Introduction
Developmental research focuses on the progression of changes occurring in an organism as it develops. Developmental changes are irreversible. There exist several differences in the magnitudes of development between periods of several years of growth. The development research psychologists seek to understand what changes cause the difference. Considering a speed processing perspective, aging results in the slow cognitive processing speeds inclusive of all the processing components. A prediction of the mean response times of adults advanced in age in comparison to younger adults proves how the cognitive processes slow down with age advancement. The simple linear memory and aging functions account for 90% of the variances that are age related considering the various wide measures (Purser, 2006). Large scale path analysis and psychometric studies argue that processing speeds are the mediators between a variety of cognitive functions and age.
The cognitive function mainly studied was the memory functionality. As such, the perspectives of processing speeds explain the processing speed reduction and the age-related decrements in memory. Age is related to the general speed factors and memory performance as well. However, the relation between age and performance of the memory is weak after statistical controls are set up for controlling the processing speeds. Path analysis results prove that the performance of a person’s memory is dependent on the processing speeds. As such, age differences in memory are not a reflection of changes in processing memories per se but are just a reflection of the processing speeds. The old people process information slower than young adults leading to a theoretical account of cognitive performances related to age. Complicated cognitive tasks require attentional capacities that are different than the simple cognitive tasks.
Measurement of the Dependent Variables
The psychologists that research the changes in the normal aging state are in agreement that some memory aspects and processing speeds change as people age, but basic behavioral changes help most people remain sharp for long periods of time. Research on what happens to a healthy brain as it ages explains the basic changes. Most research explain that one has to understand what happens on the inside to relate to the external happenings. The volume of the brain reaches its peak at the age of 20, and a decline begins to record. At the age of forty, most people note a considerable decline in the ability to remember new names. Researchers explain it as the shrinking of the cortex. The neurons atrophy and result in a reduction in the extent of nerve cell connection. Notably, there is a reduced blood flow in a normally aging brain.
The behavioral changes among people have a link to the brain changes. Verbal fluency reduces as a result of reduced blood flow in the frontal cortex (Thomas et al., 2009). However, the storage capacity of a brain is not usually an issue. As such, the brain should not be perceived as a hard drive capable of being overloaded. Instead, the issue is how efficiently a person encodes as well as retrieves information. The interference is measured by the number of distraction blocks inhibiting the encoding processes.
Description of the Design used in the Research
Research studies mainly focus on two designs of comparing a group of people under study. The longitudinal designs sample a population at intervals to study and examine the developmental effects. To study the development of memory in adults, we begin with 20-year-old young adults. The group is then studied every 20 years and the changes recorded to determine the results. The second main option is the use of the cross-sectional design. The design involves the use of several group samples and conducting a study along a certain path of development. The design saves time and is the most preferred of the two designs. Unlike the longitudinal design where a group of 20-year-olds is taken and studied for 60 years, the cross-sectional design uses four groups of age 20, 40 and so on. The two designs are at times combined to result in the study of different cohorts over time. While choosing a design, a researcher considers the validity of its ecology. The ecology of research designs is the level of application of the real-world situational settings.
Cross-sectional designs have several benefits. First, they are particular in nature. Second, is relatively inexpensive and achieves the goal of measuring the changes with development. There is also a significant commitment by the participants unlike in the longitudinal designs that take prolonged periods of time. It is, however, worth noting that the cross-sectional designs handle different individuals with a difference in the cognitive abilities.
Prediction of the Research Results
A study by psychologists referred to as (ACTIVE) Advanced Cognitive for Independent and Vital Elderly had results showing that brief mental workouts improved brain performance that remained sustained for up to five years. Training conditions for the test subjects included different thinking skills such as pattern reasoning, memorizing lists and some conditions where no training had occurred (Thatcher, North, & Biver, 2008). The volunteers received a ten-hour instruction session baseline. Five years later, there was a comparison with the untrained control subjects. The trained group indicated a significant advantage in performance on the taught thinking skills.
Conclusion
The cross-sectional abilities in the future depend on the researchers extending their boundaries and asking the possible trajectories in the patterns of the changes in the cognitive abilities. They also ought to use brain imaging technologies to achieve answers on the neurophysiological and neuroanatomical cognition underpinnings.
References
Purser, H. R. M. (2006). Short-term memory in Down syndrome. Unpublished Ph.D. thesis. University of Bristol.
Thatcher, R. W., North, D. M., & Biver, C. J. (2008). Development of Cortical Connections As Measured By EEG Coherence and Phase Delays. Human Brain Mapping, 29(12), 1400-1415
Thomas, M. S. C., Annaz, D., Ansari, D., Scerif, G., Jarrold, C., & Karmiloff-Smith, A. (2009). Using Developmental Trajectories to Understand Genetic Disorders. Journal of Speech, Language and Hearing Research, 52, 336-358. Retrieved from http://www.psyc.bbk.ac.uk/research/DNL/personalpages/Trajectories09.pdf
