Self-assessment of cancer competencies and physician assistant cancer education: instrument development and baseline testing.

PURPOSE: Although the benefits of primary and secondary prevention of cancer are well recognized among health care providers, insufficient knowledge or skill often leads to inadequate assessment and management, particularly in the primary care setting. The scant literature on physician assistant (PA) cancer-related competencies suggests that PAs may not be well-prepared in this arena. Thus, curriculum reform in PA education is paramount for improving PAs' abilities to provide cancer risk assessment and management services. The Physician Assistant Cancer Education (PACE) project was designed for such a purpose. Following instrument development, baseline measurement of perceived abilities for cancer-related core competencies was assessed in a representative cohort of PA students. METHODS: Literature search strategies, expert review, and a nationwide survey of PA program directors yielded the 26-item Competencies in Cancer Assessment and Management (C-CAM) instrument. Baseline self-efficacy data were gathered from students across eight PACE-affiliated PA programs. Statistical analysis focused upon instrument quality and comparisons of reported self-efficacy among respondent cohorts. RESULTS: Data were collected from 544 PA students. Overall instrument reliability was excellent (Chronbach's alpha 0.97). Exploratory factor analysis identified three factors explaining 72.83% of response variance. Mean values varied somewhat across institutional cohorts. Clinical students demonstrated higher self-efficacy than preclinical students. CONCLUSIONS: The C-CAM is an effective instrument to assess PA student self-efficacy in cancer prevention, risk assessment, and risk management competencies. Although a trend toward higher self-efficacy was observed among clinical students, further research is required to assess the extent to which reported self-efficacy may be expected to change over time.

Development and implementation of a health behavioral counseling curriculum for physician assistant cancer education.

A health behavioral counseling curriculum grounded in Motivational Interviewing and the Transtheoretical Model of behavior change was developed to enhance knowledge and clinical skill among physician assistant (PA) students in managing cancer risk behaviors. A literature and curriculum review informed course content, teaching strategies, and learning activities. The course was evaluated over two pilot years. Students demonstrated increased knowledge and skills regarding the basic principles of the intervention models. The course was integrated into the pre-clinical year of PA training and will be disseminated, beginning with a faculty development workshop for all PA training programs in Texas, USA.

Educating physician assistants as agents in cancer control: issues and opportunities.

BACKGROUND: Lifestyle factors (eg, smoking, diet) and compliance with screening recommendations play a role in cancer risk, and emerging technologies (eg, new vaccines, genetic testing) hold promise for improved risk management. METHODS: However, optimal outcomes from cancer control efforts require better preparation of health professionals in risk assessment, risk communication, and implementing health behavioral change strategies that are vitally important to cancer control. RESULTS AND CONCLUSION: Although physician assistants (PAs) are substantively engaged in cancer-related service delivery in primary care settings, few models exist to facilitate integration of cancer control learning experiences into the curricula used in intense, fast-paced, 24- to 30-month PA training programs.

Identification of Macrosomic, normal and intrauterine growth retarded neonates using the modified Neonatal Growth Assessment Score.

OBJECTIVE: Separation of Macrosomic, normal and intrauterine growth retarded (IUGR) neonates using the modified Neonatal Growth Assessment Score (NGAS). METHODS: A sample of 23 neonates with evidence of growth acceleration and 74 neonates classified as normal or IUGR in a previous study was used in this investigation. The prenatal growth of all neonates had been studied longitudinally with ultrasound. From the data collected, Rossavik models describing the growth trajectories of head circumference (HC), abdominal circumference (AC), thigh circumference (ThC), femur diaphysis length, head cube (A) and abdominal cube (B) were specified. These models were used to predict birth weight (WT), crown-heel length (CHL), HC, AC and ThC at birth. Actual birth measurements of WT, CHL, HC, AC and ThC were evaluated using age-specific normal size curves and compared to predicted measurements by means of the growth potential realization index (GPRI). GPRI values were evaluated by comparison to previously established normal ranges and used to calculate Neonatal Growth Assessment Scores (NGAS(5)). NGAS(5) values, together with assessments of anatomical measurements and GPRI values, were used to establish macrosomic, normal and IUGR groups. Principal components analysis was applied to the sets of GPRI values available for each neonate to provide a principal component score for separating macrosomic and normal neonates (m(2)NGAS(51)) or one to separate macrosomic, normal and IUGR neonates (m(3)NGAS(51)) using linear discriminant analysis. The groups identified by these multivariate methods were compared to the original classification and their characteristics evaluated. RESULTS: The m(2)NGAS(51) and a boundary value of 207.5% separated macrosomic and normal neonates with an accuracy of 97.3%. The m(3)NGAS(51) and boundary values of 210.0 and 182.5% separated macrosomic, normal and IUGR neonates with an accuracy of 96.9%. No single GPRI value or anatomical measurement could achieve these levels of accuracy. All normal infants were AGA but only 45.5% of the IUGR group were SGA and only 60.9% of the macrosomic group were LGA. Thirteen different types of IUGR and eleven different types of macrosomia were identified based on GPRI values. CONCLUSION: The modified NGAS accurately separates macrosomic, normal and IUGR neonates although growth abnormalities are expressed in different ways in different individuals.