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ABSTRACT: The objective of this study was to assess adaptation of the Texas Implementation of Medication Algorithm (TIMA) for bipolar disorder (BD) in the Connecticut Department of Correction. A nonrandomized sample of 20 males and 20 females, with diagnoses of BD Type I or II, was enrolled in the study. Two TIMA-trained psychiatrists treated the participants over a 12-week period following the TIMA protocol. The primary outcome measure was the Bipolar Disorder Symptom Scale. Secondary outcome measures evaluated global clinical status, comorbid symptomatology, and quality of life. Significant improvement was seen with the primary and secondary outcome measures (p < .001). Subanalyses showed differences in outcomes based on gender and whether a manic or depression algorithm was used. Antidepressant and antipsychotic medication use decreased, with increase in anticonvulsant and anxiolytic medication usage. This pilot study confirmed the effectiveness and benefits of TIMA for BD adaptation in the correctional setting.
International Journal of Offender Therapy and Comparative Criminology 11/2011; · 0.84 Impact Factor
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ABSTRACT: This article reports the findings of a Dialectical Behavioral Therapy-Corrections Modified (DBT-CM) intervention upon difficult-to-manage, impulsive, and/or aggressive incarcerated male adolescents.
A secondary analysis of a subsample of 38 male adolescents who participated in the study was conducted. A one-group pretest-posttest design was used; descriptive statistics and t-tests were conducted.
Significant changes were found in physical aggression, distancing coping methods, and number of disciplinary tickets for behavior.
The study supports the value of DBT-CM for the management of incarcerated male adolescents with difficult-to-manage aggressive behaviors.
Journal of Child and Adolescent Psychiatric Nursing 05/2011; 24(2):105-13.
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ABSTRACT: Use of medication treatment algorithms may facilitate clinical decision making, improve consistency, and reduce polypharmacy in the correctional setting. A feasibility study was conducted investigating use of Texas Implementation of Medication Algorithms (TIMA) guidelines for bipolar disorder in the Connecticut Department of Correction. Forty inmates with diagnoses of bipolar disorder were treated over a 12-week period adhering to the TIMA algorithm for bipolar disorder. Significant improvement was seen in the primary and secondary outcome measures (p<.001). This pilot project confirmed the feasibility of algorithm adaptation to the correctional setting and provided specific recommendations for successful dissemination of the TIMA algorithm for bipolar disorder in correctional settings.
Psychiatric services (Washington, D.C.) 09/2010; 61(9):865-7. · 2.81 Impact Factor
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ABSTRACT: Research in correctional settings has progressed from the exploitation of a vulnerable population in the years prior to 1978 to its current overly protective and restrictive state. With the considerable growth in the numbers of inmates with medical and mental health care needs, developing effective interventions to serve this population is paramount. There now appear to be signs of interest in and support for research with inmates by correctional agencies, academia, and health care organizations. Innes (2003) has articulated the following strategies for implementing research in prison: (1) gather stakeholders; (2) include one or more experienced research collaborators; (3) consider obtaining technical assistance from a university or the National Institute of Corrections (NIC); (4) define potential opportunities/interests that support the institution's mission; (5) develop a relationship with an IRB; (6) pilot a small proposal that is of interest and potential value to the organization. The authors illustrate the implementation of a study in a correctional system that uses these strategies.
Behavioral Sciences & the Law 09/2009; 27(5):743-52. · 0.96 Impact Factor
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Critical Care Nurse 01/2007; 26(6):47-53. · 1.08 Impact Factor
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Journal of Emergency Nursing 03/2005; 31(1):76-9; quiz 120. · 0.50 Impact Factor
