Objectives

Maladaptive cognitions related to loss are thought to contribute to development of complicated grief and are crucial to address in treatment, but tools available to assess them are limited. This paper introduces the Typical Beliefs Questionnaire (TBQ), a 25-item self-report instrument to assess cognitions that interfere with adaptation to loss.

Design

Study participants completed an assessment battery during their initial evaluation and again after completing treatment at 20 weeks. Test-retest reliability was assessed on a subsample of the participants who did not show change in complicated grief severity after the first 4 weeks of treatment. To examine latent structure of the TBQ, an exploratory factor analysis (EFA) was performed.

Setting

Academic medical centers in Boston, New York, Pittsburgh, and San Diego from 2010-2014.

Participants

394 bereaved adults who met criteria for complicated grief.

Measurements

The TBQ along with assessments of complicated grief symptoms and related avoidance, depression symptoms, functional impairment, and perceived social support.

Results

The TBQ exhibited good internal consistency (α = 0.82) and test-retest reliability (N = 105; intraclass correlation coefficient = 0.74). EFA indicated a five-factor structure: "Protesting the Death," "Negative Thoughts About the World," "Needing the Person," "Less Grief is Wrong" and "Grieving Too Much." The total score and all factors showed sensitivity to change with treatment.

Conclusions

This new tool allows a clinician to quickly and reliably ascertain presence of specific maladaptive cognitions related to complicated grief, and subsequently, to use the information to aid a diagnostic assessment, to structure the treatment, and to measure treatment outcomes.

Importance

To our knowledge, this is the first placebo-controlled randomized clinical trial to evaluate the efficacy of antidepressant pharmacotherapy, with and without complicated grief psychotherapy, in the treatment of complicated grief.

Objective

To confirm the efficacy of a targeted complicated grief treatment (CGT), determine whether citalopram (CIT) enhances CGT outcome, and examine CIT efficacy without CGT.

Design, setting, and participants

Included in the study were 395 bereaved adults who met criteria for CG recruited from March 2010 to September 2014 from academic medical centers in Boston, Massachusetts; New York, New York; Pittsburgh, Pennsylvania; and San Diego, California. Co-occurring substance abuse, psychosis, mania, and cognitive impairment were exclusionary. Study participants were randomized using site-specific permuted blocks stratified by major depression into groups prescribed CIT (n = 101), placebo (PLA; n = 99), CGT with CIT (n = 99), and CGT with PLA (n = 96). Independent evaluators conducted monthly assessments for 20 weeks. Response rates were compared under the intention-to-treat principle, including all randomized participants in a logistic regression with inverse probability weighting.

Interventions

All participants received protocolized pharmacotherapy optimized by flexible dosing, psychoeducation, grief monitoring, and encouragement to engage in activities. Half were also randomized to receive manualized CGT in 16 concurrent weekly sessions.

Main outcomes and measures

Complicated grief-anchored Clinical Global Impression scale measurments every 4 weeks. Response was measured as a rating of "much improved" or "very much improved."

Results

Of the 395 study participants, 308 (78.0%) were female and 325 (82.3%) were white. Participants' response to CGT with PLA vs PLA (82.5% vs 54.8%; relative risk [RR], 1.51; 95% CI, 1.16-1.95; P = .002; number needed to treat [NNT], 3.6) suggested the efficacy of CGT, and the addition of CIT did not significantly improve CGT outcome (CGT with CIT vs CGT with PLA: 83.7% vs 82.5%; RR, 1.01; 95% CI, 0.88-1.17; P = .84; NNT, 84). However, depressive symptoms decreased significantly more when CIT was added to treatment (CGT with CIT vs CGT with PLA: model-based adjusted mean [standard error] difference, -2.06 [1.00]; 95% CI, -4.02 to -0.11; P = .04). By contrast, adding CGT improved CIT outcome (CIT vs CGT with CIT: 69.3% vs 83.7%; RR, 1.21; 95% CI, 1.00-1.46; P = .05; NNT, 6.9). Last, participant response to CIT was not significantly different from PLA at week 12 (45.9% vs 37.9%; RR, 1.21; 95% CI, 0.82-1.81; P = .35; NNT, 12.4) or at week 20 (69.3% vs 54.8%; RR, 1.26; 95% CI, 0.95-1.68; P = .11; NNT, 6.9). Rates of suicidal ideation diminished to a substantially greater extent among participants receiving CGT than among those who did not.

Conclusions and relevance

Complicated grief treatment is the treatment of choice for CG, and the addition of CIT optimizes the treatment of co-occurring depressive symptoms.

Trial registration

clinicaltrials.gov Identifier: NCT01179568.

Background

Although Complicated Grief (CG) has been associated with comorbid Panic Disorder (PD), little is known about panic attacks in CG, and whether panic symptoms may be grief-related. The present study examines the presence and impact of grief-related panic symptoms in CG.

Methods

Individuals with CG (n=146, 78% women, mean (SD) age=52.4(15.0)) were assessed for CG, DSM-IV diagnoses, work and social impairment, and with the Panic Disorder Severity Scale modified to assess symptoms "related to or triggered by reminders of your loss" and anticipatory worry.

Results

Overall, 39.7% reported at least one full or limited-symptom grief-related panic attack over the past week, and 32.2% reported some level of anticipatory worry about grief-related panic. Of interest, 17% met DSM criteria for PD. Among those without PD, 34.7% reported at least one full or limited-symptom grief-related panic attack over the past week, and this was associated with higher CG symptom severity (t=-2.23, p<0.05), and functional impairment (t=-3.31, p<0.01). Among the full sample, controlling for CG symptom severity and current PD, the presence of at least one full or limited-symptom grief-related panic attack was independently associated with increased functional impairment (B(SE)=4.86(1.7), p<0.01).

Limitations

Limitations include a lack of assessment of non-grief-related panic symptoms and examination of a sample of individuals seeking treatment for CG.

Conclusions

Grief-related panic symptoms may be prevalent among individuals with CG and independently contribute to distress and functional impairment.

Background

Complicated grief (CG) has been recently included in the DSM-5, under the term "persistent complex bereavement disorder," as a condition requiring further study. To our knowledge, no psychometric data on any structured clinical interview for CG (SCI-CG) is available to date. In this manuscript, we introduce the SCI-CG, a 31-item "SCID-like" clinician-administered instrument to assess the presence of CG symptoms.

Methods

Participants were 281 treatment-seeking adults with CG (77.9% [n = 219] women, mean age = 52.4, standard deviation [SD] = 17.8) who were assessed with the SCI-CG and measures of depression, posttraumatic stress, anxiety, functional impairment.

Results

The SCI-CG exhibited satisfactory internal consistency (α = .78), good test-retest reliability (interclass correlation [ICC] 0.68, 95% CI [0.60-0.75]), and excellent interrater reliability (ICC = 0.95, 95% CI [0.89-0.98]). Exploratory factor analyses revealed that a five-factor structure, explaining 50.3% of the total variance, was the best fit for the data.

Conclusions

The clinician-rated SCI-CG demonstrates good internal consistency, reliability, and convergent validity in treatment-seeking individuals with CG and therefore can be a useful tool to assess CG. Although diagnostic criteria for CG have yet to be adequately validated, the SCI-CG may facilitate this process. The SCI-CG can now be used as a validated instrument in research and clinical practice.

Objective

Estimates of the penetrance of LRRK2 G2019S vary widely (24%-100%), reflective of differences in ascertainment, age, sex, ethnic group, and genetic and environmental modifiers.

Methods

The kin-cohort method was used to predict penetrance in 2,270 relatives of 474 Ashkenazi Jewish (AJ) Parkinson disease (PD) probands in the Michael J. Fox LRRK2 AJ Consortium in New York and Tel Aviv, Israel. Patients with PD were genotyped for the LRRK2 G2019S mutation and at least 7 founder GBA mutations. GBA mutation carriers were excluded. A validated family history interview, including age at onset of PD and current age or age at death for each first-degree relative, was administered. Neurologic examination and LRRK2 genotype of relatives were included when available.

Results

Risk of PD in relatives predicted to carry an LRRK2 G2019S mutation was 0.26 (95% confidence interval [CI] 0.18-0.36) to age 80 years, and was almost 3-fold higher than in relatives predicted to be noncarriers (hazard ratio [HR] 2.89, 95% CI 1.73-4.55, p < 0.001). The risk among predicted G2019S carrier male relatives (0.22, 95% CI 0.10-0.37) was similar to predicted carrier female relatives (0.29, 95% CI 0.18-0.40; HR male to female: 0.74, 95% CI 0.27-1.63, p = 0.44). In contrast, predicted noncarrier male relatives had a higher risk (0.15, 95% CI 0.11-0.20) than predicted noncarrier female relatives (0.07, 95% CI 0.04-0.10; HR male to female: 2.40, 95% CI 1.50-4.15, p < 0.001).

Conclusion

Penetrance of LRRK2 G2019S in AJ is only 26% and lower than reported in other ethnic groups. Further study of the genetic and environmental risk factors that influence G2019S penetrance is warranted.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.