These data indicate how CG symptoms cluster in a large clinical sample of patients with CG, and how such clusters can be employed to optimize sensitivity and specificity for identification of CG cases. Our results resemble prior work showing that a single factor solution fits best in a sample of bereaved individuals with a wide range of grief related symptom severity [1
]. This result provides support for a general construct of CG that discriminates people with no symptoms from those with increasing numbers of symptoms. Indeed, a large number of individuals (n=264: 34%) did not endorse any of the ICG items at the level of often or more, and the single factor IRT model predicted CG trait levels to be highly correlated with the simple count of number of symptoms present. The symptoms found to best discriminate between individuals across the single general construct of CG were similar to those previously reported in bereaved populations [1
]. Loneliness and feeling life is empty were the most discriminating (i.e. most informative), but all of the symptoms were highly informative for the general construct of CG, as is indicated by all discrimination parameters being larger than 1.
A richer understanding of the nature of CG emerged when we repeated our analyses in clinically “confirmed” CG cases alone. Six distinct clinically meaningful dimensions emerged from the factor analysis including: 1) yearning and preoccupation with the deceased, 2) anger and bitterness, 3) shock and disbelief, 4) estrangement from others, 5) hallucinations of the deceased, and 6) behavior change, including avoidance and proximity seeking. This factor analytic approach can guide parsimonious inclusion of symptoms as diagnostic criteria. For example, although longing was the most commonly reported symptom (88.5% in CG cases), it was not found to be unique, but rather clustered with other symptoms of separation distress: loneliness, preoccupation with the loved one, feeling life is now empty, and feeling it is unfair to live while the loved one died. This cluster of symptoms measuring separation distress yielded very good sensitivity (96.9%) and specificity (88.3%). Bitterness and anger also clustered, were present in nearly three quarters of CG cases, and yielded high specificity (94.7%). Symptoms of shock and disbelief together were highly prevalent (87.2%) with good specificity (93.9%). Interpersonal symptoms of “estrangement from others” emerged as a cluster as well, with at least one symptom present in more than three quarters of cases (76.7%), again with good specificity (94.2%). Avoidance of reminders clustered with distress about memories and proximity seeking (symptom cluster6), with a sensitivity of 92.4% and specificity of 86.2%.
In criteria development, empirical data should be considered alongside other available research and clinical experience; as an example, avoidance is understood to be a difficult construct to assess since people avoid thinking about things they avoid. Nevertheless, studies confirm that avoidance is important in CG [17
], and psychotherapy for CG targets this symptom [17
]. Further, our clinical experience with CG patients is consistent with the co-occurrence of compulsive proximity seeking behaviors (e.g. compulsively viewing photos, or refraining from washing things that belonged to the deceased to retain their smell) and avoidance behaviors (e.g. avoidance of favorite places shared with the deceased, unwillingness to alter areas of the house).
Another finding that emerged from our factor analysis was the clustering of “hallucinatory” symptoms. While these symptoms were not among the more common or most informative according to item IRT analyses, or even as a cluster (25%prevalence), they were highly specific (less than 2% of non-CG bereaved individuals reported at least one of them)and also mapped to the highest levels of CG severity in the IRT analysis. Thus, this symptom cluster may be considered a marker for a more severe CG diagnosis. Similar results were observed by Boelen et al, who also suggested that these symptoms be candidates for diagnostic criteria [8
This study has a number of strengths that increase confidence in the findings. All subjects were well characterized, including structured psychiatric diagnostic assessment by certified experienced clinical raters. The sample includes a wide range of ages and has a moderate degree of racial/ethnic diversity. Further, the sample includes a large group of individuals who self-identified as having CG, had a high level of ICG symptoms and were confirmed by an experienced clinician to have CG. Losses in this “confirmed” CG case cohort include parents and children in addition to romantic partners, and include death by homicide, suicide, accident and natural causes. In addition, there is a large group of bereaved individuals with a mood or anxiety disorder, as well as those without disorder.
There are also some weaknesses of our sample. In order to optimize the sample size and include a wide range of individuals, we combined data across three sites from different studies, and there was thus a lack of systematic recruitment resulting in a lack of complete data about the characteristics of the loss and a much smaller proportion of CG treatment seeking individuals in the MGH sample. We were also limited to the use of only a few clinical research based sites (MGH, University of Pittsburgh and NYSPI), somewhat limiting generalizability to community settings. Selection of the6 factor model in the CG cases, as well as the placement of items 2 and 18 were based on clinical interpretation, a procedure that is consistent with standard practice in factor analysis [14
] and with recommendations by Kraemer and colleagues [21
] regarding collaborations between clinicians and statisticians in the interpretation of data informing DSM diagnoses. Finally, findings are limited by the questions asked in the ICG itself.
In conclusion, these data add an important perspective to existing suggestions for DSM5 criteria for CG. Ideally, diagnostic criteria should discriminate ill from not ill people, including both healthy controls and patients with other psychiatric disorders. However, this is not the only goal of the criteria. A second goal is to provide away for clinicians to understand the syndrome of CG and where a given patient fits within the spectrum of people with CG. Our analyses of CG symptom frequency and clustering, derived from a large, diverse and predominantly clinical help-seeking population who underwent rigorous evaluation procedures, provide one example of how empirical data can offer guidance for DSM criteria development. Additional investigation including replication of our analyses, field testing and biological, clinical and epidemiologic research is needed to further test and refine the diagnosis of CG.