified using ICD diagnosis codes only. Further, we test the feasibility of using NLP to categorize patients based on exposure type (e.g., combat, motor vehicle crash, sexual abuse, etc.). NLP may help to identify additional trauma-exposed individuals with PTSD that are not documented/captured through ICD codes. This may lead to the identification of care gaps, novel treatment targets, and characteristics (e.g., age, sex, race/ethnicity, trauma exposure type) that may make it more/less likely to have ICD coded PTSD. To date, PTSD has been relatively underexamined within the Mental Health Research Network (MHRN) despite being identified as a priority area in this third funding cycle.

Research Questions:

Does NLP allow us to obtain estimates of the number of adults who experience PTSD that are more comparable to national epidemiologic data?
Are there differences by group (e.g., age, sex, race/ethnicity, trauma type) of those captured through NLP versus ICD diagnosis code?
Can we establish feasibility for systematically identifying trauma exposure using previously collected data within the health care system?

Methods: The project PI will convene a panel of interested MHRN investigators to discuss approach, assist in the identification of terms, interpretation and use of results, and future research. Drs. Frances Lynch, Jordan Braciszewski and Rob Penfold have expressed interest in serving on this panel and a larger invitation will be sent to all MHRN-affiliated investigators, if funded.

We propose to use simple NLP queries at 1 MHRN site to identify incidents of trauma exposure and PTSD and compare the number of cases identified through NLP compared to those identified using ICD codes only. We will Identify a cohort of adults (age 18 and over) at KPHI and develop a Bag of Words (concept unique identifiers), building off those developed by Negriff, Lynch and Penfold, to search chart notes. Following the initial search, the PI, a licensed clinical psychologist, will conduct chart review of up to 150 cases to manually review text for each concept unique identifier and flag confirmed cases (yes/no). This data will be used to retrain NLP and the process will be repeated a second time for quality assurance/validation. We will use standard methods for identifying patients based on ICD-codes only (comparison group). We will then conduct appropriate statistical analyses to examine differences in identification by groups.

Planned Product: The results of this pilot study will serve as the basis for an R01 application to the National Institute of Mental Health under the NOSI Secondary Analysis of Posttraumatic Psychopathology Data. In addition, results from this study will be presented via scientific conference presentation and/or peer-reviewed publication.

Lead Site: KPHI (PI Vanessa Simiola)

Participating Sites: N/A

Current Status:

Summary of Findings:

Publications:

Implementing Predictive Models for Identifying Suicide Risk in Adolescents

Grant Details

Funder: NIMH (MHRN III Feasibility Pilot Program)

Grant Number: U19MH121738

Project Period: 7/1/2022 – 6/30/2023

Narrative:

Background: Adolescent suicide is an urgent public health crisis. Suicide is currently the second leading cause of death among adolescents ages 10-24. Despite decades of research, suicide attempt rates continue to rise across the U.S., particularly among adolescents. Furthermore, new data suggests that adolescents were disparately impacted by the COVID-19 pandemic, with some states reporting increased rates of suicide among youth, galvanizing the urgency for increased prevention. People who die by suicide often see healthcare providers, and specifically primary care providers prior to death, including adolescents. Therefore, identifying suicide risk in healthcare settings among adolescents is an important prevention opportunity.

Mental Health Research Network (MHRN) researchers (led by Greg Simon) have developed suicide risk prediction algorithms that have potential to vastly improve identification of individuals at high risk of suicide, including adolescents. While promising, there is very little evidence to guide routine use of this powerful suicide risk identification method during healthcare encounters with adolescents. A recently completed MHRN project (led by Bobbi Jo Yarborough) explored barriers and facilitators of the use of suicide risk algorithms among adult patients, clinicians, and administrators across three MHRN systems. These stakeholders were generally supportive of implementation, but some patient participants expressed concerns about suicide risk information resulting in coercive treatment, and clinician participants expressed desire for opportunities supporting their role in implementation decision-making.

No studies (to our knowledge) have explored perspectives of adolescents, their parents/guardians or adolescent providers about how suicide risk prediction models should be implemented. Therefore, we plan to build from prior MHRN work and qualitatively elicit adolescent care providers’ perceived barriers and facilitators to implementation of these models in care delivery and their ideologies regarding risk thresholds and risk-concordant care. Simultaneously, we plan to build a qualitative understanding adolescents and family perceptions, ideas, and preferences regarding the use of suicide risk prediction models in their care.

Research questions: (1) What perspectives do primary care providers have on suicide risk prediction algorithms and what suggestions or considerations do they have for clinical practice? (2) How do primary care providers envision risk concordant care delivery to look like in clinical practice? (3) What are adolescent and parent/caregiver perceptions and preferences on the use of suicide risk predications models as a tool for enhanced clinical care? (4) What ideas or suggestions do adolescents and parents/caregivers have for comfortable and effective implementation of risk prediction algorithms in primary care?

Methods: Provider interview guides will be developed based on interview findings by the prior qualitative MHRN study (described above) which used the Consolidated Framework for Implementation Research (CFIR), with additional questions aimed at understanding risk thresholds and associated concordant care. Caregiver and adolescent interviews will explore their thoughts, ideas, and preferences regarding EHR-based suicide risk prediction models as part of patient standard of care. We will aim to interview 10-15 adolescent care providers and 10-15 caregiver-adolescent dyads across the two sites. Care providers will be purposively selected in consultation with KPWA leaders involved in an initiative to improve adolescent access to timely mental health care. The suicide risk prediction algorithm will be used to purposively sample adolescents at high risk of suicide and their parent/guardian caregivers. Identified dyads will be recruited via mailed and telephone invitation materials (developed from a prior project recruiting adolescents & caregivers). Interviews will be audio-recorded, transcribed and double-coded to support thematic content analysis.

Planned products: A synthesis of stakeholder needs/perspectives to support suicide risk prediction model implementation in routine care delivery for adolescents. This key deliverable will be used to support: 1) current predictive analytic implementation efforts across MHRN sites 2) an external grant submission to NIMH focused on application of Human-Centered Design methods to design, build, and test clinical decision support for identifying and engaging adolescents at high-risk of suicide in evidence-based healthcare, 2) a peer-reviewed manuscript submission led by Taylor Ryan, MS (PhD student in Health Systems & Population Health at the University of Washington) & Julie Richards, MPH, PhD (MHRN researcher and faculty advisor at UW).

Lead Site: KPWA (PI Julie Richards)

Participating Sites: N/A

Current Status:

Summary of Findings:

Publications:

Weight loss and perinatal depression

Grant Details

Funder: NIMH (MHRN III Feasibility Pilot Program)

Grant Number: U19MH121738

Project Period: 7/1/2021 – 6/30/2022

Narrative:

Background: Rates of overweight (body mass index (BMI)=25.0-29.9kg/m2) and obesity (BMI>30.0kg/m2) among adult American women have continuously increased for the past 20 years, with 41.9% having obesity in 20181. Obesity is a risk factor for adverse outcomes in the 85% of women who become pregnant by age 442. Most women are advised to lose weight prior to becoming pregnant, to help alleviate several pregnancy and postpartum complications3. One of these complications is the development of prenatal and postpartum mental health disorders, including depression and anxiety4. Around 10-25% of mothers will experience depression during pregnancy5 and 10-15% in the postpartum period6. Between 0.9%−22.7% of mothers will experience generalized anxiety disorder during pregnancy7 and 4.4-8.5% postpartum8. Mothers who were overweight or obese at time of pregnancy appear to have higher risk for the development of postpartum depression and anxiety compared to their normal weight counterparts9.

In the general population, losing weight, defined as losing at least 5-10% of one’s body weight10, has produced mixed results in terms of changes in mental health symptoms. Some evidence indicates weight loss is associated with improved depressive11 and anxiety symptoms12, while others have found that weight loss was associated with increased depression symptoms13 and no association with anxiety14. However, no studies have examined how the process of losing weight prior to pregnancy interacts with the development of prenatal and postpartum mental health disorders. There is also evidence that the burden of obesity15 and postpartum depression and anxiety17 is greater in African-Americans and Latina mothers compared to White mothers, suggesting racial identity may moderate the relationship between weight loss and prenatal and postpartum mental health outcomes.

This project is responsive to the NIMH strategic goal “Strengthen the Public Health Impact of NIMH-Supported Research” by identifying specific groups of individuals who may have an elevated risk for developing depression and anxiety, and specific time points (prenatal or postpartum) that may be most vulnerable to psychopathology in a large, population level dataset. By identifying these individuals and timepoints, empirically-supported interventions can be implemented and tested for efficacy in a targeted manner.

Research Question: In a cohort of women 20 to 44 years of age who have obesity and are free of a diagnosis of depression or anxiety for a year prior to pregnancy, this study aims to:

1) determine if patients who experience successful weight loss (losing at least 10% of one’s body weight) vs. those who do not, in the year prior to pregnancy, have a lower risk for new onset prenatal and postpartum depression and anxiety.

2) Determine if the magnitude of association between pre-pregnancy weight loss and prenatal and postpartum depression and anxiety is greater in African-American and Latina women compared to White women.

Methods: The study will pull data from the electronic health record system of a large Midwestern hospital system and create a sample by identifying women of reproductive age (20- 44 years old) who experienced a live birth, and have a weight recorded sometime in the year prior to pregnancy. Case-matched samples will be created based on important demographics, such as insurance status and age, and clinical factors, including BMI at time of pregnancy. These samples will be divided into two groups: those who successfully lost weight prior to pregnancy and those who did not. The research questions will be analyzed using modified Poisson models.

Planned Product: The results of this study will be published and presented at a conference. Findings will provide preliminary evidence to support an R01 submission that will involve multi- HCSRN sites. Aims of the R01 submission will be expanded to examine dose response relationships in baseline BMI and pre-natal and post-partum depression and anxiety disorder and will determine if weight loss thresholds (moving from obese to overweight vs. obese to normal weight) are associated with greater reduction in risk for prenatal and postpartum depression.