Episodic Sleep

Introduction: The purpose of this paper was to determine the link between slow-wave sleep and episodic memory changes from younger to older adults. The title of the article written by Michael K. Scullin; Sleep, Memory, and Aging: The Link Between Slow-Wave Sleep and Episodic Memory Changes From Younger to Older Adults was conducted to determine the cognitive processes in sleep, making this a quantitative and empirical study. Newman (2011) states that, “qualitative research is a descriptive approach that attempts to gain a deep understanding of particular cases and contexts; quantitative research is a systematic and empirical approach that attempts generalize results to other contexts”. Scullin definitely provides adequate information in

what slow-wave sleep is and past studies that discussed this. I didn’t find there to be much bias in the article, but enough information to understand the conclusion in which Mr. Scullin came too.
Methods: Originally 125 individuals were contacted for the study, after weeding out the participants, there were fifty-seven young adults and 41 older adults were recruited from Washington University psychology department participant pools and were assigned to one of three different groups randomly.

The three different groups were: 12-hr wake, 12-hr rest, and 24-hr (night-to-night) sleep groups (Ellenbogen et al., 2006). In spite of the fact that participants were randomly assigned to one of the three groups, they self-chose their most ideal time amid the 7–10 a.m./p.m. time to partake.

The participants were prescreened for past usage of taking medication that altered their sleep, any past/current diagnosis of a sleep disorder, and any mental disorders. Twenty-seven adults were considered ineligible after taking the screening test. The participants were also excluded if they didn’t return for their follow up session, if the excessively napped, and if there was an equipment failure leading to no sleep

data.
Materials used to conduct the research were word records, comprising of two-syllable things, were created from dictionary databases (e.g., Balota et al., 2007; Coltheart, 1981); and they were intended to be comparative in normal word length, image ability, recurrence, and solidness.

These word combinations would be used to determine cognition through sleep and wake times. Words were matched together arbitrarily, with the special case that conspicuous semantic relationship between the combined words was evaded. The conceivable impact of late rest propensities was inspected by managing the Pittsburgh Sleep Quality Index (PSQI; Buysse, Reynolds, Monk, Berman, and Kupfer, 1989), which makes inquiries seeing commonplace wake and sleep time and also the shared characteristic of rest aggravations over the previous month. These questions would be asked at certain times of day when alert relevance was determined by utilizing the MEQ (Horne and Ostberg, 1976); which makes inquiries identified with morning sharpness and in addition favored time to take a test, to work out, to work, et cetera (Scullin, 2013). Sleep was monitored utilizing an in-home unattended sleep testing device. There was a device worn on the forehead as well as a device called an Actiwatch2 which was worn on the

wrist.
This study’s first session took place at (7–10 a.m.) or at night (7–10 p.m.), and the careful time of testing relied on upon the members' self-reported most ideal execution time inside of the 7–10 a.m./p.m. extent (to diminish conceivable impacts identified with circadian mood age bunch contrasts). Members were initially requested that round out the MEQ and the PSQI. While the participants were being studied there were shown the word combinations on a computer screen as well as given easy math problems to solve. Each participant needed to score higher than 80%; if they did not score this well, they went back to the study phase.
Results: Table 1 introduces the methods and inferential measurements for sleep recording, PSQI, and MEQ scores crosswise over more youthful and more seasoned grown-ups.