Filtering by
- All Subjects: Mental Health
- All Subjects: Family
- Creators: McIntosh, Wayne
- Creators: Crawford, Daniel
- Member of: Programs and Communities
Background: Alarming levels of burnout in mental health care staff is a significant concern not only for the organization but for the individual as well. Identifying and addressing burnout ought to be an essential protocol in a behavioral health organization. Currently, burnout remains an ongoing concern for mental health care organizations as it is associated with negative impacts for staff, patients, families, and the organization.
Method: The purpose of this project is to utilize the Maslach burnout inventory (MBI) survey tool to measure burnout pre and post intervention. The intervention utilized will be mindfulness-based interventions (MBI) to reduce burnout among mental healthcare workers. Implementing mindfulness interventions has evidence that it reduces burnout rates in mental health care staff. Current literature supports mindfulness-based interventions and have showed a decrease in burnout, stress, and depersonalization.
Results: The pre-intervention results were as followed: emotional exhaustion; 40, depersonalization; 20.4 and personal accomplishment 32. The post-intervention results emotional Exhaustion; 28, depersonalization; 14.90 and personal accomplishment 30. It was found that the category for emotional exhaustion was statistically significant as it had a P value .040, whereas depersonalization was not statistically significant as the P value was .171 and personal accomplishment was not statistically significant as the P value was .577.
Discussion: The use of MBI as an intervention has robust literature supporting the effectiveness in decreasing burnout and stress in mental health care staff.
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.