Relationship Between Sleep and Depression in Adolescence

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Abstract

Recent studies suggest a decreasing duration of sleep in different parts of the world. In fact, the number of sleep hours per person has increased since 1960s, with people concentrating on work and reducing the amount of time they spend sleeping. While this pattern has improved household and national economies, it has been associated with health problems.

Mental and emotional depression, cardiovascular diseases, stroke, coronary diseases and other health issues have been linked with lack of enough sleep. In adolescents, sleep is needed for proper brain maturation. However, adolescents, especially in school years, do not get enough sleep. As such, it has been linked to emotional and mental depression.

The aim of this research was to determine the relationship between depression and sleep. With quantitative approach, the study used 98 students as participants.

They were asked to provide answers to questions in Pittsburg Sleep Quality Index (PSQI) and Center for Epidemiology Depression Scale (CES-D) questionnaires. Using SPSS for data analysis, the results indicate the presence of a correlation between elements of depression and sleep duration and quality.

Introduction

Background

In psychological view, depression is the prolonged feeling of hopelessness and sadness, prolonged condition of impaired thinking, biased processing of memory, unpleasant dreams and distortion of self-appraisals (Turek, 2005). For sometime, research has indicated the existence of a strong link between sleep and depression in humans(Cappuccio, Cooper, D’Ella, Strazzulo & Miller, 2011).

For instance, when individuals get depression, they tend to sleep too much or too little. In most cases, lack of sleep has strongly been linked with depression (Gangwisch, Babiss, Malaspina, Turner, et al., 2010).

Review of literature

According to Matricciani, Olds and Petkov (2012), depression is a serious psychological disorder that affects millions of people throughout the world. In particular, depression is common in adolescents and young adults. According to Patel and Hu (2008), adolescents who suffer from depression are known to have abnormal sleeping patterns, with the largest number reporting to stay awake over long time.

Existing research indicate that sleep is an essential requirement for brain growth and maturation during childhood and adolescents. According to Dahl and Lewin (2002), the increased rate of brain maturation during adolescent years requires adequate sleep per day.

According to Wolfson and Carskadon (2008), the average sleep duration varies between individuals in adolescents and those in late childhood, but the optimal sleep time in both groups is about 8 to 10 hours (Feinberg & Campbell, 2010). Despite this, studies have increasingly shown that adolescents do not get enough sleep per day, especially during their school years (Warner, Murray & Meyer, 2008).

In a 2006 report, the National Sleep Foundation reports that less than 20% of adolescents get the physiologically required sleep time (about 9 hours) (Gradisar, Gardner & Dohnt, 2011). In addition, the report shows that more than half of adolescents indicated that they usually slept for less than 8 hours per night during their school days (Matricciani, Blunden, Rigney, Williams & Olds, 2013).

According to Blixter (2009), some complex and multifactorial mechanisms drive and control sleep cycle in humans. Blixter (2009) argues that the subjective duration of sleep in humans has declined over the last 5 decades, with the modern society suffering from a widespread suboptimal sleep duration and poor quality of sleep (Hagenauer, Perryman, Lee & Carskadon, 2009).

However, Mattricciani, Olds and Petkov (2012) have argued that the decline in sleep duration started more than 100 years ago, predisposing children and adolescents to a number of psychological problems. Whichever the case, it is a fact that there has been an increase in the rate of reduction in sleep duration since the industrial revolution (Bin, Marshall & Glozier, 2012).

Accordingly, there is an urgent need to study and understand the complex mechanisms involved in sleep regulation and sleep duration in order to develop a better way of identifying individuals at high risk of developing depression (Van Dongen, Maislin, Mullington & Dinges, 2003).

Although psychological studies have shown that adolescents are able to compensate for sleep loss during the school week on weekends, the findings are not satisfactory to imply that adolescents in the modern world do not suffer from depression caused by lack of sleep (Sun Bin, Marshall & Glozier, 2012).

Study problem

Depression in adolescents has been linked to sleep deprivation and insomnia (O’Brien & Mindell, 2005). In addition, studies have suggested that depression leads to reduced duration of sleep and irregular schedules for sleeping (Kripke, Garfinkel, Wingard, Klauber & Marler, 2002).

In turn, sleep loss has been shown to cause depression among the adolescents (Feinberg, 2013). This is a clear indication of a sophisticated nature of the relationship between lack of sleep and depression (Carskadon & Acebo, 2002). This nature has created a problem in research than needs further investigation.

Purpose

The purpose of this research was to determine the relationship between sleep (and lack of sleep) and depression in adolescents.

Aims

  • To describe the link between sleep and depression in humans
  • To describe how lack of sleep and insomnia in adolescents lead to depression

Hypothesis

This study hypothesizes that a strong link between depression and sleep exists in humans, where adolescents with insomnia and reduced sleeping durations are likely to suffer from depression.

Methods

Study design

This study was a quantitative study that sought to describe the relationship between sleep and depression in adolescents. Participants were drawn from students in a college, whose ages ranged between 19 and 25 years. This means that the study focused on sleep deprivation and depression among late adolescents and early adults.

Participants

Some 98 subjects were recruited for the study- 28 subjects (28.6%) were males and the rest 70 (71.4%) were females. To be included in the study, a subject was a student in the selected college and be aged between 18 and 25 years. In addition, a person was not supposed to have a history of mental problems.

Finally, subjects were supposed to belong to either of the two genders (male, M, or female, F), which means that transgendered (TG) individuals were excluded from the study.

Materials and apparatus

Data collection was done with questionnaires

All the 64 participants were asked to finish two sets of standard questionnaires- the Pittsburg Sleep Quality Index (PSQI) and the Center for Epidemiology Depression Scale (CES-D).

Procedure

The data collection was done in two weeks, after which the data analysis begun. With PSQI, each participant was asked to provide honest information regarding his or her sleep behaviour. The purpose was to gain information on an individual’s average sleep time, possible sleeping problems and possible effects of sleep deprivation on work, study and leisure (Babson, Trainor, Feldner & Blumenthal, 2010).

With CES-D, participants were asked to provide information concerning their feelings towards certain things during the day as a way of describing the presence (and degree) of depression in individuals (Jackson, Stough, Howard, Spong, et al., 2011).

Data analysis

Data analysis was done with specific statistical tools- SPSS and lab data. With these tools, the aim is to develop the relationship between sleep and depression in the subjects (Szklo-Coxe, Peppard, Finn et al., 2010). Graphs and correctional charts were developed using SPSS tool to describe the relationship.

In this case, the study depended on Person Correlation Scale to determine the association between sleep duration and depression in the subjects. Standard deviation, mean and range values are essential in describing the statistical aspects of sleep duration in PSQI data.

The analyzed data was done within the statistical limits provided along with the statistical tools used. As such, the researcher expected any error associated with the capacity of the two statistical tools to affect the data outcomes.

Results

With SPSS, a number of statistical evidence was indicated to support the existence of a relationship between sleep duration and depressed moods in the subjects. First, the validity of the returned questionnaires was excellent, with the SPSS results indicating a 100.0 per cent rate of validity. This means that all the 98 participants were able to return a complete set of duly filled in questionnaires.

Secondly, the SPSS analysis of depression in the participants using PANAS questionnaires indicated that the mean of the number of participants reporting Positive Affect was 33.34 and a standard deviation of 5.740. On the other hand, a mean of 20.70 of the total number of participants (N=98) reported a Negative Affect.

Sleep duration reported by all the participants ranged between 5 and 12 hours and had a mean of 7.633 and a standard deviation of 1.1500. In addition, SPSS returned a mean value of.88 and a standard deviation of.763 for SLPQUAL. The total PSQI had a mean of 6.29 and a standard deviation of 2.528.

SPSS Output

Descriptive Statistics
N Range Minimum Maximum Mean Std. Deviation
Age 98 29 19 48 22.08 4.181
Positive Affect 98 29 19 48 33.34 5.740
Negative Affect 98 27 10 37 20.70 6.196
DURAT 98 7.0 5.0 12.0 7.633 1.1500
SLPQUAL 98 3 0 3 .88 .763
TotPSQI 98 14 1 15 6.29 2.528
Valid N (listwise) 98

Figure 1: SPSS output showing the range, mean and standard deviation of various aspects of sleep and depression

The study also sought to determine the relationship between depressions and sleep duration in both genders. In addition, it was necessary to determine a comparison of the two genders in terms of the relationship between the two variables.

In this case, the SPSS results indicated that female participants had a mean range of 22.07 and a standard deviation of 4.305. On the other hand, male participants had a mean value of 22.11 and a standard deviation of 3.928.

Gender Statistic Std. Error
Age 1 Mean 22.07 .515
Std. Deviation 4.305
Minimum 19
Maximum 48
2 Mean 22.11 .742
Std. Deviation 3.928
Minimum 19
Maximum 36

Figure 2: SPSS output table showing descriptive per gender

the correlation of sleep duration and aspects of depression were considered with Pearson correlation toll using SPSS. For instance, the correlation between Negative Affect and Duration (sleep) returned a 2-tailed degree of significance of.948 and a Pearson correlation value of -.007 for the 98 participants.

Similarly, the correlation between Negative Affect and SLPQUAL returned a 2-tailed value for degree of significance of.365 and a Pearson correlation value of 0.93.

Correlations
Negative Affect DURAT
Negative Affect Pearson Correlation 1 -.007
Sig. (2-tailed) .948
N 98 98
DURAT Pearson Correlation -.007 1
Sig. (2-tailed) .948
N 98 98

Figure 3: Correlation between Negative Affect and sleep Duration

Correlations
Negative Affect SLPQUAL
Negative Affect Pearson Correlation 1 .093
Sig. (2-tailed) .365
N 98 98
SLPQUAL Pearson Correlation .093 1
Sig. (2-tailed) .365
N 98 98

Figure 4: correlation between Negative Affect and Sleep quality

Correlations
Negative Affect TotPSQI
Negative Affect Pearson Correlation 1 .207*
Sig. (2-tailed) .040
N 98 98
TotPSQI Pearson Correlation .207* 1
Sig. (2-tailed) .040
N 98 98
*. Correlation is significant at the 0.05 level (2-tailed).

Figure 5: correlation between Negative Affect and Total PSQI

Conclusion

To derive an analysis and conclusion from the data results, it is necessary to determine the statistical facts of the SPSS tool that was used in the study. First, for a correlation to be perfect positive, the Pearson’s r must be positive and vice versa.

In addition, Pearson’s r is symmetric, meaning that the correlation between “a” and “b” is equal to the correlation between “b” and “a”. Thirdly, the correlation is a bivariate correlation coefficient, which assumes that the relationship between the two variables is always linear.

With this in mind, it is possible to evaluate the relationship between various aspects of sleep with aspects of depression as used in this research. First, the relationship between Negative Affect and sleep Duration is negative, which means that the longer the duration of sleep, the lower the possibility of giving a negative feeling of an issue.

Secondly, the Pearson correlation between Negative Affect and sleep quality is positive, which gives a positive relationship between the two variables.

The relationship between Positive Affect and sleep duration is positive, which implies that the longer the duration of sleep time, the larger the possibility of having a positive attitude towards some issue. The relationship between “Sleep Qual” and positive Affect is negative, which is the opposite of the relationship between “Sleep Qual” and Negative Affect.

From the results, it is clear that there exists a relationship between sleep duration and depression. For instance, the probability of reporting a positive attitude towards an issue increases with an increase in the duration of time of sleep. On the other hand, the probability of a student giving a negative attitude towards a given issue increases with the decreased in the duration of sleep time.

Therefore, we conclude that decrease in the duration of time spent on sleep increases the rate of depression in adolescents and early adults. These results studies have suggested that depression leads to reduced duration of sleep and irregular schedules for sleeping.

Therefore, the study confirms the hypothesis that that a strong link between depression and sleep exists in humans, where adolescents with insomnia and reduced sleeping durations are likely to suffer from depression.

References

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