Implications of depression in rheumatoid arthritis: do subtypes really matter?

OBJECTIVE: To examine depressive disorders and health status in patients with rheumatoid arthritis (RA), controlling for potential confounds. METHOD: Subjects (n = 426) completed measures of depressive symptoms (Center for Epidemiological Studies Depression Scale [CES-D]) and health status (Arthritis Impact Measurement Scales 2 [AIMS2]), via cross-sectional survey. Subjects (n = 299) with few depressive symptoms (CES-D < or = 10) were not evaluated further. Subjects with CES-D > or = 11 were interviewed using the Primary Care Evaluation of Mental Disorders to diagnose major depressive disorder (MDD; n = 46), dysthymic disorder (DD; n = 21), or minor depressive disorder (MND; n = 18). RESULTS: Regression analyses examined differences between the depressive disorders on AIMS2 subscales. Health status scores were similar between the depressive disorder subcategories; significant differences were found between MDD and MND on AIMS2 Physical scores and MDD and DD on AIMS2 Symptom scores. CONCLUSION: Regarding health status, presence of depression itself seems to overshadow differences between depression subtypes; antidepressant treatments/referrals for persons with concomitant RA and any depressive disorder subtype appear warranted.

Differentiation of three brain injury family types.

The purpose of this study was to advance the research on brain injury families by differentiating between families with one of three family types. Participants were 76 primary caregivers of individuals with brain injuries recruited through the brain injury association of a Southern state in the US. Families were classified as Balanced (n = 33), Mid-range (n = 24), or Extreme (n = 19) type using the Family Adaptability and Cohesion Evaluation Scales II (FACES II). Three two-way discriminant analyses were performed using eight variables to discriminate between the family types. Results indicated that the affective and cognitive functioning of the family members with the brain injuries, family adaptation, and primary caregiver age were the strongest factors that differentiated the three family types. These findings suggest that Balanced, Mid-range, and Extreme families are distinct subgroups within the brain injury family population. The results, thus, may be beneficial for improving the efficacy of family intervention following brain injury and facilitating the development of long-term family supports.

A multidimensional longitudinal analysis of family coping with brain injury.

Longitudinal research is needed to advance knowledge and practice in the area of family coping with brain injury. The purpose of this investigation was to examine the dimensions that underlie family coping with brain injury across a 2-year time period (1995 to 1997). Two-dimensional configurations of 30 family coping behaviours indicated a like family coping pattern of cognitive versus behavioural coping (Dimension 1) in both 1995 and 1997. The data also showed that families had a differing, or changed, family coping pattern along Dimension 2 from brain injury-focused coping versus family-to-community fit in 1995 to seeking professional help versus intra-family coping in 1997. Results thus indicated both changes and consistent coping patterns within the same group of families across time. Such information can be used to guide clinical family intervention, the development of long-term family support services, and future brain injury family research.

Relationship of family schema to family adaptation to brain injury.

The relationship between family schema and family adaptation to brain injury was investigated. Participants were 87 primary caregivers of persons with brain injuries in Wisconsin who are part of a comprehensive, longitudinal study of family adaptation to having a member with a brain injury. Stepwise multiple regression of variables measuring family schema on family adaptation indicated that manageability and meaningfulness were predictive of family adaptation. Thus the hypothesis that family adaptation can be predicted from variables measuring family schema was supported. Family intervention and research implications are discussed.