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Effects of Technology on Adolescent Sleep and Mental Health: Johansson et al.’s Study Analysis Essay (Critical Writing)

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Abstract

Insufficient sleep has been affecting adolescents all over the world regardless of their race and gender. The primary goal of this research paper is to provide diversified information on how the Internet has reduced the quality of life among adolescents. To portray the effects of insufficient sleep, the paper links educational performance between internet addicts and the rest of the population. The research article gives information on the effect of technology on sleep, making this its great strength. The paper addresses the general health implications of insufficient sleep. Not digging deep into the specific implications of technology use makes the paper of the paper incomplete and leaves room for improvement.

Background

Problem and Purpose Statement

Daytime functions such as study, work, and play activities determine the quality of one’s living. The quality of life depends on the sleep one gets, whether sufficient or insufficient. This paper aims to provide the effects of technological devices, such as phones, computers, and video games, on the number of sleep Adolescents all over the world (Johansson et al., 2016). Explaining the relationship between technology use and reduced quality of life clarifies the problem.

The significance of using different ethnic groups in the paper was to show the regions with the highest propensity to stress and suicidal ideation worldwide. The high dependency on technological devices proses sleep users, which triggers negative psychological thoughts and threats, including depression (Johansson et al., 2016). The problem statement serves as a tool for adolescents to know when technological use is causing adverse effects on their lives and seek professional help.

Ideally, adolescents require more sleep than people in the post-puberty stage. A sleep time of more than 7.3 hours, portrayed by many adolescents worldwide, brings a make in their homeostatic processes (Johansson et al., 2016). The critical argument in the research paper is to show the alterations in sleep-wake patterns and how they are triggered by lack of sleep. The primary aim of this paper is to study the psychological differences between an adolescent dictated to technological devices and another free from addiction. The notable difference in carrying out similar daily activities is the standard measure of the effects of using devices before bedtime.

Literature Review

In the literature review, the research paper addresses the psychological issues due to insufficient sleep. Lack of sleep among adolescents has become detrimental to their health and well-being. Health implications, such as obesity and homeostatic imbalances, which are the imbalance of sleep, have resulted from insufficient sleep (Khor et al., 2021). Adolescents worldwide have the highest population that uses electronic devices. Due to the high internet consumption before bed, regardless of race, occupation, and gender, they have portrayed reduced motivation in studies, lowering their overall quality of life.

Survey

The survey instrument, a critical part of the literature review, shows the prevalence of the Internet in adolescents based on race and gender. According to the available research, over 97 % of adolescents worldwide use electronic devices, with the highest percentage being mobile phone users (Johansson et al., 2016). Amongst the Internet users, most of the adolescents reportedly had slight rotation and poor judgment concerning daytime activities.

Lack of sleep among adolescents is the problem area of the research paper, and therefore, regulating the use of technology before bedtime hours is the ultimate solution of the study.

According to the survey reports on sleeping habits, the average sleep hours among adolescents was 7.3 hours (Johansson et al., 2016). Therefore, the study’s objective is to enlighten adolescents on the effects of these poor sleeping habits. The parent study, the primary method used to determine the overall effect of poor sleeping habits, surveys adopt a solution-oriented approach that gives recommendations on how to avoid using electronic devices before bedtime.

Research Limitations

In the research study, several limitations comprise the reliability and validity of the results obtained. The survey used 1508 Americans of different races as the study sample (Khor et al., 2021). The number is relatively small and unlikely to represent the sleeping habits of the entire American population. In the survey, the National Sleep Foundation takes diverse livings within America to represent their native zones, such as the Hispania, which represents Latinos and blacks for Africans (Johansson et al., 2016). Some adolescents have problems sleeping and, due to that, use technological devices to occupy themselves during the night. The research study does not use these facts to table sleeping habits, increasing the irrelevance of the paper.

Key Concepts and Variables

The key concept in the research paper is the adverse effects of using technology at bedtime. Direct devices, including mobile phones, iPods, televisions, and music devices, are the essential tools leading to adolescent sleep deprivation (Sharman & Illingworth, 2020). Inadequate sleep is perceived to be less than seven hours, while adequate is ten hours for adolescents. When technology becomes harmful to the user and what the adverse impacts of using technology are is the research question in this paper. Contrary to benefits, over-reliance on technological devices since phones, computers, and televisions have resulted in psychological implications such as high crime rates, immorality, and lack of motivation.

Methodology

Study Design

Sampling and random surveys on adolescents made the primary study design of the impacts of technology on adolescent sleeping habits. Digit dialing was the primary telephone survey method for the selected population. Uunprogrammed calls made by SDR Consulting ensured that the information was reliable since it was free from bias (Bonnar et al., 2019). Telephone and internet surveys are the principal data collection methods in the survey. Using these technologies improves the research study designs since the target population also uses the devices.

Sample Selection

Random grouping performances are selected during the sample selection. SDR Consulting Inc., the center of sampling quotas in unique tastes, gives relevant information on adolescents’ demographic patterns. The maximum sampling error allowed in the selection of the sample is 5 % (Johansson et al., 2016). A sub-sample of 255 adolescents aged 13- 21 was selected (Johansson et al., 2016). A large number of participants makes the statistical data and the research results reliable.

Grouping young adolescents with older adolescents was a critical step in showing the trends of the use of technology, which reduces with an increase in age. During the initial survey, 1,508 Americans were selected as the test group by the sleep experts at the National Sleep Foundation Adolescents (van den Eijnden et al., 2021). All the participants, who include Caucasians, Africans, and Hispanians, underwent an 18-minute survey to determine their phone usage before bedtime. For this case study, the number of participants is ideal to ensure a lack of results for a larger population.

Data Collection Instruments

Sleep quality, adolescent sleep habits, demographics, and technology use are the four survey instruments adopted. Sleep habits, broadly grouped into waking time, bedtime, and naps, portray the prevalence among adolescents who get quality sleep. The quality of sleep, therefore, was determined on a specific scale referred to as the Likert, which assessed the ease and difficulty of falling asleep among adolescents (van den Eijnden et al., 2021). Regarding demographics, particular ethnic groups, such as Africans and Caucasians, have different exposure to technological devices.

Internal and External Validity

The appropriateness of a particular study to provide the desired answers defines its reliability. On the other hand, the quality of data to measure exacts the parameter, which is intended to be called validity. The study aims to determine the impacts of technology use amongst adolescents and promote reliability and validity. Internal validity features in the study design include demographics such as gender, ethnicity, and race (Sharman & Illingworth, 2020). External validity is promoted by the difference in gender in the survey study; male adolescents spent more time on technological use before bedtime than their female counterparts. The rate of psychological problems, such as suicidal ideation, is higher than in females.

Instrument Reliability and Validity

A sample of adolescents from diverse ethnic and racial backgrounds substantiates instrumental reliability within the research study. Since the continuous variable in the study is adolescent sleeping habits, the data analysis plan depended on the frequency and deviations in sleep among the respondents. In addition to sleep habits, sleep quality, an independent variable, was measured using the 4-item Likert Scale (Sharman & Illingworth, 2020). The sleep adequacy obtained from the results determined adolescents’ quality of day activities, making the study appropriate. The sleeping habits and frequency, which are the variables, are controlled and measured through a comparative approach, where the participants’ responses are compared.

Equipment and Materials

The technological equipment used in the study design included television, video games, computers, and mobile phones. The devices make up a considerable percentage of the instruments used before bedtime, which have a high chance of addiction. The information collected is convincing since it portrays that the reliance on these devices promises visual arousal, necessitating addiction. During the survey, the calls made to the participants were voluntary pickings (De Zambotti et al., 2019). Moral rights, such as information transparency and the integrity of the company agents, were ensured as critical tools to attain truthful information.

Results

From the sample study, the populations portrayed diverse sleep patterns depending on their race, gender, and occupation. Generally, 9% of the adolescents went to bed crying late and slept below six hours (De Zambotti et al., 2019). Comparing the younger to the older adolescents, the older went to bed late and woke up late. Due to the inadequate sleep promoted by poor sleeping patterns, 67% of adolescents woke up unrefreshed. The unrefreshed conditions led to poor completion of daily activities. Waking up late caused drowsy drying among 18% of the old adolescents, predisposing road accidents.

Regarding technological uses and bedtime, the study survey portrayed that phone usage was the major contributor to late sleeping. 55% of the 255 adolescents who participated in the survey used bed before bedtime, with men being sores addicts at 69%. Females constituted 31% (Johansson et al., 2016). The study analysis, p, gives the correlation between adequate and inadequate sleep. In the statistical analysis, the independent students were assigned the value t, and their speech habits were analyzed using Pearson’s r for the variables that were continuous. The weekday sleep routine for the students (t=255) was recorded to be greater than 0.15 on the Likert scale, f= 0.15 (Johansson et al., 2016). Using these dependent variables, such as sleep time, 40% of the students woke up very late, resulting in a negative correlation of -0.16 on the Likert scale (r = -0.16). The negative values showed high levels of inadequate sleep among the selected sample.

The National Sleep Foundation’s sleep expert’s information was extracted from abstract analysis, making it reliable and transparent. The organization’s results can be used for further statistical research due to random sampling and non-biased analysis (Sharman & Illingworth, 2020). The study survey provides adequate therapeutical approaches to revert the implications and lead a healthy lifestyle for adolescents suffering from psychological conditions due to poor sleeping habits.

Discussion

The paper addressed the psychological consequences of using technological devices before sleep. The psychological effects of technology use are detrimental since they cause serious health problems to the user. Adolescents are the most vulnerable lot due to their relative inactivity related to adults. Therefore, unchecked technological use among adolescents can result in delinquent, drug, and sexual abuse (Bonnar et al., 2019). The results extracted from the statistical data portray that most adolescents’ sleeping habits have been altered by technological use, reducing their productivity and physical activity.

Mental growth is as essential as physical growth, so adequate sleep is critical among adolescents. The results of the research, which portray that high use of technology promotes negative psychological issues, are consistent with previous studies that relate sexual immorality to technological use. This research study provides additional information on the scientific relationship between lifestyle diseases. The small sample of adolescents chosen in the study might lead to misleading information about the health location of technological use. The limitation is an opportunity for further research, including a more significant sample for reliable results.

In conclusion, the paper enlightens adolescents on the negative impacts of technology use before sleep. In the literature review, the over-reliance on technology leads to addiction, which promotes psychological disorders. Inadequate sleep is widely spread amongst young and old adolescents, regardless of race and ethnicity. Educating adolescents, regardless of age, on the importance of regulated internet use and proper sleep will promote disengagement from electronic devices.

References

Bonnar, D., Castine, B., Kakoschke, N., & Sharp, G. (2019). Sleep Health, 5(6), 647-650. Web.

De Zambotti, M., Cellini, N., Goldstone, A., Colrain, I. M., & Baker, F. C. (2019). . Medicine and Science in Sports and Exercise, 51(7), 1538. Web.

Johansson, A. E., Petrisko, M. A., & Chasens, E. R. (2016). . Journal of Pediatric Nursing, 31(5), 498-504. Web.

Khor, S. P., McClure, A., Aldridge, G., Bei, B., & Yap, M. B. (2021). . Sleep Medicine Reviews, p. 56. Web.

Sharman, R., & Illingworth, G. (2020). . Current Opinion in Physiology, 15, 23-28. Web.

van den Eijnden, R. J., Geurts, S. M., Ter Bogt, T. F., van der Rijst, V. G., & Koning, I. M. (2021). . International Journal of Environmental Research and Public Health, 18(3). Web.

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