Research shows that highly educated individuals have at least 20 graphomotor features associated with clock drawing with hands set for '10 after 11' (Davoudi et al., 2021). Research has yet to understand clock drawing features in individuals with fewer years of education. In the current study, we compared older adults with < 8 years of education to those with > 9 years of education on number and pattern of graphomotor feature relationships in the clock drawing command condition.

Participants age 65+ from the University of Florida (UF) and UF Health (N= 10,491) completed both command and copy conditions of the digital Clock Drawing Test (dCDT) as a part of a federally-funded investigation. Participants were categorized into two education groups: < 8 years of education (n= 304) and > 9 years of education (n= 10,187). Propensity score matching was then used to match participants from each subgroup (n= 266 for each subgroup) on the following demographic characteristics: age, sex, race, and ethnicity (n= 532, age= 74.99±6.21, education= 10.41±4.45, female= 42.7%, non-white= 32.0%). Network models were derived using Bayesian Structure Learning (BSL) with the hill-climbing algorithm to obtain optimal directed acyclic graphs (DAGs) from all possible solutions in each subgroup for the dCDT command condition.

Both education groups retained 13 of 91 possible edges (14.29%). For the < 8 years of education group (education= 6.65±1.74, ASA= 3.08±0.35), the network included 3 clock face (CF), 7 digit, and 3 hour hand (HH) and minute hand (MH) independent, or “parent,” features connected to the retained edges (BIC= -7395.24). In contrast, the > 9 years of education group (education= 14.17±2.88, ASA= 2.90±0.46) network retained 1 CF, 6 digit, 5 HH and MH, and 1 additional parent features representing the total number of pen strokes (BIC= -6689.92). Both groups showed that greater distance from the HH to the center of the clock also had greater distance from the MH to the center of the clock [ßz(< 8 years)= 0.73, ßz(> 9 years)= 0.76]. Groups were similar in the size of the digit height relative to the distance of the digits to the CF [ßz(< 8 years)= 0.27, ßz(> 9 years)= 0.56]. Larger HH angle was associated with larger MH angle across groups [ßz(< 8 years)= 0.28, ßz(> 9 years)= 0.23].

Education groups differed in the ratio of dCDT parent feature types. Specifically, copy clock production in older adults with < 8 years of education relied more heavily on CF parent features. In contrast, older adults with > 9 years of education relied more heavily on HH and MH parent features. Individuals with < 8 years of education may more infrequently present the concept of time in the clock drawing command condition. This study highlights the importance of considering education level in interpreting dCDT scores and features.

Chronic musculoskeletal pain is associated with neurobiological, physiological, and cellular measures. Importantly, we have previously demonstrated that a biobehavioral and psychosocial resilience index appears to have a protective relationship on the same biomarkers. Less is known regarding the relationships between chronic musculoskeletal pain, protective factors, and brain aging. This study investigates the relationships between clinical pain, a resilience index, and brain age. We hypothesized that higher reported chronic pain would correlate with older appearing brains, and the resilience index will attenuate the strength of the relationship between chronic pain and brain age.

Participants were drawn from an ongoing observational multisite study and included adults with chronic pain who also reported knee pain (N = 135; age = 58.3 ± 8.1; 64% female; 49% non-Hispanic Black, 51% non-Hispanic White; education Mdn = some college; income level Mdn = $30,000 - $40,000; MoCA M = 24.27 ± 3.49). Measures included the Graded Chronic Pain Scale (GCPS), characteristic pain intensity (CPI) and disability, total pain body sites; and a cognitive screening (MoCA). The resilience index consisted of validated biobehavioral (e.g., smoking, waist/hip ratio, and active coping) and psychosocial measures (e.g., optimism, positive affect, negative affect, perceived stress, and social support). T1-weighted MRI data were obtained. Surface area metrics were calculated in FreeSurfer using the Human Connectome Project's multi-modal cortical parcellation scheme. We calculated brain age in R using previously validated and trained machine learning models. Chronological age was subtracted from predicted brain age to generate a brain age gap (BAG). With higher scores of BAG indicating predicated age is older than chronological age. Three parallel hierarchical regression models (each containing one of three pain measures) with three blocks were performed to assess the relationships between chronic pain and the resilience index in relation to BAG, adjusting for covariates. For each model, Block 1 entered the covariates, Block 2 entered a pain score, and Block 3 entered the resilience index.

GCPS CPI (R2 change = .033, p = .027) and GCPS disability (R2 change = 0.038, p = 0.017) significantly predicted BAG beyond the effects of the covariates, but total pain sites (p = 0.865) did not. The resilience index was negatively correlated and a significant predictor of BAG in all three models (p < .05). With the resilience index added in Block 3, both GCPS CPI (p = .067) and GCPS disability (p = .066) measures were no longer significant in their respective models. Additionally, higher education/income (p = 0.016) and study site (p = 0.031) were also significant predictors of BAG.

In this sample, higher reported chronic pain correlated with older appearing brains, and higher resilience attenuated this relationship. The biobehavioral and psychosocial resilience index was associated with younger appearing brains. While our data is cross-sectional, findings are encouraging that interventions targeting both chronic pain and biobehavioral and psychosocial factors (e.g., coping strategies, positive and negative affect, smoking, and social support) might buffer brain aging. Future directions include assessing if chronic pain and resilience factors can predict brain aging over time.

Research shows that highly educated individuals have at least 20 graphomotor features associated with clock drawing with hands set for '10 after 11' (Davoudi et al., 2021). Research has yet to understand clock drawing features in individuals with fewer years of education. In the current study, we compared older adults with < 8 years of education to those with > 9 years of education on number and pattern of graphomotor feature relationships in the clock drawing copy condition.

Participants age 65+ from the University of Florida (UF) and UF Health (N= 10,491) completed command and copy digital Clock Drawing Tests (dCDT) as a part of a federally-funded investigation. Participants were categorized into two groups: < 8 years of education (n= 304) and > 9 years of education (n= 10,187). Propensity score matching was used to match participants from each subgroup (n= 266 for each subgroup) on the following: age, sex, race, and ethnicity (n= 532, age= 74.99±6.21, education= 10.41±4.45, female= 42.7%, non-white= 32.0%). Network models were derived using Bayesian Structure Learning (BSL) with the hill-climbing algorithm to obtain optimal directed acyclic graphs (DAGs) from all possible solutions in each subgroup for the dCDT copy condition.

The < 8 years of education group (education= 6.65±1.74, ASA= 3.08±0.35), retained 12 of 91 possible edges (13.19%, BIC= -7775.50). The network retained 2 clock face (CF), 5 digit, and 5 hour hand (HH) and minute hand (MH) independent, or “parent,” features connected to the retained edges. In contrast, the > 9 years of education group (education= 14.17±2.88, ASA= 2.90±0.46) network retained 15 of 91 possible edges (16.48%, BIC= -8261.484). The network retained 2 CF, 6 digit, 4 HH and MH, and an additional 3 total stroke parent features. Both groups showed that greater distance from the HH to the clock center also had greater distance from the MH to the clock center (ßz= 0.73, both). Groups were similar in digit width size relative to digit height [ßz(< 8 years)= 0.72, ßz(> 9 years)= 0.74]. Digit height size related to CF area [ßz(< 8 years)= 0.44, ßz(> 9 years)= 0.62] and CF area related to the digit distance to the CF across groups [ßz(< 8 years)= 0.39, ßz(> 9 years)= 0.46]. Greater distance from the MH to the clock center was associated with smaller MH angle [ßz(< 8 years)= -0.35, ßz(> 9 years)= -0.31], whereas greater digit misplacement was associated with larger MH angle across groups [ßz(< 8 years)= 0.14, ßz(> 9 years)= 0.29].

Education groups differed in the ratio of dCDT parent feature types. Specifically, copy clock production in older adults with < 8 years of education relied more evenly across CF, digit, and MH and HH parent features. In contrast, those with > 9 years of education differed in the additional reliance on total stroke parent features. Individuals with < 8 years of education may more heavily rely upon visual referencing when copying a clock. This study highlights the importance of considering education level in interpreting dCDT scores and features.

Cognitive behavior therapy (CBT) is effective for most patients with a social anxiety disorder (SAD) but a substantial proportion fails to remit. Experimental and clinical research suggests that enhancing CBT using imagery-based techniques could improve outcomes. It was hypothesized that imagery-enhanced CBT (IE-CBT) would be superior to verbally-based CBT (VB-CBT) on pre-registered outcomes.

A randomized controlled trial of IE-CBT v. VB-CBT for social anxiety was completed in a community mental health clinic setting. Participants were randomized to IE (n = 53) or VB (n = 54) CBT, with 1-month (primary end point) and 6-month follow-up assessments. Participants completed 12, 2-hour, weekly sessions of IE-CBT or VB-CBT plus 1-month follow-up.

Intention to treat analyses showed very large within-treatment effect sizes on the social interaction anxiety at all time points (ds = 2.09–2.62), with no between-treatment differences on this outcome or clinician-rated severity [1-month OR = 1.45 (0.45, 4.62), p = 0.53; 6-month OR = 1.31 (0.42, 4.08), p = 0.65], SAD remission (1-month: IE = 61.04%, VB = 55.09%, p = 0.59); 6-month: IE = 58.73%, VB = 61.89%, p = 0.77), or secondary outcomes. Three adverse events were noted (substance abuse, n = 1 in IE-CBT; temporary increase in suicide risk, n = 1 in each condition, with one being withdrawn at 1-month follow-up).

Group IE-CBT and VB-CBT were safe and there were no significant differences in outcomes. Both treatments were associated with very large within-group effect sizes and the majority of patients remitted following treatment.

Even in cases with complexity, simple techniques can be useful to target a specific symptom. Intrusive mental images are highly disruptive, drive emotion, and contribute to maintaining psychopathology. Cognitive science suggests that we might target intrusive images using competing tasks.

We describe an imagery competing task technique within cognitive behavioural therapy (CBT) with a patient with bipolar disorder and post-traumatic stress disorder (PTSD) symptoms. The intervention – including Tetris computer game-play – was used (1) to target a specific image within one therapy session, and (2) to manage multiple images in daily life.

A single case (AB) design was used. (1) To target a specific image, the patient brought the image to mind and, after mental rotation instructions and game-play practice, played Tetris for 10 minutes. Outcomes, pre- and post-technique, were: vividness/distress ratings when the image was brought to mind; reported intrusion frequency over a week. (2) To manage multiple images, the patient used the intervention after an intrusive image occurred. Outcomes were weekly measures of: (a) imagery characteristics; (b) symptoms of PTSD, anxiety, depression and mania.

(1) For the target image, there were reductions in vividness (80% to 40%), distress (70% to 0%), and intrusion frequency (daily to twice/week). (2) For multiple images, there were reductions from baseline to follow-up in (a) imagery vividness (38%), realness (66%) and compellingness (23%), and (b) PTSD symptoms (Impact of Events Scale-Revised score 26.33 to 4.83).

This low-intensity intervention aiming to directly target intrusive mental imagery may offer an additional, complementary tool in CBT.

To describe the initial results of implementing pharmacogenomics testing in a community-based psychiatry practice and potential impacts on medication management.

Retrospective chart review of prospectively maintained medical records of all adult patients with pharmacogenomics results from 9/01/2017 to 6/30/2019 under the care of psychiatrist and clinical pharmacist.

A total of 51 patients met inclusion criteria. A total of 7 pharmacokinetic genes and, due to changes in the test report over time, a range of 6-10 pharmacodynamic genes relevant to psychotropic medications were evaluated per patient. Every patient had genetic variations, with an average of 6.1 per patient (range 3-9; SD= 1.5). Patients were taking an average of 3.6 (range 1-8; SD=1.7) psychiatric medications at the time of the genetic test, to treat an average of 5 psychiatric conditions (range 1-9; SD=2.2). An average of 1.2 (range 0-4; SD=1.0) gene-drug interactions were uncovered per patient. Following review by psychiatrist and pharmacist, medication adjustments resulted in patients remaining on an average of 3.6 psychiatric medications, but decreasing the average number of gene-drug interactions per patient to 0.8 (range 0-3, SD=0.8).

The large number of genetic variations observed per patient is consistent with previous findings 1-2. The decrease in number of gene-drug interactions following testing demonstrates the practical utility of pharmacogenomics information to guide medication therapy. This study did not examine outcomes such as improvement in psychiatric condition or reduction in medication adverse effects; however, these endpoints have been evaluated in other trials 3-4.

Pharmacogenomics testing presents an opportunity for a personalized medicine approach in a community-based psychiatry practice.

There is demand for new, effective and scalable treatments for depression, and development of new forms of cognitive bias modification (CBM) of negative emotional processing biases has been suggested as possible interventions to meet this need.

We report two double blind RCTs, in which volunteers with high levels of depressive symptoms (Beck Depression Inventory ii (BDI-ii) > 14) completed a brief course of emotion recognition training (a novel form of CBM using faces) or sham training. In Study 1 (N = 36), participants completed a post-training emotion recognition task whilst undergoing functional magnetic resonance imaging to investigate neural correlates of CBM. In Study 2 (N = 190), measures of mood were assessed post-training, and at 2-week and 6-week follow-up.

In both studies, CBM resulted in an initial change in emotion recognition bias, which (in Study 2) persisted for 6 weeks after the end of training. In Study 1, CBM resulted in increases neural activation to happy faces, with this effect driven by an increase in neural activity in the medial prefrontal cortex and bilateral amygdala. In Study 2, CBM did not lead to a reduction in depressive symptoms on the BDI-ii, or on related measures of mood, motivation and persistence, or depressive interpretation bias at either 2 or 6-week follow-ups.

CBM of emotion recognition has effects on neural activity that are similar in some respects to those induced by Selective Serotonin Reuptake Inhibitors (SSRI) administration (Study 1), but we find no evidence that this had any later effect on self-reported mood in an analogue sample of non-clinical volunteers with low mood (Study 2).

Despite a reported high rate of mental disorders in refugees, scientific knowledge on their risk of suicide attempt and suicide is scarce. We aimed to investigate (1) the risk of suicide attempt and suicide in refugees in Sweden, according to their country of birth, compared with Swedish-born individuals and (2) to what extent time period effects, socio-demographics, labour market marginalisation (LMM) and morbidity explain these associations.

Three cohorts comprising the entire population of Sweden, 16–64 years at 31 December 1999, 2004 and 2009 (around 5 million each, of which 3.3–5.0% refugees), were followed for 4 years each through register linkage. Additionally, the 2004 cohort was followed for 9 years, to allow analyses by refugees' country of birth. Crude and multivariate hazard ratios (HRs) with 95% confidence intervals (CIs) were computed. The multivariate models were adjusted for socio-demographic, LMM and morbidity factors.

In multivariate analyses, HRs regarding suicide attempt and suicide in refugees, compared with Swedish-born, ranged from 0.38–1.25 and 0.16–1.20 according to country of birth, respectively. Results were either non-significant or showed lower risks for refugees. Exceptions were refugees from Iran (HR 1.25; 95% CI 1.14–1.41) for suicide attempt. The risk for suicide attempt in refugees compared with the Swedish-born diminished slightly across time periods.

Refugees seem to be protected from suicide attempt and suicide relative to Swedish-born, which calls for more studies to disentangle underlying risk and protective factors.

Subclinical delusional ideas, including persecutory beliefs, in otherwise healthy individuals are heritable symptoms associated with increased risk for psychotic illness, possibly representing an expression of one end of a continuum of psychosis severity. The identification of variation in brain function associated with these symptoms may provide insights about the neurobiology of delusions in clinical psychosis.

A resting-state functional magnetic resonance imaging scan was collected from 131 young adults with a wide range of severity of subclinical delusional beliefs, including persecutory ideas. Because of evidence for a key role of the amygdala in fear and paranoia, resting-state functional connectivity of the amygdala was measured.

Connectivity between the amygdala and early visual cortical areas, including striate cortex (V1), was found to be significantly greater in participants with high (n = 43) v. low (n = 44) numbers of delusional beliefs, particularly in those who showed persistence of those beliefs. Similarly, across the full sample, the number of and distress associated with delusional beliefs were positively correlated with the strength of amygdala-visual cortex connectivity. Moreover, further analyses revealed that these effects were driven by those who endorsed persecutory beliefs.

These findings are consistent with the hypothesis that aberrant assignments of threat to sensory stimuli may lead to the downstream development of delusional ideas. Taken together with prior findings of disrupted sensory-limbic coupling in psychosis, these results suggest that altered amygdala-visual cortex connectivity could represent a marker of psychosis-related pathophysiology across a continuum of symptom severity.