Balancing Nursing Science With Biobehavioral Approaches

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Tailored Nurse Support Program Promoting Positive Parenting and Family Preservation

Background Public health nurse home visiting is a promising approach for addressing the complex needs of families at risk of child maltreatment. The Colorado Nurse Support Program advances service provision by using evidence-based practices to provide tailored assessment and intervention to low-income, primiparous, and multiparous families with children under 18 years of age identified as high risk by county human service systems. Objectives This study aimed to test the effects of the Nurse Support Program on child protective services case characteristics between Nurse Support Program families and a demographically comparable reference group of families and evaluate changes in parenting outcomes from pre- to postprogram involvement for Nurse Support Program families. Methods We used a matched comparison group quasi-experimental design in which families in the Nurse Support Program (n = 48) were compared to families (n = 150) who were identified using administrative data from Colorado’s Comprehensive Child Welfare Information System. Outcomes were child protective case characteristics (child protection referrals, open assessments, founded assessments, open cases, and children’s placement in out-of-home care) and parenting outcomes. Results Nurse Support Program families were less likely to have a child protection case opened or have their child placed in out-of-home care. There were no significant between-group differences in child protection referrals, open assessments, or founded assessments. Families in the Nurse Support Program showed improvements in parenting outcomes over time. Discussion Findings suggest that the Nurse Support Program is a successful public health nurse home-visiting approach to promote positive parenting and family preservation among families with complex needs. Implementing tailored public health nurse home-visiting programs, such as the Nurse Support Program, should continue to be evaluated and supported to mitigate the public health risk of child maltreatment.

An Evaluation of the Multifactorial Model of Cancer-Related Cognitive Impairment

Background Up to 45% of patients report cancer-related cognitive impairment (CRCI). A variety of characteristics are associated with the occurrence and/or severity of CRCI. However, an important gap in knowledge of risk factors for CRCI is the relative contribution of each factor. The multifactorial model of cancer-related cognitive impairment (MMCRCI) is a conceptual model of CRCI that can be used to evaluate the strength of relationships between various factors and CRCI. Objectives The purpose of this study was to use structural regression methods to evaluate the MMCRCI using data from a large sample of outpatients receiving chemotherapy (n = 1,343). Specifically, the relationships between self-reported CRCI and four MMCRCI concepts (i.e., social determinants of health, patient-specific factors, treatment factors, and co-occurring symptoms) were examined. The goals were to determine how well the four concepts predicted CRCI and determine the relative contribution of each concept to deficits in perceived cognitive function. Methods This study is part of a larger, longitudinal study that evaluated the symptom experience of oncology outpatients receiving chemotherapy. Adult patients were diagnosed with breast, gastrointestinal, gynecological, or lung cancer; had received chemotherapy within the preceding 4 weeks; were scheduled to receive at least two additional cycles of chemotherapy; were able to read, write, and understand English; and gave written informed consent. Self-reported CRCI was assessed using the attentional function index. Available study data were used to define the latent variables. Results On average, patients were 57 years of age, college educated, and with a mean Karnofsky Performance Status score of 80. Of the four concepts evaluated, whereas co-occurring symptoms explained the largest amount of variance in CRCI, treatment factors explained the smallest amount of variance. A simultaneous structural regression model that estimated the joint effect of the four exogenous latent variables on the CRCI latent variable was not significant. Discussion These findings suggest that testing individual components of the MMCRCI may provide useful information on the relationships among various risk factors, as well as refinements of the model. In terms of risk factors for CRCI, co-occurring symptoms may be more significant than treatment factors, patient-specific factors, and/or social determinants of health in patients receiving chemotherapy.