Mental Health Service Use in Depressed Military Personnel: A Systematic Review

Evaluating the Acceptability and Feasibility of Collecting Passive Smartphone Data to Estimate Psychological Functioning in U.S. Service Members and Veterans: A Pilot Study

INTRODUCTION

This study investigated the acceptability and feasibility of digital phenotyping in a military sample with a history of traumatic brain injury and co-occurring psychological and cognitive symptoms. The first aim was to evaluate the acceptability of digital phenotyping by (1a) quantifying the proportion of participants willing to download the app and rates of dropout and app discontinuation and (1b) reviewing the stated reasons for both refusing and discontinuing use of the app. The second aim was to investigate technical feasibility by (2a) characterizing the amount and frequency of transferred data and (2b) documenting technical challenges. Exploratory aim 3 sought to leverage data on phone and keyboard interactions to predict if a participant (a) is depressed and (b) has depression that improves over the course of the study.

MATERIALS AND METHODS

A passive digital phenotyping app (Mindstrong Discovery) functioned in the background of the participants' smartphones and passively collected phone usage and typing kinematics data.

RESULTS

Fifteen out of 16 participants (93.8%) consented to install the app on their personal smartphone devices. Four participants (26.7%) discontinued the use of the app partway through the study, primarily because of keyboard usability and technical issues. Fourteen out of 15 participants (93.3%) had at least one data transfer, and the median number of days with data was 40 out of a possible 57 days. The exploratory machine learning models predicting depression status and improvement in depression performed better than chance.

CONCLUSIONS

The findings of this pilot study suggest that digital phenotyping is acceptable and feasible in a military sample and provides support for future larger investigations of this technology.

Metabolomics and Self-Reported Depression, Anxiety, and Phobic Symptoms in the VA Normative Aging Study

Traditional approaches to understanding metabolomics in mental illness have focused on investigating a single disorder or comparisons between diagnoses, but a growing body of evidence suggests substantial mechanistic overlap in mental disorders that could be reflected by the metabolome. In this study, we investigated associations between global plasma metabolites and abnormal scores on the depression, anxiety, and phobic anxiety subscales of the Brief Symptom Inventory (BSI) among 405 older males who participated in the Normative Aging Study (NAS). Our analysis revealed overlapping and distinct metabolites associated with each mental health dimension subscale and four metabolites belonging to xenobiotic, carbohydrate, and amino acid classes that were consistently associated across all three symptom dimension subscales. Furthermore, three of these four metabolites demonstrated a higher degree of alteration in men who reported poor scores in all three dimensions compared to men with poor scores in only one, suggesting the potential for shared underlying biology but a differing degree of perturbation when depression and anxiety symptoms co-occur. Our findings implicate pathways of interest relevant to the overlap of mental health conditions in aging veterans and could represent clinically translatable targets underlying poor mental health in this high-risk population.

Impact of the COVID-19 pandemic on the mental health and well-being of Veterans' spouses: a cross sectional analysis

BACKGROUND

COVID-19 has negatively impacted the mental health and well-being of both Canadians and the world as a whole, with Veterans, in particular, showing increased rates of depression, anxiety, and PTSD. Spouses and common-law partners often serve as primary caregivers and sources of support for Veterans, which may have a deleterious effect on mental health and increase risk of burnout. Pandemic related stressors may increase burden and further exacerbate distress; yet the effect of the pandemic on the mental health and well-being of Veterans' spouses is currently unknown. This study explores the self-reported mental health and well-being of a group of spouses of Canadian Armed Forces Veterans and their adoption of new ways to access healthcare remotely (telehealth), using baseline data from an ongoing longitudinal survey.

METHODS

Between July 2020 and February 2021, 365 spouses of Veterans completed an online survey regarding their general mental health, lifestyle changes, and experiences relating to the COVID-19 pandemic. Also completed were questions relating to their use of and satisfaction with health-care treatment services during the pandemic.

RESULTS

Reported rates of probable major depressive disorder (MDD), generalized anxiety disorder (GAD), alcohol use disorder (AUD), and PTSD were higher than the general public, with 50-61% believing their symptoms either directly related to or were made worse by the pandemic. Those reporting being exposed to COVID-19 were found to have significantly higher absolute scores on mental health measures than those reporting no exposure. Over 56% reported using telehealth during the pandemic, with over 70% stating they would continue its use post-pandemic.

CONCLUSIONS

This is the first Canadian study to examine the impact of the COVID-19 pandemic specifically on the mental health and well-being of Veterans' spouses. Subjectively, the pandemic negatively affected the mental health of this group, however, the pre-pandemic rate for mental health issues in this population is unknown. These results have important implications pertaining to future avenues of research and clinical/programme development post-pandemic, particularly relating to the potential need for increased support for spouses of Veterans, both as individuals and in their role as supports for Veterans.

Nigella sativa extract in the treatment of depression and serum Brain-Derived Neurotrophic Factor (BDNF) levels

BACKGROUND

Here, we aimed to investigate the therapeutic effects of Nigella sativa extract on serum brain-derived neurotrophic factor (BDNF) and depression score in patients with depression.

MATERIALS AND METHODS

This clinical trial was performed in 2021 in the hospitals of military forces in Tehran on 52 male patients with major depressive disorder treated with sertraline. We used the Depression, Anxiety, and Stress Scale-21 Items (DASS-21) questionnaire to assess the patients. Serum BDNF levels were measured by the enzyme-linked immunosorbent assay. Patients were then divided into two groups receiving 1000 mg N. sativa oil extract, daily, and placebo. Both groups received sertraline for at least 3 months. DASS-21 questionnaire and serum BDNF levels were measured after 10 weeks.

RESULTS

After treatments, we observed significantly decreased DASS-21 score (-11.24 ± 5.69) in the intervention group (P < 0.001) and placebo (-2.72 ± 6.19, P = 0.032), but patients in the intervention group had significantly lower scores (50.1 ± 6.8 vs. 58.2 ± 5.6, respectively, P < 0.001). Furthermore, patients in the intervention group had significantly decreased depression score (-5.5 ± 2.47, P < 0.001) and lower scores compared to the placebo (P < 0.001) (18.6 ± 2.7 vs. 23.4 ± 2.1 in intervention and placebo, respectively). We also observed significantly increased BDNF levels in the intervention group after the treatments (6.08 ± 3.76, P < 0.001) compared to the placebo group (29.4 ± 3.6 vs. 24.9 ± 2.1, P < 0.001). Serum BDNF levels had also significant reverse correlations with DASS-21 score (r = -0.35, P = 0.011) and depression score (r = -0.45, P = 0.001).

CONCLUSION

The use of N. sativa resulted in decreased depression score and increase in serum BDNF levels that indicate the importance and efficacy of this drug.

Well-being of Canadian Veterans during the COVID-19 pandemic: cross-sectional results from the COVID-19 Veteran well-being study

BACKGROUND

The impacts of the COVID-19 pandemic have disproportionally affected different population groups. Veterans are more likely to have pre-existing mental health conditions compared to the general Canadian population, experience compounded stressors resulting from disruptions to familial, social, and occupational domains, and were faced with changes in health-care delivery (e.g. telehealth). The objectives of this study are to assess (a) the mental health impact of COVID-19 and related life changes on the well-being of Veterans and (b) perceptions of and satisfaction with changes in health-care treatments and delivery during the pandemic.

METHODS

A total of 1136 Canadian Veterans participated in an online survey. Participants completed questions pertaining to their mental health and well-being, lifestyle changes, and concerns relating to the COVID-19 pandemic, as well as experiences and satisfaction with health-care treatments during the pandemic.

RESULTS

Results showed that 55.9% of respondents reported worse mental health functioning compared to before the pandemic. The frequency of probable posttraumatic stress disorder, major depressive disorder, generalized anxiety disorder, alcohol use disorder, and suicidal ideation were 34.2%, 35.3%, 26.8%, 13.0%, and 22.0%, respectively. Between 38.6% and 53.1% of respondents attributed their symptoms as either directly related to or exacerbated by the pandemic. Approximately 18% of respondents reported using telehealth for mental health services during the pandemic, and among those, 72.8% indicated a choice to use telehealth even after the pandemic.

CONCLUSIONS

This study found that Veterans experienced worsening mental health as a result of the COVID-19 pandemic. The use of telehealth services was widely endorsed by mental health treatment-seeking Veterans who transitioned to virtual care during the pandemic. Our findings have important clinical and programmeadministrator implications, emphasizing the need to reach out to support veterans, especially those with pre-existing mental health conditions and to enhance and maintain virtual care even post-pandemic.

Pathways to mental health care in active military populations across the Five-Eyes nations: An integrated perspective

Military service is associated with increased risk of mental health problems. Previous reviews have pointed to under-utilization of mental health services in military populations. Building on the most recent systematic review, our narrative, critical review takes a complementary approach and considers research across the Five-Eyes nations from the past six years to update and broaden the discussion on pathways to mental healthcare in military populations. We find that at a broad population level, there is improvement in several indicators of mental health care access, with greater gains in initial engagement, time to first treatment contact, and subjective satisfaction with care, and smaller gains in objective indicators of adequacy of care. Among individual-level barriers to care-seeking, there is progress in improving recognition of need for care and reducing stigma concerns. Among organizational-level barriers, there are advances in availability of services and cultural acceptance of care-seeking. Other barriers, such as concerns around confidentiality, career impact, and deployability persist, however, and may account for some remaining unmet need. To address these barriers, new initiatives that are more evidence-based, theoretically-driven, and culturally-sensitive, are therefore needed, and must be rigorously evaluated to ensure they bring about additional improvements in pathways to care.

The global prevalence of depression, suicide ideation, and attempts in the military forces: a systematic review and Meta-analysis of cross sectional studies

BACKGROUND

Given the wide range of depressive disorders, suicidal ideation and suicide attempts in various military studies around the world, determining the exact prevalence of these disorders in line with health planning as well as care and treatment service designing for military forces can be useful. The aim of the present meta-analysis was to determine the pooled prevalence of depressive disorders, suicide thoughts, and attempts in the military.

METHODS

The present systematic review and meta-analysis study was performed based on PRISMA criteria in 5 steps of the search strategy, screening and selection of articles, data extraction, evaluation of article quality and meta-analysis. International databases (PubMed (Medline), Scopus, Web of science, Embase (Elsevier), PsycInfo (Ovid), Cochrane CENTRAL (Ovid)) were searched using related keywords extracted from Mesh and Emtree. After screening and final selection of articles, data were extracted and qualitative evaluation was performed using the NOS checklist.

RESULTS

The results of meta-analysis showed that the prevalence of depression in active military forces and veterans was 23% (%95 CI: 20-26%) and 20% (%95 CI: 18-22%), respectively. In addition, the prevalence of suicidal ideation and attempts in the military was 11% (%95 CI: 10-13%) and 11% (%95 CI: 9-13%), respectively. The prevalence of suicide ideation and attempts in drug-using military was 18% (%95 CI: 7-33%) and 30% (%95 CI: 23-36%), respectively. The prevalence of suicidal ideation and attempts in military consuming alcohol were 9% (%95 CI: 4-13%) and 8% (%95 CI: 7-10%), respectively. In militaries with AIDS / HIV, the prevalence of suicide attempts was 5% (%95 CI: 4-8%).

CONCLUSION

Therefore, it is necessary to develop and design training and intervention programs in order to increase the awareness of the military, especially veterans, to prevent the occurrence of suicide and depression.

Machine Learning Methods to Evaluate the Depression Status of Chinese Recruits: A Diagnostic Study

PURPOSE

Traditional questionnaires assessing the severity of depression are limited and might not be appropriate for military personnel. We intend to explore the diagnostic ability of three machine learning methods for evaluating the depression status of Chinese recruits, using the Chinese version of Beck Depression Inventory-II (BDI-II) as the standard.

PATIENTS AND METHODS

Our diagnostic study was carried out in Luoyang City (Henan Province, China; 10/16/2018-12/10/2018) with a sample of 1000 Chinese male recruits selected using cluster convenient sampling. All participants completed the BDI and 3 questionnaires including the data of demographics, military careers and 18 factors. The participants were randomly selected as the training set and the testing at 2:1. The machine learning methods tested for assessing the presence or absence of depression status were neural network (NN), support vector machine (SVM), and decision tree (DT).

RESULTS

A total of 1000 participants completed the questionnaires, with 223 reporting depression status and 777 not. The highest sensitivity was observed for DT (94.1%), followed by SVM (93.4%) and NN (93.1%). The highest specificity was observed for NN (60.0%), followed by SVM (58.8%) and DT (43.3%). The area under the curve (AUC) of the SVM was the largest (0.862) compared with NN (0.860) and DT (0.734). The regression prediction error and error volatility of the SVM were the smallest.

CONCLUSION

The SVM has the smallest prediction error and error volatility, as well as the largest AUC compared with NN and DT for assessing the presence or absence of depression status in Chinese recruits.