Judy Carlson, EdD, MSN, APRN, BCN

Traumatic brain injury (TBI) is the signature injury of post-9/11 military operations, impacting > 441,000 combat veterans from 2001 to 2021 and 87% diagnosed with mild TBI (mTBI).^1,2 The most common cause of mTBI during these operations was blast exposures stemming from improvised explosive devices, rocket-propelled grenades, or land mines. mTBI was once thought to be self-limiting, lasting hours or days postinjury, but is now recognized as a complex focal and diffuse injury causing a cascade of molecular and biochemical responses with significant physiologic effects lasting for a longer duration. A significant number of combat veterans with mTBI (23%-48%) experience long-standing postconcussive symptoms (PCSs) for many years postinjury.^3-5

Developing and implementing strategies to reduce persistent symptoms associated with mTBI is of critical importance. Veterans diagnosed with mTBI and experiencing PCSs present ongoing treatment challenges to the health care system due to limited or suboptimal treatment options.^6,7 According to the 2021 US Department of Veterans Affairs (VA) and US Department of Defense (DoD) clinical guidelines for postacute mTBI, treatment for PCSs should be symptom focused. ^8,9 For instance, veterans with migraine headaches associated with mTBIs are often treated with abortive agents (eg, triptans) and preventive medications (eg, anticonvulsants and tricyclics).¹⁰ Cognitive dysfunction and insomnia are treated with cognitive rehabilitation programs, cognitive behaviorial therapy, occupational therapy, and medications (eg, hypnotics for insomnia).^11,12 The 2021 VA/DoD guidelines note that veteran and military focus groups described greater success with nonpharmacologic treatments than with pharmacologic treatments.⁸ The VA launched an enterprise-wide Whole Health Service program with the requirement that complementary and integrative health approaches must be available to veterans.¹³ As a nonpharmacologic, integrative, and noninvasive modality, neurofeedback (NFB) supports the VA Whole Health initiative and veterans’ preferences for integrative treatments.¹⁴

Neurofeedback

Rather than a symptom management approach, Defina et al described the possibilities of brain repair in TBI by treatments to enhance neuroplasticity, thereby establishing a more normalized or stable brain environment and enabling the brain to reorganize itself and function more normally.¹⁵ NFB has been shown to influence neuroplasticity,¹⁶ as evident in microstructural changes in white and gray matter¹⁷ and its ability to contribute to functional rehabilitation by restoring connectivity in specific areas of the brain that may have been impaired.¹⁸ The benefits of neuroenhancement strategies include potentially reduced pain for patients with mTBI and improved quality of life (QOL).¹⁹

NFB assists individuals by helping them become more aware of and self-regulate their physiology.^20,21 Because there are several types of NFB (eg, quantitative electroencephalography, Z-scored, α-θ) that differ in terms of equipment, mechanism of action, focus, and patient and clinician procedures, it is important to note that this study used a novel technologically advanced form of NFB, referred to as infra-low frequency (ILF) NFB. It works by reflecting a person’s brain wave activity via conventional electroencephalography back to the person through the visual cortex, thus providing relevant information to which the brain responds to improve core state regulation.²²

In 2006, ILF NFB developers sought to extend NFB capability into the slow cortical potential domain (< 0.1 Hz) and then gradually extended to lower frequencies on the basis of favorable clinical responses.^22,23 In 2017, the technology reached an ILF capacity that appeared to be helpful for several clinical issues. These developments depended on instrumentation capable of low noise signal detection down to the lowest frequency of interest. Instrumentation was developed for the purpose (eg, Bee Medic Cygnet NFB).

Although mTBI has been a clinical focus in NFB since the 1980s, there are few published studies demonstrating the efficacy of ILF NFB relating to the PCSs of interest in this study, and 2 suggested ILF NFB positively affected change in PCS severity.^24,25 Other studies found that ILF NFB decreased incidence of migraines and tension type headaches.^26,27 However, the findings of these studies had limited generalizability due to methodologic limitations, such as selection bias and small sample sizes.^24-27 Of importance to this article, there are also several publications on the efficacy of ILF NFB in clinical settings.^28-33

This article presents the second analysis of data from veterans who completed ILF NFB intervention and control group procedures during a 5-year randomized controlled trial (RCT). The RCT included veterans who experienced an mTBI while participating in post-9/11 military operations to evaluate the impact of ILF NFB on chronic PCSs, including headache, insomnia, and attention dysfunction. Initial results of this trial demonstrated significant differences between the intervention and control groups with strong effect sizes on all outcome measures at the end of treatment.³⁴

Methods

Participants included male and nonpregnant female veterans with a diagnosed mTBI during post-9/11 military operations; aged 18 to 65 years; reports of persistent (ie, > 3 months in duration) headaches, insomnia, and attention difficulties; and able to read and write English, comprehend what is read, and follow directions. mTBI diagnosis was verified for each veteran via the electronic health record. Patients were excluded if they had a severe TBI diagnosis or impaired decision-making capacity; were unable to comply with study visit schedule; or endorsed active suicidal intent on the Columbia-Suicide Severity Rating Scale.³⁵

Recruitment efforts included: (1) letters sent to eligible veterans with mTBI who were identified by clinical informatics data after waiver of Health Insurance Portability and Accountability Act was obtained; veterans could contact the research team directly or the research team would call the veteran 2 weeks after the letter was sent; (2) veterans could be referred by a clinician; and (3) veterans could self-refer based on flyers and other study marketing materials.

The study was conducted from 2019 to 2024 at Spark M. Matsunaga VA Medical Center, in Honolulu, Hawaii. Four private research spaces in compliance with human research standards were used for consent, treatment, and assessment.

Consenting Procedure and Randomization

The privacy rights of potential participants were observed, and interested veterans who met the eligibility criteria underwent an informed consent procedure and were administered the Columbia-Suicide Severity Rating Scale.³⁵ Those veterans not indicating active suicidal intent were randomized into the intervention or control group. Once randomized, the participant was enrolled and scheduled for baseline assessment.

All procedures of this study were performed in adherence with relevant laws and institutional guidelines. The study was reviewed and approved by the VA Pacific Islands Health Care System Institutional Review Board (#2019-06-JC/Promise 0003).

Outcome Measures

The outcome measures were administered at baseline, midpoint (3-7 weeks), end of treatment (6-12 weeks), and at a 2-month follow-up appointment with the research assistant or project coordinator.

The primary outcome measures include the Headache Impact Test (HIT-6), TBIQOL Headache Pain item short form, Insomnia Severity Index (ISI), Quality of Life in Neurological Disorders (Neuro-QOL) Sleep Disturbance short form, and attention measure: QIKtest Continuous Performance Test (QIKtest) (Table 1).^36-44

Secondary outcome measures included QOL After Brain Injury (QOLIBRI), Neuro- QOL Satisfaction With Roles/Activities short form (Neuro-QOL Satisfaction), Neuro-QOL Ability to Participate in Roles/Activities short form (Neuro-QOL Participate), Depression Anxiety Stress Scales (DASS-21), Patient Health Questionnaire-9 (PHQ-9), Posttraumatic Stress Disorder (PTSD) Checklist for DSM-5 (PCL-5), and the General Symptom Inventory (eAppendix 1).^39,42,45-52

Sample

Seventy-two participants (36 in each group) were needed to have adequate statistical power for the analysis. Presuming attrition, the goal was to recruit 100 veterans. Literature on NFB studies of patients with mTBI have reported dropout rates ranging from 10% to 30%.^53,54 Assuming a dropout rate of 28% and a moderate autocorrelation of 0.6 among repeated measures, this sample size ensured the detection of an average difference of at least 0.49 SDs with a power of 80% in the NFB intervention group compared with the control group using a 2-tailed significance level of 0.05.

Control Group

Following baseline assessment, control group participants received 8 phone calls (1 call/wk) from 1 of 4 clinical investigators over 8 to 10 weeks. During each 15-minute call, 1 of the following health topics was discussed: sleep hygiene, basic nutritional concepts, beverage choices, positive thinking, thought reframing, fitness, daily calming activity, and enhancement of focus strategies. A script for each topic was used to guide each call.

Intervention Group

Following baseline assessment, intervention group participants completed 20 half-hour ILF NFB sessions, typically receiving 3 sessions per week over an 8- to 10-week period. ILF NFB treatments were administered by 1 of 4 licensed health care employees who had received substantial ILF NFB training and achieved a skill reliability index score of 0.95, ensuring the skill level of the ILF NFB providers was equal. A script was used by the ILF NFB providers during the ILF NFB sessions to keep the interaction approach consistent with all participants.

All procedures were explained in advance to participants and voluntary participation affirmed. At the first session, participants filled out a clinical symptom checklist of 5 symptoms (eAppendix 1).^39,42,45-49 The initial rating on the symptom checklist was reflective of their experience over the past month, while in each subsequent session, participants indicated their experience of those symptoms that day. ILF NFB providers were never privy to participants’ primary or secondary outcome measures data during the study, so these recurring clinical symptom checklist ratings, as well as other feedback provided by participants on their experience within and between sessions, were the clinical data used to make decisions about ILF NFB treatment protocol.

The Othmer Optimal Response Frequency (ORF) protocol was used for participants in this study.⁵⁵ Through an iterative process, ORF protocol establishes the specific frequency point along the 0.000001 mHz to 0.1 Hz continuum, which is optimal to diminish symptoms experienced in real-time during the session (eg, tension or pain in shoulders; racing thoughts).

During each ILF NFB session, participants were seated comfortably and encouraged to look at the feedback screen. The moving images on the game screen provided almost instantaneous feedback (within 500 ms) to participants about their brain functioning, as ascertained by electrodes placed on the scalp as dictated by study protocol.⁵⁶ A standardized protocol for site placement was used beginning with T3-T4, followed by the weekly addition of a site as tolerated in the following sequence: T4-P4, FP2-T4, and FP1-T4. More information about the ILF NFB procedures are outlined in the report of the pilot study and RCT initial results.^22,34

Statistical Analysis

Eighty-seven participants were randomized, with 43 assigned to the intervention group and 44 to the control group to achieve the enrollment goal of ≥ 36 participants in each group. This report is the second analysis of data from this RCT that employed a per-protocol approach, analyzing a subset of participants who fully adhered to the study protocol and completed all study procedures. Outcome scores at baseline, midpoint, end of treatment, and 2-month follow-up were summarized as means with corresponding 95% CIs. Group comparisons at the end of treatment and 2-month follow-up time points were conducted using 2-sample t tests. All statistical tests were 2-sided with a significance level of .05 (Type I error rate). SAS software version 9.4 Maintenance 8 was used for statistical analysis. Cohen d analyses were used for effect sizes.

Results

Seventy-four participants fully adhered to the study protocol and were included in the present analyses, with 38 in the control group and 36 in the intervention group. eAppendix 2 depicts the flow of participants through this study. There were no adverse events related to treatment, and the 13 participants who withdrew typically reported difficulty with scheduling or transportation as the primary reason. This study also took place during the COVID-19 pandemic, which likely had some impact on enrollment; participants were differentially impacted by changes in employment and moves to the continental United States.

Participants were aged 30 to 60 years (mean [SD], 45.4 [8.0]). Most participants (90.5%) were male, and multiracial and White were the most common racial identities (Table 2). Participant characteristics were largely balanced across randomized groups. Similarly, test scores on the primary variables of interest in this study and secondary clinical variables assessed were comparable across participants (Table 3).

Primary Variables of Interest Analyses

This study’s hypothesis was that those who completed ILF NFB treatment per protocol would demonstrate statistically significant improvement in symptoms related to headaches, sleep disturbance, and difficulty with attention when compared with veterans in the control group. This hypothesis was partially supported. A 2-sample t test showed that veterans in the intervention group demonstrated significant improvement in headache symptoms compared with veterans in the control group on the HIT-6 at the end-of-treatment (P < .001, d = 1.53) and 2-month follow-up assessment (P < .001, d = 1.14). This pattern also was consistent with the TBI-QOL Headache Pain item short form, with veterans in the intervention group showing improvement beyond those in the control group at the end-of-treatment (P < .001, d = 0.89) and 2-month follow-up assessment (P < .001, d = 0.83). Two-sample t tests also demonstrated significant improvement in subjective reports of sleep; those in the intervention group had significantly lower scores on the ISI at the end-of-study (P < .001, d = 1.53) and 2-month follow-up assessment (P < .001, d = 0.97). This pattern also held true for the Neuro-QOL Sleep Disturbance short form subtest, which demonstrated significantly more improvement in the intervention group compared with the control group at the end-of-study (P < .001, d = 0.97) and 2-month follow- up assessment (P < .001, d = 0.92). improvement in attention was not supported by the present results. A 2-sample t test found no significant difference between performance on the QIKtest for veterans in the intervention group vs the control group at the end-of-study (P = .40, d = 0.19) or the 2-month follow-up (P = .43, d = 0.20) (eAppendix 3).

Secondary Variables of Interest Analysis

Secondary variables examined differences in QOL, PTSD, depressive symptoms, and general symptoms reported between veterans in the intervention and control groups. Results demonstrated that veterans in the intervention group showed improvement above and beyond those in the control group on all measures. In regard to QOL, veterans in the intervention group had significantly higher scores on the Neuro-QOL Participate subtest than those in the control group at the end-of-study (P = .01, d = 0.89) and 2-month follow-up assessment (P < .001, d = 0.62). A similar pattern was found for the Neuro-QOL Satisfaction subtest, with veterans in the intervention group showing significantly higher scores than those in the control group at the end-of-study (P = .001, d = 0.95) and 2-month follow-up assessment (P < .001, d = 0.62). This also held true on the QOLIBRI, with veterans in the intervention group demonstrating significantly higher scores than those in the control group at the end-of-study (P = .001, d = 0.92) and 2-month follow-up assessment (P < .001, d = 0.66).

Veterans in the intervention group had significantly lower scores on the PCL-5 than those in the control group at the end-of- study (P = .003, d = 0.78) and 2-month follow-up assessment (P = .001, d = 0.72). Veterans in the intervention group also had significantly lower scores on the PHQ-9 than those in the control group at the end-of-study (P < .001, d = 0.98) and 2-month follow-up assessment (P < .001, d = 0.83). Veterans in the intervention group had significantly lower scores on the DASS- 21 than those in the control group at the end-of-study (P = .002, d = 0.80) and 2-month follow-up assessment (P = .001, d = 0.77). They also had significantly lower scores on the General Symptom Inventory than those in the control group at the end-of-study (P = .02, d = 0.75) and 2-month follow-up assessment (P = .002, d = 0.57). A clinically significant shift of score occurred for each of the measures except DASS-21 (eAppendix 3). eAppendix 4 depicts the change in scores for the intervention group at the end of treatment and the clinically significant shift score of each measure.

Discussion

The results of this RCT revealed a promising impact of ILF NFB on the commonly experienced persistent PCSs of headaches and disrupted sleep. Veterans in the intervention group demonstrated statistically significant improvement in headache symptoms compared with veterans in the control group when assessed at the end of treatment and during a 2-month follow-up. The statistical significance of these improvements was also supported by large or very large effect sizes. In addition to these primary variables of interest, veterans in the intervention group notably demonstrated significant improvement compared with those in the control group in a number of secondary clinical measures, including QOL, traumatic stress-related symptoms, depressive symptoms, and general symptom report. The clinical impact was further supported by the clinically relevant shift in scores in the intervention group.

The data did not support the hypothesis that attention concerns would show significant improvement following ILF NFB. Performance on an attention measure did not differ significantly between groups at either the end-of-treatment or 2-month follow up assessment. The QIKtest, a continuous performance test used to measure attention, was a go/no-go task and calculated based on a combination of various types of errors and outlier responses. The stimulus for this task is a series of computerized, blinking lights, for which participants are tasked with discriminating targets and nontargets under time pressure. However, the order of the stimuli are consistent across administrations, rather than being randomized, introducing a potential confound of practice effects on this task since patients were administered the QIKtest 3 times in a 2-month period and again 2 months later. Veterans in the control group notably improved in their average performance of this task from baseline to the endpoint of their treatment participation and demonstrated further improvement at the 2-month follow-up assessment; this pattern would be consistent with potential practice effects and warrants caution in its interpretation for both groups.

Previously published ILF NFB clinical studies that used the QIKtest and found positive results were mostly conducted among children and teen populations across longer treatment periods. This research may indicate the QIKtest is not an appropriate measure to assess adults who have specialized training in responding to stimuli (ie, trained military personnel). This suggests the concept of attention dysfunction experienced by veterans and the best method to measure it may need to be explored further. This construct may not be related to the focus and skill in prolonged attention needed in selecting go/ no-go tasks, but rather related to a broader conceptual basis involving memory, recall, clarity of rational thought, and decision making impacted by the mTBI. For instance, a study among combat veterans with mTBI and PTSD found that performance on objective cognitive measures did not significantly correlate with their subjective reports of cognitive difficulties.⁵⁷ This reflects the pattern of the present study, in which subjective reports of attention improved over time on the clinical symptom checklist filled out by participants at each session, but the objective measure did not. The mean attention dysfunction score was 6 at session 1 and 1 to 2 at session 20 (lower scores are better on a 10-point scale).

Strengths and Limitations

This study presents results stemming from the first RCT examining clinical effectiveness of ILF NFB in a VA setting for veterans with diagnoses of mTBI. The study design shows promising external validity. Veterans were able to participate in a treatment consisting of 20 sessions over a period of typically 8 to 10 weeks, entailing 2 to 3 sessions per week, with an attrition of only 18% over the course of the study. Notably, attrition rates may have been impacted by the time course of the study, which was recruiting and running participants throughout the COVID-19 pandemic (March 2020 to May 2023). No attrition was due to the intervention itself, and no adverse reactions to ILF NFB were reported during the course of the study. Other strengths of the study include the ethnically and racially diverse participants, representative of the population of veterans in Hawaii. Additionally, all ILF NFB providers underwent supervised ILF NFB training and achieved a skill reliability index score of 0.95 prior to providing ILF NFB to the intervention group.

This study was not blinded. Neither veterans nor ILF NFB providers were blinded and were therefore aware of the randomly assigned groups. Research assistants administering the periodic assessments were meant to be blinded to condition by design; however, as the study progressed, a research assistant became unintentionally aware of each study participant's condition based on required documentation in the veteran’s health records; more notes were present for those in the intervention group (20 specialist notes) than the control group (8 notes). While the presence of a control group represents a strength relative to much of the existing ILF NFB literature, the control group in this case did not account for the total time spent with the researchers. Participants in the intervention group met with researchers for 20 total sessions as opposed to 8 telephone calls. Therefore, the study design cannot fully rule out the differential impact of demand characteristics between the 2 groups, nor can it fully address or rule out the impact of differential motivation and expectations between groups. There is also evidence that technological innovation can influence the expectations of research participants, meaning that the intervention group may have been unduly influenced by the novelty of the ILF NFB technology, to which the control group did not have exposure.⁵⁸

A second attention measure for this study would have been beneficial, perhaps in identifying true change in attention ability or providing more insight into finding better methods to assess attention among veterans with mTBI. ILF NFB demonstrated significant impact across multiple outcome measures of clinical relevance for veterans diagnosed with mTBI, including the primary outcome variables of headache and sleep. The strength of the improvements seen in these areas, supported by large practical effects as well as veterans’ subjective reports, indicates much promise. Follow-up studies may also focus on the potential effectiveness of ILF NFB as a treatment of the secondary concerns measured in this study, including traumatic stress-related and depressive symptoms, and may explore the added benefit, if any, of ILF NFB alongside other evidence-based treatments for traumatic stress-related and mood disorders (eg, cognitive behavioral therapy). Using functional magnetic resonance imaging before and after assessments to determine actual brain enhancement with ILF NFB for certain disorders in which a brain signature exists (ie, migraine) should be explored. Further examination of ILF NFB as an intervention for attention may also be warranted, using more effective measures of attention in the population of veterans with mTBI, given the concerns noted earlier. Future research on this topic will need to clearly define attention in relation to the veteran experience and use relevant measures.

Conclusions

This study supports ILF NFB as a safe, noninvasive, nonpharmacologic treatment that may be effective in addressing the complex clinical concerns of veterans diagnosed with mTBI, a population for whom effective treatments have been difficult to identify. This intervention can provide veterans with a desirable and effective nonpharmacologic alternative in their care.

Traumatic brain injury (TBI) is the signature injury of post-9/11 military operations, impacting > 441,000 combat veterans from 2001 to 2021 and 87% diagnosed with mild TBI (mTBI).^1,2 The most common cause of mTBI during these operations was blast exposures stemming from improvised explosive devices, rocket-propelled grenades, or land mines. mTBI was once thought to be self-limiting, lasting hours or days postinjury, but is now recognized as a complex focal and diffuse injury causing a cascade of molecular and biochemical responses with significant physiologic effects lasting for a longer duration. A significant number of combat veterans with mTBI (23%-48%) experience long-standing postconcussive symptoms (PCSs) for many years postinjury.^3-5

Developing and implementing strategies to reduce persistent symptoms associated with mTBI is of critical importance. Veterans diagnosed with mTBI and experiencing PCSs present ongoing treatment challenges to the health care system due to limited or suboptimal treatment options.^6,7 According to the 2021 US Department of Veterans Affairs (VA) and US Department of Defense (DoD) clinical guidelines for postacute mTBI, treatment for PCSs should be symptom focused. ^8,9 For instance, veterans with migraine headaches associated with mTBIs are often treated with abortive agents (eg, triptans) and preventive medications (eg, anticonvulsants and tricyclics).¹⁰ Cognitive dysfunction and insomnia are treated with cognitive rehabilitation programs, cognitive behaviorial therapy, occupational therapy, and medications (eg, hypnotics for insomnia).^11,12 The 2021 VA/DoD guidelines note that veteran and military focus groups described greater success with nonpharmacologic treatments than with pharmacologic treatments.⁸ The VA launched an enterprise-wide Whole Health Service program with the requirement that complementary and integrative health approaches must be available to veterans.¹³ As a nonpharmacologic, integrative, and noninvasive modality, neurofeedback (NFB) supports the VA Whole Health initiative and veterans’ preferences for integrative treatments.¹⁴

Neurofeedback

Rather than a symptom management approach, Defina et al described the possibilities of brain repair in TBI by treatments to enhance neuroplasticity, thereby establishing a more normalized or stable brain environment and enabling the brain to reorganize itself and function more normally.¹⁵ NFB has been shown to influence neuroplasticity,¹⁶ as evident in microstructural changes in white and gray matter¹⁷ and its ability to contribute to functional rehabilitation by restoring connectivity in specific areas of the brain that may have been impaired.¹⁸ The benefits of neuroenhancement strategies include potentially reduced pain for patients with mTBI and improved quality of life (QOL).¹⁹

NFB assists individuals by helping them become more aware of and self-regulate their physiology.^20,21 Because there are several types of NFB (eg, quantitative electroencephalography, Z-scored, α-θ) that differ in terms of equipment, mechanism of action, focus, and patient and clinician procedures, it is important to note that this study used a novel technologically advanced form of NFB, referred to as infra-low frequency (ILF) NFB. It works by reflecting a person’s brain wave activity via conventional electroencephalography back to the person through the visual cortex, thus providing relevant information to which the brain responds to improve core state regulation.²²

In 2006, ILF NFB developers sought to extend NFB capability into the slow cortical potential domain (< 0.1 Hz) and then gradually extended to lower frequencies on the basis of favorable clinical responses.^22,23 In 2017, the technology reached an ILF capacity that appeared to be helpful for several clinical issues. These developments depended on instrumentation capable of low noise signal detection down to the lowest frequency of interest. Instrumentation was developed for the purpose (eg, Bee Medic Cygnet NFB).

Although mTBI has been a clinical focus in NFB since the 1980s, there are few published studies demonstrating the efficacy of ILF NFB relating to the PCSs of interest in this study, and 2 suggested ILF NFB positively affected change in PCS severity.^24,25 Other studies found that ILF NFB decreased incidence of migraines and tension type headaches.^26,27 However, the findings of these studies had limited generalizability due to methodologic limitations, such as selection bias and small sample sizes.^24-27 Of importance to this article, there are also several publications on the efficacy of ILF NFB in clinical settings.^28-33

This article presents the second analysis of data from veterans who completed ILF NFB intervention and control group procedures during a 5-year randomized controlled trial (RCT). The RCT included veterans who experienced an mTBI while participating in post-9/11 military operations to evaluate the impact of ILF NFB on chronic PCSs, including headache, insomnia, and attention dysfunction. Initial results of this trial demonstrated significant differences between the intervention and control groups with strong effect sizes on all outcome measures at the end of treatment.³⁴

Methods

Participants included male and nonpregnant female veterans with a diagnosed mTBI during post-9/11 military operations; aged 18 to 65 years; reports of persistent (ie, > 3 months in duration) headaches, insomnia, and attention difficulties; and able to read and write English, comprehend what is read, and follow directions. mTBI diagnosis was verified for each veteran via the electronic health record. Patients were excluded if they had a severe TBI diagnosis or impaired decision-making capacity; were unable to comply with study visit schedule; or endorsed active suicidal intent on the Columbia-Suicide Severity Rating Scale.³⁵

Recruitment efforts included: (1) letters sent to eligible veterans with mTBI who were identified by clinical informatics data after waiver of Health Insurance Portability and Accountability Act was obtained; veterans could contact the research team directly or the research team would call the veteran 2 weeks after the letter was sent; (2) veterans could be referred by a clinician; and (3) veterans could self-refer based on flyers and other study marketing materials.

The study was conducted from 2019 to 2024 at Spark M. Matsunaga VA Medical Center, in Honolulu, Hawaii. Four private research spaces in compliance with human research standards were used for consent, treatment, and assessment.

Consenting Procedure and Randomization

The privacy rights of potential participants were observed, and interested veterans who met the eligibility criteria underwent an informed consent procedure and were administered the Columbia-Suicide Severity Rating Scale.³⁵ Those veterans not indicating active suicidal intent were randomized into the intervention or control group. Once randomized, the participant was enrolled and scheduled for baseline assessment.

All procedures of this study were performed in adherence with relevant laws and institutional guidelines. The study was reviewed and approved by the VA Pacific Islands Health Care System Institutional Review Board (#2019-06-JC/Promise 0003).

Outcome Measures

The outcome measures were administered at baseline, midpoint (3-7 weeks), end of treatment (6-12 weeks), and at a 2-month follow-up appointment with the research assistant or project coordinator.

The primary outcome measures include the Headache Impact Test (HIT-6), TBIQOL Headache Pain item short form, Insomnia Severity Index (ISI), Quality of Life in Neurological Disorders (Neuro-QOL) Sleep Disturbance short form, and attention measure: QIKtest Continuous Performance Test (QIKtest) (Table 1).^36-44

Secondary outcome measures included QOL After Brain Injury (QOLIBRI), Neuro- QOL Satisfaction With Roles/Activities short form (Neuro-QOL Satisfaction), Neuro-QOL Ability to Participate in Roles/Activities short form (Neuro-QOL Participate), Depression Anxiety Stress Scales (DASS-21), Patient Health Questionnaire-9 (PHQ-9), Posttraumatic Stress Disorder (PTSD) Checklist for DSM-5 (PCL-5), and the General Symptom Inventory (eAppendix 1).^39,42,45-52

Sample

Seventy-two participants (36 in each group) were needed to have adequate statistical power for the analysis. Presuming attrition, the goal was to recruit 100 veterans. Literature on NFB studies of patients with mTBI have reported dropout rates ranging from 10% to 30%.^53,54 Assuming a dropout rate of 28% and a moderate autocorrelation of 0.6 among repeated measures, this sample size ensured the detection of an average difference of at least 0.49 SDs with a power of 80% in the NFB intervention group compared with the control group using a 2-tailed significance level of 0.05.

Control Group

Following baseline assessment, control group participants received 8 phone calls (1 call/wk) from 1 of 4 clinical investigators over 8 to 10 weeks. During each 15-minute call, 1 of the following health topics was discussed: sleep hygiene, basic nutritional concepts, beverage choices, positive thinking, thought reframing, fitness, daily calming activity, and enhancement of focus strategies. A script for each topic was used to guide each call.

Intervention Group

Following baseline assessment, intervention group participants completed 20 half-hour ILF NFB sessions, typically receiving 3 sessions per week over an 8- to 10-week period. ILF NFB treatments were administered by 1 of 4 licensed health care employees who had received substantial ILF NFB training and achieved a skill reliability index score of 0.95, ensuring the skill level of the ILF NFB providers was equal. A script was used by the ILF NFB providers during the ILF NFB sessions to keep the interaction approach consistent with all participants.

All procedures were explained in advance to participants and voluntary participation affirmed. At the first session, participants filled out a clinical symptom checklist of 5 symptoms (eAppendix 1).^39,42,45-49 The initial rating on the symptom checklist was reflective of their experience over the past month, while in each subsequent session, participants indicated their experience of those symptoms that day. ILF NFB providers were never privy to participants’ primary or secondary outcome measures data during the study, so these recurring clinical symptom checklist ratings, as well as other feedback provided by participants on their experience within and between sessions, were the clinical data used to make decisions about ILF NFB treatment protocol.

The Othmer Optimal Response Frequency (ORF) protocol was used for participants in this study.⁵⁵ Through an iterative process, ORF protocol establishes the specific frequency point along the 0.000001 mHz to 0.1 Hz continuum, which is optimal to diminish symptoms experienced in real-time during the session (eg, tension or pain in shoulders; racing thoughts).

During each ILF NFB session, participants were seated comfortably and encouraged to look at the feedback screen. The moving images on the game screen provided almost instantaneous feedback (within 500 ms) to participants about their brain functioning, as ascertained by electrodes placed on the scalp as dictated by study protocol.⁵⁶ A standardized protocol for site placement was used beginning with T3-T4, followed by the weekly addition of a site as tolerated in the following sequence: T4-P4, FP2-T4, and FP1-T4. More information about the ILF NFB procedures are outlined in the report of the pilot study and RCT initial results.^22,34

Statistical Analysis

Eighty-seven participants were randomized, with 43 assigned to the intervention group and 44 to the control group to achieve the enrollment goal of ≥ 36 participants in each group. This report is the second analysis of data from this RCT that employed a per-protocol approach, analyzing a subset of participants who fully adhered to the study protocol and completed all study procedures. Outcome scores at baseline, midpoint, end of treatment, and 2-month follow-up were summarized as means with corresponding 95% CIs. Group comparisons at the end of treatment and 2-month follow-up time points were conducted using 2-sample t tests. All statistical tests were 2-sided with a significance level of .05 (Type I error rate). SAS software version 9.4 Maintenance 8 was used for statistical analysis. Cohen d analyses were used for effect sizes.

Results

Seventy-four participants fully adhered to the study protocol and were included in the present analyses, with 38 in the control group and 36 in the intervention group. eAppendix 2 depicts the flow of participants through this study. There were no adverse events related to treatment, and the 13 participants who withdrew typically reported difficulty with scheduling or transportation as the primary reason. This study also took place during the COVID-19 pandemic, which likely had some impact on enrollment; participants were differentially impacted by changes in employment and moves to the continental United States.

Participants were aged 30 to 60 years (mean [SD], 45.4 [8.0]). Most participants (90.5%) were male, and multiracial and White were the most common racial identities (Table 2). Participant characteristics were largely balanced across randomized groups. Similarly, test scores on the primary variables of interest in this study and secondary clinical variables assessed were comparable across participants (Table 3).

Primary Variables of Interest Analyses

This study’s hypothesis was that those who completed ILF NFB treatment per protocol would demonstrate statistically significant improvement in symptoms related to headaches, sleep disturbance, and difficulty with attention when compared with veterans in the control group. This hypothesis was partially supported. A 2-sample t test showed that veterans in the intervention group demonstrated significant improvement in headache symptoms compared with veterans in the control group on the HIT-6 at the end-of-treatment (P < .001, d = 1.53) and 2-month follow-up assessment (P < .001, d = 1.14). This pattern also was consistent with the TBI-QOL Headache Pain item short form, with veterans in the intervention group showing improvement beyond those in the control group at the end-of-treatment (P < .001, d = 0.89) and 2-month follow-up assessment (P < .001, d = 0.83). Two-sample t tests also demonstrated significant improvement in subjective reports of sleep; those in the intervention group had significantly lower scores on the ISI at the end-of-study (P < .001, d = 1.53) and 2-month follow-up assessment (P < .001, d = 0.97). This pattern also held true for the Neuro-QOL Sleep Disturbance short form subtest, which demonstrated significantly more improvement in the intervention group compared with the control group at the end-of-study (P < .001, d = 0.97) and 2-month follow- up assessment (P < .001, d = 0.92). improvement in attention was not supported by the present results. A 2-sample t test found no significant difference between performance on the QIKtest for veterans in the intervention group vs the control group at the end-of-study (P = .40, d = 0.19) or the 2-month follow-up (P = .43, d = 0.20) (eAppendix 3).

Secondary Variables of Interest Analysis

Secondary variables examined differences in QOL, PTSD, depressive symptoms, and general symptoms reported between veterans in the intervention and control groups. Results demonstrated that veterans in the intervention group showed improvement above and beyond those in the control group on all measures. In regard to QOL, veterans in the intervention group had significantly higher scores on the Neuro-QOL Participate subtest than those in the control group at the end-of-study (P = .01, d = 0.89) and 2-month follow-up assessment (P < .001, d = 0.62). A similar pattern was found for the Neuro-QOL Satisfaction subtest, with veterans in the intervention group showing significantly higher scores than those in the control group at the end-of-study (P = .001, d = 0.95) and 2-month follow-up assessment (P < .001, d = 0.62). This also held true on the QOLIBRI, with veterans in the intervention group demonstrating significantly higher scores than those in the control group at the end-of-study (P = .001, d = 0.92) and 2-month follow-up assessment (P < .001, d = 0.66).

Veterans in the intervention group had significantly lower scores on the PCL-5 than those in the control group at the end-of- study (P = .003, d = 0.78) and 2-month follow-up assessment (P = .001, d = 0.72). Veterans in the intervention group also had significantly lower scores on the PHQ-9 than those in the control group at the end-of-study (P < .001, d = 0.98) and 2-month follow-up assessment (P < .001, d = 0.83). Veterans in the intervention group had significantly lower scores on the DASS- 21 than those in the control group at the end-of-study (P = .002, d = 0.80) and 2-month follow-up assessment (P = .001, d = 0.77). They also had significantly lower scores on the General Symptom Inventory than those in the control group at the end-of-study (P = .02, d = 0.75) and 2-month follow-up assessment (P = .002, d = 0.57). A clinically significant shift of score occurred for each of the measures except DASS-21 (eAppendix 3). eAppendix 4 depicts the change in scores for the intervention group at the end of treatment and the clinically significant shift score of each measure.

Discussion

The results of this RCT revealed a promising impact of ILF NFB on the commonly experienced persistent PCSs of headaches and disrupted sleep. Veterans in the intervention group demonstrated statistically significant improvement in headache symptoms compared with veterans in the control group when assessed at the end of treatment and during a 2-month follow-up. The statistical significance of these improvements was also supported by large or very large effect sizes. In addition to these primary variables of interest, veterans in the intervention group notably demonstrated significant improvement compared with those in the control group in a number of secondary clinical measures, including QOL, traumatic stress-related symptoms, depressive symptoms, and general symptom report. The clinical impact was further supported by the clinically relevant shift in scores in the intervention group.

The data did not support the hypothesis that attention concerns would show significant improvement following ILF NFB. Performance on an attention measure did not differ significantly between groups at either the end-of-treatment or 2-month follow up assessment. The QIKtest, a continuous performance test used to measure attention, was a go/no-go task and calculated based on a combination of various types of errors and outlier responses. The stimulus for this task is a series of computerized, blinking lights, for which participants are tasked with discriminating targets and nontargets under time pressure. However, the order of the stimuli are consistent across administrations, rather than being randomized, introducing a potential confound of practice effects on this task since patients were administered the QIKtest 3 times in a 2-month period and again 2 months later. Veterans in the control group notably improved in their average performance of this task from baseline to the endpoint of their treatment participation and demonstrated further improvement at the 2-month follow-up assessment; this pattern would be consistent with potential practice effects and warrants caution in its interpretation for both groups.

Previously published ILF NFB clinical studies that used the QIKtest and found positive results were mostly conducted among children and teen populations across longer treatment periods. This research may indicate the QIKtest is not an appropriate measure to assess adults who have specialized training in responding to stimuli (ie, trained military personnel). This suggests the concept of attention dysfunction experienced by veterans and the best method to measure it may need to be explored further. This construct may not be related to the focus and skill in prolonged attention needed in selecting go/ no-go tasks, but rather related to a broader conceptual basis involving memory, recall, clarity of rational thought, and decision making impacted by the mTBI. For instance, a study among combat veterans with mTBI and PTSD found that performance on objective cognitive measures did not significantly correlate with their subjective reports of cognitive difficulties.⁵⁷ This reflects the pattern of the present study, in which subjective reports of attention improved over time on the clinical symptom checklist filled out by participants at each session, but the objective measure did not. The mean attention dysfunction score was 6 at session 1 and 1 to 2 at session 20 (lower scores are better on a 10-point scale).

Strengths and Limitations

This study presents results stemming from the first RCT examining clinical effectiveness of ILF NFB in a VA setting for veterans with diagnoses of mTBI. The study design shows promising external validity. Veterans were able to participate in a treatment consisting of 20 sessions over a period of typically 8 to 10 weeks, entailing 2 to 3 sessions per week, with an attrition of only 18% over the course of the study. Notably, attrition rates may have been impacted by the time course of the study, which was recruiting and running participants throughout the COVID-19 pandemic (March 2020 to May 2023). No attrition was due to the intervention itself, and no adverse reactions to ILF NFB were reported during the course of the study. Other strengths of the study include the ethnically and racially diverse participants, representative of the population of veterans in Hawaii. Additionally, all ILF NFB providers underwent supervised ILF NFB training and achieved a skill reliability index score of 0.95 prior to providing ILF NFB to the intervention group.

This study was not blinded. Neither veterans nor ILF NFB providers were blinded and were therefore aware of the randomly assigned groups. Research assistants administering the periodic assessments were meant to be blinded to condition by design; however, as the study progressed, a research assistant became unintentionally aware of each study participant's condition based on required documentation in the veteran’s health records; more notes were present for those in the intervention group (20 specialist notes) than the control group (8 notes). While the presence of a control group represents a strength relative to much of the existing ILF NFB literature, the control group in this case did not account for the total time spent with the researchers. Participants in the intervention group met with researchers for 20 total sessions as opposed to 8 telephone calls. Therefore, the study design cannot fully rule out the differential impact of demand characteristics between the 2 groups, nor can it fully address or rule out the impact of differential motivation and expectations between groups. There is also evidence that technological innovation can influence the expectations of research participants, meaning that the intervention group may have been unduly influenced by the novelty of the ILF NFB technology, to which the control group did not have exposure.⁵⁸

A second attention measure for this study would have been beneficial, perhaps in identifying true change in attention ability or providing more insight into finding better methods to assess attention among veterans with mTBI. ILF NFB demonstrated significant impact across multiple outcome measures of clinical relevance for veterans diagnosed with mTBI, including the primary outcome variables of headache and sleep. The strength of the improvements seen in these areas, supported by large practical effects as well as veterans’ subjective reports, indicates much promise. Follow-up studies may also focus on the potential effectiveness of ILF NFB as a treatment of the secondary concerns measured in this study, including traumatic stress-related and depressive symptoms, and may explore the added benefit, if any, of ILF NFB alongside other evidence-based treatments for traumatic stress-related and mood disorders (eg, cognitive behavioral therapy). Using functional magnetic resonance imaging before and after assessments to determine actual brain enhancement with ILF NFB for certain disorders in which a brain signature exists (ie, migraine) should be explored. Further examination of ILF NFB as an intervention for attention may also be warranted, using more effective measures of attention in the population of veterans with mTBI, given the concerns noted earlier. Future research on this topic will need to clearly define attention in relation to the veteran experience and use relevant measures.

Conclusions

This study supports ILF NFB as a safe, noninvasive, nonpharmacologic treatment that may be effective in addressing the complex clinical concerns of veterans diagnosed with mTBI, a population for whom effective treatments have been difficult to identify. This intervention can provide veterans with a desirable and effective nonpharmacologic alternative in their care.

Traumatic brain injury (TBI) is the signature injury of post-9/11 military operations, impacting > 441,000 combat veterans from 2001 to 2021 and 87% diagnosed with mild TBI (mTBI).^1,2 The most common cause of mTBI during these operations was blast exposures stemming from improvised explosive devices, rocket-propelled grenades, or land mines. mTBI was once thought to be self-limiting, lasting hours or days postinjury, but is now recognized as a complex focal and diffuse injury causing a cascade of molecular and biochemical responses with significant physiologic effects lasting for a longer duration. A significant number of combat veterans with mTBI (23%-48%) experience long-standing postconcussive symptoms (PCSs) for many years postinjury.^3-5

Developing and implementing strategies to reduce persistent symptoms associated with mTBI is of critical importance. Veterans diagnosed with mTBI and experiencing PCSs present ongoing treatment challenges to the health care system due to limited or suboptimal treatment options.^6,7 According to the 2021 US Department of Veterans Affairs (VA) and US Department of Defense (DoD) clinical guidelines for postacute mTBI, treatment for PCSs should be symptom focused. ^8,9 For instance, veterans with migraine headaches associated with mTBIs are often treated with abortive agents (eg, triptans) and preventive medications (eg, anticonvulsants and tricyclics).¹⁰ Cognitive dysfunction and insomnia are treated with cognitive rehabilitation programs, cognitive behaviorial therapy, occupational therapy, and medications (eg, hypnotics for insomnia).^11,12 The 2021 VA/DoD guidelines note that veteran and military focus groups described greater success with nonpharmacologic treatments than with pharmacologic treatments.⁸ The VA launched an enterprise-wide Whole Health Service program with the requirement that complementary and integrative health approaches must be available to veterans.¹³ As a nonpharmacologic, integrative, and noninvasive modality, neurofeedback (NFB) supports the VA Whole Health initiative and veterans’ preferences for integrative treatments.¹⁴

Neurofeedback

Rather than a symptom management approach, Defina et al described the possibilities of brain repair in TBI by treatments to enhance neuroplasticity, thereby establishing a more normalized or stable brain environment and enabling the brain to reorganize itself and function more normally.¹⁵ NFB has been shown to influence neuroplasticity,¹⁶ as evident in microstructural changes in white and gray matter¹⁷ and its ability to contribute to functional rehabilitation by restoring connectivity in specific areas of the brain that may have been impaired.¹⁸ The benefits of neuroenhancement strategies include potentially reduced pain for patients with mTBI and improved quality of life (QOL).¹⁹

NFB assists individuals by helping them become more aware of and self-regulate their physiology.^20,21 Because there are several types of NFB (eg, quantitative electroencephalography, Z-scored, α-θ) that differ in terms of equipment, mechanism of action, focus, and patient and clinician procedures, it is important to note that this study used a novel technologically advanced form of NFB, referred to as infra-low frequency (ILF) NFB. It works by reflecting a person’s brain wave activity via conventional electroencephalography back to the person through the visual cortex, thus providing relevant information to which the brain responds to improve core state regulation.²²

In 2006, ILF NFB developers sought to extend NFB capability into the slow cortical potential domain (< 0.1 Hz) and then gradually extended to lower frequencies on the basis of favorable clinical responses.^22,23 In 2017, the technology reached an ILF capacity that appeared to be helpful for several clinical issues. These developments depended on instrumentation capable of low noise signal detection down to the lowest frequency of interest. Instrumentation was developed for the purpose (eg, Bee Medic Cygnet NFB).

Although mTBI has been a clinical focus in NFB since the 1980s, there are few published studies demonstrating the efficacy of ILF NFB relating to the PCSs of interest in this study, and 2 suggested ILF NFB positively affected change in PCS severity.^24,25 Other studies found that ILF NFB decreased incidence of migraines and tension type headaches.^26,27 However, the findings of these studies had limited generalizability due to methodologic limitations, such as selection bias and small sample sizes.^24-27 Of importance to this article, there are also several publications on the efficacy of ILF NFB in clinical settings.^28-33

This article presents the second analysis of data from veterans who completed ILF NFB intervention and control group procedures during a 5-year randomized controlled trial (RCT). The RCT included veterans who experienced an mTBI while participating in post-9/11 military operations to evaluate the impact of ILF NFB on chronic PCSs, including headache, insomnia, and attention dysfunction. Initial results of this trial demonstrated significant differences between the intervention and control groups with strong effect sizes on all outcome measures at the end of treatment.³⁴

Methods

Participants included male and nonpregnant female veterans with a diagnosed mTBI during post-9/11 military operations; aged 18 to 65 years; reports of persistent (ie, > 3 months in duration) headaches, insomnia, and attention difficulties; and able to read and write English, comprehend what is read, and follow directions. mTBI diagnosis was verified for each veteran via the electronic health record. Patients were excluded if they had a severe TBI diagnosis or impaired decision-making capacity; were unable to comply with study visit schedule; or endorsed active suicidal intent on the Columbia-Suicide Severity Rating Scale.³⁵

Recruitment efforts included: (1) letters sent to eligible veterans with mTBI who were identified by clinical informatics data after waiver of Health Insurance Portability and Accountability Act was obtained; veterans could contact the research team directly or the research team would call the veteran 2 weeks after the letter was sent; (2) veterans could be referred by a clinician; and (3) veterans could self-refer based on flyers and other study marketing materials.

The study was conducted from 2019 to 2024 at Spark M. Matsunaga VA Medical Center, in Honolulu, Hawaii. Four private research spaces in compliance with human research standards were used for consent, treatment, and assessment.

Consenting Procedure and Randomization

The privacy rights of potential participants were observed, and interested veterans who met the eligibility criteria underwent an informed consent procedure and were administered the Columbia-Suicide Severity Rating Scale.³⁵ Those veterans not indicating active suicidal intent were randomized into the intervention or control group. Once randomized, the participant was enrolled and scheduled for baseline assessment.

All procedures of this study were performed in adherence with relevant laws and institutional guidelines. The study was reviewed and approved by the VA Pacific Islands Health Care System Institutional Review Board (#2019-06-JC/Promise 0003).

Outcome Measures

The outcome measures were administered at baseline, midpoint (3-7 weeks), end of treatment (6-12 weeks), and at a 2-month follow-up appointment with the research assistant or project coordinator.

The primary outcome measures include the Headache Impact Test (HIT-6), TBIQOL Headache Pain item short form, Insomnia Severity Index (ISI), Quality of Life in Neurological Disorders (Neuro-QOL) Sleep Disturbance short form, and attention measure: QIKtest Continuous Performance Test (QIKtest) (Table 1).^36-44

Secondary outcome measures included QOL After Brain Injury (QOLIBRI), Neuro- QOL Satisfaction With Roles/Activities short form (Neuro-QOL Satisfaction), Neuro-QOL Ability to Participate in Roles/Activities short form (Neuro-QOL Participate), Depression Anxiety Stress Scales (DASS-21), Patient Health Questionnaire-9 (PHQ-9), Posttraumatic Stress Disorder (PTSD) Checklist for DSM-5 (PCL-5), and the General Symptom Inventory (eAppendix 1).^39,42,45-52

Sample

Seventy-two participants (36 in each group) were needed to have adequate statistical power for the analysis. Presuming attrition, the goal was to recruit 100 veterans. Literature on NFB studies of patients with mTBI have reported dropout rates ranging from 10% to 30%.^53,54 Assuming a dropout rate of 28% and a moderate autocorrelation of 0.6 among repeated measures, this sample size ensured the detection of an average difference of at least 0.49 SDs with a power of 80% in the NFB intervention group compared with the control group using a 2-tailed significance level of 0.05.

Control Group

Following baseline assessment, control group participants received 8 phone calls (1 call/wk) from 1 of 4 clinical investigators over 8 to 10 weeks. During each 15-minute call, 1 of the following health topics was discussed: sleep hygiene, basic nutritional concepts, beverage choices, positive thinking, thought reframing, fitness, daily calming activity, and enhancement of focus strategies. A script for each topic was used to guide each call.

Intervention Group

Following baseline assessment, intervention group participants completed 20 half-hour ILF NFB sessions, typically receiving 3 sessions per week over an 8- to 10-week period. ILF NFB treatments were administered by 1 of 4 licensed health care employees who had received substantial ILF NFB training and achieved a skill reliability index score of 0.95, ensuring the skill level of the ILF NFB providers was equal. A script was used by the ILF NFB providers during the ILF NFB sessions to keep the interaction approach consistent with all participants.

All procedures were explained in advance to participants and voluntary participation affirmed. At the first session, participants filled out a clinical symptom checklist of 5 symptoms (eAppendix 1).^39,42,45-49 The initial rating on the symptom checklist was reflective of their experience over the past month, while in each subsequent session, participants indicated their experience of those symptoms that day. ILF NFB providers were never privy to participants’ primary or secondary outcome measures data during the study, so these recurring clinical symptom checklist ratings, as well as other feedback provided by participants on their experience within and between sessions, were the clinical data used to make decisions about ILF NFB treatment protocol.

The Othmer Optimal Response Frequency (ORF) protocol was used for participants in this study.⁵⁵ Through an iterative process, ORF protocol establishes the specific frequency point along the 0.000001 mHz to 0.1 Hz continuum, which is optimal to diminish symptoms experienced in real-time during the session (eg, tension or pain in shoulders; racing thoughts).

During each ILF NFB session, participants were seated comfortably and encouraged to look at the feedback screen. The moving images on the game screen provided almost instantaneous feedback (within 500 ms) to participants about their brain functioning, as ascertained by electrodes placed on the scalp as dictated by study protocol.⁵⁶ A standardized protocol for site placement was used beginning with T3-T4, followed by the weekly addition of a site as tolerated in the following sequence: T4-P4, FP2-T4, and FP1-T4. More information about the ILF NFB procedures are outlined in the report of the pilot study and RCT initial results.^22,34

Statistical Analysis

Eighty-seven participants were randomized, with 43 assigned to the intervention group and 44 to the control group to achieve the enrollment goal of ≥ 36 participants in each group. This report is the second analysis of data from this RCT that employed a per-protocol approach, analyzing a subset of participants who fully adhered to the study protocol and completed all study procedures. Outcome scores at baseline, midpoint, end of treatment, and 2-month follow-up were summarized as means with corresponding 95% CIs. Group comparisons at the end of treatment and 2-month follow-up time points were conducted using 2-sample t tests. All statistical tests were 2-sided with a significance level of .05 (Type I error rate). SAS software version 9.4 Maintenance 8 was used for statistical analysis. Cohen d analyses were used for effect sizes.

Results

Seventy-four participants fully adhered to the study protocol and were included in the present analyses, with 38 in the control group and 36 in the intervention group. eAppendix 2 depicts the flow of participants through this study. There were no adverse events related to treatment, and the 13 participants who withdrew typically reported difficulty with scheduling or transportation as the primary reason. This study also took place during the COVID-19 pandemic, which likely had some impact on enrollment; participants were differentially impacted by changes in employment and moves to the continental United States.

Participants were aged 30 to 60 years (mean [SD], 45.4 [8.0]). Most participants (90.5%) were male, and multiracial and White were the most common racial identities (Table 2). Participant characteristics were largely balanced across randomized groups. Similarly, test scores on the primary variables of interest in this study and secondary clinical variables assessed were comparable across participants (Table 3).

Primary Variables of Interest Analyses

This study’s hypothesis was that those who completed ILF NFB treatment per protocol would demonstrate statistically significant improvement in symptoms related to headaches, sleep disturbance, and difficulty with attention when compared with veterans in the control group. This hypothesis was partially supported. A 2-sample t test showed that veterans in the intervention group demonstrated significant improvement in headache symptoms compared with veterans in the control group on the HIT-6 at the end-of-treatment (P < .001, d = 1.53) and 2-month follow-up assessment (P < .001, d = 1.14). This pattern also was consistent with the TBI-QOL Headache Pain item short form, with veterans in the intervention group showing improvement beyond those in the control group at the end-of-treatment (P < .001, d = 0.89) and 2-month follow-up assessment (P < .001, d = 0.83). Two-sample t tests also demonstrated significant improvement in subjective reports of sleep; those in the intervention group had significantly lower scores on the ISI at the end-of-study (P < .001, d = 1.53) and 2-month follow-up assessment (P < .001, d = 0.97). This pattern also held true for the Neuro-QOL Sleep Disturbance short form subtest, which demonstrated significantly more improvement in the intervention group compared with the control group at the end-of-study (P < .001, d = 0.97) and 2-month follow- up assessment (P < .001, d = 0.92). improvement in attention was not supported by the present results. A 2-sample t test found no significant difference between performance on the QIKtest for veterans in the intervention group vs the control group at the end-of-study (P = .40, d = 0.19) or the 2-month follow-up (P = .43, d = 0.20) (eAppendix 3).

Secondary Variables of Interest Analysis

Secondary variables examined differences in QOL, PTSD, depressive symptoms, and general symptoms reported between veterans in the intervention and control groups. Results demonstrated that veterans in the intervention group showed improvement above and beyond those in the control group on all measures. In regard to QOL, veterans in the intervention group had significantly higher scores on the Neuro-QOL Participate subtest than those in the control group at the end-of-study (P = .01, d = 0.89) and 2-month follow-up assessment (P < .001, d = 0.62). A similar pattern was found for the Neuro-QOL Satisfaction subtest, with veterans in the intervention group showing significantly higher scores than those in the control group at the end-of-study (P = .001, d = 0.95) and 2-month follow-up assessment (P < .001, d = 0.62). This also held true on the QOLIBRI, with veterans in the intervention group demonstrating significantly higher scores than those in the control group at the end-of-study (P = .001, d = 0.92) and 2-month follow-up assessment (P < .001, d = 0.66).

Veterans in the intervention group had significantly lower scores on the PCL-5 than those in the control group at the end-of- study (P = .003, d = 0.78) and 2-month follow-up assessment (P = .001, d = 0.72). Veterans in the intervention group also had significantly lower scores on the PHQ-9 than those in the control group at the end-of-study (P < .001, d = 0.98) and 2-month follow-up assessment (P < .001, d = 0.83). Veterans in the intervention group had significantly lower scores on the DASS- 21 than those in the control group at the end-of-study (P = .002, d = 0.80) and 2-month follow-up assessment (P = .001, d = 0.77). They also had significantly lower scores on the General Symptom Inventory than those in the control group at the end-of-study (P = .02, d = 0.75) and 2-month follow-up assessment (P = .002, d = 0.57). A clinically significant shift of score occurred for each of the measures except DASS-21 (eAppendix 3). eAppendix 4 depicts the change in scores for the intervention group at the end of treatment and the clinically significant shift score of each measure.

Discussion

The results of this RCT revealed a promising impact of ILF NFB on the commonly experienced persistent PCSs of headaches and disrupted sleep. Veterans in the intervention group demonstrated statistically significant improvement in headache symptoms compared with veterans in the control group when assessed at the end of treatment and during a 2-month follow-up. The statistical significance of these improvements was also supported by large or very large effect sizes. In addition to these primary variables of interest, veterans in the intervention group notably demonstrated significant improvement compared with those in the control group in a number of secondary clinical measures, including QOL, traumatic stress-related symptoms, depressive symptoms, and general symptom report. The clinical impact was further supported by the clinically relevant shift in scores in the intervention group.

The data did not support the hypothesis that attention concerns would show significant improvement following ILF NFB. Performance on an attention measure did not differ significantly between groups at either the end-of-treatment or 2-month follow up assessment. The QIKtest, a continuous performance test used to measure attention, was a go/no-go task and calculated based on a combination of various types of errors and outlier responses. The stimulus for this task is a series of computerized, blinking lights, for which participants are tasked with discriminating targets and nontargets under time pressure. However, the order of the stimuli are consistent across administrations, rather than being randomized, introducing a potential confound of practice effects on this task since patients were administered the QIKtest 3 times in a 2-month period and again 2 months later. Veterans in the control group notably improved in their average performance of this task from baseline to the endpoint of their treatment participation and demonstrated further improvement at the 2-month follow-up assessment; this pattern would be consistent with potential practice effects and warrants caution in its interpretation for both groups.

Previously published ILF NFB clinical studies that used the QIKtest and found positive results were mostly conducted among children and teen populations across longer treatment periods. This research may indicate the QIKtest is not an appropriate measure to assess adults who have specialized training in responding to stimuli (ie, trained military personnel). This suggests the concept of attention dysfunction experienced by veterans and the best method to measure it may need to be explored further. This construct may not be related to the focus and skill in prolonged attention needed in selecting go/ no-go tasks, but rather related to a broader conceptual basis involving memory, recall, clarity of rational thought, and decision making impacted by the mTBI. For instance, a study among combat veterans with mTBI and PTSD found that performance on objective cognitive measures did not significantly correlate with their subjective reports of cognitive difficulties.⁵⁷ This reflects the pattern of the present study, in which subjective reports of attention improved over time on the clinical symptom checklist filled out by participants at each session, but the objective measure did not. The mean attention dysfunction score was 6 at session 1 and 1 to 2 at session 20 (lower scores are better on a 10-point scale).

Strengths and Limitations

This study presents results stemming from the first RCT examining clinical effectiveness of ILF NFB in a VA setting for veterans with diagnoses of mTBI. The study design shows promising external validity. Veterans were able to participate in a treatment consisting of 20 sessions over a period of typically 8 to 10 weeks, entailing 2 to 3 sessions per week, with an attrition of only 18% over the course of the study. Notably, attrition rates may have been impacted by the time course of the study, which was recruiting and running participants throughout the COVID-19 pandemic (March 2020 to May 2023). No attrition was due to the intervention itself, and no adverse reactions to ILF NFB were reported during the course of the study. Other strengths of the study include the ethnically and racially diverse participants, representative of the population of veterans in Hawaii. Additionally, all ILF NFB providers underwent supervised ILF NFB training and achieved a skill reliability index score of 0.95 prior to providing ILF NFB to the intervention group.

This study was not blinded. Neither veterans nor ILF NFB providers were blinded and were therefore aware of the randomly assigned groups. Research assistants administering the periodic assessments were meant to be blinded to condition by design; however, as the study progressed, a research assistant became unintentionally aware of each study participant's condition based on required documentation in the veteran’s health records; more notes were present for those in the intervention group (20 specialist notes) than the control group (8 notes). While the presence of a control group represents a strength relative to much of the existing ILF NFB literature, the control group in this case did not account for the total time spent with the researchers. Participants in the intervention group met with researchers for 20 total sessions as opposed to 8 telephone calls. Therefore, the study design cannot fully rule out the differential impact of demand characteristics between the 2 groups, nor can it fully address or rule out the impact of differential motivation and expectations between groups. There is also evidence that technological innovation can influence the expectations of research participants, meaning that the intervention group may have been unduly influenced by the novelty of the ILF NFB technology, to which the control group did not have exposure.⁵⁸

A second attention measure for this study would have been beneficial, perhaps in identifying true change in attention ability or providing more insight into finding better methods to assess attention among veterans with mTBI. ILF NFB demonstrated significant impact across multiple outcome measures of clinical relevance for veterans diagnosed with mTBI, including the primary outcome variables of headache and sleep. The strength of the improvements seen in these areas, supported by large practical effects as well as veterans’ subjective reports, indicates much promise. Follow-up studies may also focus on the potential effectiveness of ILF NFB as a treatment of the secondary concerns measured in this study, including traumatic stress-related and depressive symptoms, and may explore the added benefit, if any, of ILF NFB alongside other evidence-based treatments for traumatic stress-related and mood disorders (eg, cognitive behavioral therapy). Using functional magnetic resonance imaging before and after assessments to determine actual brain enhancement with ILF NFB for certain disorders in which a brain signature exists (ie, migraine) should be explored. Further examination of ILF NFB as an intervention for attention may also be warranted, using more effective measures of attention in the population of veterans with mTBI, given the concerns noted earlier. Future research on this topic will need to clearly define attention in relation to the veteran experience and use relevant measures.

Conclusions

This study supports ILF NFB as a safe, noninvasive, nonpharmacologic treatment that may be effective in addressing the complex clinical concerns of veterans diagnosed with mTBI, a population for whom effective treatments have been difficult to identify. This intervention can provide veterans with a desirable and effective nonpharmacologic alternative in their care.

On March 11, 2020, the World Health Organization designated COVID- 19 as a pandemic.¹ Pandemics have historically impacted physical and mental health across all populations, but especially health care workers (HCWs).² Nurses and other HCWs were profoundly impacted by the pandemic.^3-8

Throughout the pandemic, nurses continued to provide care while working in short-staffed workplaces, facing increased exposure to COVID-19, and witnessing COVID—19–related morbidity and mortality.⁹ Many nurses were mandated to cross-train in unfamiliar clinical settings and adjust to new and prolonged shift schedules. Physical and emotional exhaustion associated with managing care for individuals with COVID-19, shortage of personal protective equipment (PPE), risk of infection, fear of secondary transmission to family members, feelings of being rejected by others, and social isolation, led to HCWs’ increased vulnerability to psychological impacts of the pandemic.^8,10

A meta-analysis of 65 studies with > 79,000 participants found HCWs experienced significant levels of anxiety, depression, stress, insomnia, and other mental health issues, such as posttraumatic stress disorder (PTSD). Female HCWs, nurses, and frontline responders experienced a higher incidence of psychological impact.¹¹ Other meta-analyses revealed that nurses’ compassion satisfaction, compassion fatigue, and burnout levels were significantly impacted with increased levels of burnout among nurses who had a friend or family member diagnosed with COVID- 19 or experienced prolonged threat of exposure to the virus.^12,13 A study of 350 nurses found high rates of perceived transgressions by others, and betrayal.⁸ Nurse leaders and staff nurses had to persevere as moral distress became pervasive among nursing staff, which led to complex and often unsustainable circumstances. ¹⁴ The themes identified in the literature about the pandemic’s impact as well as witnessing nurse colleagues’ distress with patient mortality and death of coworkers during the early phase of the COVID-19 pandemic compelled a group of Veterans Health Administration (VHA) nurses to form a research team to understand the scope of impact and identify possible solutions.

Since published studies on the impact of pandemics on HCWs, including nurses, primarily focused on inpatient settings, the investigators of this study sought to capture the experiences of outpatient and inpatient nurses providing care in the US Department of Veterans Affairs (VA) Sierra Pacific Network (Veterans Integrated Service Network [VISN] 21), which has facilities in northern California, Hawaii, and Nevada.^15-19 The purpose of this study was to identify the impact of COVID-19 on nurses caring for veterans in both outpatient and inpatient settings at VISN 21 facilities from March 2020 to September 2022, to inform leadership about the extent the virus affected nurses, and identify strategies that address current and future impacts of pandemics.

METHODS

This retrospective descriptive survey adapted the Pandemic Impact Survey by Purcell et al, which included the Moral Injury Events Scale, Primary Care PTSD Screener, the Patient Health Questionnaire-2 for depression, and a modified burnout scale.^20-24 The survey of 70 Likert-scale questions was intended to measure nurses’ needs, burnout, moral distress, depression and stress symptoms, work-related factors, and intent to remain working in their current position. A nurse was defined broadly and included those employed as licensed vocational nurses (LVN), licensed practical nurses (LPN), registered nurses (RN), nurses with advanced degrees, advanced practice registered nurses (APRNs), and nurses with other certifications or licenses.

The VA Pacific Islands Research and Development Committee reviewed and approved the institutional review board-exempted study. The VISN 21 union was notified; only limited demographic information and broad VA tenure categories were collected to protect privacy. The principal investigator redacted facility identifier data after each facility had participated.

The survey was placed in REDCAP and a confidential link was emailed to all VISN 21 inpatient and outpatient nurses during March 2023. Because a comprehensive VISN 21 list of nurse email addresses was unavailable, the email was distributed by nursing leadership at each facility. Nurses received an email reminder at the 2-week halfway point, prompting them to complete the survey. The email indicated the purpose and voluntary nature of the study and cautioned nurses that they might experience stress while answering survey questions. Stress management resources were provided.

Descriptive statistics were used to report the results. Data were aggregated for analyzing and reporting purposes.

RESULTS

In March 2023, 860 of 5586 nurses (15%) responded to the survey. Respondents included 344 clinical inpatient nurses (40%) and 516 clinical outpatient nurses (60%); 688 (80%) were RNs, 129 (15%) were LPNs/LVNs, and 43 (5%) were APRNs. Of 849 respondents to provide their age, 15 (2%) were < 30 years, 163 (19%) were 30 to 39 years, 232 (27%) were 40 to 49 years, 259 (30%) were 50 to 59 years, and 180 (21%) were ≥ 60 years.

The survey found that 688 nurses reported job satisfaction (80%) and 75% of all respondents (66% among inpatient nurses) reported feeling happy with the care they delivered. Both inpatient and outpatient nurses indicated they could rely on staff. Sixty percent (n = 516) of the nurses indicated that facility management considered workplace health and safety and supervisors showed concern for subordinates, although inpatient nurses reported a lower percentage (Table 1).

Two hundred fifty-eight nurses (30%) reported having nurse colleagues who died and 52 (6%) had ≥ 3 colleagues who died. Among respondents, 292 had ≥ 3 patients who died after contracting COVID-19 and 232 (27%) had a significant person in their life die. More than one-half (54%; n = 464) of nurses had to limit contact with a family member who had COVID-19. Most nurses reported concerns about their colleagues (91%), were concerned about bringing COVID-19 home (82%), and stayed away from family during the pandemic (56%) (Table 2).

A total of 593 nurses (69%) reported feeling overwhelmed from the workload associated with the pandemic, 490 (57%) felt frustrated with role changes, 447 (52%) were stressed because of short staffing, and 327 (38%) felt stressed because of being assigned or floated to different patient care areas. Among inpatient nurses, 158 (46%) reported stress related to being floated. Coworker absenteeism caused challenges for 697 nurses (81%) (Table 3).

Nurses suggested a number of changes that could improve working conditions, including flexible scheduling (54%) and more hours of leave, which was requested by 43% of outpatient/inpatient nurses and 53% of inpatient alone nurses. Access to COVID-19 testing and PPE was endorsed as a workplace need by 439 nurses; the need for access to PPE was reported by 43% of inpatient-only nurses vs 29% of outpatient/inpatient nurses. The need for adequate staffing was reported by 54% of nurses although the rate was higher among those working inpatient settings (66%) (Table 4).

Four hundred sixty-four nurses (54%) felt tense and irritable at home because of work and 447 had ≥ 1 symptoms of burnout (Table 5). In terms of moral distress, > 30% of nurses witnessed morally incongruent situations, 10% felt their own moral code was violated, and > 30% felt betrayed by others (Table 6). Among respondents, 16% to 21% of nurses reported depressive symptoms (eAppendix). About 50% of nurses intended to stay in their current position while 20% indicated an intention to leave for another VA position.

DISCUSSION

This study identified the impact of COVID-19 on nurses who work in VISN 21. The survey included a significant number of nurses who work in outpatient settings, which differed from most other published studies to date.^15-19 This study found that inpatient and outpatient nurses were similarly impacted by the COVID-19 pandemic, although there were differences. A high percentage of nurses reported job satisfaction despite the personal and professional impact of the pandemic.

Caring for veterans can result in a therapeutic relationship with a deep appreciation of veterans’ service and sensitivity to their needs.²⁵ Some nurses reported that they feel it is a privilege to care for veterans.

Most nurses who participated in this study felt they could rely on their colleagues and were concerned about their health and wellbeing. Kissel et al explored protective factors for nurses during the pandemic and found participants often reported that their coworkers were positive safeguards.¹⁷ At least 50% of respondents reported that management considered workplace safety and was concerned about their welfare. Previous research has found that a positive working organization that promoted safety and concern for staff were protective factors against stress among HCWs.²⁶ A literature review of 3 coronavirus outbreaks illustrated the support from supervisors and colleagues promoted resiliency and reduced stress disorders.³

Similar to other studies, study respondents experienced profound losses, including the deaths of colleagues, patients, and family. In 2021 Howell reported that HCWs experienced increased stress, fear, anxiety, and other negative emotions following news of colleagues’ deaths from COVID-19.²⁷ Kissel et al reported that nurses frequently described pandemic-related physical and psychological harm and witnessing distress that they had not been previously exposed to.¹⁷

Our findings illustrate the tightrope nurses walked while caring for patients and concerns about the health of their colleagues and family. Consistent with our findings, Howell found that HCWs were afraid of contracting the infection at work and then unknowingly giving it to others such as patients, coworkers, and household members. ²⁷ Murat et al reported that some nurses chose to live separately during the pandemic to avoid spreading COVID-19 to relatives.¹⁹ Several researchers found that concerns about family and children were prevalent and led to fear, anxiety, and burnout among nurses.^18,28,29 Shah et al suggested that nurses experiencing death in the workplace and within their family may have resulted in fear and anxiety about returning to work.²⁹ Garcia and Calvo argued that nurses may have been stigmatized as carriers of COVID-19.¹⁶ In addition, the loss of prepandemic workplace rituals may have impacted performance, team connection, and functioning, and led to increased turnover and decreased attachment to the organization.³⁰

This study described the significant workplace issues nurses endured during the pandemic, including being overwhelmed with additional and/or multiple roles and frustrated and stressed with role changes and short staffing. Nurses endorsed workplace challenges in the context of coworker absenteeism and reassignments to different areas, such as intensive care units (ICUs).¹⁷ Researchers also reported that displaced team members experienced loneliness and isolation when they were removed from their usual place of work and experienced distress caring for patients beyond their perceived competency or comfort.^17,31 Nurses also experienced rapid organizational changes, resource scarcity, high patient-to-nurse ratios, inconsistent or limited communications, and the absence of protocols for prolonged mass casualty events.¹⁷ These challenges, such as significant uncertainty and rapidly changing working conditions, were shared experiences suggested to be similar to “tumbling into chaos,” and likened to the overwhelming situations faced during patient surges to a medical “war zone.”¹⁷

Study respondents indicated that nurses wanted better access to critical supplies, PPE, and COVID-19 testing; more flexible scheduling; longer leave times; and staffing that was appropriate to the patient volumes. These findings aligned with previous research. Howell found that HCWs, especially nurses, worried about childcare because of school closures and increased work hours.²⁷ Nurses felt that hospital support was inaccessible or inadequate and worried about access to essential resources.^17-19,27 Studies also found excessive workloads, and many nurses needed mental or financial assistance from the hospital in addition to more rest and less work.^18,28 An editorial highlighted the potential adverse effects that a lack of PPE could have on staff ’s mental health because of perceptions of institutional betrayal, which occurs when trusted and powerful organizations seemingly act in ways that can harm those dependent on them for safety and well-being.³²

Consistent with other research, this study found that a majority of nurses experienced significant burnout symptoms. The number of nurses reporting symptoms of burnout increased during the pandemic with ICU nurses reporting the highest levels.^17,33 Soto-Rubio et al emphasized that working conditions experienced by nurses, such as interpersonal conflict, lack of trust in administration, workload, and role conflict, contributed to burnout during COVID-19.³⁴ Other studies found that nurses experienced burnout caused by uncertainty, intense work, and extra duties contributed to higher burnout scores.^18,19 It is not surprising that researchers have indicated that nurses experiencing burnout might display depressive and stress-related symptoms, insomnia, and concentration and memory problems.¹⁹

The results of this study indicate that one-third of participating nurses were experiencing moral distress. Burton et al described COVID-19 as an environment in which nurses witnessed, experienced, and at times had to participate in acts that involved ethical violations in care, institutional betrayal, and traumatic strain.⁹ Of note, our findings revealed that both inpatient and outpatient nurses experienced moral distress. Interestingly, Mantri et al found that COVID-19 increased moral injury but not burnout among health professionals, which differed from the results of this study.³⁵

The findings of this study indicate that many nurses experienced depressive symptoms. A systematic review found a similar percentage of HCWs experienced depression while caring for patients with COVID- 19, though a Chinese study found a higher percentage.^36,37 Previous research also found that the most difficult aspect of the COVID- 19 pandemic for nurses was coping with mental disorders such as depression, and that many experienced difficulty sleeping/ had poor sleep quality, believed a similar disaster would occur in the future, were irritated or angered easily, and experienced emotional exhaustion.^15,19 The long-term mental and physical ramifications of caring for individuals with COVID-19 remain unknown. However, previous research suggests a high prevalence of depression, insomnia, anxiety, and distress, which could impair nurses’ professional performance.²⁹

This study reported that a majority of nurses intended to stay in their current position and about 20% intended to leave for another position within the VA. Similar findings conducted early in the pandemic indicated that most participants did not intend to quit nursing.¹⁹

This study’s findings suggest the COVID-19 pandemic had an adverse impact on VISN 21 nurses. It is critical to develop, implement, and adopt adequate measures as early as possible to support the health care system, especially nurses.¹⁸

Implications

Before the COVID-19 pandemic, discussing burnout and moral anguish was common, primarily in critical care.¹⁴ However, these experiences became more widespread throughout nursing settings during the pandemic. Nurse leaders have been identified as responsible for ensuring the environmental safety and personal well-being of their colleagues during and after pandemics.¹⁴

Studies of HCW experiences during COVID-19 provide many insights into future preparedness, strategies to best handle another pandemic during its acute stage, and techniques to address issues that might persist. This study and others suggest that comprehensive interventions in preparation for, during, and after a pandemic are needed. We break down strategies into pandemic and postpandemic interventions based on a synthesis of the literature and the research team’s knowledge and expertise.^{3,14-16,27,29,36,38-44}

Pandemic interventions. During a pandemic, it is important that nurses are adequately cared for to ensure they can continue to provide quality care for others. Resources supporting emotional well-being and addressing moral distress offered during a pandemic are essential. Implementing meaningful strategies could enhance nurses’ health and wellbeing. It is essential that leaders provide nurses a safe work environment/experience during a pandemic by instituting meaningful resources. In addition, developing best practices for leadership are critical.

Postpandemic interventions. Personal experiences of depression, burnout, and moral distress have not spontaneously resolved as the pandemic receded. Providing postpandemic interventions to lessen ongoing and lingering depressive, burnout, and moral distress symptoms experienced by frontline workers are critical. These interventions might prevent long-term health issues and the exodus of nurses.

Postpandemic interventions should include the integration of pandemic planning into new or existing educational or training programs for staff. Promotion and support of mental health services by health system leadership for nursing personnel implemented as a usual service will play an important role in preparing for future pandemics. A key role in preparation is developing and maintaining cooperation and ongoing mutual understanding, respect, and communication between leadership and nursing staff.

Future Research

This study’s findings inform VHA leadership and society about how a large group of nurses were impacted by COVID-19 while caring for patients in inpatient and outpatient settings and could provide a basis for extending this research to other groups of nurses or health care personnel. Future research might be helpful in identifying the impact of COVID-19 on nursing leadership. During conversations with nursing leadership, a common theme identified was that nurses did not feel that leadership was fully prepared for the level of emergency the pandemic created both personally and professionally; leadership expressed experiences similar to nurses providing direct care and felt powerless to help their nursing staff. Other areas of research could include identifying underlying factors contributing to burnout and moral distress and describing nurses’ expectations of or needs from leadership to best manage burnout and moral distress.

Limitations

Experiences of nurses who stopped working were not captured and information about their experiences might have different results. The survey distribution was limited to 2 emails (an initial email and a second at midpoint) sent at the discretion of the nurse executive of each facility. The study timeline was long because of complex regulatory protective processes inherent in the VHA system for researchers to include initial institutional review board review process, union notifications, and each facility’s response to the survey. Although 860 nurses participated, this was 15% of the 5586 VISN 21 nurses at the time of the study. Many clinical inpatient nurses do not have regular access to email, which might have impacted participation rate.

CONCLUSIONS

This study identified the impact COVID-19 had on nurses who worked in a large hospital system. The research team outlined strategies to be employed during and after the pandemic, such as preplanning for future pandemics to provide a framework for a comprehensive pandemic response protocol.

This study adds to generalized knowledge because it captured voices of inpatient and outpatient nurses, the latter had not been previously studied. As nurses and health care organizations move beyond the pandemic with a significant number of nurses continuing to experience effects, there is a need to institute interventions to assist nurses in healing and begin preparations for future pandemics.

On March 11, 2020, the World Health Organization designated COVID- 19 as a pandemic.¹ Pandemics have historically impacted physical and mental health across all populations, but especially health care workers (HCWs).² Nurses and other HCWs were profoundly impacted by the pandemic.^3-8

Throughout the pandemic, nurses continued to provide care while working in short-staffed workplaces, facing increased exposure to COVID-19, and witnessing COVID—19–related morbidity and mortality.⁹ Many nurses were mandated to cross-train in unfamiliar clinical settings and adjust to new and prolonged shift schedules. Physical and emotional exhaustion associated with managing care for individuals with COVID-19, shortage of personal protective equipment (PPE), risk of infection, fear of secondary transmission to family members, feelings of being rejected by others, and social isolation, led to HCWs’ increased vulnerability to psychological impacts of the pandemic.^8,10

A meta-analysis of 65 studies with > 79,000 participants found HCWs experienced significant levels of anxiety, depression, stress, insomnia, and other mental health issues, such as posttraumatic stress disorder (PTSD). Female HCWs, nurses, and frontline responders experienced a higher incidence of psychological impact.¹¹ Other meta-analyses revealed that nurses’ compassion satisfaction, compassion fatigue, and burnout levels were significantly impacted with increased levels of burnout among nurses who had a friend or family member diagnosed with COVID- 19 or experienced prolonged threat of exposure to the virus.^12,13 A study of 350 nurses found high rates of perceived transgressions by others, and betrayal.⁸ Nurse leaders and staff nurses had to persevere as moral distress became pervasive among nursing staff, which led to complex and often unsustainable circumstances. ¹⁴ The themes identified in the literature about the pandemic’s impact as well as witnessing nurse colleagues’ distress with patient mortality and death of coworkers during the early phase of the COVID-19 pandemic compelled a group of Veterans Health Administration (VHA) nurses to form a research team to understand the scope of impact and identify possible solutions.

Since published studies on the impact of pandemics on HCWs, including nurses, primarily focused on inpatient settings, the investigators of this study sought to capture the experiences of outpatient and inpatient nurses providing care in the US Department of Veterans Affairs (VA) Sierra Pacific Network (Veterans Integrated Service Network [VISN] 21), which has facilities in northern California, Hawaii, and Nevada.^15-19 The purpose of this study was to identify the impact of COVID-19 on nurses caring for veterans in both outpatient and inpatient settings at VISN 21 facilities from March 2020 to September 2022, to inform leadership about the extent the virus affected nurses, and identify strategies that address current and future impacts of pandemics.

METHODS

This retrospective descriptive survey adapted the Pandemic Impact Survey by Purcell et al, which included the Moral Injury Events Scale, Primary Care PTSD Screener, the Patient Health Questionnaire-2 for depression, and a modified burnout scale.^20-24 The survey of 70 Likert-scale questions was intended to measure nurses’ needs, burnout, moral distress, depression and stress symptoms, work-related factors, and intent to remain working in their current position. A nurse was defined broadly and included those employed as licensed vocational nurses (LVN), licensed practical nurses (LPN), registered nurses (RN), nurses with advanced degrees, advanced practice registered nurses (APRNs), and nurses with other certifications or licenses.

The VA Pacific Islands Research and Development Committee reviewed and approved the institutional review board-exempted study. The VISN 21 union was notified; only limited demographic information and broad VA tenure categories were collected to protect privacy. The principal investigator redacted facility identifier data after each facility had participated.

The survey was placed in REDCAP and a confidential link was emailed to all VISN 21 inpatient and outpatient nurses during March 2023. Because a comprehensive VISN 21 list of nurse email addresses was unavailable, the email was distributed by nursing leadership at each facility. Nurses received an email reminder at the 2-week halfway point, prompting them to complete the survey. The email indicated the purpose and voluntary nature of the study and cautioned nurses that they might experience stress while answering survey questions. Stress management resources were provided.

Descriptive statistics were used to report the results. Data were aggregated for analyzing and reporting purposes.

RESULTS

In March 2023, 860 of 5586 nurses (15%) responded to the survey. Respondents included 344 clinical inpatient nurses (40%) and 516 clinical outpatient nurses (60%); 688 (80%) were RNs, 129 (15%) were LPNs/LVNs, and 43 (5%) were APRNs. Of 849 respondents to provide their age, 15 (2%) were < 30 years, 163 (19%) were 30 to 39 years, 232 (27%) were 40 to 49 years, 259 (30%) were 50 to 59 years, and 180 (21%) were ≥ 60 years.

The survey found that 688 nurses reported job satisfaction (80%) and 75% of all respondents (66% among inpatient nurses) reported feeling happy with the care they delivered. Both inpatient and outpatient nurses indicated they could rely on staff. Sixty percent (n = 516) of the nurses indicated that facility management considered workplace health and safety and supervisors showed concern for subordinates, although inpatient nurses reported a lower percentage (Table 1).

Two hundred fifty-eight nurses (30%) reported having nurse colleagues who died and 52 (6%) had ≥ 3 colleagues who died. Among respondents, 292 had ≥ 3 patients who died after contracting COVID-19 and 232 (27%) had a significant person in their life die. More than one-half (54%; n = 464) of nurses had to limit contact with a family member who had COVID-19. Most nurses reported concerns about their colleagues (91%), were concerned about bringing COVID-19 home (82%), and stayed away from family during the pandemic (56%) (Table 2).

A total of 593 nurses (69%) reported feeling overwhelmed from the workload associated with the pandemic, 490 (57%) felt frustrated with role changes, 447 (52%) were stressed because of short staffing, and 327 (38%) felt stressed because of being assigned or floated to different patient care areas. Among inpatient nurses, 158 (46%) reported stress related to being floated. Coworker absenteeism caused challenges for 697 nurses (81%) (Table 3).

Nurses suggested a number of changes that could improve working conditions, including flexible scheduling (54%) and more hours of leave, which was requested by 43% of outpatient/inpatient nurses and 53% of inpatient alone nurses. Access to COVID-19 testing and PPE was endorsed as a workplace need by 439 nurses; the need for access to PPE was reported by 43% of inpatient-only nurses vs 29% of outpatient/inpatient nurses. The need for adequate staffing was reported by 54% of nurses although the rate was higher among those working inpatient settings (66%) (Table 4).

Four hundred sixty-four nurses (54%) felt tense and irritable at home because of work and 447 had ≥ 1 symptoms of burnout (Table 5). In terms of moral distress, > 30% of nurses witnessed morally incongruent situations, 10% felt their own moral code was violated, and > 30% felt betrayed by others (Table 6). Among respondents, 16% to 21% of nurses reported depressive symptoms (eAppendix). About 50% of nurses intended to stay in their current position while 20% indicated an intention to leave for another VA position.

DISCUSSION

This study identified the impact of COVID-19 on nurses who work in VISN 21. The survey included a significant number of nurses who work in outpatient settings, which differed from most other published studies to date.^15-19 This study found that inpatient and outpatient nurses were similarly impacted by the COVID-19 pandemic, although there were differences. A high percentage of nurses reported job satisfaction despite the personal and professional impact of the pandemic.

Caring for veterans can result in a therapeutic relationship with a deep appreciation of veterans’ service and sensitivity to their needs.²⁵ Some nurses reported that they feel it is a privilege to care for veterans.

Most nurses who participated in this study felt they could rely on their colleagues and were concerned about their health and wellbeing. Kissel et al explored protective factors for nurses during the pandemic and found participants often reported that their coworkers were positive safeguards.¹⁷ At least 50% of respondents reported that management considered workplace safety and was concerned about their welfare. Previous research has found that a positive working organization that promoted safety and concern for staff were protective factors against stress among HCWs.²⁶ A literature review of 3 coronavirus outbreaks illustrated the support from supervisors and colleagues promoted resiliency and reduced stress disorders.³

Similar to other studies, study respondents experienced profound losses, including the deaths of colleagues, patients, and family. In 2021 Howell reported that HCWs experienced increased stress, fear, anxiety, and other negative emotions following news of colleagues’ deaths from COVID-19.²⁷ Kissel et al reported that nurses frequently described pandemic-related physical and psychological harm and witnessing distress that they had not been previously exposed to.¹⁷

Our findings illustrate the tightrope nurses walked while caring for patients and concerns about the health of their colleagues and family. Consistent with our findings, Howell found that HCWs were afraid of contracting the infection at work and then unknowingly giving it to others such as patients, coworkers, and household members. ²⁷ Murat et al reported that some nurses chose to live separately during the pandemic to avoid spreading COVID-19 to relatives.¹⁹ Several researchers found that concerns about family and children were prevalent and led to fear, anxiety, and burnout among nurses.^18,28,29 Shah et al suggested that nurses experiencing death in the workplace and within their family may have resulted in fear and anxiety about returning to work.²⁹ Garcia and Calvo argued that nurses may have been stigmatized as carriers of COVID-19.¹⁶ In addition, the loss of prepandemic workplace rituals may have impacted performance, team connection, and functioning, and led to increased turnover and decreased attachment to the organization.³⁰

This study described the significant workplace issues nurses endured during the pandemic, including being overwhelmed with additional and/or multiple roles and frustrated and stressed with role changes and short staffing. Nurses endorsed workplace challenges in the context of coworker absenteeism and reassignments to different areas, such as intensive care units (ICUs).¹⁷ Researchers also reported that displaced team members experienced loneliness and isolation when they were removed from their usual place of work and experienced distress caring for patients beyond their perceived competency or comfort.^17,31 Nurses also experienced rapid organizational changes, resource scarcity, high patient-to-nurse ratios, inconsistent or limited communications, and the absence of protocols for prolonged mass casualty events.¹⁷ These challenges, such as significant uncertainty and rapidly changing working conditions, were shared experiences suggested to be similar to “tumbling into chaos,” and likened to the overwhelming situations faced during patient surges to a medical “war zone.”¹⁷

Study respondents indicated that nurses wanted better access to critical supplies, PPE, and COVID-19 testing; more flexible scheduling; longer leave times; and staffing that was appropriate to the patient volumes. These findings aligned with previous research. Howell found that HCWs, especially nurses, worried about childcare because of school closures and increased work hours.²⁷ Nurses felt that hospital support was inaccessible or inadequate and worried about access to essential resources.^17-19,27 Studies also found excessive workloads, and many nurses needed mental or financial assistance from the hospital in addition to more rest and less work.^18,28 An editorial highlighted the potential adverse effects that a lack of PPE could have on staff ’s mental health because of perceptions of institutional betrayal, which occurs when trusted and powerful organizations seemingly act in ways that can harm those dependent on them for safety and well-being.³²

Consistent with other research, this study found that a majority of nurses experienced significant burnout symptoms. The number of nurses reporting symptoms of burnout increased during the pandemic with ICU nurses reporting the highest levels.^17,33 Soto-Rubio et al emphasized that working conditions experienced by nurses, such as interpersonal conflict, lack of trust in administration, workload, and role conflict, contributed to burnout during COVID-19.³⁴ Other studies found that nurses experienced burnout caused by uncertainty, intense work, and extra duties contributed to higher burnout scores.^18,19 It is not surprising that researchers have indicated that nurses experiencing burnout might display depressive and stress-related symptoms, insomnia, and concentration and memory problems.¹⁹

The results of this study indicate that one-third of participating nurses were experiencing moral distress. Burton et al described COVID-19 as an environment in which nurses witnessed, experienced, and at times had to participate in acts that involved ethical violations in care, institutional betrayal, and traumatic strain.⁹ Of note, our findings revealed that both inpatient and outpatient nurses experienced moral distress. Interestingly, Mantri et al found that COVID-19 increased moral injury but not burnout among health professionals, which differed from the results of this study.³⁵

The findings of this study indicate that many nurses experienced depressive symptoms. A systematic review found a similar percentage of HCWs experienced depression while caring for patients with COVID- 19, though a Chinese study found a higher percentage.^36,37 Previous research also found that the most difficult aspect of the COVID- 19 pandemic for nurses was coping with mental disorders such as depression, and that many experienced difficulty sleeping/ had poor sleep quality, believed a similar disaster would occur in the future, were irritated or angered easily, and experienced emotional exhaustion.^15,19 The long-term mental and physical ramifications of caring for individuals with COVID-19 remain unknown. However, previous research suggests a high prevalence of depression, insomnia, anxiety, and distress, which could impair nurses’ professional performance.²⁹

This study reported that a majority of nurses intended to stay in their current position and about 20% intended to leave for another position within the VA. Similar findings conducted early in the pandemic indicated that most participants did not intend to quit nursing.¹⁹

This study’s findings suggest the COVID-19 pandemic had an adverse impact on VISN 21 nurses. It is critical to develop, implement, and adopt adequate measures as early as possible to support the health care system, especially nurses.¹⁸

Implications

Before the COVID-19 pandemic, discussing burnout and moral anguish was common, primarily in critical care.¹⁴ However, these experiences became more widespread throughout nursing settings during the pandemic. Nurse leaders have been identified as responsible for ensuring the environmental safety and personal well-being of their colleagues during and after pandemics.¹⁴

Studies of HCW experiences during COVID-19 provide many insights into future preparedness, strategies to best handle another pandemic during its acute stage, and techniques to address issues that might persist. This study and others suggest that comprehensive interventions in preparation for, during, and after a pandemic are needed. We break down strategies into pandemic and postpandemic interventions based on a synthesis of the literature and the research team’s knowledge and expertise.^{3,14-16,27,29,36,38-44}

Pandemic interventions. During a pandemic, it is important that nurses are adequately cared for to ensure they can continue to provide quality care for others. Resources supporting emotional well-being and addressing moral distress offered during a pandemic are essential. Implementing meaningful strategies could enhance nurses’ health and wellbeing. It is essential that leaders provide nurses a safe work environment/experience during a pandemic by instituting meaningful resources. In addition, developing best practices for leadership are critical.

Postpandemic interventions. Personal experiences of depression, burnout, and moral distress have not spontaneously resolved as the pandemic receded. Providing postpandemic interventions to lessen ongoing and lingering depressive, burnout, and moral distress symptoms experienced by frontline workers are critical. These interventions might prevent long-term health issues and the exodus of nurses.

Postpandemic interventions should include the integration of pandemic planning into new or existing educational or training programs for staff. Promotion and support of mental health services by health system leadership for nursing personnel implemented as a usual service will play an important role in preparing for future pandemics. A key role in preparation is developing and maintaining cooperation and ongoing mutual understanding, respect, and communication between leadership and nursing staff.

Future Research

This study’s findings inform VHA leadership and society about how a large group of nurses were impacted by COVID-19 while caring for patients in inpatient and outpatient settings and could provide a basis for extending this research to other groups of nurses or health care personnel. Future research might be helpful in identifying the impact of COVID-19 on nursing leadership. During conversations with nursing leadership, a common theme identified was that nurses did not feel that leadership was fully prepared for the level of emergency the pandemic created both personally and professionally; leadership expressed experiences similar to nurses providing direct care and felt powerless to help their nursing staff. Other areas of research could include identifying underlying factors contributing to burnout and moral distress and describing nurses’ expectations of or needs from leadership to best manage burnout and moral distress.

Limitations

Experiences of nurses who stopped working were not captured and information about their experiences might have different results. The survey distribution was limited to 2 emails (an initial email and a second at midpoint) sent at the discretion of the nurse executive of each facility. The study timeline was long because of complex regulatory protective processes inherent in the VHA system for researchers to include initial institutional review board review process, union notifications, and each facility’s response to the survey. Although 860 nurses participated, this was 15% of the 5586 VISN 21 nurses at the time of the study. Many clinical inpatient nurses do not have regular access to email, which might have impacted participation rate.

CONCLUSIONS

This study identified the impact COVID-19 had on nurses who worked in a large hospital system. The research team outlined strategies to be employed during and after the pandemic, such as preplanning for future pandemics to provide a framework for a comprehensive pandemic response protocol.

This study adds to generalized knowledge because it captured voices of inpatient and outpatient nurses, the latter had not been previously studied. As nurses and health care organizations move beyond the pandemic with a significant number of nurses continuing to experience effects, there is a need to institute interventions to assist nurses in healing and begin preparations for future pandemics.

On March 11, 2020, the World Health Organization designated COVID- 19 as a pandemic.¹ Pandemics have historically impacted physical and mental health across all populations, but especially health care workers (HCWs).² Nurses and other HCWs were profoundly impacted by the pandemic.^3-8

Throughout the pandemic, nurses continued to provide care while working in short-staffed workplaces, facing increased exposure to COVID-19, and witnessing COVID—19–related morbidity and mortality.⁹ Many nurses were mandated to cross-train in unfamiliar clinical settings and adjust to new and prolonged shift schedules. Physical and emotional exhaustion associated with managing care for individuals with COVID-19, shortage of personal protective equipment (PPE), risk of infection, fear of secondary transmission to family members, feelings of being rejected by others, and social isolation, led to HCWs’ increased vulnerability to psychological impacts of the pandemic.^8,10

A meta-analysis of 65 studies with > 79,000 participants found HCWs experienced significant levels of anxiety, depression, stress, insomnia, and other mental health issues, such as posttraumatic stress disorder (PTSD). Female HCWs, nurses, and frontline responders experienced a higher incidence of psychological impact.¹¹ Other meta-analyses revealed that nurses’ compassion satisfaction, compassion fatigue, and burnout levels were significantly impacted with increased levels of burnout among nurses who had a friend or family member diagnosed with COVID- 19 or experienced prolonged threat of exposure to the virus.^12,13 A study of 350 nurses found high rates of perceived transgressions by others, and betrayal.⁸ Nurse leaders and staff nurses had to persevere as moral distress became pervasive among nursing staff, which led to complex and often unsustainable circumstances. ¹⁴ The themes identified in the literature about the pandemic’s impact as well as witnessing nurse colleagues’ distress with patient mortality and death of coworkers during the early phase of the COVID-19 pandemic compelled a group of Veterans Health Administration (VHA) nurses to form a research team to understand the scope of impact and identify possible solutions.

Since published studies on the impact of pandemics on HCWs, including nurses, primarily focused on inpatient settings, the investigators of this study sought to capture the experiences of outpatient and inpatient nurses providing care in the US Department of Veterans Affairs (VA) Sierra Pacific Network (Veterans Integrated Service Network [VISN] 21), which has facilities in northern California, Hawaii, and Nevada.^15-19 The purpose of this study was to identify the impact of COVID-19 on nurses caring for veterans in both outpatient and inpatient settings at VISN 21 facilities from March 2020 to September 2022, to inform leadership about the extent the virus affected nurses, and identify strategies that address current and future impacts of pandemics.

METHODS

This retrospective descriptive survey adapted the Pandemic Impact Survey by Purcell et al, which included the Moral Injury Events Scale, Primary Care PTSD Screener, the Patient Health Questionnaire-2 for depression, and a modified burnout scale.^20-24 The survey of 70 Likert-scale questions was intended to measure nurses’ needs, burnout, moral distress, depression and stress symptoms, work-related factors, and intent to remain working in their current position. A nurse was defined broadly and included those employed as licensed vocational nurses (LVN), licensed practical nurses (LPN), registered nurses (RN), nurses with advanced degrees, advanced practice registered nurses (APRNs), and nurses with other certifications or licenses.

The VA Pacific Islands Research and Development Committee reviewed and approved the institutional review board-exempted study. The VISN 21 union was notified; only limited demographic information and broad VA tenure categories were collected to protect privacy. The principal investigator redacted facility identifier data after each facility had participated.

The survey was placed in REDCAP and a confidential link was emailed to all VISN 21 inpatient and outpatient nurses during March 2023. Because a comprehensive VISN 21 list of nurse email addresses was unavailable, the email was distributed by nursing leadership at each facility. Nurses received an email reminder at the 2-week halfway point, prompting them to complete the survey. The email indicated the purpose and voluntary nature of the study and cautioned nurses that they might experience stress while answering survey questions. Stress management resources were provided.

Descriptive statistics were used to report the results. Data were aggregated for analyzing and reporting purposes.

RESULTS

In March 2023, 860 of 5586 nurses (15%) responded to the survey. Respondents included 344 clinical inpatient nurses (40%) and 516 clinical outpatient nurses (60%); 688 (80%) were RNs, 129 (15%) were LPNs/LVNs, and 43 (5%) were APRNs. Of 849 respondents to provide their age, 15 (2%) were < 30 years, 163 (19%) were 30 to 39 years, 232 (27%) were 40 to 49 years, 259 (30%) were 50 to 59 years, and 180 (21%) were ≥ 60 years.

The survey found that 688 nurses reported job satisfaction (80%) and 75% of all respondents (66% among inpatient nurses) reported feeling happy with the care they delivered. Both inpatient and outpatient nurses indicated they could rely on staff. Sixty percent (n = 516) of the nurses indicated that facility management considered workplace health and safety and supervisors showed concern for subordinates, although inpatient nurses reported a lower percentage (Table 1).

Two hundred fifty-eight nurses (30%) reported having nurse colleagues who died and 52 (6%) had ≥ 3 colleagues who died. Among respondents, 292 had ≥ 3 patients who died after contracting COVID-19 and 232 (27%) had a significant person in their life die. More than one-half (54%; n = 464) of nurses had to limit contact with a family member who had COVID-19. Most nurses reported concerns about their colleagues (91%), were concerned about bringing COVID-19 home (82%), and stayed away from family during the pandemic (56%) (Table 2).

A total of 593 nurses (69%) reported feeling overwhelmed from the workload associated with the pandemic, 490 (57%) felt frustrated with role changes, 447 (52%) were stressed because of short staffing, and 327 (38%) felt stressed because of being assigned or floated to different patient care areas. Among inpatient nurses, 158 (46%) reported stress related to being floated. Coworker absenteeism caused challenges for 697 nurses (81%) (Table 3).

Nurses suggested a number of changes that could improve working conditions, including flexible scheduling (54%) and more hours of leave, which was requested by 43% of outpatient/inpatient nurses and 53% of inpatient alone nurses. Access to COVID-19 testing and PPE was endorsed as a workplace need by 439 nurses; the need for access to PPE was reported by 43% of inpatient-only nurses vs 29% of outpatient/inpatient nurses. The need for adequate staffing was reported by 54% of nurses although the rate was higher among those working inpatient settings (66%) (Table 4).

Four hundred sixty-four nurses (54%) felt tense and irritable at home because of work and 447 had ≥ 1 symptoms of burnout (Table 5). In terms of moral distress, > 30% of nurses witnessed morally incongruent situations, 10% felt their own moral code was violated, and > 30% felt betrayed by others (Table 6). Among respondents, 16% to 21% of nurses reported depressive symptoms (eAppendix). About 50% of nurses intended to stay in their current position while 20% indicated an intention to leave for another VA position.

DISCUSSION

This study identified the impact of COVID-19 on nurses who work in VISN 21. The survey included a significant number of nurses who work in outpatient settings, which differed from most other published studies to date.^15-19 This study found that inpatient and outpatient nurses were similarly impacted by the COVID-19 pandemic, although there were differences. A high percentage of nurses reported job satisfaction despite the personal and professional impact of the pandemic.

Caring for veterans can result in a therapeutic relationship with a deep appreciation of veterans’ service and sensitivity to their needs.²⁵ Some nurses reported that they feel it is a privilege to care for veterans.

Most nurses who participated in this study felt they could rely on their colleagues and were concerned about their health and wellbeing. Kissel et al explored protective factors for nurses during the pandemic and found participants often reported that their coworkers were positive safeguards.¹⁷ At least 50% of respondents reported that management considered workplace safety and was concerned about their welfare. Previous research has found that a positive working organization that promoted safety and concern for staff were protective factors against stress among HCWs.²⁶ A literature review of 3 coronavirus outbreaks illustrated the support from supervisors and colleagues promoted resiliency and reduced stress disorders.³

Similar to other studies, study respondents experienced profound losses, including the deaths of colleagues, patients, and family. In 2021 Howell reported that HCWs experienced increased stress, fear, anxiety, and other negative emotions following news of colleagues’ deaths from COVID-19.²⁷ Kissel et al reported that nurses frequently described pandemic-related physical and psychological harm and witnessing distress that they had not been previously exposed to.¹⁷

Our findings illustrate the tightrope nurses walked while caring for patients and concerns about the health of their colleagues and family. Consistent with our findings, Howell found that HCWs were afraid of contracting the infection at work and then unknowingly giving it to others such as patients, coworkers, and household members. ²⁷ Murat et al reported that some nurses chose to live separately during the pandemic to avoid spreading COVID-19 to relatives.¹⁹ Several researchers found that concerns about family and children were prevalent and led to fear, anxiety, and burnout among nurses.^18,28,29 Shah et al suggested that nurses experiencing death in the workplace and within their family may have resulted in fear and anxiety about returning to work.²⁹ Garcia and Calvo argued that nurses may have been stigmatized as carriers of COVID-19.¹⁶ In addition, the loss of prepandemic workplace rituals may have impacted performance, team connection, and functioning, and led to increased turnover and decreased attachment to the organization.³⁰

This study described the significant workplace issues nurses endured during the pandemic, including being overwhelmed with additional and/or multiple roles and frustrated and stressed with role changes and short staffing. Nurses endorsed workplace challenges in the context of coworker absenteeism and reassignments to different areas, such as intensive care units (ICUs).¹⁷ Researchers also reported that displaced team members experienced loneliness and isolation when they were removed from their usual place of work and experienced distress caring for patients beyond their perceived competency or comfort.^17,31 Nurses also experienced rapid organizational changes, resource scarcity, high patient-to-nurse ratios, inconsistent or limited communications, and the absence of protocols for prolonged mass casualty events.¹⁷ These challenges, such as significant uncertainty and rapidly changing working conditions, were shared experiences suggested to be similar to “tumbling into chaos,” and likened to the overwhelming situations faced during patient surges to a medical “war zone.”¹⁷

Study respondents indicated that nurses wanted better access to critical supplies, PPE, and COVID-19 testing; more flexible scheduling; longer leave times; and staffing that was appropriate to the patient volumes. These findings aligned with previous research. Howell found that HCWs, especially nurses, worried about childcare because of school closures and increased work hours.²⁷ Nurses felt that hospital support was inaccessible or inadequate and worried about access to essential resources.^17-19,27 Studies also found excessive workloads, and many nurses needed mental or financial assistance from the hospital in addition to more rest and less work.^18,28 An editorial highlighted the potential adverse effects that a lack of PPE could have on staff ’s mental health because of perceptions of institutional betrayal, which occurs when trusted and powerful organizations seemingly act in ways that can harm those dependent on them for safety and well-being.³²

Consistent with other research, this study found that a majority of nurses experienced significant burnout symptoms. The number of nurses reporting symptoms of burnout increased during the pandemic with ICU nurses reporting the highest levels.^17,33 Soto-Rubio et al emphasized that working conditions experienced by nurses, such as interpersonal conflict, lack of trust in administration, workload, and role conflict, contributed to burnout during COVID-19.³⁴ Other studies found that nurses experienced burnout caused by uncertainty, intense work, and extra duties contributed to higher burnout scores.^18,19 It is not surprising that researchers have indicated that nurses experiencing burnout might display depressive and stress-related symptoms, insomnia, and concentration and memory problems.¹⁹

The results of this study indicate that one-third of participating nurses were experiencing moral distress. Burton et al described COVID-19 as an environment in which nurses witnessed, experienced, and at times had to participate in acts that involved ethical violations in care, institutional betrayal, and traumatic strain.⁹ Of note, our findings revealed that both inpatient and outpatient nurses experienced moral distress. Interestingly, Mantri et al found that COVID-19 increased moral injury but not burnout among health professionals, which differed from the results of this study.³⁵

The findings of this study indicate that many nurses experienced depressive symptoms. A systematic review found a similar percentage of HCWs experienced depression while caring for patients with COVID- 19, though a Chinese study found a higher percentage.^36,37 Previous research also found that the most difficult aspect of the COVID- 19 pandemic for nurses was coping with mental disorders such as depression, and that many experienced difficulty sleeping/ had poor sleep quality, believed a similar disaster would occur in the future, were irritated or angered easily, and experienced emotional exhaustion.^15,19 The long-term mental and physical ramifications of caring for individuals with COVID-19 remain unknown. However, previous research suggests a high prevalence of depression, insomnia, anxiety, and distress, which could impair nurses’ professional performance.²⁹

This study reported that a majority of nurses intended to stay in their current position and about 20% intended to leave for another position within the VA. Similar findings conducted early in the pandemic indicated that most participants did not intend to quit nursing.¹⁹

This study’s findings suggest the COVID-19 pandemic had an adverse impact on VISN 21 nurses. It is critical to develop, implement, and adopt adequate measures as early as possible to support the health care system, especially nurses.¹⁸

Implications

Before the COVID-19 pandemic, discussing burnout and moral anguish was common, primarily in critical care.¹⁴ However, these experiences became more widespread throughout nursing settings during the pandemic. Nurse leaders have been identified as responsible for ensuring the environmental safety and personal well-being of their colleagues during and after pandemics.¹⁴

Studies of HCW experiences during COVID-19 provide many insights into future preparedness, strategies to best handle another pandemic during its acute stage, and techniques to address issues that might persist. This study and others suggest that comprehensive interventions in preparation for, during, and after a pandemic are needed. We break down strategies into pandemic and postpandemic interventions based on a synthesis of the literature and the research team’s knowledge and expertise.^{3,14-16,27,29,36,38-44}

Pandemic interventions. During a pandemic, it is important that nurses are adequately cared for to ensure they can continue to provide quality care for others. Resources supporting emotional well-being and addressing moral distress offered during a pandemic are essential. Implementing meaningful strategies could enhance nurses’ health and wellbeing. It is essential that leaders provide nurses a safe work environment/experience during a pandemic by instituting meaningful resources. In addition, developing best practices for leadership are critical.

Postpandemic interventions. Personal experiences of depression, burnout, and moral distress have not spontaneously resolved as the pandemic receded. Providing postpandemic interventions to lessen ongoing and lingering depressive, burnout, and moral distress symptoms experienced by frontline workers are critical. These interventions might prevent long-term health issues and the exodus of nurses.

Postpandemic interventions should include the integration of pandemic planning into new or existing educational or training programs for staff. Promotion and support of mental health services by health system leadership for nursing personnel implemented as a usual service will play an important role in preparing for future pandemics. A key role in preparation is developing and maintaining cooperation and ongoing mutual understanding, respect, and communication between leadership and nursing staff.

Future Research

This study’s findings inform VHA leadership and society about how a large group of nurses were impacted by COVID-19 while caring for patients in inpatient and outpatient settings and could provide a basis for extending this research to other groups of nurses or health care personnel. Future research might be helpful in identifying the impact of COVID-19 on nursing leadership. During conversations with nursing leadership, a common theme identified was that nurses did not feel that leadership was fully prepared for the level of emergency the pandemic created both personally and professionally; leadership expressed experiences similar to nurses providing direct care and felt powerless to help their nursing staff. Other areas of research could include identifying underlying factors contributing to burnout and moral distress and describing nurses’ expectations of or needs from leadership to best manage burnout and moral distress.

Limitations

Experiences of nurses who stopped working were not captured and information about their experiences might have different results. The survey distribution was limited to 2 emails (an initial email and a second at midpoint) sent at the discretion of the nurse executive of each facility. The study timeline was long because of complex regulatory protective processes inherent in the VHA system for researchers to include initial institutional review board review process, union notifications, and each facility’s response to the survey. Although 860 nurses participated, this was 15% of the 5586 VISN 21 nurses at the time of the study. Many clinical inpatient nurses do not have regular access to email, which might have impacted participation rate.

CONCLUSIONS

This study identified the impact COVID-19 had on nurses who worked in a large hospital system. The research team outlined strategies to be employed during and after the pandemic, such as preplanning for future pandemics to provide a framework for a comprehensive pandemic response protocol.

This study adds to generalized knowledge because it captured voices of inpatient and outpatient nurses, the latter had not been previously studied. As nurses and health care organizations move beyond the pandemic with a significant number of nurses continuing to experience effects, there is a need to institute interventions to assist nurses in healing and begin preparations for future pandemics.