Case Study: A Transactional Analysis Model for a Single Mother and Her Adult Child With Bipolar Disorder

This case study describes a transactional analysis model based on the strain of a single mother with an adult son suffering from bipolar I disorder. The study examines interaction patterns within the clinical setting; the therapeutic view examines contextual factors that affect this mother and her adult son through assessment and recovery with transactional analysis therapy. The 16-session therapeutic experience of a client and his mother is presented. The subjects in the case study were administered the Sixteen Personality Factor Questionnaire (16PF) assessment tool during the second and 16th sessions. There was a significant change from pretest to posttest stens scores regarding increased scores in emotional stability from 2 (extremely low) to 4 (average), rule consciousness from 1 (extremely low) to 3 (moderately low), openness to change from 6 (average) to 8 (moderately high), and self-control from 1 (extremely low) to 4 (average). Decreased scores included apprehension from 9 (extremely high) to 7 (average) and tension from 6 (average) to 3 (moderately low). Behavioral changes after a 1-month follow-up included taking the bus to sign up for a college class, taking his medication as prescribed, getting a part-time job in the kitchen at the Veteran Administration Medical Center, and developing a budget to manage his disability check.

Impact of race on survival of prostate cancer patients treated with noncurative intent

5069 Background: We previously reported that African American (AA) men have a higher recurrence rate than Caucasian (CA) men treated with radical prostatectomy at the New York Veteran Administration Medical Center (NY-VAMC), an equal access to care facility (J Urol. 2006). In the current study, we attempted to examine the differences in survival of AA and CA prostate cancer (PC) patients with clinically detected localized disease treated with non curative intent. We hypothesized that comparing patients whose PC was not altered by primary treatment might give a better idea about the difference, if any, of the natural history of PC in AA compared to CA patients. Methods: Men diagnosed with PC at NY-VAMC during 1990–2005 were identified. Inclusion criteria were: 1) biopsy confirmed PC; 2) no evidence of metastatic disease within 6 months after diagnosis; 3) no curative intent treatment. Results: The study included 530 men (288 AA and 242 CA) with median follow-up of 8.1 years (range: 0.6–17.6 years). AA men presented with significantly higher PSA compared to CA patients (median 18.5 versus 11.4 respectively, p = 0.004), however, there were no differences in age at presentation (median 73 versus 74, p = 0.98) or Gleason score (23% of AA and CA had Gleason >7, p = 0.92). Of the 530 patients, 198 (37%) are alive with disease, 67 (13%) died of prostate cancer, 206 (39%) died of other causes, and 59 (11%) died of unknown causes. AA patients had shorter median overall survival compared to CA patients (8 versus 9 years, respectively), however, the difference was not significant (p = 0.29). Factors most predictive of mortality by Cox regression multivariable analysis were PSA at diagnosis (p = 0.001), Gleason score (p = 0.04), and age of patient at diagnosis (p < 0.0001). Race was not an independent predictor of mortality in this model (p = 0.37). Competing risk analysis distinguishing the types of death is underway. Conclusions: The extended follow up available for our study cohort points to non PC related mortality as the major cause of death in patients treated with non-curative intent. No significant financial relationships to disclose.

Predictors of Depression in Geriatric Medically Ill Inpatients

Objective: Depression in medically ill inpatients has been associated with increased morbidity and mortality. The purpose of this study was to identify variables that would successfully predict depression in this population. Methods: The sample consisted of 314 male, medically ill veterans, age 60 and older, admitted to the acute medical service at Baltimore Veteran Administration Medical Center. Sixty of 314 patients met criteria for Major Depression and scored 11 or higher on the Geriatric Depression Scale. Variables assessing age, race, social support, severity of illness, degree of functional disability, life satisfaction, and hopelessness were included in a logistic regression analysis as predictors of depression. Results: The variables that significantly predicted depression were derived from the Beck Hopelessness Scale, Life Satisfaction Score, and the Cumulative Illness Rating Score. Conclusions: The results indicated that medically ill inpatients who feel hopeless about the future, feel the best years of their lives are behind them, and have serious medical problems are likely to be clinically depressed.