Mental Health

Requests for medical aid in dying (MAID) within the Veterans Health Administration (VHA) present unique ethical, legal, and clinical challenges. MAID is a process in which a physician provides a terminally ill patient with the means to end their own life. It is expressly prohibited by federal law, including within the US Department of Veterans Affairs (VA), regardless of its legality at the state level.¹ MAID is also prohibited within community care institutions funded by the VA. The American Medical Association, American Geriatrics Society, and American Academy of Hospice and Palliative Medicine have adopted neutral positions regarding MAID due to varying opinions among their respective members.^2-4 VHA palliative care clinicians are trained to identify and honor preferences for care and alleviate physical and emotional distress, which may complicate the management of MAID requests. Veterans can request MAID due to their desire for autonomy and pain relief, but the VHA prohibits clinicians from honoring these specific preferences. The inability to help veterans achieve their care preferences conflicts with the core mission of palliative care to reduce suffering and respect end-of-life wishes.

This case report describes the management of a veteran who requested MAID while also exhibiting active suicidal ideation. The patient’s distress stemmed from fears of impending loss of autonomy and functional decline, factors frequently linked to requests for MAID in terminally ill patients.^5,6 Addressing the veteran’s request for MAID required balancing respect for patient autonomy and concerns about future suffering with the VA mission to protect veterans from self-harm and provide mental health care for suicidal ideation. This case highlights the importance of nuanced clinical approaches, ethical reflection, and interdisciplinary collaboration in navigating such complex scenarios. Informed consent was obtained from the patient’s family and health care agent (HCA) to publish this report.

Case Presentation

A 73-year-old male veteran, with Parkinson disease (PD), diagnosed at age 52 years, was referred to palliative care following diagnosis of a glioblastoma multiforme (GBM). The patient also had a history of major depressive disorder (MDD), suicidal ideation (SI), benign prostatic hypertrophy, and migraines. He was divorced, had no children, and his only sibling (sister) was deceased. His brother-in-law served as his HCA.

The patient had many close friends in the community, was an architect by training, and was active in the removal of barriers and increasing access for people with disabilities. Since 2010, about 7 years before his PD diagnosis, the patient used psychiatry and psychology resources to treat MDD, functional decline, and SI. He was hospitalized in 2016 after self-administration of heroin. During the hospitalization the patient received a high risk for suicide label. He articulated a firm and long-standing belief in his right to die and shared plans to end his life when he experienced a significant decline in his independence and quality of life (QoL).

When diagnosed with PD, the patient shared that his QoL was of utmost importance. He was aware that he would have significant physical decline as PD progressed and felt like there would be a point when his QoL would not be acceptable. When that happened, he wanted to end his life by available means. He was followed closely by his VHA care team for physical and emotional distress.

When diagnosed with a GBM in 2023, the patient declined treatment and was referred to palliative care, which had sporadically treated him for PD-related distress prior to 2023. During his previous palliative care visits, the patient had discussed a desire to engage in MAID when his functional status declined. After the GBM diagnosis, he reported no acute intent to harm himself with heroin, but planned to travel to Vermont for MAID when he felt he no longer had an adequate QoL based on functional capability.

Pharmacologic and nonpharmacologic approaches were used to treat the patient’s pain. He reported significant benefit from biofeedback therapy provided by the VA Headache Center of Excellence. This work also reconnected him to meditation, which he used daily to relieve pain and distress. The patient managed head pain with nonpharmacologic and pharmacologic interventions for 6 months and reported satisfaction with his QoL.

After 6 months, imaging showed progression of the brain tumor, which was associated with more fatigue and memory decline. At that time, the patient was enrolled in home hospice and reported continued intent to pursue MAID in Vermont but had not taken steps toward carrying it out. The patient understood the VA could not assist him in pursuing MAID; however, his care team was able to assist him in sharing his preferences for care with his loved ones and health care power of attorney.

He experienced rapid functional and cognitive decline due to progression of the GBM and was admitted to the VA Connecticut Healthcare System (VACHS) acute care unit where he exhibited confusion and screened positive for delirium using the Confusion Assessment Method.⁷ His physical and cognitive deterioration was likely due to the progressive brain tumor, and the patient lacked the capacity to make complex medical decisions. Formal consent was obtained from his HCA to transfer him to inpatient hospice. Psychiatry followed the patient throughout.

After 4 weeks of hospice care, the patient had a witnessed suicide attempt while the nurse was assisting him in the bathroom. The patient attempted to use hospital pajamas to hang himself when he wrapped a hospital gown around his neck and stated he was trying to tie a knot. Due to his confusion and delirium, the patient was unable to express his reasoning for the suicide attempt. He was seen by the Psychiatry service, which determined that his suicide risk was low to intermediate. The Psychiatry service did not recommend a 1:1 safety sitter, but suggested medication changes. Levetiracetam was discontinued, and valproate 500 mg orally twice daily was initiated for seizure prevention.

The hospice team was informed of the suicide attempt and psychiatry recommendations. The suicide prevention team was also updated following this event and agreed with psychiatry recommendations. The patient continued to decline, was no longer able to get out of bed, and had minimal speech. The patient received comfort medications, including intravenous morphine 2 mg and lorazepam 0.5 mg as needed ≤ 4 times daily. He died 8 days later.

Discussion

Chronic medical illness has been associated with increased suicide risk.^8-10 The increased risk of suicide in chronically ill patients has been described as having as a bidirectional relationship with MDD, with depression not only increasing the risk of chronic medical illness but new-onset chronic medical illness being associated with new onset depression.^11,12 Chronic medical conditions are associated with numerous psychiatric disorders, and the presence of a comorbid psychiatric illness is associated with higher rates of hospitalization, emergency department visits, and increased health care costs.¹³ Research has found that the association between suicide risk and chronic medical illness remains even after accounting for comorbid mental health disorders.¹⁴ This has been postulated to be due to a multitude of interpersonal, behavioral, cognitive, and affective factors (eg, perceived burdensomeness, loneliness, stress, pain catastrophizing, self-criticism).¹⁵ Additionally, some researchers have questioned whether suicidality constitutes a distinct mental disorder.¹⁶

Patients with cancer are at increased risk for suicidal ideation (including passive death wishes) and suicide attempts.^17,18 Recent data indicate that compared with the general population, there is an 85% increased risk of suicide mortality in patients with cancer.¹⁹ Studies show the incidence of suicide is greater for individuals with cancer compared with the general population, with standardized mortality ratios ranging from 1.4 to 5.7.^20-22

Among patients with cancer, suicide risk is associated with several factors: worse prognosis, older age, male sex, living in a socioeconomically vulnerable environment, and increased communication about suicidal intent prior to death.^23-25 Just as the prevalence of suicidal ideation in people with cancer varies widely, reported rates of suicidality in caregivers of patients with cancer range from 2.7% to 71%.^17,26 A survey of health care workers indicated the following reasons patients with cancer may die by suicide or seek aid in assisted suicide: social isolation, pain, physical impairment, loss of autonomy and meaning, terminal illness, and psychic distress and desperation.²⁷

As with cancer, patients with PD exhibit increased suicidal ideation compared with the general population.^28,29 Two studies found the suicide rate in individuals with PD is about twice as high as it is in the general population.^30,31 Among people with PD, male sex, younger age, initial onset of motor symptoms in the upper or both upper and lower extremities, history of depression or any psychiatric diagnosis, delusions, higher levodopa dosing, and urban residence have been clinically correlated with suicide. Jumping has been a frequent method of suicide.^30,31

Some research has evaluated the perspectives of loved ones after a patient chooses MAID. A study in the Netherlands found that 92% of relatives surveyed believed that access to MAID improved QoL and reduced pain at the end of life.³² In another, family members of individuals who used MAID reported higher quality on items related to physical symptom control and preparedness for death, compared with individuals who did not pursue MAID or who requested but did not receive it. There were no differences on items assessing connectedness to their loved one, being unafraid of death, level of consciousness, or global quality of death items.³³ Another study found no significant differences in depression rates, grief, or use of mental health services among Oregon families whose loved ones died using MAID compared with those who did not.³⁴

The higher suicide rate among terminally ill patients highlights the complex issue of MAID and the right to die. It is important to differentiate between euthanasia and medically-assisted dying. Euthanasia is an act whereby a person other than the patient acts to cause death. In MAID, the patient is provided with a medication that they self-administer. Recent Gallup polls found that > 70% of Americans believe physicians should be “allowed by law to end the patient’s life by some painless means if the patient and his or her family request it.”³⁵

It is important to acknowledge MAID in the context of chronic suicidality, like in the case described in this article. It is imperative not to dismiss reports of suicidality in this population. Ignoring reports of suicidal ideation may lead to decreased access to pharmacologic and nonpharmacologic interventions. It is also important to maintain a timeline of symptom occurrence and to differentiate between chronic suicidality and the desire to die associated with having a terminal illness. A thorough assessment is necessary to assess whether the patient’s decision stems from a calculated decision with preserved capacity or from underlying mental health conditions. Other factors that may lead the patient to a hastened death (ie, pain, poor psychosocial support, delirium, cognitive impairment, incomplete understanding of treatment/prognosis) need to be addressed prior to finalizing choices. In this case, an assessment was performed by psychiatry, psychology, social work, and chaplains to ensure comprehensive evaluation.

The VHA offers resources to assist individuals experiencing suicidal ideation, including suicide prevention coordinators who work directly with veterans and offer consultation to teams working with veterans at risk for suicide. Support for VHA clinicians who treat veterans considering MAID may help address any moral distress. In this case, the care team met early for overnight sign-out, had daily core hospice team meetings, as-needed safety huddles, and weekly care plan meetings to ensure maximal physical and emotional comfort for the patient. These meetings cultivate open, honest, and transparent discussions regarding any staff concerns or personal distress around the plan of care. The VACHS chief well-being officer was also available for all staff.

A systematic review of the impact of MAID on clinicians found that MAID legislation influenced emotional responses. For countries whose MAID legislation emphasized alleviation from pain in addition to terminal illness, clinicians reported more emotional reflection. Whereas, in countries where MAID legislation is stricter and can be applied solely for terminal illness, clinicians reported a stronger and more polarizing range of emotions.³⁶ This highlights the potential influence of the context in which clinicians work on their emotional experience with MAID. Given that MAID is not permitted in the VA, staff members may experience heightened emotional responses. In a survey of US adults, there was an interest in using MAID but there were knowledge deficits regarding the process and legality.³⁷

Legal aspects come into play as well with regards to MAID. Eligibility requires the patient be aged ≥ 18 years, be terminally ill with a prognosis of ≤ 6 months, have the capacity to make their own health care decision, and be able to self-administer the medication. States also may have residency restrictions. Special care and adequate education are needed, as having anyone but the patient administer the medication may be considered criminal. Furthermore, since MAID is not allowed federally, this creates further distress in VHA clinicians entrusted to minimizing pain for patients.

Strategies to support veterans given prohibition of MAID include: conversations about the patient’s values, clarifying reasons for request, assessing all domains of distress, affirming concerns with compassion and nonjudgment, addressing any pain using pharmacologic and nonpharmacologic interventions, providing education on other permissible options for end-of-life care, and consulting other specialties.³⁸

End-of-life options permitted by the VA include withholding/ withdrawing life-sustaining treatments, palliative sedation, and voluntary stopping of eating and drinking.³⁹ Given the complexities of MAID, the VHA should initiate discussions of MAID, educate clinicians on what they can and cannot do as federal employees, and establish committees to discuss approaches that could minimize pain for patients and clinician distress.

Conclusions

Caring for veterans who request MAID requires clinicians to navigate a complex intersection of ethical obligations, legal constraints, and patient preferences. Within the VHA, where MAID is prohibited, clinicians must balance respect for patient autonomy with adherence to VA regulations. Comprehensive assessment to identify sources of distress, interdisciplinary collaboration, and recognition of permissible alternatives that align with patients’ values are essential to provide effective end-of-life care at the VHA for individuals considering MAID. As requests for MAID continue to emerge in clinical practice, the VHA has an opportunity to strengthen clinician education, clarify institutional expectations, and promote supportive structures that reduce both patient suffering and clinician moral distress.

Requests for medical aid in dying (MAID) within the Veterans Health Administration (VHA) present unique ethical, legal, and clinical challenges. MAID is a process in which a physician provides a terminally ill patient with the means to end their own life. It is expressly prohibited by federal law, including within the US Department of Veterans Affairs (VA), regardless of its legality at the state level.¹ MAID is also prohibited within community care institutions funded by the VA. The American Medical Association, American Geriatrics Society, and American Academy of Hospice and Palliative Medicine have adopted neutral positions regarding MAID due to varying opinions among their respective members.^2-4 VHA palliative care clinicians are trained to identify and honor preferences for care and alleviate physical and emotional distress, which may complicate the management of MAID requests. Veterans can request MAID due to their desire for autonomy and pain relief, but the VHA prohibits clinicians from honoring these specific preferences. The inability to help veterans achieve their care preferences conflicts with the core mission of palliative care to reduce suffering and respect end-of-life wishes.

This case report describes the management of a veteran who requested MAID while also exhibiting active suicidal ideation. The patient’s distress stemmed from fears of impending loss of autonomy and functional decline, factors frequently linked to requests for MAID in terminally ill patients.^5,6 Addressing the veteran’s request for MAID required balancing respect for patient autonomy and concerns about future suffering with the VA mission to protect veterans from self-harm and provide mental health care for suicidal ideation. This case highlights the importance of nuanced clinical approaches, ethical reflection, and interdisciplinary collaboration in navigating such complex scenarios. Informed consent was obtained from the patient’s family and health care agent (HCA) to publish this report.

Case Presentation

A 73-year-old male veteran, with Parkinson disease (PD), diagnosed at age 52 years, was referred to palliative care following diagnosis of a glioblastoma multiforme (GBM). The patient also had a history of major depressive disorder (MDD), suicidal ideation (SI), benign prostatic hypertrophy, and migraines. He was divorced, had no children, and his only sibling (sister) was deceased. His brother-in-law served as his HCA.

The patient had many close friends in the community, was an architect by training, and was active in the removal of barriers and increasing access for people with disabilities. Since 2010, about 7 years before his PD diagnosis, the patient used psychiatry and psychology resources to treat MDD, functional decline, and SI. He was hospitalized in 2016 after self-administration of heroin. During the hospitalization the patient received a high risk for suicide label. He articulated a firm and long-standing belief in his right to die and shared plans to end his life when he experienced a significant decline in his independence and quality of life (QoL).

When diagnosed with PD, the patient shared that his QoL was of utmost importance. He was aware that he would have significant physical decline as PD progressed and felt like there would be a point when his QoL would not be acceptable. When that happened, he wanted to end his life by available means. He was followed closely by his VHA care team for physical and emotional distress.

When diagnosed with a GBM in 2023, the patient declined treatment and was referred to palliative care, which had sporadically treated him for PD-related distress prior to 2023. During his previous palliative care visits, the patient had discussed a desire to engage in MAID when his functional status declined. After the GBM diagnosis, he reported no acute intent to harm himself with heroin, but planned to travel to Vermont for MAID when he felt he no longer had an adequate QoL based on functional capability.

Pharmacologic and nonpharmacologic approaches were used to treat the patient’s pain. He reported significant benefit from biofeedback therapy provided by the VA Headache Center of Excellence. This work also reconnected him to meditation, which he used daily to relieve pain and distress. The patient managed head pain with nonpharmacologic and pharmacologic interventions for 6 months and reported satisfaction with his QoL.

After 6 months, imaging showed progression of the brain tumor, which was associated with more fatigue and memory decline. At that time, the patient was enrolled in home hospice and reported continued intent to pursue MAID in Vermont but had not taken steps toward carrying it out. The patient understood the VA could not assist him in pursuing MAID; however, his care team was able to assist him in sharing his preferences for care with his loved ones and health care power of attorney.

He experienced rapid functional and cognitive decline due to progression of the GBM and was admitted to the VA Connecticut Healthcare System (VACHS) acute care unit where he exhibited confusion and screened positive for delirium using the Confusion Assessment Method.⁷ His physical and cognitive deterioration was likely due to the progressive brain tumor, and the patient lacked the capacity to make complex medical decisions. Formal consent was obtained from his HCA to transfer him to inpatient hospice. Psychiatry followed the patient throughout.

After 4 weeks of hospice care, the patient had a witnessed suicide attempt while the nurse was assisting him in the bathroom. The patient attempted to use hospital pajamas to hang himself when he wrapped a hospital gown around his neck and stated he was trying to tie a knot. Due to his confusion and delirium, the patient was unable to express his reasoning for the suicide attempt. He was seen by the Psychiatry service, which determined that his suicide risk was low to intermediate. The Psychiatry service did not recommend a 1:1 safety sitter, but suggested medication changes. Levetiracetam was discontinued, and valproate 500 mg orally twice daily was initiated for seizure prevention.

The hospice team was informed of the suicide attempt and psychiatry recommendations. The suicide prevention team was also updated following this event and agreed with psychiatry recommendations. The patient continued to decline, was no longer able to get out of bed, and had minimal speech. The patient received comfort medications, including intravenous morphine 2 mg and lorazepam 0.5 mg as needed ≤ 4 times daily. He died 8 days later.

Discussion

Chronic medical illness has been associated with increased suicide risk.^8-10 The increased risk of suicide in chronically ill patients has been described as having as a bidirectional relationship with MDD, with depression not only increasing the risk of chronic medical illness but new-onset chronic medical illness being associated with new onset depression.^11,12 Chronic medical conditions are associated with numerous psychiatric disorders, and the presence of a comorbid psychiatric illness is associated with higher rates of hospitalization, emergency department visits, and increased health care costs.¹³ Research has found that the association between suicide risk and chronic medical illness remains even after accounting for comorbid mental health disorders.¹⁴ This has been postulated to be due to a multitude of interpersonal, behavioral, cognitive, and affective factors (eg, perceived burdensomeness, loneliness, stress, pain catastrophizing, self-criticism).¹⁵ Additionally, some researchers have questioned whether suicidality constitutes a distinct mental disorder.¹⁶

Patients with cancer are at increased risk for suicidal ideation (including passive death wishes) and suicide attempts.^17,18 Recent data indicate that compared with the general population, there is an 85% increased risk of suicide mortality in patients with cancer.¹⁹ Studies show the incidence of suicide is greater for individuals with cancer compared with the general population, with standardized mortality ratios ranging from 1.4 to 5.7.^20-22

Among patients with cancer, suicide risk is associated with several factors: worse prognosis, older age, male sex, living in a socioeconomically vulnerable environment, and increased communication about suicidal intent prior to death.^23-25 Just as the prevalence of suicidal ideation in people with cancer varies widely, reported rates of suicidality in caregivers of patients with cancer range from 2.7% to 71%.^17,26 A survey of health care workers indicated the following reasons patients with cancer may die by suicide or seek aid in assisted suicide: social isolation, pain, physical impairment, loss of autonomy and meaning, terminal illness, and psychic distress and desperation.²⁷

As with cancer, patients with PD exhibit increased suicidal ideation compared with the general population.^28,29 Two studies found the suicide rate in individuals with PD is about twice as high as it is in the general population.^30,31 Among people with PD, male sex, younger age, initial onset of motor symptoms in the upper or both upper and lower extremities, history of depression or any psychiatric diagnosis, delusions, higher levodopa dosing, and urban residence have been clinically correlated with suicide. Jumping has been a frequent method of suicide.^30,31

Some research has evaluated the perspectives of loved ones after a patient chooses MAID. A study in the Netherlands found that 92% of relatives surveyed believed that access to MAID improved QoL and reduced pain at the end of life.³² In another, family members of individuals who used MAID reported higher quality on items related to physical symptom control and preparedness for death, compared with individuals who did not pursue MAID or who requested but did not receive it. There were no differences on items assessing connectedness to their loved one, being unafraid of death, level of consciousness, or global quality of death items.³³ Another study found no significant differences in depression rates, grief, or use of mental health services among Oregon families whose loved ones died using MAID compared with those who did not.³⁴

The higher suicide rate among terminally ill patients highlights the complex issue of MAID and the right to die. It is important to differentiate between euthanasia and medically-assisted dying. Euthanasia is an act whereby a person other than the patient acts to cause death. In MAID, the patient is provided with a medication that they self-administer. Recent Gallup polls found that > 70% of Americans believe physicians should be “allowed by law to end the patient’s life by some painless means if the patient and his or her family request it.”³⁵

It is important to acknowledge MAID in the context of chronic suicidality, like in the case described in this article. It is imperative not to dismiss reports of suicidality in this population. Ignoring reports of suicidal ideation may lead to decreased access to pharmacologic and nonpharmacologic interventions. It is also important to maintain a timeline of symptom occurrence and to differentiate between chronic suicidality and the desire to die associated with having a terminal illness. A thorough assessment is necessary to assess whether the patient’s decision stems from a calculated decision with preserved capacity or from underlying mental health conditions. Other factors that may lead the patient to a hastened death (ie, pain, poor psychosocial support, delirium, cognitive impairment, incomplete understanding of treatment/prognosis) need to be addressed prior to finalizing choices. In this case, an assessment was performed by psychiatry, psychology, social work, and chaplains to ensure comprehensive evaluation.

The VHA offers resources to assist individuals experiencing suicidal ideation, including suicide prevention coordinators who work directly with veterans and offer consultation to teams working with veterans at risk for suicide. Support for VHA clinicians who treat veterans considering MAID may help address any moral distress. In this case, the care team met early for overnight sign-out, had daily core hospice team meetings, as-needed safety huddles, and weekly care plan meetings to ensure maximal physical and emotional comfort for the patient. These meetings cultivate open, honest, and transparent discussions regarding any staff concerns or personal distress around the plan of care. The VACHS chief well-being officer was also available for all staff.

A systematic review of the impact of MAID on clinicians found that MAID legislation influenced emotional responses. For countries whose MAID legislation emphasized alleviation from pain in addition to terminal illness, clinicians reported more emotional reflection. Whereas, in countries where MAID legislation is stricter and can be applied solely for terminal illness, clinicians reported a stronger and more polarizing range of emotions.³⁶ This highlights the potential influence of the context in which clinicians work on their emotional experience with MAID. Given that MAID is not permitted in the VA, staff members may experience heightened emotional responses. In a survey of US adults, there was an interest in using MAID but there were knowledge deficits regarding the process and legality.³⁷

Legal aspects come into play as well with regards to MAID. Eligibility requires the patient be aged ≥ 18 years, be terminally ill with a prognosis of ≤ 6 months, have the capacity to make their own health care decision, and be able to self-administer the medication. States also may have residency restrictions. Special care and adequate education are needed, as having anyone but the patient administer the medication may be considered criminal. Furthermore, since MAID is not allowed federally, this creates further distress in VHA clinicians entrusted to minimizing pain for patients.

Strategies to support veterans given prohibition of MAID include: conversations about the patient’s values, clarifying reasons for request, assessing all domains of distress, affirming concerns with compassion and nonjudgment, addressing any pain using pharmacologic and nonpharmacologic interventions, providing education on other permissible options for end-of-life care, and consulting other specialties.³⁸

End-of-life options permitted by the VA include withholding/ withdrawing life-sustaining treatments, palliative sedation, and voluntary stopping of eating and drinking.³⁹ Given the complexities of MAID, the VHA should initiate discussions of MAID, educate clinicians on what they can and cannot do as federal employees, and establish committees to discuss approaches that could minimize pain for patients and clinician distress.

Conclusions

Caring for veterans who request MAID requires clinicians to navigate a complex intersection of ethical obligations, legal constraints, and patient preferences. Within the VHA, where MAID is prohibited, clinicians must balance respect for patient autonomy with adherence to VA regulations. Comprehensive assessment to identify sources of distress, interdisciplinary collaboration, and recognition of permissible alternatives that align with patients’ values are essential to provide effective end-of-life care at the VHA for individuals considering MAID. As requests for MAID continue to emerge in clinical practice, the VHA has an opportunity to strengthen clinician education, clarify institutional expectations, and promote supportive structures that reduce both patient suffering and clinician moral distress.

Requests for medical aid in dying (MAID) within the Veterans Health Administration (VHA) present unique ethical, legal, and clinical challenges. MAID is a process in which a physician provides a terminally ill patient with the means to end their own life. It is expressly prohibited by federal law, including within the US Department of Veterans Affairs (VA), regardless of its legality at the state level.¹ MAID is also prohibited within community care institutions funded by the VA. The American Medical Association, American Geriatrics Society, and American Academy of Hospice and Palliative Medicine have adopted neutral positions regarding MAID due to varying opinions among their respective members.^2-4 VHA palliative care clinicians are trained to identify and honor preferences for care and alleviate physical and emotional distress, which may complicate the management of MAID requests. Veterans can request MAID due to their desire for autonomy and pain relief, but the VHA prohibits clinicians from honoring these specific preferences. The inability to help veterans achieve their care preferences conflicts with the core mission of palliative care to reduce suffering and respect end-of-life wishes.

This case report describes the management of a veteran who requested MAID while also exhibiting active suicidal ideation. The patient’s distress stemmed from fears of impending loss of autonomy and functional decline, factors frequently linked to requests for MAID in terminally ill patients.^5,6 Addressing the veteran’s request for MAID required balancing respect for patient autonomy and concerns about future suffering with the VA mission to protect veterans from self-harm and provide mental health care for suicidal ideation. This case highlights the importance of nuanced clinical approaches, ethical reflection, and interdisciplinary collaboration in navigating such complex scenarios. Informed consent was obtained from the patient’s family and health care agent (HCA) to publish this report.

Case Presentation

A 73-year-old male veteran, with Parkinson disease (PD), diagnosed at age 52 years, was referred to palliative care following diagnosis of a glioblastoma multiforme (GBM). The patient also had a history of major depressive disorder (MDD), suicidal ideation (SI), benign prostatic hypertrophy, and migraines. He was divorced, had no children, and his only sibling (sister) was deceased. His brother-in-law served as his HCA.

The patient had many close friends in the community, was an architect by training, and was active in the removal of barriers and increasing access for people with disabilities. Since 2010, about 7 years before his PD diagnosis, the patient used psychiatry and psychology resources to treat MDD, functional decline, and SI. He was hospitalized in 2016 after self-administration of heroin. During the hospitalization the patient received a high risk for suicide label. He articulated a firm and long-standing belief in his right to die and shared plans to end his life when he experienced a significant decline in his independence and quality of life (QoL).

When diagnosed with PD, the patient shared that his QoL was of utmost importance. He was aware that he would have significant physical decline as PD progressed and felt like there would be a point when his QoL would not be acceptable. When that happened, he wanted to end his life by available means. He was followed closely by his VHA care team for physical and emotional distress.

When diagnosed with a GBM in 2023, the patient declined treatment and was referred to palliative care, which had sporadically treated him for PD-related distress prior to 2023. During his previous palliative care visits, the patient had discussed a desire to engage in MAID when his functional status declined. After the GBM diagnosis, he reported no acute intent to harm himself with heroin, but planned to travel to Vermont for MAID when he felt he no longer had an adequate QoL based on functional capability.

Pharmacologic and nonpharmacologic approaches were used to treat the patient’s pain. He reported significant benefit from biofeedback therapy provided by the VA Headache Center of Excellence. This work also reconnected him to meditation, which he used daily to relieve pain and distress. The patient managed head pain with nonpharmacologic and pharmacologic interventions for 6 months and reported satisfaction with his QoL.

After 6 months, imaging showed progression of the brain tumor, which was associated with more fatigue and memory decline. At that time, the patient was enrolled in home hospice and reported continued intent to pursue MAID in Vermont but had not taken steps toward carrying it out. The patient understood the VA could not assist him in pursuing MAID; however, his care team was able to assist him in sharing his preferences for care with his loved ones and health care power of attorney.

He experienced rapid functional and cognitive decline due to progression of the GBM and was admitted to the VA Connecticut Healthcare System (VACHS) acute care unit where he exhibited confusion and screened positive for delirium using the Confusion Assessment Method.⁷ His physical and cognitive deterioration was likely due to the progressive brain tumor, and the patient lacked the capacity to make complex medical decisions. Formal consent was obtained from his HCA to transfer him to inpatient hospice. Psychiatry followed the patient throughout.

After 4 weeks of hospice care, the patient had a witnessed suicide attempt while the nurse was assisting him in the bathroom. The patient attempted to use hospital pajamas to hang himself when he wrapped a hospital gown around his neck and stated he was trying to tie a knot. Due to his confusion and delirium, the patient was unable to express his reasoning for the suicide attempt. He was seen by the Psychiatry service, which determined that his suicide risk was low to intermediate. The Psychiatry service did not recommend a 1:1 safety sitter, but suggested medication changes. Levetiracetam was discontinued, and valproate 500 mg orally twice daily was initiated for seizure prevention.

The hospice team was informed of the suicide attempt and psychiatry recommendations. The suicide prevention team was also updated following this event and agreed with psychiatry recommendations. The patient continued to decline, was no longer able to get out of bed, and had minimal speech. The patient received comfort medications, including intravenous morphine 2 mg and lorazepam 0.5 mg as needed ≤ 4 times daily. He died 8 days later.

Discussion

Chronic medical illness has been associated with increased suicide risk.^8-10 The increased risk of suicide in chronically ill patients has been described as having as a bidirectional relationship with MDD, with depression not only increasing the risk of chronic medical illness but new-onset chronic medical illness being associated with new onset depression.^11,12 Chronic medical conditions are associated with numerous psychiatric disorders, and the presence of a comorbid psychiatric illness is associated with higher rates of hospitalization, emergency department visits, and increased health care costs.¹³ Research has found that the association between suicide risk and chronic medical illness remains even after accounting for comorbid mental health disorders.¹⁴ This has been postulated to be due to a multitude of interpersonal, behavioral, cognitive, and affective factors (eg, perceived burdensomeness, loneliness, stress, pain catastrophizing, self-criticism).¹⁵ Additionally, some researchers have questioned whether suicidality constitutes a distinct mental disorder.¹⁶

Patients with cancer are at increased risk for suicidal ideation (including passive death wishes) and suicide attempts.^17,18 Recent data indicate that compared with the general population, there is an 85% increased risk of suicide mortality in patients with cancer.¹⁹ Studies show the incidence of suicide is greater for individuals with cancer compared with the general population, with standardized mortality ratios ranging from 1.4 to 5.7.^20-22

Among patients with cancer, suicide risk is associated with several factors: worse prognosis, older age, male sex, living in a socioeconomically vulnerable environment, and increased communication about suicidal intent prior to death.^23-25 Just as the prevalence of suicidal ideation in people with cancer varies widely, reported rates of suicidality in caregivers of patients with cancer range from 2.7% to 71%.^17,26 A survey of health care workers indicated the following reasons patients with cancer may die by suicide or seek aid in assisted suicide: social isolation, pain, physical impairment, loss of autonomy and meaning, terminal illness, and psychic distress and desperation.²⁷

As with cancer, patients with PD exhibit increased suicidal ideation compared with the general population.^28,29 Two studies found the suicide rate in individuals with PD is about twice as high as it is in the general population.^30,31 Among people with PD, male sex, younger age, initial onset of motor symptoms in the upper or both upper and lower extremities, history of depression or any psychiatric diagnosis, delusions, higher levodopa dosing, and urban residence have been clinically correlated with suicide. Jumping has been a frequent method of suicide.^30,31

Some research has evaluated the perspectives of loved ones after a patient chooses MAID. A study in the Netherlands found that 92% of relatives surveyed believed that access to MAID improved QoL and reduced pain at the end of life.³² In another, family members of individuals who used MAID reported higher quality on items related to physical symptom control and preparedness for death, compared with individuals who did not pursue MAID or who requested but did not receive it. There were no differences on items assessing connectedness to their loved one, being unafraid of death, level of consciousness, or global quality of death items.³³ Another study found no significant differences in depression rates, grief, or use of mental health services among Oregon families whose loved ones died using MAID compared with those who did not.³⁴

The higher suicide rate among terminally ill patients highlights the complex issue of MAID and the right to die. It is important to differentiate between euthanasia and medically-assisted dying. Euthanasia is an act whereby a person other than the patient acts to cause death. In MAID, the patient is provided with a medication that they self-administer. Recent Gallup polls found that > 70% of Americans believe physicians should be “allowed by law to end the patient’s life by some painless means if the patient and his or her family request it.”³⁵

It is important to acknowledge MAID in the context of chronic suicidality, like in the case described in this article. It is imperative not to dismiss reports of suicidality in this population. Ignoring reports of suicidal ideation may lead to decreased access to pharmacologic and nonpharmacologic interventions. It is also important to maintain a timeline of symptom occurrence and to differentiate between chronic suicidality and the desire to die associated with having a terminal illness. A thorough assessment is necessary to assess whether the patient’s decision stems from a calculated decision with preserved capacity or from underlying mental health conditions. Other factors that may lead the patient to a hastened death (ie, pain, poor psychosocial support, delirium, cognitive impairment, incomplete understanding of treatment/prognosis) need to be addressed prior to finalizing choices. In this case, an assessment was performed by psychiatry, psychology, social work, and chaplains to ensure comprehensive evaluation.

The VHA offers resources to assist individuals experiencing suicidal ideation, including suicide prevention coordinators who work directly with veterans and offer consultation to teams working with veterans at risk for suicide. Support for VHA clinicians who treat veterans considering MAID may help address any moral distress. In this case, the care team met early for overnight sign-out, had daily core hospice team meetings, as-needed safety huddles, and weekly care plan meetings to ensure maximal physical and emotional comfort for the patient. These meetings cultivate open, honest, and transparent discussions regarding any staff concerns or personal distress around the plan of care. The VACHS chief well-being officer was also available for all staff.

A systematic review of the impact of MAID on clinicians found that MAID legislation influenced emotional responses. For countries whose MAID legislation emphasized alleviation from pain in addition to terminal illness, clinicians reported more emotional reflection. Whereas, in countries where MAID legislation is stricter and can be applied solely for terminal illness, clinicians reported a stronger and more polarizing range of emotions.³⁶ This highlights the potential influence of the context in which clinicians work on their emotional experience with MAID. Given that MAID is not permitted in the VA, staff members may experience heightened emotional responses. In a survey of US adults, there was an interest in using MAID but there were knowledge deficits regarding the process and legality.³⁷

Legal aspects come into play as well with regards to MAID. Eligibility requires the patient be aged ≥ 18 years, be terminally ill with a prognosis of ≤ 6 months, have the capacity to make their own health care decision, and be able to self-administer the medication. States also may have residency restrictions. Special care and adequate education are needed, as having anyone but the patient administer the medication may be considered criminal. Furthermore, since MAID is not allowed federally, this creates further distress in VHA clinicians entrusted to minimizing pain for patients.

Strategies to support veterans given prohibition of MAID include: conversations about the patient’s values, clarifying reasons for request, assessing all domains of distress, affirming concerns with compassion and nonjudgment, addressing any pain using pharmacologic and nonpharmacologic interventions, providing education on other permissible options for end-of-life care, and consulting other specialties.³⁸

End-of-life options permitted by the VA include withholding/ withdrawing life-sustaining treatments, palliative sedation, and voluntary stopping of eating and drinking.³⁹ Given the complexities of MAID, the VHA should initiate discussions of MAID, educate clinicians on what they can and cannot do as federal employees, and establish committees to discuss approaches that could minimize pain for patients and clinician distress.

Conclusions

Caring for veterans who request MAID requires clinicians to navigate a complex intersection of ethical obligations, legal constraints, and patient preferences. Within the VHA, where MAID is prohibited, clinicians must balance respect for patient autonomy with adherence to VA regulations. Comprehensive assessment to identify sources of distress, interdisciplinary collaboration, and recognition of permissible alternatives that align with patients’ values are essential to provide effective end-of-life care at the VHA for individuals considering MAID. As requests for MAID continue to emerge in clinical practice, the VHA has an opportunity to strengthen clinician education, clarify institutional expectations, and promote supportive structures that reduce both patient suffering and clinician moral distress.

In leveraging existing, readily available evidence-based health care information (eg, systematic reviews, clinical practice guidelines), clinicians have historically made recommendations based on treatment responses of the average patient.¹ Recently, this approach has been expanded into data-driven, evidence-based precision medical care for individuals across a wide range of disciplines and care settings. These precision medicine approaches use information related to an individual’s genes, environment, and lifestyle to tailor recommendations regarding prevention, diagnosis, and treatment.

Applying precision medicine approaches to the unique exposures and experiences of service members and veterans—particularly those who served in combat environments—through the incorporation of biopsychosocial factors into medical decision-making may be even more pertinent. This sentiment is reflected in Section 305 of the Commander John Scott Hannon Veterans Mental Health Care Improvement Act of 2019, which outlines the Precision Medicine Initiative of the US Department of Veterans Affairs (VA) to identify and validate brain and mental health biomarkers.² Despite widespread consensus regarding the promise of precision medicine, large, rich datasets with elements pertaining to common military exposures such as traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are limited.

Existing datasets, most of which are relatively small or focus on specific cohorts (eg, older veterans, transitioning veterans), continue to create barriers to advancing precision medicine. For example, in classically designed clinical trials, analyses are generally conducted in a manner that may obfuscate efficacy among subcohorts of individuals, thereby underscoring the need to explore alternative strategies to unify existing datasets capable of revealing such heterogeneity.³ The evidence base for precision medical care is limited, drawing from published trials with relatively small sample sizes and even larger cohort studies have limited biomarker data. Additionally, these models are often exploratory during development, and to avoid statistical overfitting of an exploratory model, validation in similar datasets is needed—an added burden when data sources are small or underpowered to begin with.

A promising approach is to combine and harmonize the largest, most deeply characterized data sources from similar samples. Although combining such datasets may appear to require minimal time and effort, harmonizing similar variables in an evidence-based and replicable manner requires time and expertise, even when participant characteristics and outcomes are similar.^4-7

Challenges related to harmonization are related to the wide range of strategies (eg, self-report questionnaires, clinical interviews, electronic health record review) used to measure common brain and mental health constructs, such as depression. Even when similar methods (eg, self-report measures) are implemented, challenges persist. For example, if a study used a depression measure that focused primarily on cognitive symptoms (eg, pessimism, self-dislike, suicidal ideation) and another study used a depression measure composed of items more heavily weighted towards somatic symptoms (eg, insomnia, loss of appetite, weight loss, decreased libido), combining their data could be challenging, particularly if researchers, clinicians, or administrators are interested in more than dichotomous outcomes (eg, depression vs no depression).^8,9

To address this knowledge gap and harmonize multimodal data from varied sources, well-planned and reproducible curation is needed. Longitudinal cohort studies of service members and veterans with military combat and training exposure histories provide researchers and other stakeholders access to extant biopsychosocial data shown to affect risk for adverse health outcomes; however, efforts to facilitate individually tailored treatment or other precision medicine approaches would benefit from the synthesis of such datasets.¹⁰

Members of the VA Total Brain Diagnostics (TBD) team are engaged in harmonizing variables from the Long-Term Impact of Military-Relevant Brain Injury Consortium–Chronic Effects of Neurotrauma Consortium (LIMBIC-CENC)¹¹ and the Translational Research Center for TBI and Stress Disorders (TRACTS).^12-21 While there is overlap across LIMBIC-CENC and TRACTS with respect to data domains, considerable data harmonization is needed to allow for future valid and meaningful analyses, particularly those involving multivariable predictors.

Data Sources

Both data sources for the TBD harmonization project, LIMBIC-CENC and TRACTS, include extensive, longitudinal data collected from relatively large cohorts of veterans and service members with combat exposure. Both studies collect detailed data related to potential brain injury history and include participants with and without a history of TBI. Similarly, both include extensive collection of fluid biomarkers and imaging data, as well as measures of biopsychosocial functioning.

Data collection sites for LIMBIC-CENC include 16 recruitment sites, 9 at VA medical centers (Richmond, Houston, Tampa, San Antonio, Portland, Minneapolis, Boston, Salisbury, San Diego) and 7 at military treatment sites (Alexandria, San Diego, Tampa, Tacoma, Columbia, Coronado, Hinesville), in addition to 11 assessment sites (Richmond, Houston, Tampa, San Antonio, Portland, Minneapolis, Boston, Salisbury, San Diego, Alexandria, Augusta). Data for TRACTS are collected at sites in Boston and Houston.

LIMBIC-CENC is a 12-year, 17-site cohort of service members and veteran participants with combat exposure who are well characterized at baseline and undergo annual reassessments. As of December 2025, > 3100 participants have been recruited, and nearly 90% remain in follow-up. Data collection includes > 6200 annual follow-up evaluations and > 1550 5-year re-evaluations, with 400 enrolled participants followed up annually.

TRACTS is a 16-year, 2-site cohort of veterans with combat exposure who complete comprehensive assessments at enrollment, undergo annual reassessments, and complete comprehensive reassessment every 5 years thereafter. As of December 2025, > 1075 participants have completed baseline (Time 1) assessments, > 600 have completed the 2-year re-evaluation (Time 2), > 175 have completed the 5-year re-evaluation (Time 3), and > 35 have completed 10-year evaluations (Time 4), with about 50 new participants added and 100 enrolled participants followed up annually. More data on participant characteristics are available for both LIMBIC-CENC and TRACTS in previous publications.^11,22These 2 ongoing, prospective, longitudinal cohorts of service members and veterans offer access to a wide range of potential risk factors that can affect response to care and outcomes, including demographics (eg, age, sex), injury characteristics (eg, pre-exposure factors, exposure factors), biomarkers (eg, serum, saliva, brain imaging, evoked potentials), and functional measures (eg, computerized posturography, computerized eye tracking, sensory testing, clinical examination, neuropsychological assessments, symptom questionnaires).

Harmonization Strategy

Pooling and harmonizing data from large studies evaluating similar participant cohorts and conditions involves numerous steps to appropriately handle a variety of measurements and disparate variable names. The TBD team adapted a model data harmonization system developed by O’Neil et al through initial work harmonizing the Federal Interagency Traumatic Brain Injury Research Informatics System (FITBIR).^4-7 This process was expanded and generalized by the research team to combine data from LIMBIC-CENC and TRACTS to create a single pooled dataset for analysis (Figure).

This approach was selected because it accommodates heterogeneous study designs (eg, cross-sectional, longitudinal, case-control), data collection methods (eg, clinical assessment, self-reported, objective blood, and imaging biomarkers), and various assessments of the same construct (ie, different measures of brain injury). While exact matches for data collection methods and measures may be easily harmonized, the timing of assessment, number of assessments, assessment tool version, and other factors must be considered. The goal was to harmonize data from LIMBIC-CENC and TRACTS to allow additional data sources to be harmonized and incorporated in the future.

Original data files from each study were reshaped to represent participant-level observations with 1 unique measurement per row. The measurement represents what information was collected and the value recorded represents the unique observation. These data are linked to metadata from the original study, which includes the study’s definition of each measurement, how it was collected, and any available information regarding when it was collected in reference to study enrollment or injury. Additional information on the file source, row, and column position of each data point was added to enable recreation of the original data as needed.

The resulting dataset was used to harmonize measurements from LIMBIC-CENC and TRACTS into a priori-defined schemas for brain- and mental health-relevant concepts, including TBI severity, PTSD, substance use, depression, suicidal ideation, and functioning (including cognitive, physical, and social functioning). This process was facilitated using natural language processing (NLP). Each study uniquely defines all measurements and provides written definitions with the data. Measurement definitions serve as records describing what was collected, how it was collected, and how the study may have uniquely defined information for its purposes. For example, definitions of exposure to brain injury and severity of brain injury may differ between studies, and the study-provided definition defines these differences.

Definitions were converted into numeric vectors through sentence embedding, a process that preserves the semantic meaning of the definition.²³ Cosine similarity was used as the primary metric to compare the semantic textual similarity between pairs of measurement definitions. Cosine similarity ranges from 0 to 1, where 0 indicates no meaningful similarity and 1 indicates they have identical meanings.²⁴ This approach leverages the relationship between the definitions of each measurement provided by a study and enables quick comparison of all pairwise combinations of measurement definitions between studies.

Subsets of similar measurements across studies were organized into a priori-defined schema. Clinical experts then reviewed each schema and further refined them into domains, (eg, mechanism of injury, clinical signs, acute symptoms) and subdomains (children), such as loss of consciousness, amnesia, and alteration of consciousness. This approach allows efficient handling of 2 specific cases that commonly occur when pooling and harmonizing datasets: (1) identifying the same measurement with differing names; and (2) identifying different measurements with definitions that each relate to the same domain.

The Table provides a general example of the schema for TBI severity. This was an iterative process in which clinical experts reviewed study-defined measurement definitions to develop general harmonized domains, and NLP techniques facilitated and accelerated identification and organization of measurements within these domains.

Expected Impact

Harmonization combining LIMBIC-CENC and TRACTS datasets is ongoing. Preliminary descriptive analyses of baseline cohort data indicate that harmonization across data sources is appropriate, given the lack of significant heterogeneity across sites and studies for most domains. Work by members of the TBD team is expected to lay the foundation for the use of existing and ongoing prospective, longitudinal datasets (eg, LIMBIC-CENC, TRACTS) and linked large datasets (eg, VA Informatics and Computing Infrastructure including electronic health records, VA Million Veteran Program, DaVINCI [US Department of Defense and VA Infrastructure for Clinical Intelligence]) to generate generalizable, clinically relevant information to advance precision brain and mental health care among service members and veterans.

By enhancing existing practice, this synthesized dataset has the potential to inform tailored and personalized medicine approaches designed to meet the needs of veterans and service members. These data will serve as the starting point for multivariable models examining the intersection of physiologic, behavioral, and environmental factors. The goal of this data harmonization effort is to better elucidate how clinicians and researchers can select optimal approaches for veterans and service members with TBI histories by accounting for a comprehensive set of physiologic, behavioral, and environmental factors in an individually tailored manner. These data may further extend existing clinical practice guideline approaches, inform shared decision-making, and enhance functional outcomes beyond those currently available.

Conclusions

Individuals who have served in the military have unique biopsychosocial exposures that are associated with brain and mental health disorders. To address these needs, the nationwide TBD team has initiated the creation of a unified, longitudinal dataset that includes harmonized measures from existing LIMBIC-CENC and TRACTS protocols. Initial data harmonization efforts are required to facilitate precision prognostics, diagnostics, and tailored interventions, with the goal of improving veterans’ brain and mental health and psychosocial functioning and enabling tailored and evidence-informed, individualized clinical care.

In leveraging existing, readily available evidence-based health care information (eg, systematic reviews, clinical practice guidelines), clinicians have historically made recommendations based on treatment responses of the average patient.¹ Recently, this approach has been expanded into data-driven, evidence-based precision medical care for individuals across a wide range of disciplines and care settings. These precision medicine approaches use information related to an individual’s genes, environment, and lifestyle to tailor recommendations regarding prevention, diagnosis, and treatment.

Applying precision medicine approaches to the unique exposures and experiences of service members and veterans—particularly those who served in combat environments—through the incorporation of biopsychosocial factors into medical decision-making may be even more pertinent. This sentiment is reflected in Section 305 of the Commander John Scott Hannon Veterans Mental Health Care Improvement Act of 2019, which outlines the Precision Medicine Initiative of the US Department of Veterans Affairs (VA) to identify and validate brain and mental health biomarkers.² Despite widespread consensus regarding the promise of precision medicine, large, rich datasets with elements pertaining to common military exposures such as traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are limited.

Existing datasets, most of which are relatively small or focus on specific cohorts (eg, older veterans, transitioning veterans), continue to create barriers to advancing precision medicine. For example, in classically designed clinical trials, analyses are generally conducted in a manner that may obfuscate efficacy among subcohorts of individuals, thereby underscoring the need to explore alternative strategies to unify existing datasets capable of revealing such heterogeneity.³ The evidence base for precision medical care is limited, drawing from published trials with relatively small sample sizes and even larger cohort studies have limited biomarker data. Additionally, these models are often exploratory during development, and to avoid statistical overfitting of an exploratory model, validation in similar datasets is needed—an added burden when data sources are small or underpowered to begin with.

A promising approach is to combine and harmonize the largest, most deeply characterized data sources from similar samples. Although combining such datasets may appear to require minimal time and effort, harmonizing similar variables in an evidence-based and replicable manner requires time and expertise, even when participant characteristics and outcomes are similar.^4-7

Challenges related to harmonization are related to the wide range of strategies (eg, self-report questionnaires, clinical interviews, electronic health record review) used to measure common brain and mental health constructs, such as depression. Even when similar methods (eg, self-report measures) are implemented, challenges persist. For example, if a study used a depression measure that focused primarily on cognitive symptoms (eg, pessimism, self-dislike, suicidal ideation) and another study used a depression measure composed of items more heavily weighted towards somatic symptoms (eg, insomnia, loss of appetite, weight loss, decreased libido), combining their data could be challenging, particularly if researchers, clinicians, or administrators are interested in more than dichotomous outcomes (eg, depression vs no depression).^8,9

To address this knowledge gap and harmonize multimodal data from varied sources, well-planned and reproducible curation is needed. Longitudinal cohort studies of service members and veterans with military combat and training exposure histories provide researchers and other stakeholders access to extant biopsychosocial data shown to affect risk for adverse health outcomes; however, efforts to facilitate individually tailored treatment or other precision medicine approaches would benefit from the synthesis of such datasets.¹⁰

Members of the VA Total Brain Diagnostics (TBD) team are engaged in harmonizing variables from the Long-Term Impact of Military-Relevant Brain Injury Consortium–Chronic Effects of Neurotrauma Consortium (LIMBIC-CENC)¹¹ and the Translational Research Center for TBI and Stress Disorders (TRACTS).^12-21 While there is overlap across LIMBIC-CENC and TRACTS with respect to data domains, considerable data harmonization is needed to allow for future valid and meaningful analyses, particularly those involving multivariable predictors.

Data Sources

Both data sources for the TBD harmonization project, LIMBIC-CENC and TRACTS, include extensive, longitudinal data collected from relatively large cohorts of veterans and service members with combat exposure. Both studies collect detailed data related to potential brain injury history and include participants with and without a history of TBI. Similarly, both include extensive collection of fluid biomarkers and imaging data, as well as measures of biopsychosocial functioning.

Data collection sites for LIMBIC-CENC include 16 recruitment sites, 9 at VA medical centers (Richmond, Houston, Tampa, San Antonio, Portland, Minneapolis, Boston, Salisbury, San Diego) and 7 at military treatment sites (Alexandria, San Diego, Tampa, Tacoma, Columbia, Coronado, Hinesville), in addition to 11 assessment sites (Richmond, Houston, Tampa, San Antonio, Portland, Minneapolis, Boston, Salisbury, San Diego, Alexandria, Augusta). Data for TRACTS are collected at sites in Boston and Houston.

LIMBIC-CENC is a 12-year, 17-site cohort of service members and veteran participants with combat exposure who are well characterized at baseline and undergo annual reassessments. As of December 2025, > 3100 participants have been recruited, and nearly 90% remain in follow-up. Data collection includes > 6200 annual follow-up evaluations and > 1550 5-year re-evaluations, with 400 enrolled participants followed up annually.

TRACTS is a 16-year, 2-site cohort of veterans with combat exposure who complete comprehensive assessments at enrollment, undergo annual reassessments, and complete comprehensive reassessment every 5 years thereafter. As of December 2025, > 1075 participants have completed baseline (Time 1) assessments, > 600 have completed the 2-year re-evaluation (Time 2), > 175 have completed the 5-year re-evaluation (Time 3), and > 35 have completed 10-year evaluations (Time 4), with about 50 new participants added and 100 enrolled participants followed up annually. More data on participant characteristics are available for both LIMBIC-CENC and TRACTS in previous publications.^11,22These 2 ongoing, prospective, longitudinal cohorts of service members and veterans offer access to a wide range of potential risk factors that can affect response to care and outcomes, including demographics (eg, age, sex), injury characteristics (eg, pre-exposure factors, exposure factors), biomarkers (eg, serum, saliva, brain imaging, evoked potentials), and functional measures (eg, computerized posturography, computerized eye tracking, sensory testing, clinical examination, neuropsychological assessments, symptom questionnaires).

Harmonization Strategy

Pooling and harmonizing data from large studies evaluating similar participant cohorts and conditions involves numerous steps to appropriately handle a variety of measurements and disparate variable names. The TBD team adapted a model data harmonization system developed by O’Neil et al through initial work harmonizing the Federal Interagency Traumatic Brain Injury Research Informatics System (FITBIR).^4-7 This process was expanded and generalized by the research team to combine data from LIMBIC-CENC and TRACTS to create a single pooled dataset for analysis (Figure).

This approach was selected because it accommodates heterogeneous study designs (eg, cross-sectional, longitudinal, case-control), data collection methods (eg, clinical assessment, self-reported, objective blood, and imaging biomarkers), and various assessments of the same construct (ie, different measures of brain injury). While exact matches for data collection methods and measures may be easily harmonized, the timing of assessment, number of assessments, assessment tool version, and other factors must be considered. The goal was to harmonize data from LIMBIC-CENC and TRACTS to allow additional data sources to be harmonized and incorporated in the future.

Original data files from each study were reshaped to represent participant-level observations with 1 unique measurement per row. The measurement represents what information was collected and the value recorded represents the unique observation. These data are linked to metadata from the original study, which includes the study’s definition of each measurement, how it was collected, and any available information regarding when it was collected in reference to study enrollment or injury. Additional information on the file source, row, and column position of each data point was added to enable recreation of the original data as needed.

The resulting dataset was used to harmonize measurements from LIMBIC-CENC and TRACTS into a priori-defined schemas for brain- and mental health-relevant concepts, including TBI severity, PTSD, substance use, depression, suicidal ideation, and functioning (including cognitive, physical, and social functioning). This process was facilitated using natural language processing (NLP). Each study uniquely defines all measurements and provides written definitions with the data. Measurement definitions serve as records describing what was collected, how it was collected, and how the study may have uniquely defined information for its purposes. For example, definitions of exposure to brain injury and severity of brain injury may differ between studies, and the study-provided definition defines these differences.

Definitions were converted into numeric vectors through sentence embedding, a process that preserves the semantic meaning of the definition.²³ Cosine similarity was used as the primary metric to compare the semantic textual similarity between pairs of measurement definitions. Cosine similarity ranges from 0 to 1, where 0 indicates no meaningful similarity and 1 indicates they have identical meanings.²⁴ This approach leverages the relationship between the definitions of each measurement provided by a study and enables quick comparison of all pairwise combinations of measurement definitions between studies.

Subsets of similar measurements across studies were organized into a priori-defined schema. Clinical experts then reviewed each schema and further refined them into domains, (eg, mechanism of injury, clinical signs, acute symptoms) and subdomains (children), such as loss of consciousness, amnesia, and alteration of consciousness. This approach allows efficient handling of 2 specific cases that commonly occur when pooling and harmonizing datasets: (1) identifying the same measurement with differing names; and (2) identifying different measurements with definitions that each relate to the same domain.

The Table provides a general example of the schema for TBI severity. This was an iterative process in which clinical experts reviewed study-defined measurement definitions to develop general harmonized domains, and NLP techniques facilitated and accelerated identification and organization of measurements within these domains.

Expected Impact

Harmonization combining LIMBIC-CENC and TRACTS datasets is ongoing. Preliminary descriptive analyses of baseline cohort data indicate that harmonization across data sources is appropriate, given the lack of significant heterogeneity across sites and studies for most domains. Work by members of the TBD team is expected to lay the foundation for the use of existing and ongoing prospective, longitudinal datasets (eg, LIMBIC-CENC, TRACTS) and linked large datasets (eg, VA Informatics and Computing Infrastructure including electronic health records, VA Million Veteran Program, DaVINCI [US Department of Defense and VA Infrastructure for Clinical Intelligence]) to generate generalizable, clinically relevant information to advance precision brain and mental health care among service members and veterans.

By enhancing existing practice, this synthesized dataset has the potential to inform tailored and personalized medicine approaches designed to meet the needs of veterans and service members. These data will serve as the starting point for multivariable models examining the intersection of physiologic, behavioral, and environmental factors. The goal of this data harmonization effort is to better elucidate how clinicians and researchers can select optimal approaches for veterans and service members with TBI histories by accounting for a comprehensive set of physiologic, behavioral, and environmental factors in an individually tailored manner. These data may further extend existing clinical practice guideline approaches, inform shared decision-making, and enhance functional outcomes beyond those currently available.

Conclusions

Individuals who have served in the military have unique biopsychosocial exposures that are associated with brain and mental health disorders. To address these needs, the nationwide TBD team has initiated the creation of a unified, longitudinal dataset that includes harmonized measures from existing LIMBIC-CENC and TRACTS protocols. Initial data harmonization efforts are required to facilitate precision prognostics, diagnostics, and tailored interventions, with the goal of improving veterans’ brain and mental health and psychosocial functioning and enabling tailored and evidence-informed, individualized clinical care.

In leveraging existing, readily available evidence-based health care information (eg, systematic reviews, clinical practice guidelines), clinicians have historically made recommendations based on treatment responses of the average patient.¹ Recently, this approach has been expanded into data-driven, evidence-based precision medical care for individuals across a wide range of disciplines and care settings. These precision medicine approaches use information related to an individual’s genes, environment, and lifestyle to tailor recommendations regarding prevention, diagnosis, and treatment.

Applying precision medicine approaches to the unique exposures and experiences of service members and veterans—particularly those who served in combat environments—through the incorporation of biopsychosocial factors into medical decision-making may be even more pertinent. This sentiment is reflected in Section 305 of the Commander John Scott Hannon Veterans Mental Health Care Improvement Act of 2019, which outlines the Precision Medicine Initiative of the US Department of Veterans Affairs (VA) to identify and validate brain and mental health biomarkers.² Despite widespread consensus regarding the promise of precision medicine, large, rich datasets with elements pertaining to common military exposures such as traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are limited.

Existing datasets, most of which are relatively small or focus on specific cohorts (eg, older veterans, transitioning veterans), continue to create barriers to advancing precision medicine. For example, in classically designed clinical trials, analyses are generally conducted in a manner that may obfuscate efficacy among subcohorts of individuals, thereby underscoring the need to explore alternative strategies to unify existing datasets capable of revealing such heterogeneity.³ The evidence base for precision medical care is limited, drawing from published trials with relatively small sample sizes and even larger cohort studies have limited biomarker data. Additionally, these models are often exploratory during development, and to avoid statistical overfitting of an exploratory model, validation in similar datasets is needed—an added burden when data sources are small or underpowered to begin with.

A promising approach is to combine and harmonize the largest, most deeply characterized data sources from similar samples. Although combining such datasets may appear to require minimal time and effort, harmonizing similar variables in an evidence-based and replicable manner requires time and expertise, even when participant characteristics and outcomes are similar.^4-7

Challenges related to harmonization are related to the wide range of strategies (eg, self-report questionnaires, clinical interviews, electronic health record review) used to measure common brain and mental health constructs, such as depression. Even when similar methods (eg, self-report measures) are implemented, challenges persist. For example, if a study used a depression measure that focused primarily on cognitive symptoms (eg, pessimism, self-dislike, suicidal ideation) and another study used a depression measure composed of items more heavily weighted towards somatic symptoms (eg, insomnia, loss of appetite, weight loss, decreased libido), combining their data could be challenging, particularly if researchers, clinicians, or administrators are interested in more than dichotomous outcomes (eg, depression vs no depression).^8,9

To address this knowledge gap and harmonize multimodal data from varied sources, well-planned and reproducible curation is needed. Longitudinal cohort studies of service members and veterans with military combat and training exposure histories provide researchers and other stakeholders access to extant biopsychosocial data shown to affect risk for adverse health outcomes; however, efforts to facilitate individually tailored treatment or other precision medicine approaches would benefit from the synthesis of such datasets.¹⁰

Members of the VA Total Brain Diagnostics (TBD) team are engaged in harmonizing variables from the Long-Term Impact of Military-Relevant Brain Injury Consortium–Chronic Effects of Neurotrauma Consortium (LIMBIC-CENC)¹¹ and the Translational Research Center for TBI and Stress Disorders (TRACTS).^12-21 While there is overlap across LIMBIC-CENC and TRACTS with respect to data domains, considerable data harmonization is needed to allow for future valid and meaningful analyses, particularly those involving multivariable predictors.

Data Sources

Both data sources for the TBD harmonization project, LIMBIC-CENC and TRACTS, include extensive, longitudinal data collected from relatively large cohorts of veterans and service members with combat exposure. Both studies collect detailed data related to potential brain injury history and include participants with and without a history of TBI. Similarly, both include extensive collection of fluid biomarkers and imaging data, as well as measures of biopsychosocial functioning.

Data collection sites for LIMBIC-CENC include 16 recruitment sites, 9 at VA medical centers (Richmond, Houston, Tampa, San Antonio, Portland, Minneapolis, Boston, Salisbury, San Diego) and 7 at military treatment sites (Alexandria, San Diego, Tampa, Tacoma, Columbia, Coronado, Hinesville), in addition to 11 assessment sites (Richmond, Houston, Tampa, San Antonio, Portland, Minneapolis, Boston, Salisbury, San Diego, Alexandria, Augusta). Data for TRACTS are collected at sites in Boston and Houston.

LIMBIC-CENC is a 12-year, 17-site cohort of service members and veteran participants with combat exposure who are well characterized at baseline and undergo annual reassessments. As of December 2025, > 3100 participants have been recruited, and nearly 90% remain in follow-up. Data collection includes > 6200 annual follow-up evaluations and > 1550 5-year re-evaluations, with 400 enrolled participants followed up annually.

TRACTS is a 16-year, 2-site cohort of veterans with combat exposure who complete comprehensive assessments at enrollment, undergo annual reassessments, and complete comprehensive reassessment every 5 years thereafter. As of December 2025, > 1075 participants have completed baseline (Time 1) assessments, > 600 have completed the 2-year re-evaluation (Time 2), > 175 have completed the 5-year re-evaluation (Time 3), and > 35 have completed 10-year evaluations (Time 4), with about 50 new participants added and 100 enrolled participants followed up annually. More data on participant characteristics are available for both LIMBIC-CENC and TRACTS in previous publications.^11,22These 2 ongoing, prospective, longitudinal cohorts of service members and veterans offer access to a wide range of potential risk factors that can affect response to care and outcomes, including demographics (eg, age, sex), injury characteristics (eg, pre-exposure factors, exposure factors), biomarkers (eg, serum, saliva, brain imaging, evoked potentials), and functional measures (eg, computerized posturography, computerized eye tracking, sensory testing, clinical examination, neuropsychological assessments, symptom questionnaires).

Harmonization Strategy

Pooling and harmonizing data from large studies evaluating similar participant cohorts and conditions involves numerous steps to appropriately handle a variety of measurements and disparate variable names. The TBD team adapted a model data harmonization system developed by O’Neil et al through initial work harmonizing the Federal Interagency Traumatic Brain Injury Research Informatics System (FITBIR).^4-7 This process was expanded and generalized by the research team to combine data from LIMBIC-CENC and TRACTS to create a single pooled dataset for analysis (Figure).

This approach was selected because it accommodates heterogeneous study designs (eg, cross-sectional, longitudinal, case-control), data collection methods (eg, clinical assessment, self-reported, objective blood, and imaging biomarkers), and various assessments of the same construct (ie, different measures of brain injury). While exact matches for data collection methods and measures may be easily harmonized, the timing of assessment, number of assessments, assessment tool version, and other factors must be considered. The goal was to harmonize data from LIMBIC-CENC and TRACTS to allow additional data sources to be harmonized and incorporated in the future.

Original data files from each study were reshaped to represent participant-level observations with 1 unique measurement per row. The measurement represents what information was collected and the value recorded represents the unique observation. These data are linked to metadata from the original study, which includes the study’s definition of each measurement, how it was collected, and any available information regarding when it was collected in reference to study enrollment or injury. Additional information on the file source, row, and column position of each data point was added to enable recreation of the original data as needed.

The resulting dataset was used to harmonize measurements from LIMBIC-CENC and TRACTS into a priori-defined schemas for brain- and mental health-relevant concepts, including TBI severity, PTSD, substance use, depression, suicidal ideation, and functioning (including cognitive, physical, and social functioning). This process was facilitated using natural language processing (NLP). Each study uniquely defines all measurements and provides written definitions with the data. Measurement definitions serve as records describing what was collected, how it was collected, and how the study may have uniquely defined information for its purposes. For example, definitions of exposure to brain injury and severity of brain injury may differ between studies, and the study-provided definition defines these differences.

Definitions were converted into numeric vectors through sentence embedding, a process that preserves the semantic meaning of the definition.²³ Cosine similarity was used as the primary metric to compare the semantic textual similarity between pairs of measurement definitions. Cosine similarity ranges from 0 to 1, where 0 indicates no meaningful similarity and 1 indicates they have identical meanings.²⁴ This approach leverages the relationship between the definitions of each measurement provided by a study and enables quick comparison of all pairwise combinations of measurement definitions between studies.

Subsets of similar measurements across studies were organized into a priori-defined schema. Clinical experts then reviewed each schema and further refined them into domains, (eg, mechanism of injury, clinical signs, acute symptoms) and subdomains (children), such as loss of consciousness, amnesia, and alteration of consciousness. This approach allows efficient handling of 2 specific cases that commonly occur when pooling and harmonizing datasets: (1) identifying the same measurement with differing names; and (2) identifying different measurements with definitions that each relate to the same domain.

The Table provides a general example of the schema for TBI severity. This was an iterative process in which clinical experts reviewed study-defined measurement definitions to develop general harmonized domains, and NLP techniques facilitated and accelerated identification and organization of measurements within these domains.

Expected Impact

Harmonization combining LIMBIC-CENC and TRACTS datasets is ongoing. Preliminary descriptive analyses of baseline cohort data indicate that harmonization across data sources is appropriate, given the lack of significant heterogeneity across sites and studies for most domains. Work by members of the TBD team is expected to lay the foundation for the use of existing and ongoing prospective, longitudinal datasets (eg, LIMBIC-CENC, TRACTS) and linked large datasets (eg, VA Informatics and Computing Infrastructure including electronic health records, VA Million Veteran Program, DaVINCI [US Department of Defense and VA Infrastructure for Clinical Intelligence]) to generate generalizable, clinically relevant information to advance precision brain and mental health care among service members and veterans.

By enhancing existing practice, this synthesized dataset has the potential to inform tailored and personalized medicine approaches designed to meet the needs of veterans and service members. These data will serve as the starting point for multivariable models examining the intersection of physiologic, behavioral, and environmental factors. The goal of this data harmonization effort is to better elucidate how clinicians and researchers can select optimal approaches for veterans and service members with TBI histories by accounting for a comprehensive set of physiologic, behavioral, and environmental factors in an individually tailored manner. These data may further extend existing clinical practice guideline approaches, inform shared decision-making, and enhance functional outcomes beyond those currently available.

Conclusions

Individuals who have served in the military have unique biopsychosocial exposures that are associated with brain and mental health disorders. To address these needs, the nationwide TBD team has initiated the creation of a unified, longitudinal dataset that includes harmonized measures from existing LIMBIC-CENC and TRACTS protocols. Initial data harmonization efforts are required to facilitate precision prognostics, diagnostics, and tailored interventions, with the goal of improving veterans’ brain and mental health and psychosocial functioning and enabling tailored and evidence-informed, individualized clinical care.

Military culture may hold 2 salient risk factors for eating disorders: exposure to trauma and body condition standards. A recent study from the US Department of Veteran Affairs (VA) Salisbury Health Care System (VASHCS) found that veterans with posttraumatic stress disorder (PTSD) are more likely to report eating disturbances—particularly issues related to body dissatisfaction and dissatisfaction with eating habits. A 2019 study found that one-third of veterans who were overweight or obese screened positive for engaging in “making weight” behaviors during military service, or unhealthy weight control strategies. Frequently reported weight management behavior was excessive exercise, fasting/skipping meals, sitting in a sauna/wearing a latex suit, laxatives, diuretics, and vomiting.

Service members who are “normal” weight by civilian standards may be labeled “overweight” by the military. In a March 12 memo, Secretary of Defense Pete Hegseth ordered a US Department of Defense review of existing standards for physical fitness, body composition, and grooming. “Our troops will be fit — not fat. Our troops will look sharp — not sloppy. We seek only quality — not quotas. BOTTOM LINE: our @DeptofDefense will make standards HIGH & GREAT again — across the entire force,” he posted on X.

The desire to control weight to fit military standards, however, isn’t the only risk factor. Researchers at VASHCS surveyed 527 post-9/11 veterans (80.7% male) who typically deployed 1 or 2 times. All participants completed the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; the Neuro-Quality of Life in Neurological Disorders Positive Affect and Well-Being Scale (PAWB); and the Eating Disturbances Scale. 

Nearly half (46%) of the sample met diagnostic criteria for a lifetime PTSD diagnosis. The study also reported significantly greater eating disturbances in veterans with a lifetime PTSD diagnosis than those without. Women reported significantly greater eating disturbances than men.

Most participants (80%) reported some level of dissatisfaction with their eating disturbances and 74% of participants reported feeling as if they were too fat.

Eating disturbances include refusing food, overexercising, overeating, and misusing laxatives or diuretic pills. Previous research that suggest that 10% to 15% of female veterans and 4% to 8% of male veterans report clinically significant disordered eating behaviors, especially binge eating. One study found that 78% of 45,477 overweight or obese veterans receiving care in VA facilities reported clinically significant binge eating. In a 2021 study, 254 veterans presenting for routine clinical care completed self‐report questionnaires assessing eating disorders, PTSD, depression, and shame, and 31% met probable criteria for bulimia nervosa, binge‐eating disorder, or purging disorder.

According to a 2023 study, eating disturbances that do not meet diagnostic criteria for a formal disorder can be problematic and may function as coping strategies for some facets of military life. The VASHCS researchers found that interventions focused on PAWB, such as acceptance and commitment therapy or compassion-focused therapy, may have potential as a protective factor. Including components that foster hope, optimism, and personal strength may positively mitigate the relationship between PTSD and eating disturbances. PAWB was significantly correlated with eating disturbances; individuals with a lifetime PTSD diagnosis reported significantly lower PAWB than those without.

Interventions grounded in positive psychology have shown promise. A group-based program found “noticeable” (although nonsignificant) improvements in optimistic thinking and treatment engagement. The study also cites that clinicians are beginning to incorporate positive psychology strategies (eg, gratitude journaling, goal setting, and “best possible self” visualization) as adjuncts to traditional treatments. Positive psychology, they write, holds “significant promise as a complementary approach to enhance recovery outcomes in both PTSD and eating disorders.” 

Military culture may hold 2 salient risk factors for eating disorders: exposure to trauma and body condition standards. A recent study from the US Department of Veteran Affairs (VA) Salisbury Health Care System (VASHCS) found that veterans with posttraumatic stress disorder (PTSD) are more likely to report eating disturbances—particularly issues related to body dissatisfaction and dissatisfaction with eating habits. A 2019 study found that one-third of veterans who were overweight or obese screened positive for engaging in “making weight” behaviors during military service, or unhealthy weight control strategies. Frequently reported weight management behavior was excessive exercise, fasting/skipping meals, sitting in a sauna/wearing a latex suit, laxatives, diuretics, and vomiting.

Service members who are “normal” weight by civilian standards may be labeled “overweight” by the military. In a March 12 memo, Secretary of Defense Pete Hegseth ordered a US Department of Defense review of existing standards for physical fitness, body composition, and grooming. “Our troops will be fit — not fat. Our troops will look sharp — not sloppy. We seek only quality — not quotas. BOTTOM LINE: our @DeptofDefense will make standards HIGH & GREAT again — across the entire force,” he posted on X.

The desire to control weight to fit military standards, however, isn’t the only risk factor. Researchers at VASHCS surveyed 527 post-9/11 veterans (80.7% male) who typically deployed 1 or 2 times. All participants completed the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; the Neuro-Quality of Life in Neurological Disorders Positive Affect and Well-Being Scale (PAWB); and the Eating Disturbances Scale. 

Nearly half (46%) of the sample met diagnostic criteria for a lifetime PTSD diagnosis. The study also reported significantly greater eating disturbances in veterans with a lifetime PTSD diagnosis than those without. Women reported significantly greater eating disturbances than men.

Most participants (80%) reported some level of dissatisfaction with their eating disturbances and 74% of participants reported feeling as if they were too fat.

Eating disturbances include refusing food, overexercising, overeating, and misusing laxatives or diuretic pills. Previous research that suggest that 10% to 15% of female veterans and 4% to 8% of male veterans report clinically significant disordered eating behaviors, especially binge eating. One study found that 78% of 45,477 overweight or obese veterans receiving care in VA facilities reported clinically significant binge eating. In a 2021 study, 254 veterans presenting for routine clinical care completed self‐report questionnaires assessing eating disorders, PTSD, depression, and shame, and 31% met probable criteria for bulimia nervosa, binge‐eating disorder, or purging disorder.

According to a 2023 study, eating disturbances that do not meet diagnostic criteria for a formal disorder can be problematic and may function as coping strategies for some facets of military life. The VASHCS researchers found that interventions focused on PAWB, such as acceptance and commitment therapy or compassion-focused therapy, may have potential as a protective factor. Including components that foster hope, optimism, and personal strength may positively mitigate the relationship between PTSD and eating disturbances. PAWB was significantly correlated with eating disturbances; individuals with a lifetime PTSD diagnosis reported significantly lower PAWB than those without.

Interventions grounded in positive psychology have shown promise. A group-based program found “noticeable” (although nonsignificant) improvements in optimistic thinking and treatment engagement. The study also cites that clinicians are beginning to incorporate positive psychology strategies (eg, gratitude journaling, goal setting, and “best possible self” visualization) as adjuncts to traditional treatments. Positive psychology, they write, holds “significant promise as a complementary approach to enhance recovery outcomes in both PTSD and eating disorders.” 

Military culture may hold 2 salient risk factors for eating disorders: exposure to trauma and body condition standards. A recent study from the US Department of Veteran Affairs (VA) Salisbury Health Care System (VASHCS) found that veterans with posttraumatic stress disorder (PTSD) are more likely to report eating disturbances—particularly issues related to body dissatisfaction and dissatisfaction with eating habits. A 2019 study found that one-third of veterans who were overweight or obese screened positive for engaging in “making weight” behaviors during military service, or unhealthy weight control strategies. Frequently reported weight management behavior was excessive exercise, fasting/skipping meals, sitting in a sauna/wearing a latex suit, laxatives, diuretics, and vomiting.

Service members who are “normal” weight by civilian standards may be labeled “overweight” by the military. In a March 12 memo, Secretary of Defense Pete Hegseth ordered a US Department of Defense review of existing standards for physical fitness, body composition, and grooming. “Our troops will be fit — not fat. Our troops will look sharp — not sloppy. We seek only quality — not quotas. BOTTOM LINE: our @DeptofDefense will make standards HIGH & GREAT again — across the entire force,” he posted on X.

The desire to control weight to fit military standards, however, isn’t the only risk factor. Researchers at VASHCS surveyed 527 post-9/11 veterans (80.7% male) who typically deployed 1 or 2 times. All participants completed the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; the Neuro-Quality of Life in Neurological Disorders Positive Affect and Well-Being Scale (PAWB); and the Eating Disturbances Scale. 

Nearly half (46%) of the sample met diagnostic criteria for a lifetime PTSD diagnosis. The study also reported significantly greater eating disturbances in veterans with a lifetime PTSD diagnosis than those without. Women reported significantly greater eating disturbances than men.

Most participants (80%) reported some level of dissatisfaction with their eating disturbances and 74% of participants reported feeling as if they were too fat.

Eating disturbances include refusing food, overexercising, overeating, and misusing laxatives or diuretic pills. Previous research that suggest that 10% to 15% of female veterans and 4% to 8% of male veterans report clinically significant disordered eating behaviors, especially binge eating. One study found that 78% of 45,477 overweight or obese veterans receiving care in VA facilities reported clinically significant binge eating. In a 2021 study, 254 veterans presenting for routine clinical care completed self‐report questionnaires assessing eating disorders, PTSD, depression, and shame, and 31% met probable criteria for bulimia nervosa, binge‐eating disorder, or purging disorder.

According to a 2023 study, eating disturbances that do not meet diagnostic criteria for a formal disorder can be problematic and may function as coping strategies for some facets of military life. The VASHCS researchers found that interventions focused on PAWB, such as acceptance and commitment therapy or compassion-focused therapy, may have potential as a protective factor. Including components that foster hope, optimism, and personal strength may positively mitigate the relationship between PTSD and eating disturbances. PAWB was significantly correlated with eating disturbances; individuals with a lifetime PTSD diagnosis reported significantly lower PAWB than those without.

Interventions grounded in positive psychology have shown promise. A group-based program found “noticeable” (although nonsignificant) improvements in optimistic thinking and treatment engagement. The study also cites that clinicians are beginning to incorporate positive psychology strategies (eg, gratitude journaling, goal setting, and “best possible self” visualization) as adjuncts to traditional treatments. Positive psychology, they write, holds “significant promise as a complementary approach to enhance recovery outcomes in both PTSD and eating disorders.” 

For patients with cancer, the determining factor in whether they pursue mental health services is often whether their oncologist explicitly says it is a good idea, a psychologist said during the July Association of VA Hematology and Oncology (AVAHO) seminar in Long Beach, California, on treating veterans with renal cell carcinoma (RCC).

Kysa Christie, PhD, of the West Los Angeles Veterans Affairs Medical Center, presented findings from a 2018 study in which researchers asked Swiss patients with cancer whether their oncologist discussed their emotional health with them. 

In terms of boosting intake, it did not matter if oncologists acknowledged distress or pointed out that psychosocial services existed. Instead, a direct recommendation made a difference, increasing the likelihood of using the services over a 4-month period after initial assessment (odds ratio, 6.27).

“What it took was, ‘I really recommend this. This is something that I would want you to try,’” Christie said. 

Oncologists are crucial links between patients and mental health services, Christie said: “If people don’t ask about [distress], you’re not going to see it, but it’s there. Distress is the norm, right? It is not a weakness. It is something that we expect to see.”

Christie noted that an estimated 20% of cancer patients have major depressive disorder, and 35% to 40% have a diagnosable psychiatric condition. RCC shows disproportionately high rates of mental strain. According to Christie, research suggests that about three-fourths of the population report elevated levels of distress as evidenced by patients who scored ≥ 5 on the NCCN Distress Thermometer. Patients with cancer have an estimated 20% higher risk of suicide, especially during the first 12 months after diagnosis and at end of life, she added.

“Early during a diagnosis phase, where you’re having a lot of tests being done, you know something is happening. But you don’t know what,” Christie said. “It could be very serious. That’s just a lot of stress to hold and not know how to plan for.”

After diagnosis, routine could set in and lower distress, she said. Then terminal illness may spike it back up again. Does mental health treatment work in patients with cancer?

“There’s a really strong body of evidence-based treatments for depression, anxiety, adjustment disorders, and coping with different cancers,” Christie said. But it is a step too far to expect patients to ask for help while they are juggling appointments, tests, infusions, and more. “It’s a big ask, right? It’s setting people up for failure.”

To help, Christie said she is embedded with a medical oncology team and routinely talks with the staff about which patients may need help. “One thing I like to do is try to have brief visits with veterans and introduce myself when they come to clinic. I treat it like an opt-out rather than an opt-in program: I’ll just pop into the exam room. They don’t have to ask to see me.”

Christie focuses on open-ended questions and talks about resources ranging from support groups and brief appointments to extensive individual therapy. 

Another approach is a strategy known as the “warm handoff,” when an oncologist directly introduces a patient to a mental health professional. “It’s a transfer of care in front of the veteran: It’s much more time-efficient than putting in a referral.”

Christie explained how this can work. A clinician will ask her to meet with a patient during an appointment, perhaps in a couple minutes.

“Then I pop into the room, and the oncologist says, ‘Thanks for joining us. This is Mr. Jones. He has been experiencing feelings of anxiety and sadness, and we’d appreciate your help in exploring some options that might help.’  I turn to the patient and ask, ‘What more would you add?’ Then I either take Mr. Jones back to my office or stay in clinic, and we’re off to the races.”

Christie reported no disclosures.

For patients with cancer, the determining factor in whether they pursue mental health services is often whether their oncologist explicitly says it is a good idea, a psychologist said during the July Association of VA Hematology and Oncology (AVAHO) seminar in Long Beach, California, on treating veterans with renal cell carcinoma (RCC).

Kysa Christie, PhD, of the West Los Angeles Veterans Affairs Medical Center, presented findings from a 2018 study in which researchers asked Swiss patients with cancer whether their oncologist discussed their emotional health with them. 

In terms of boosting intake, it did not matter if oncologists acknowledged distress or pointed out that psychosocial services existed. Instead, a direct recommendation made a difference, increasing the likelihood of using the services over a 4-month period after initial assessment (odds ratio, 6.27).

“What it took was, ‘I really recommend this. This is something that I would want you to try,’” Christie said. 

Oncologists are crucial links between patients and mental health services, Christie said: “If people don’t ask about [distress], you’re not going to see it, but it’s there. Distress is the norm, right? It is not a weakness. It is something that we expect to see.”

Christie noted that an estimated 20% of cancer patients have major depressive disorder, and 35% to 40% have a diagnosable psychiatric condition. RCC shows disproportionately high rates of mental strain. According to Christie, research suggests that about three-fourths of the population report elevated levels of distress as evidenced by patients who scored ≥ 5 on the NCCN Distress Thermometer. Patients with cancer have an estimated 20% higher risk of suicide, especially during the first 12 months after diagnosis and at end of life, she added.

“Early during a diagnosis phase, where you’re having a lot of tests being done, you know something is happening. But you don’t know what,” Christie said. “It could be very serious. That’s just a lot of stress to hold and not know how to plan for.”

After diagnosis, routine could set in and lower distress, she said. Then terminal illness may spike it back up again. Does mental health treatment work in patients with cancer?

“There’s a really strong body of evidence-based treatments for depression, anxiety, adjustment disorders, and coping with different cancers,” Christie said. But it is a step too far to expect patients to ask for help while they are juggling appointments, tests, infusions, and more. “It’s a big ask, right? It’s setting people up for failure.”

To help, Christie said she is embedded with a medical oncology team and routinely talks with the staff about which patients may need help. “One thing I like to do is try to have brief visits with veterans and introduce myself when they come to clinic. I treat it like an opt-out rather than an opt-in program: I’ll just pop into the exam room. They don’t have to ask to see me.”

Christie focuses on open-ended questions and talks about resources ranging from support groups and brief appointments to extensive individual therapy. 

Another approach is a strategy known as the “warm handoff,” when an oncologist directly introduces a patient to a mental health professional. “It’s a transfer of care in front of the veteran: It’s much more time-efficient than putting in a referral.”

Christie explained how this can work. A clinician will ask her to meet with a patient during an appointment, perhaps in a couple minutes.

“Then I pop into the room, and the oncologist says, ‘Thanks for joining us. This is Mr. Jones. He has been experiencing feelings of anxiety and sadness, and we’d appreciate your help in exploring some options that might help.’  I turn to the patient and ask, ‘What more would you add?’ Then I either take Mr. Jones back to my office or stay in clinic, and we’re off to the races.”

Christie reported no disclosures.

For patients with cancer, the determining factor in whether they pursue mental health services is often whether their oncologist explicitly says it is a good idea, a psychologist said during the July Association of VA Hematology and Oncology (AVAHO) seminar in Long Beach, California, on treating veterans with renal cell carcinoma (RCC).

Kysa Christie, PhD, of the West Los Angeles Veterans Affairs Medical Center, presented findings from a 2018 study in which researchers asked Swiss patients with cancer whether their oncologist discussed their emotional health with them. 

In terms of boosting intake, it did not matter if oncologists acknowledged distress or pointed out that psychosocial services existed. Instead, a direct recommendation made a difference, increasing the likelihood of using the services over a 4-month period after initial assessment (odds ratio, 6.27).

“What it took was, ‘I really recommend this. This is something that I would want you to try,’” Christie said. 

Oncologists are crucial links between patients and mental health services, Christie said: “If people don’t ask about [distress], you’re not going to see it, but it’s there. Distress is the norm, right? It is not a weakness. It is something that we expect to see.”

Christie noted that an estimated 20% of cancer patients have major depressive disorder, and 35% to 40% have a diagnosable psychiatric condition. RCC shows disproportionately high rates of mental strain. According to Christie, research suggests that about three-fourths of the population report elevated levels of distress as evidenced by patients who scored ≥ 5 on the NCCN Distress Thermometer. Patients with cancer have an estimated 20% higher risk of suicide, especially during the first 12 months after diagnosis and at end of life, she added.

“Early during a diagnosis phase, where you’re having a lot of tests being done, you know something is happening. But you don’t know what,” Christie said. “It could be very serious. That’s just a lot of stress to hold and not know how to plan for.”

After diagnosis, routine could set in and lower distress, she said. Then terminal illness may spike it back up again. Does mental health treatment work in patients with cancer?

“There’s a really strong body of evidence-based treatments for depression, anxiety, adjustment disorders, and coping with different cancers,” Christie said. But it is a step too far to expect patients to ask for help while they are juggling appointments, tests, infusions, and more. “It’s a big ask, right? It’s setting people up for failure.”

To help, Christie said she is embedded with a medical oncology team and routinely talks with the staff about which patients may need help. “One thing I like to do is try to have brief visits with veterans and introduce myself when they come to clinic. I treat it like an opt-out rather than an opt-in program: I’ll just pop into the exam room. They don’t have to ask to see me.”

Christie focuses on open-ended questions and talks about resources ranging from support groups and brief appointments to extensive individual therapy. 

Another approach is a strategy known as the “warm handoff,” when an oncologist directly introduces a patient to a mental health professional. “It’s a transfer of care in front of the veteran: It’s much more time-efficient than putting in a referral.”

Christie explained how this can work. A clinician will ask her to meet with a patient during an appointment, perhaps in a couple minutes.

“Then I pop into the room, and the oncologist says, ‘Thanks for joining us. This is Mr. Jones. He has been experiencing feelings of anxiety and sadness, and we’d appreciate your help in exploring some options that might help.’  I turn to the patient and ask, ‘What more would you add?’ Then I either take Mr. Jones back to my office or stay in clinic, and we’re off to the races.”

Christie reported no disclosures.