Can Depression be Diagnosed by Response to Mother's Face? A Personalized Attachment-Based Paradigm for Diagnostic fMRI

OBJECTIVE: Objective measurement of depression remains elusive. Depression has been associated with insecure attachment, and both have been associated with changes in brain reactivity in response to viewing standard emotional and neutral faces. In this study, we developed a method to calculate predicted scores for the Beck Depression Inventory II (BDI-II) using personalized stimuli: fMRI imaging of subjects viewing pictures of their own mothers. METHODS: 28 female subjects ages 18-30 (14 healthy controls and 14 unipolar depressed diagnosed by MINI psychiatric interview) were scored on the Beck Depression Inventory II (BDI-II) and the Adult Attachment Interview (AAI) coherence of mind scale of global attachment security. Subjects viewed pictures of Mother (M), Friend (F) and Stranger (S), during functional magnetic resonance imaging (fMRI). Using a principal component regression method (PCR), a predicted Beck Depression Inventory II (BDI-II) score was obtained from activity patterns in the paracingulate gyrus (Brodmann area 32) and compared to clinical diagnosis and the measured BDI-II score. The same procedure was performed for AAI coherence of mind scores. RESULTS: Activity patterns in BA-32 identified depressed subjects. The categorical agreement between the derived BDI-II score (using the standard clinical cut-score of 14 on the BDI-II) and depression diagnosis by MINI psychiatric interview was 89%, with sensitivity 85.7% and specificity 92.8%. Predicted and measured BDI-II scores had a correlation of 0.55. Prediction of attachment security was not statistically significant. CONCLUSIONS: Brain activity in response to viewing one's mother may be diagnostic of depression. Functional magnetic resonance imaging using personalized paradigms has the potential to provide objective assessments, even when behavioral measures are not informative. Further, fMRI based diagnostic algorithms may enhance our understanding of the neural mechanisms of depression by identifying distinctive neural features of the illness

Complex modeling with detailed temporal predictors does not improve health records-based suicide risk prediction

Suicide risk prediction models can identify individuals for targeted intervention. Discussions of transparency, explainability, and transportability in machine learning presume complex prediction models with many variables outperform simpler models. We compared random forest, artificial neural network, and ensemble models with 1500 temporally defined predictors to logistic regression models. Data from 25,800,888 mental health visits made by 3,081,420 individuals in 7 health systems were used to train and evaluate suicidal behavior prediction models. Model performance was compared across several measures. All models performed well (area under the receiver operating curve [AUC]: 0.794-0.858). Ensemble models performed best, but improvements over a regression model with 100 predictors were minimal (AUC improvements: 0.006-0.020). Results are consistent across performance metrics and subgroups defined by race, ethnicity, and sex. Our results suggest simpler parametric models, which are easier to implement as part of routine clinical practice, perform comparably to more complex machine learning methods

Construct development: The Suicide Trigger Scale (STS-2), a measure of a hypothesized suicide trigger state

This study aims to develop the construct of a 'suicide trigger state' by exploring data gathered with a novel psychometric self-report instrument, the STS-2. The STS-2, was administered to 141 adult psychiatric patients with suicidal ideation. Multiple statistical methods were used to explore construct validity and structure. Cronbach's alpha (0.949) demonstrated excellent internal consistency. Factor analyses yielded two-component solutions with good agreement. The first component described near-psychotic somatization and ruminative flooding, while the second described frantic hopelessness. ROC analysis determined an optimal cut score for a history of suicide attempt, with significance of p < 0.03. Logistic regression analysis found items sensitive to history of suicide attempt described ruminative flooding, doom, hopelessness, entrapment and dread. The STS-2 appears to measure a distinct and novel clinical entity, which we speculatively term the 'suicide trigger state.' High scores on the STS-2 associate with reported history of past suicide attempt

Love and suicide: the structure of the Affective Intensity Rating Scale (AIRS) and its relation to suicidal behavior.

BACKGROUND: Suicide has been linked to intense negative affect. However, little is known about the range of affects experienced by suicidal persons, or the separate effects of affect valence and intensity. We examine a novel self-report scale, the 17-item Affective Intensity Rating Scale (AIRS), and its relation to suicidality in a high-risk sample. METHODOLOGY/PRINCIPAL FINDINGS: Patients presenting with suicidality were recruited from the Emergency Department in a large urban hospital, and completed a battery of assessments there. Structure of the AIRS was assessed using Maximum Likelihood Factor Analysis with Oblimin rotation. Convergent and divergent validity were assessed by regressing AIRS subscales against Brief Symptom Inventory subscales. Relation to suicidality was assessed by regression of suicide attempt status against scale and subscale scores, and individual items and two-way item interactions, along with significant clinical and demographic factors. 176 subjects were included in analyses. Three reliable subscales were identified within the AIRS measure: positive feelings towards self, negative feelings towards self, and negative feelings towards other. Only individual AIRS items associated significantly with suicide attempt status; strong 'feelings of love' associated positively with actual suicide attempt, while 'feelings of calm' and 'positive feelings towards self' associated negatively. Interaction analyses suggest 'calm' moderates the association of 'love' with suicide attempt. CONCLUSIONS/SIGNIFICANCE: Factor analysis of the AIRS is consistent with a circumplex model of affect. Affective dimensions did not predict suicidal behavior, but intense feelings of love, particularly in the absence of protective feelings of calm or positive self-view associated with current attempt

Emotional Responses to Suicidal Patients: Factor Structure, Construct, and Predictive Validity of the Therapist Response Questionnaire-Suicide Form

BackgroundMental health professionals have a pivotal role in suicide prevention. However, they also often have intense emotional responses, or countertransference, during encounters with suicidal patients. Previous studies of the Therapist Response Questionnaire-Suicide Form (TRQ-SF), a brief novel measure aimed at probing a distinct set of suicide-related emotional responses to patients found it to be predictive of near-term suicidal behavior among high suicide-risk inpatients. The purpose of this study was to validate the TRQ-SF in a general outpatient clinic setting.MethodsAdult psychiatric outpatients (N = 346) and their treating mental health professionals (N = 48) completed self-report assessments following their first clinic meeting. Clinician measures included the TRQ-SF, general emotional states and traits, therapeutic alliance, and assessment of patient suicide risk. Patient suicidal outcomes and symptom severity were assessed at intake and one-month follow-up. Following confirmatory factor analysis of the TRQ-SF, factor scores were examined for relationships with clinician and patient measures and suicidal outcomes.ResultsFactor analysis of the TRQ-SF confirmed three dimensions: (1) affiliation, (2) distress, and (3) hope. The three factors also loaded onto a single general factor of negative emotional response toward the patient that demonstrated good internal reliability. The TRQ-SF scores were associated with measures of clinician state anger and anxiety and therapeutic alliance, independently of clinician personality traits after controlling for the state- and patient-specific measures. The total score and three subscales were associated in both concurrent and predictive ways with patient suicidal outcomes, depression severity, and clinicians’ judgment of patient suicide risk, but not with global symptom severity, thus indicating specifically suicide-related responses.ConclusionThe TRQ-SF is a brief and reliable measure with a 3-factor structure. It demonstrates construct validity for assessing distinct suicide-related countertransference to psychiatric outpatients. Mental health professionals’ emotional responses to their patients are concurrently indicative and prospectively predictive of suicidal thoughts and behaviors. Thus, the TRQ-SF is a useful tool for the study of countertransference in the treatment of suicidal patients and may help clinicians make diagnostic and therapeutic use of their own responses to improve assessment and intervention for individual suicidal patients

Correction: Emergency Room Validation of the Revised Suicide Trigger Scale (STS-3): A Measure of a Hypothesized Suicide Trigger State

BACKGROUND: The Suicide Trigger Scale (STS) was designed to measure the construct of an affective ‘suicide trigger state.’ This study aims to extend the inpatient setting validation study of the original Suicide Trigger Scale version 2 to the revised Suicide Trigger Scale version 3 (STS-3) in an acute psychiatric emergency room setting. METHODS: The 42-item STS-3 and a brief psychological test battery were administered to 183 adult psychiatric patients with suicidal ideation or attempt in the psychiatric emergency room, and re-administered to subjects at 1 year follow up. Factor analysis, linear and logistic regressions were used to examine construct structure, divergent and convergent validity, and construct validity, respectively. RESULTS: The STS-3 demonstrated strong internal consistency (Cronbach’s alpha 0.94). Factor analysis yielded a three-factor solution, which explained 43.4% of the variance. Principal axis factor analysis was used to identify three reliable subscales: Frantic Hopelessness, Ruminative Flooding, and Near-Psychotic Somatization (Cronbach’s alphas 0.90, 0.80, and 0.76, respectively). Significant positive associations were observed between Frantic Hopelessness and BSI depression and anxiety subscales, between Ruminative Flooding and BSI anxiety and paranoia subscales, and Near Psychotic Somatization and BSI somatization subscales. Suicidal subjects with suicide attempt history had mean scores 7 points higher than those without history of suicide attempts. Frantic hopelessness was a significant predictor of current suicide attempt when only attempts requiring at least some medical attention were considered. CONCLUSION: The STS-3 measures a distinct clinical entity, provisionally termed the ‘suicide trigger state.’ Scores on the STS-3 or select subscales appear to relate to degree of suicidality in terms of severity of ideation, history of attempt, and presence of substantive current attempts. Further study is required to confirm the factor structure and better understand the nature of these relations

Comparison of Brain Activity Correlating with Self-Report versus Narrative Attachment Measures During Conscious Appraisal of an Attachment Figure

Objectives: The Adult Attachment Interview (AAI) has been the gold standard of attachment assessment, but requires special training. The Relationship Scales Questionnaire (RSQ) is a widely-used self-report measure. We investigate how each correlates with brain activity during appraisal of subjects' mothers.Methods: 28 women were scored on the AAI, RSQ, and mood measures. During functional magnetic resonance imaging, subjects viewed their mothers in neutral-, valence-, and salience-rating conditions. We identified regions where contrasts in brain activity between appraisal and neutral viewing conditions correlated with each measure of attachment after covarying for mood. AAI and RSQ measures were then compared in terms of the extent to which regions of correlating brain activity overlapped with default mode network (DMN) versus executive frontal network (EFN) masks and cortical versus subcortical masks. Additionally, interactions with mood were examined.Results: Salience and valence processing associated with increased thalamo-striatal, posterior cingulate, and visual cortex activity. Salience processing decreased PFC activity, whereas valence processing increased left insula activity. Activity correlating with AAI vs. RSQ measures demonstrated significantly more DMN and subcortical involvement. Interactions with mood were observed in the middle temporal gyrus and precuneus for both measures.Conclusions: The AAI appears to disproportionately correlate with conscious appraisal associated activity in DMN and subcortical structures, while the RSQ appears to tap EFN structures more extensively. Thus, the AAI may assess more interoceptive, 'core-self'-related processes, while the RSQ captures higher-order cognitions involved in attachment. Shared interaction effects between mood and AAI and RSQ-measures may suggest that processes tapped by each belong to a common system