Music Therapy to Reduce Agitation in Dementia

This condition severely affects the day to day activities of the victim. For example, the victim could pay twice or even more for the same bill due to the inability to recall that he or she had already paid. Dementia is known to cause anxiety or rather agitation to the victim during its late stages. For this reason, there have been several attempts to find a non-pharmacological intervention that can effectively curb the agitation. Music therapy has been pinpointed as an intervention that can be used to bring about relaxation in patients suffering from dementia (Matthews, 2015). According to the report, one of the non-pharmacological measures is music therapy, which utilizes music to improve the health condition of the victim of dementia.

This measure is said to be applicable to patients of all ages. It further defines concepts, like agitation as a behavioral problem that induces stress to the patient. The approach to integration has been satisfactorily described; it comprises nurse interventions through such ways as group music therapy. This way, the nurses can enhance the wellbeing of the patient through holistic care. To obtain relevant results, the reviewers performed their search using a combination of relevant words, such as music, agitation, intervention, and dementia (Craig, 2014). These keywords are exhaustive considering that the fact that their aim was to determine the efficiency of music therapy. It follows, therefore, that they only needed information on dementia and music therapy both as a treatment for anxiety caused by dementia and as an intervention.

Their search initially yielded fifty results. From these results, they applied other means to identify those that were more relevant to their research question. For example, the aforementioned article treated the patients to music therapy for fifty minutes three times a week. The samples mostly had the information that they needed to successfully conduct their research except for three articles that did not have the requirements for the previous agitation in their sampling criteria (Craig, 2014). Even so, this was minor and, therefore, it did not deter them from using the three resources without having to contact the original researchers. Quality Appraisal The reviewers utilized well-defined set of criteria to assess the quality of the primary studies. They utilized the measurement tool used in each and every study to weigh the quality of the information presented.

An example of a primary study that adopted more than one assessment tool was one by Choi et al (2009), which utilized both the Cohen-Mansfield Agitation Inventory and the Neuropsychiatric Inventory. Data Extraction Adequate information was collected concerning the study findings, sample characteristics, and study design. The study design employed by all the researchers in the primary studies was experimental one where each researcher made a music choice according to his or her objectives. Some chose songs that were familiar to the partakers to arouse memory associations. The findings of these studies indicated that there was a sizeable reduction in the anxiety during the intervention period. Given the data from all these groups, the data collected by the reviewers featured enhanced integrity.

Data Analysis The reviewers pooled the data obtained based on the severity of the agitation after the intervention. The anxiety and the behavioral disturbances were observed to return to their initial level after the intervention by all the researchers. This way, the pooled data suggested there is a need for the music therapy to be applied on a longstanding basis in order to attain lasting effects. For the integration of data, the reviewers utilized the intervention adopted for the control group. Background music produced negative outcomes because it had no capacity to engage the partakers and it created room for other distractors. The data analysis was thorough and credible. This is because it was able to integrate the data into different sets of data as well as pool them together into one dataset.