Suicidal Ideation: Linking the Role of Major Depressive Disorder & Noncombat Trauma

Research Paper Title

Factors Associated With Suicide Ideation in US Army Soldiers During Deployment in Afghanistan.

Background

Understanding suicide ideation (SI) during combat deployment can inform prevention and treatment during and after deployment.

Therefore the purpose of this study was to examine associations of sociodemographic characteristics, lifetime and past-year stressors, and mental disorders with 30-day SI among a representative sample of US Army soldiers deployed in Afghanistan.

Methods

In this survey study, soldiers deployed to Afghanistan completed self-administered questionnaires in July 2012. The sample was weighted to represent all 87 032 soldiers serving in Afghanistan. Prevalence of lifetime, past-year, and 30-day SI and mental disorders was determined. Logistic regression analyses examined risk factors associated with SI. Data analyses for this study were conducted between August 2018 and August 2019.

The main outcomes and measures were suicide ideation, lifetime and 12-month stressors, and mental disorders were assessed with questionnaires. Administrative records identified sociodemographic characteristics and suicide attempts.

Results

A total of 3,957 soldiers (3473 [weighted 87.5%] male; 2135 [weighted 52.6%] aged ≤29 years) completed self-administered questionnaires during their deployment in Afghanistan.

Lifetime, past-year, and 30-day SI prevalence estimates were 11.7%, 3.0%, and 1.9%, respectively. Among soldiers with SI, 44.2% had major depressive disorder (MDD) and 19.3% had posttraumatic stress disorder in the past 30-day period.

A series of analyses of the 23 grouped variables potentially associated with SI resulted in a final model of sex; race/ethnicity; lifetime noncombat trauma; past 12-month relationship problems, legal problems, and death or illness of a friend or family member; and MDD.

In this final multi-variable model, white race/ethnicity (odds ratio [OR], 3.1 [95% CI, 1.8-5.1]), lifetime noncombat trauma (OR, 2.1 [95% CI, 1.1-4.0]), and MDD (past 30 days: OR, 31.8 [95% CI, 15.0-67.7]; before past 30 days: OR, 4.9 [95% CI, 2.5-9.6]) were associated with SI.

Among the 85 soldiers with past 30-day SI, from survey administration through 12 months after returning from deployment, 6% (5 participants) had a documented suicide attempt vs 0.14% (6 participants) of the 3872 soldiers without SI.

Conclusions

This study suggests that major depressive disorder and noncombat trauma are important factors in identifying SI risk during combat deployment.

Reference

Ursano, R.J., Mash, H.B.H., Kessler, R.C., Naifeh, J.A., Fullerton, C.S., Aliaga, P.A., Stokes, C.M., Wynn, G.H., Ng, T.H.H., Dinh, H.M., Gonzalez, O.I., Zaslavsky, A.M., Sampson, N.A., Kao, T-C., Heeringa, S.G., Nock, M.K. & Stein, M.B. (2020) Factors Associated With Suicide Ideation in US Army Soldiers During Deployment in Afghanistan. JAMA Network Open. 3(1):e1919935. doi: 10.1001/jamanetworkopen.2019.19935.

Is Type 2 Diabetes an Independent Risk Factor for Alzheimer Patients with Depression?

Research Paper Title

Analysis of Risk Factors for Depression in Alzheimer’s Disease Patients.

Background

Depression, which affects about 52% of Alzheimer’s disease (AD) patients, can worsen cognitive impairment and increase mortality and suicide rates.

The researchers hope to provide clinical evidence for the prevention and treatment of depression in AD patients by investigating related risk factors of depression in AD patients.

Methods

158 AD inpatients of the Department of Neurology, Daping Hospital from September 2017 to March 2019 were enrolled. General information, laboratory tests, cognitive and emotional function assessments of the inpatients were collected.

Logistic regression was used to analyse the risk factors of depression in AD patients, and the relationship between 17 Hamilton depression scale scores and HbA1c levels in AD patients was further analysed.

Results

The prevalence of age, gender, hypertension, hyperlipidemia, Type 2 diabetes mellitus (T2DM), and white matter lesions (WML) in the AD with depression group was significantly different from without depression group.

Hypertension, T2DM, and WML are independent risk factors for depression in AD patients.

The depression scores of AD patients with HbA1c>6.5% were significantly higher than AD patients with HbA1c ≤ 6.5%, and there were significant difference in depression scale scores between using anti-diabetes drugs group and not using anti-diabetes drugs group whose HbA1c level is >6.5%, while no difference in depression scores between using anti-diabetes drugs group and not using anti-diabetes drugs group whose HbA1c level is ≤6.5%.

Conclusions

T2DM is an independent risk factor for AD patients with depression.

Increased HbA1c levels aggravate depression in AD patients, and controlling HbA1c levels and anti-diabetes drugs can reduce the severity of depression in AD patients.

Reference

Yang, H., Hong, W., Chen, L., Tao, Y., Peng, Z. & Zhou, H. (2020) Analysis of Risk Factors for Depression in Alzheimer’s Disease Patients. The International Journal of Neuroscience. 1-6. doi: 10.1080/00207454.2020.1730369. Online ahead of print.

Are Soldiers-in-training Likely to Seek Help when Experiencing a Problem?

Research Paper Title

Identifying Risk and Resilience Factors Associated With the Likelihood of Seeking Mental Health Care Among U.S. Army Soldiers-in-Training

Background

The Department of Defence aims to maintain mission readiness of its service members. Therefore, it is important to understand factors associated with treatment seeking in order to identify areas of prevention and intervention early in a soldier’s career that can promote positive functioning and increase their likelihood of seeking mental health care when necessary.

Methods

Using a theory of planned behaviour lens, this study identified potential barriers (risk) and facilitators (resilience) to treatment seeking among 24,717 soldiers-in-training who participated in the New Soldiers Study component of the “Army Study to Assess Risk and Resilience in Servicemembers” (Army STARRS). Hierarchal linear regression modelling and independent samples t-tests were used to examine associations between demographics and study variables, intersections of risk and resilience, and to explore differences in the likelihood of seeking help based on mental health diagnoses.

Results

A four-stage hierarchical linear regression was conducted, using likelihood of help-seeking as the dependent variable, to identify the most salient factors related to help-seeking. “Step one” of the analysis revealed soldiers-in-training who identified as female, Hispanic or Other ethnicity, and married, divorced, or separated reported a greater likelihood of seeking help. “Step two” of the analysis indicated soldiers-in-training with a history of sexual trauma, experience of impaired parenting, and clinical levels of mental health symptomatology (anxiety, depression, PTSD) reported a greater likelihood of seeking help.

Inversely, soldiers-in-training with a history of emotional trauma and parental absence/separation reported a lower likelihood of seeking help. “Step three” of the analysis demonstrated soldiers-in-training with a prior history of seeking help and larger social networks had a greater likelihood of seeking help. “Step four” of the analysis revealed several interactive effects between risk and resilience factors.

Specifically, soldiers-in-training who reported greater depressive symptomatology in combination with prior history of treatment seeking reported a greater likelihood of help seeking, whereas soldiers-in-training who reported prior sexual trauma and PTSD in combination with large social networks reported a lower likelihood of seeking help. Finally, a greater percentage of soldiers-in-training with clinical levels of anxiety, depression, and PTSD indicated they would likely seek help in comparison to soldiers-in-training without clinical symptoms.

Conclusions

Findings suggest few soldiers-in-training are likely to seek help when experiencing a problem. General efforts to encourage help-seeking when needed are warranted with particular focus on subsets of soldiers-in-training (e.g., men, those with a history of some adverse childhood experiences).

Strengths of this study include the examination of a large sample of soldiers-in-training to identify possible leverage points for early intervention or prevention prior to entering stressful military operating environments.

Limitations of this study include the examination of only one military branch and exclusion of soldiers not “in-training.”

Future studies could consider replicating the current study using a sample of military personnel longitudinally to track behavioral trends as well as looking at military populations outside of basic combat training.

Reference

Duncan, J.M., Reed-Fitzke, K., Ferraro, A.J., Wojciak, A.S., Smith, K.M. & Sanchez, K. (2020) Identifying Risk and Resilience Factors Associated With the Likelihood of Seeking Mental Health Care Among U.S. Army Soldiers-in-Training. Military Medicine. doi: 10.1093/milmed/usz483. Online ahead of print.

Is there a Link between Sleeplessness and Alzheimer’s?

Just one sleepless night raises levels of a protein linked to Alzheimer’s disease in the blood of young men (Benedict et al., 2020).

This suggests getting into good sleep habits at an early age may help ward off the illness.

People with Alzheimer’s have clumps of two sticky proteins –
beta-amyloid and tau – in their brains. Previous work has found that one night of sleep deprivation raises beta-amyloid levels in our brains, but less is known about tau.

Jonathan Cedernaes at Uppsala University in Sweden and his team
recruited 15 healthy young men. They measured tau levels in the
men’s blood after a full night’s sleep and after a night of no sleep.

After the sleepless night, tau levels in blood rose by 17%. After
the good night, the rise was 2%.

While it is a small study that looked only at men, the finding adds to growing evidence that people with poor sleep are more likely to develop Alzheimer’s decades later, says Cedernaes.

More research is needed to confirm that sleep deprivation increases tau in the brain, since blood levels are not necessarily indicative of amounts in the brain, says Cedernaes. And higher blood levels of tau after sleep deprivation could be a sign that the brain is clearing out the protein rather than accumulating it, he says.

The role tau plays in Alzheimer’s is unclear – it may be a side effect, not a cause. Similarly, while lack of sleep has been linked to Alzheimer’s disease, it is possible that this is an early sign of
the condition, rather than a contributing factor.

References

Benedict, C., Blennow, K., Zetterberg, H. & Cedarnaes, J. (2020) Effects of acute sleep loss on diurnal plasma dynamics of CNS health biomarkers in young men. Neurology. 94(11). DOI: https://doi.org/10.1212/WNL.0000000000008866.

Klein, A. (2020) Alzheimer’s Protein Rise Without Sleep. New Scientist. 18 January 2020, pp.17.

Can We Use Smartphones in the Assessment & Prediction of Mental Health?

Research Paper Title

Digital phenotyping for assessment and prediction of mental health outcomes: a scoping review protocol.

Background

Rapid advancements in technology and the ubiquity of personal mobile digital devices have brought forth innovative methods of acquiring healthcare data.

Smartphones can capture vast amounts of data both passively through inbuilt sensors or connected devices and actively via user engagement.

This scoping review aims to evaluate evidence to date on the use of passive digital sensing/phenotyping in assessment and prediction of mental health.

Methods

The methodological framework proposed by Arksey and O’Malley will be used to conduct the review following the five-step process.

A three-step search strategy will be used:

  1. Initial limited search of online databases namely, MEDLINE for literature on digital phenotyping or sensing for key terms;
  2. Comprehensive literature search using all identified keywords, across all relevant electronic databases: IEEE Xplore, MEDLINE, the Cochrane Database of Systematic Reviews, PubMed, the ACM Digital Library and Web of Science Core Collection (Science Citation Index Expanded and Social Sciences Citation Index), Scopus; and
  3. Snowballing approach using the reference and citing lists of all identified key conceptual papers and primary studies.

Data will be charted and sorted using a thematic analysis approach.

Findings

The findings from this systematic scoping review will be reported at scientific meetings and published in a peer-reviewed journal.

Reference

Spinazze, P., Rykov, Y., Bottle, A. & Car, J. (2019) Digital phenotyping for assessment and prediction of mental health outcomes: a scoping review protocol. BMJ Open. 9(12):e032255. doi: 10.1136/bmjopen-2019-032255.

Why is it Important to Identify Mental Health Problems among Employees in Physically Demanding Jobs?

Research Paper Title

Physical working conditions and subsequent disability retirement due to any cause, mental disorders and musculoskeletal diseases: does the risk vary by common mental disorders?

Background

Physical work exposures and common mental disorders (CMD) have been linked to increased risk of work disability, but their joint associations with disability retirement due to any cause, mental disorders or musculoskeletal diseases have not been examined.

Methods

The data for exposures and covariates were from the Finnish Helsinki Health Study occupational cohort surveys in 2000-2002, 2007 and 2012.

The researchers used 12,458 observations from 6159 employees, who were 40-60 years old at baseline.

CMD were measured by the General Health Questionnaire (GHQ-12, cut-off point 3+).

Four self-reported work exposures (hazardous exposures, physical workload, computer and shift work) were combined with CMD and categorized as “neither”, “work exposure only”, “CMD only”, and “both”.

Associations with register-based disability retirement were assessed with Cox proportional hazards models for sample survey data adjusting for confounders over 5-year follow-up.

Additionally, synergy indices were calculated for the combined effects.

Results

Those reporting CMD and high physical workload had a greater risk of disability retirement due to any cause (HR 4.26, 95% CI 3.60-5.03), mental disorders (HR 5.41, 95% CI 3.87-7.56), and musculoskeletal diseases (HR 4.46, 95% CI 3.49-5.71) when compared to those with neither.

Synergy indices indicated that these associations were synergistic.

Similar associations were observed for CMD and hazardous exposures, but not for combined exposures to CMD and computer or shift work.

Conclusions

Identification of mental health problems among employees in physically demanding jobs is important to support work ability and reduce the risk of premature exit from work due to disability.

Reference

Halonen J.I., Mänty, M., Pietiläinen, O., Kujanpää, T., Kanerva, N., Lahti, J., Lahelma, E., Rahkonen, O. & Lallukka, T. (2020) Physical working conditions and subsequent disability retirement due to any cause, mental disorders and musculoskeletal diseases: does the risk vary by common mental disorders? Social Psychiatry and Psychiatric Epidemiology. doi: 10.1007/s00127-019-01823-6. [Epub ahead of print].

Mental Stress Tasks & the Prefrontal Cortex

Research Paper Title

Relationship Between Cerebral Blood Oxygenation and Electrical Activity During Mental Stress Tasks: Simultaneous Measurements of NIRS and EEG.

Background

The incidence of stress-induced psychological and somatic diseases has been increasing rapidly, and it is important to clarify the neurophysiological mechanisms of stress response in order to establish effective stress management methods.

The researchers previously reported that the prefrontal cortex (PFC) plays an important role in stress response.

Methods

In the present study, the researchers employed near-infrared spectroscopy (NIRS) and electroencephalography (EEG) to investigate the characteristics of PFC activity during mental arithmetic tasks.

A two-channel NIRS device was used to measure haemoglobin (Hb) concentration changes in the bilateral PFC during a mental arithmetic task (2 min) in normal adults.

Simultaneously, EEG was used to also measure bilateral PFC activity during the same task.

They evaluated concentration changes of oxy-Hb induced by the task while analysing α wave changes using power spectrum analysis.

Results

It was observed that oxy-Hb in the bilateral PFC increased significantly during the task (p < 0.05), while α wave power in the PFC decreased significantly (p < 0.01).

Conclusions

The present results indicate that mental stress tasks caused the activation of the bilateral PFC.

Simultaneous measurements of NIRS and EEG are useful for evaluating the neurophysiological mechanism of stress responses in the brain.

Reference

Nagasawa, Y., Ishida, M., Komuro, Y., Ushioda, S., Hu, L. & Sakatani, K. (2020) Relationship Between Cerebral Blood Oxygenation and Electrical Activity During Mental Stress Tasks: Simultaneous Measurements of NIRS and EEG. Advances in Experimental Medicine and Biology. 1232:99-104. doi: 10.1007/978-3-030-34461-0_14.

Can We Model Essential Connections in Obsessive-Compulsive Disorder Patients using Functional MRI?

Research Paper Title

Modeling essential connections in obsessive-compulsive disorder patients using functional MRI.

Background

Obsessive-compulsive disorder (OCD) is a mental disease in which people experience uncontrollable and repetitive thoughts or behaviours.

Clinical diagnosis of OCD is achieved by using neuropsychological assessment metrics, which are often subjectively affected by psychologists and patients.

In this study, the researchers propose a classification model for OCD diagnosis using functional MR images.

Methods

Using functional connectivity (FC) matrices calculated from brain region of interest (ROI) pairs, a novel Riemann Kernel principal component analysis (PCA) model is employed for feature extraction, which preserves the topological information in the FC matrices.

Hierarchical features are then fed into an ensemble classifier based on the XGBoost algorithm.

Finally, decisive features extracted during classification are used to investigate the brain FC variations between patients with OCD and healthy controls.

Results

The proposed algorithm yielded a classification accuracy of 91.8%.

Additionally, the well-known cortico-striatal-thalamic-cortical (CSTC) circuit and cerebellum were found as highly related regions with OCD.

To further analyse the cerebellar-related function in OCD, the researchers demarcated cerebellum into three sub-regions according to their anatomical and functional property.

Using these three functional cerebellum regions as seeds for brain connectivity computation, statistical results showed that patients with OCD have decreased posterior cerebellar connections.

Conclusions

This study provides a new and efficient method to characterise patients with OCD using resting-state functional MRI.

The researchers also provide a new perspective to analyse disease-related features.

Despite of CSTC circuit, their model-driven feature analysis reported cerebellum as an OCD-related region.

This paper may provide novel insight to the understanding of genetic aetiology of OCD.

Reference

Xing, X., Jin, L., Li, Q., Yang, Q., Han, H., Xu, C., Wei, Z., Zhan, Y., Zhou, X.S., Xue, Z., Chu, X., Peng, Z. & Shi, F. (2020) Modeling essential connections in obsessive-compulsive disorder patients using functional MRI. Brain and Behavior. 10(2):e01499. doi: 10.1002/brb3.1499. Epub 2020 Jan 1.

What is the Intergenerational Transmission of Risk for PTSD Symptoms & the Roles of Maternal and Child Emotion Dysregulation?

Research Paper Title

Intergenerational transmission of risk for PTSD symptoms in African American children: The roles of maternal and child emotion dysregulation.

Background

Emotion dysregulation is a transdiagnostic risk factor for many mental health disorders and develops in the context of early trauma exposure.

Research suggests inter-generational risk associated with trauma exposure and post-traumatic stress disorder (PTSD), such that maternal trauma experiences and related symptoms can negatively impact child outcomes across development.

The goals of the present study were to examine child and mother correlates of child PTSD symptoms and the unique roles of child and maternal emotion dysregulation in understanding child PTSD symptoms.

Methods

Subjects included 105 African American mother-child dyads from an urban hospital serving primarily low-income minority individuals.

Results

Correlational results showed that child trauma exposure, child emotion dysregulation, maternal depressive symptoms, maternal emotion dysregulation, and potential for maternal child abuse all were significantly associated with child PTSD symptoms (ps < 0.05).

Hierarchical linear regression models revealed that child trauma exposure, maternal depression, and maternal abuse potential accounted for 29% of the variance in child PTSD symptoms (p < 0.001).

Both child emotion dysregulation (Rchange² = 0.14, p < .001) and maternal emotion dysregulation (Rchange² = 0.04, p < .05) were significantly associated with child PTSD symptoms independent of other risk factors and potential for maternal abuse was no longer a significant predictor.

Conclusions

These results suggest that maternal emotion dysregulation may be an important factor in influencing their child’s PTSD symptoms above and beyond child-specific variables.

Both maternal and child emotion dysregulation could be valuable treatment targets for improving maternal mental health and parenting behaviours and bolstering child health outcomes, thus reducing inter-generational transmission of risk associated with trauma.

Reference

Powers, A., Stevens, J.S., O’Banion, D., Stenson, A.F., Kaslow, N., Jovanovic, T. & Bradley, B. (2020) Intergenerational transmission of risk for PTSD symptoms in African American children: The roles of maternal and child emotion dysregulation. Psychological Trauma: Theory, Research, Practice and Policy. doi: 10.1037/tra0000543. [Epub ahead of print].

Can Testing by Questionnaire Guide Decisions to Refer Adults in Mental Health Services to Autism Diagnostic Services?

Research Paper Title

Testing adults by questionnaire for social and communication disorders, including autism spectrum disorders, in an adult mental health service population.

Background

Autism is difficult to identify in adults due to lack of validated self-report questionnaires.

The researchers compared the effectiveness of the autism-spectrum quotient (AQ) and the Ritvo autism-Asperger’s diagnostic scale-revised (RAADS-R) questionnaires in adult mental health services in two English counties.

Methods

A sub-sample of adults who completed the AQ and RAADS-R were invited to take part in an autism diagnostic observation schedule (ADOS Module 4) assessment with probability of selection weighted by scores on the questionnaires.

Results

There were 364 men and 374 women who consented to take part. Recorded diagnoses were most commonly mood disorders (44%) and mental and behavioural disorders due to alcohol/substance misuse (19%), and 4.8% (95% CI [2.9, 7.5]) were identified with autism (ADOS Module 4 10+).

One had a pre-existing diagnosis of autism; five (26%) had borderline personality disorders (all female) and three (17%) had mood disorders.

The AQ and RAADS-R had fair test accuracy (area under receiver operating characteristic [ROC] curve 0.77 and 0.79, respectively).

AQ sensitivity was 0.79 (95% CI [0.54, 0.94]) and specificity was 0.77 (95% CI [0.65, 0.86]); RAADS-R sensitivity was 0.75 (95% CI [0.48, 0.93]) and specificity was 0.71 (95% CI [0.60, 0.81]).

Conclusions

The AQ and RAADS-R can guide decisions to refer adults in mental health services to autism diagnostic services.

Reference

Brugha, T., Tyrer, F., Leaver, A., Lewis, S., Seaton, S., Morgan, Z., Tromans, S. & van Rensburg, K. (2020) Testing adults by questionnaire for social and communication disorders, including autism spectrum disorders, in an adult mental health service population. International Journal of Methods in Psychiatric Research. 29(1):e1814. doi: 10.1002/mpr.1814. Epub 2020 Jan 10.