An SPSS data analysis was conducted to synthesis and analyse the raw results. Through the SPSS software, a t-test was conducted for the three sets of data obtained. For hypothesis 1 and 2, an independent t-test was conduced and for hypothesis 3 a repeated measures t-test was conducted. An Independent-samples t-test with an alpha level of .05 was used to compare children with a traumatic brain injury against an orthopaedic control. At both 7 and 13 years old, those in the OC group had a higher mean score on the Digit Span Standard test. The correlation between the scores of both TBI groups and both OC groups was positively weak. This indicates that there is not a clear relationship between the two groups. The t-test was statistically significant …show more content…
for all 3 tests. Discussion The findings of the study were that children who had a TBI at 13 years old had a better working memory development than children who had a TBI at 7 years old.
Children with OC also had better working memory development, at 7 and 13 years old, than children with TBI. All of my hypotheses were supported and the results are consistent with the results obtained in previous research. As seen with Barnes, Swank and Ewing-Cobbs (2017), who ran a study focusing on children with TBI at 8 and 14 years of age, it was expected that this research would obtain results that highlighted the improvement of working memory functions with age. Past research also found the younger children tend to have more problems with their working memory after TBI, especially compared to older children who have sustained the same severity TBI (Keenan, Clark, Holubkov, Cox and Ewing-Cobbs, 2018). This study adds to the understanding of impact of age on working memory following TBI and extends the knowledge by researching specific age categories. This provides a fuller picture as to how brain development in children varies the impact of TBI on working memory functions. A strength of the study was that it focused on children aged 7 and 13 years, which is something that is rarely studied specifically. The unique changes that occur in the brain between 7 and 13 can play an important role in the
altering of working memory when a TBI is present (). Another strength was that both groups were sampled from the same population, allowing for easier control of confounding variables, such as participation in any rehab programs, which could impact the brain development of the participants. A limitation of the study was that it did not measure the impact different TBI severities had on working memory. The study focused on moderate brain injury at two age groups exclusively, limiting the information we can gather from it. Also the variability between when participants could have gotten the TBI creates inconsistency within the results that should have been more closely contained. Another limitation was that the sample, for both the TBI and OC groups, was rather small (n=28, n=32). This significantly influences the amount of generalizable information we can obtain during the study. Even with these limitations, this research profoundly adds to the current understanding of the relationship between age and working memory with a TBI. This research will add to the knowledge about how trauma to the brain can effect working memory is integral to develop techniques to improve functioning in children with TBI. Future research should focus on comparing children with TBI at various ages and various severities, to get a complete picture of the situation. Combining the information found during this study and adding more conditions, such as severe TBI and the influence on working memory at 8 years old etc. will assist in rounding out the missing research. Age is an important factor that influences TBI influence on verbal working memory. Overall, OI children have a better working memory function compared to their TBI counterparts. Working memory is a process related to the “manipulation and transformation of verbal and visual information” (kid sense, para 2). It is a necessary part of a child’s cognitive abilities and overall academic performance (Newsome, Steinberg, Schiebel, Troyanskaya, Chu, Hanten, et. al, 2008). Traumatic brain injuries (TBI) are one of the leading causes of harm to children, affecting their working memory (Wilde, Newsome, Bigler, Pertab, Merkely, Hanten, et. al, 2011). TBI is considered as any outside influences that impact the productivities of the brain (whatsnewintraumaticbrain-reis). The topic of effects of TBI on children’s working memory is widely studied due to the consequences TBI can have on children’s brain function (Wilde, Newsome, Bigler, Pertab, Merkely, Hanten, et. al, 2011). A widely used comparison group to TBI is Orthopaedic injury (OI) (). OI is “injury to parts of the muscular skeletal system” (emoryhealthcare). Previous research has explored the relationship between age and TBI severity when it comes to children’s working memory after sustaining a traumatic brain injury (startingmetaanalysisarticle). Phillips, Parry, Mandalis and Lah’s (2015) findings conclude that children are highly likely to have damage to their working memory in areas relating to intricate processing in the central executive, which relates to verbal working memory. The meta-analysis also concluded that age and injury severity are crucial elements when it comes to children’s working memory (previousreference). This was supported in Levin, Hanten, Zhang and Ewing-Cobbs’ (2002) research, which found that TBI severity negatively impacted participant’s performance on working memory tests as participants tended to perform worse when they had a more severe TBI. The study noted an improvement in working memory with age, with participant’s showing growth in their working memory abilities over time (2002researchfromabove). Both, Gorman, Barnes, Swank and Ewing-Cobbs (2017) and Keenan, Clark, Holubkov, Cox and Ewing-Cobbs (2018) studied how older children with TBI have a significantly better working memory than children who have a TBI at a younger age. Barnes, Swank and Ewing-Cobbs (2017) found that 14 years old children with TBI performed better in working memory tasks than 8 year old children with the same severity TBI. This was suggested to be due to the brain maturation difference between the two age groups (sameasabove). Adding to that, it is concluded that the younger the child is when they sustain a TBI; the impact on their working memory will be significantly more negatively affected (Keenan, Clark, Holubkov, Cox and Ewing-Cobbs, 2018). This study will attempt to add to the existing research as well as report areas missing in past research by exploring the growth of children’s working memory with a traumatic brain injury against an orthopaedic control group, at 7 and 13 years. The overall aim of the study was to investigate whether age has an impact on verbal working memory, in children with a moderate TBI, at two age categories: 7 and 13 years of age. For the first test, the aim was to examine how children with a TBI compare against children with an OC in verbal working memory at 7 years of age. It is hypothesised that children with TBI will show reduced performance on a verbal working memory task at 7 years compared to OI children. The aim of the second test was to examine how children with a TBI compare against children with an OI in verbal working memory at 13 years of age. It was hypothesised that children with TBI will show similar performance on a verbal memory task at 13 years compared to OI children. The third test focused on exploring the progress of working memory in children with TBI between 7 and 13 years of age. It was hypothesised that children with TBI will show an improvement in performance on verbal working memory task performance from 7 to 13 years of age. Method Participants Children, who had an accidental brain injury at 3 to 6 years old, were conveniently sampled from the Emergency department at Monash children’s hospital in Melbourne, Australia during January 2009 and 2012. The participants must have a clear indication of a traumatic brain injury and must have gone through a stage of altered consciousness. Capability to engage in cognitive testing was also necessary. Through convenience sampling from an advertisement at the hospital, children with an orthopaedic injury, ages 7 and 13, were studied as a control group. Any individuals who did not speak English as their first language, had any prior brain injuries or had a previous neurological or developmental disorder were not considered as participants. Materials Digit span backwards subset from the Wechsler Intelligence scale for children was used to measure participants working memory. Questionaries were completed by the participant’s parents in relation to executive, behavioural and social functioning levels. SPSS was used to analyse the raw data received during the tests. Procedure Children underwent a separate neuropsychological assessment to evaluate their intellectual, cognitive and academic performance at 7 and 13 years of age. This was fulfilled by a child psychologist in training. Parent’s also engaged with a questionnaire that fleshed out the participant’s executive, behavioural and social functioning levels. Their socio-economic standing was also disclosed. The children’s medical history was obtained and documented. Design This study uses an independent measures design to test both hypothesis one and two, as there are 2 individual groups of participants. Hypothesis three uses a repeated measures study design, as the same group of participants are utilized in both circumstances. The independent variable is the age of the children and the dependent variable is the level of functioning of their working memory.
Collected data were subjected to analysis of variance using the SAS (9.1, SAS institute, 2004) statistical software package. Statistical assessments of differences between mean values were performed by the LSD test at P = 0.05.
In response to the question set, I will go into detail of the study, consisting of the background, main hypotheses, as well the aims, procedure and results gathered from the study; explaining the four research methods chosen to investigate, furthering into the three methods actually tested.
I intend to explore the effects of a parietal brain injury from the perspective of a neuropsychologist; ranging from types of tests that are employed when trying to determine the extent of the damage, to gaining an understanding of how this damage will affect the rest of the brain and/or the body. I will also explore the effects of a brain injury from the perspective of the family members, and their experiences with the changes that occur during the rehabilitation process. According to The Neuropsychology Center, “neuropsychological assessment is a systematic clinical diagnostic procedure used to determine the extent of any possible behavioral deficits following diagnosed or suspected brain injury”(www.neuropsych.com). As mentioned previously, a brain injury can be the result of many types of injuries or disorders, thus a broad range of assessment procedures have been developed to encompass these possibilities.
Traumatic brain injuries (TBI) account to a third (30.5%) of all injury-related deaths in the U.S. with an estimated 1.7 million individuals sustaining TBI each year (Center for Disease Control and Prevention, 2010). Classifications of brain injury (e.g., mild, moderate and severe) is mostly done using the Glasgow coma scale (GCS) which has gained broad acceptance for the assessment of the severity of brain damage (Bauer & Fritz, 2004). Recent studies suggest that almost all patients with moderate or severe TBI have a period of recovery during which they are responsive but confused. This state is commonly referred to as the post-traumatic amnesia. Post-traumatic amnesia (PTA) is defined as “a failure of continuous memory” (Artiola et al., 1980; p.377). PTA is often cited as the best method for codifying the degree, level of recovery and outcome after a closed head injury (e.g., Artieola et al., 1980; Tate, Pfaff, & Jurjevic, 2000). PTA duration is a better indicator of outcome than early injury scales such as the GCS score (Richardson et al., 2009).This analysis will examine the limitations of the general PTA assessment scale, and investigate the benefits and limitations of both retrospective and prospective methods used to measure the duration of PTA.
Thesis: Concussions affect children and adults of all ages causing physical, emotional and metal trauma to a person and their brain.
Yates, Keith, et al. “Longitudinal Trajectories of Postconcussive Symptoms in Children With Mild Traumatic Brain Injuries and Their Relationship to Acute Clinical Status.” Pediatrics. 123.3 (2009) : 735-743. Web. 11 Apr. 2014.
Scientific American 306.2 (2012): 66-71. Print. The. Brady, Erik. “Changing the Game on Youth Concussions.”
...however issues such as reliability, validity and bias occur when studying brain damaged patients therefore is not always a valid way of studying working memory (in Smith, 2007).
Children who suffer from Traumatic Brain Injury might suffer from learning disabilities as a result of their injury.
Traumatic brain injury (TBI) is are complex and always have large degrees of symptoms. Traumatic brain injuries (TBI) also are the cause of many different disabilities. Each person is different and in every brain injury are different, bringing a devastating change into their lives on the day of the occurrence of the brain injury. The occurrence of brain injuries are wide spread into a large spectrum of different causes and there are different degrees of TBI.
indicates towards a fraud. On eof the most important qualities or benefits of this model is that it understands the pattern in the data and generates the result. Once the result is generated the model checks as to how close was the result from the actual results. Based on this analysis the model adjusts its weights to give an accurate result the next time. Once this model has been trained to give accurate results, it can be used to analyze other data as well. Even when Neural Networks are widely accepted, they are not really used that much in the marketing industry merely by the fact that data preparation for this model is very complex time consuming as compared to the Regression Analysis. The marketers are much comfortable using the Regression Analysis over Neural Networks because of the ease of interpreting the results in the Regression Analysis.
The authors of this article have outlined the purpose, aims, and objectives of the study. It also provides the methods used which is quantitative approach to collect the data, the results, conclusion of the study. It is important that the author should present the essential components of the study in the abstract because the abstract may be the only section that is read by readers to decide if the study is useful or not or to continue reading (Coughlan, Cronin, and Ryan, 2007; Ingham-Broomfield, 2008 p.104; Stockhausen and Conrick, 2002; Nieswiadomy, 2008 p.380).
Thematic analysis is espoused to be the foundational approach to qualitative analysis and methods (Saunders et al., 2016 as stated in Braun and Clarke, 2006: 78) and it is a useful method used to identify and analyse the order and patterns of qualitative data (Attride-Stirling, 2001). Qualitative research method depicts the correlation that exists between data and events, creating the pictorial representation of what one thinks a given data says (Saunders et al., 2016). They also opined that, qualitative data analysis is cogent, interactive and iterative. Also, Joana and Jill (2011) and Saunders et al (2016) postulate that, qualitative research brings meanings from words and images as opposed to numbers. However, despite its robustness and rigour of its application, it is skewed more to the interpretivist ideologies since researchers draw conclusion from participants and the hypothesis being forecasted (Joana and Jill, 2011; Saunders et al., 2016).
Stocchetti, N., Pagan, F., Calappi, E., Canavesi, K., Beretta, L., Citerio, G., … Colombo, A., (2004). Inaccurate early assessment of neurological severity in head injury. Journal of Neurotrauma, 21(9), 1131-1140. doi:10.1089/neu.2004.21.1131
Luciana M, Lindeke L, Georgieff M, Mills M, Nelson CA. Neurobehavioral evidence for working-memory deficits in school-aged children with histories of prematurity. Developmental medicine and child neurology. 1999;41(8):521-533.