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- All Subjects: Family
- Creators: Bradley, Robert
- Creators: Agliano, Courtney
physical health compared to children without cancer. Many studies have been done to examine the effects of emotional distress and mental health on the cancer patient, as well as the role of familial support. It was found that children with cancer may suffer from depression, anxiety, PTSD, and socio-emotional problems as a result of the trauma of being diagnosed and treated for a pervasive, life-threatening disease. Late effects may also worsen co-morbid mental health disorders. Childhood cancer patients who experience co-morbid mental health problems of depression and anxiety end up having a longer duration of recovery, as well as a worsened outcome than others with a single disorder (Massie, 2004). It was also shown that family members are affected emotionally and mentally from dealing with childhood cancer. Not only is the cancer patient at risk for PTSD during or after treatment, but also family members (National Cancer Institute, 2015). Siblings of the child with cancer may experience feelings of loneliness, fear, and anxiety, as the parent’s attention is focused on the child suffering with cancer. According to the National Cancer Institute (2015), familial problems can affect the child’s ability to adjust to the diagnosis and treatment in a positive way. However, children with strong familial and social support adjust easier to living with cancer. A common theme found in literature is that regular mental health checkups during and after cancer treatment is important for quality of life. Therefore, it is important for all childhood cancer patients and their families to receive information about mental health awareness, as well as therapeutic interventions that are developed for families caring for a child with cancer.
Method: Twenty families with children 10 years and older were recruited to participate in a 3-week equine assisted learning program at a therapeutic riding center in Phoenix, Arizona. Sessions included groundwork activities with horses used to promote life skills using experiential learning theory. The study design included a mixed-method quasi-experimental one-group pretest posttest design using the following mental health instruments: Devereaux Student Strengths Assessment, Brief Family Assessment Measure (3 dimensions), and Family Satisfaction Scale to measure child social-emotional competence, family function, and family satisfaction, respectively. Acceptability was determined using a Likert-type questionnaire with open-ended questions to gain a qualitative thematic perspective of the experience.
Results: Preliminary pretest and posttest comparisons were statistically significant for improvements in family satisfaction (p = 0.001, M = -5.84, SD = 5.63), all three domains of family function (General Scale: p = 0.005, M = 6.84, SD = 9.20; Self-Rating Scale: p = 0.050, M = 6.53, SD = 12.89; and Dyadic Relationship Scale: p = 0.028, M = 3.47, SD = 7.18), and child social-emotional competence (p = 0.015, M = -4.05, SD 5.95). Effect sizes were moderate to large (d > 0.5) for all but one instrument (Self-Rating Scale), suggesting a considerable magnitude of change over the three-week period. The intervention was highly accepted among both children and adults. Themes of proximity, self-discovery, and regard for others emerged during evaluation of qualitative findings. Longitudinal comparisons of baseline and 3-month follow-up remain in-progress, a topic available for future discussion.
Discussion: Results help to validate equine assisted learning as a valuable tool in the promotion of child social-emotional intelligence strengthened in part by the promotion of family function and family satisfaction. For mental health professionals, these results serve as a reminder of the alternatives that are available, as well as the importance of partnerships within the community. For therapeutic riding centers, these results help equine professionals validate their programs and gain a foothold within the scientific community. Additionally, they invite future riding centers to follow course in incorporating evidence into their programs and examining new directions for growth within the mental health community.
Background:
Approximately 1 in 5 U.S. school-aged children are obese. There are many known health complications associated with obesity including premature death. Family-based obesity interventions that promote healthy lifestyle habits are effective at enabling children to make changes needed to avoid long-term health complications associated with obesity. The purpose of this evidence-based practice intervention was to evaluate the effectiveness of a family-based obesity intervention on familial lifestyle behaviors related to nutrition, physical activity, and screen time.
Methods:
Two overweight-obese children (according to CDC criteria) ages 8-12 years old visiting a pediatric primary care clinic in a suburban neighborhood located in the southwest region were recruited to participate in this evidence-based practice intervention based on inclusion and exclusion criteria. Familial lifestyle behaviors were assessed using the Family Health Behavior Scale (FHBS) prior to receiving an educational intervention addressing nutritional, physical activity, and screen time recommendations and again after following these recommendation for 6-weeks. Additionally, scheduled follow-up phone calls were made every 3 or 6-weeks addressing any parental questions that surfaced. Data was insufficient for statistical analysis, however, anecdotal recommendations for future implementation of this intervention resulted.
Results:
Of the two patients who participated, pre- and post-intervention data was only attainable from one patient. That patient did have improved scores within each of the 4 FHBS subscales (parent behaviors, physical activity, mealtime routines, and child behaviors). Overall, 11 of the 27 behaviors assessed improved, 12 behaviors resulted in no change, and 4 behaviors worsened. Recommendations related to a more successful implementation of this intervention in the future include improved provider participation (buy-in), utilization of broader inclusion criteria, consideration of the implementation time-frame, and application of the Health Belief Model for addressing existing barriers for each patient prior to implementing the intervention.
Conclusions:
In order to determine the effectiveness of this intervention a larger sample size and completed post-intervention data are needed. The small sample size and lack of post-intervention data inhibits proper data analyzation and significance from being determined.