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Running Head: FAMILY RISK FACTOR, DEPRESSION AND SLEEP DISTURBANCE 1

Family Risk Factor and Depression predicts Sleep disturbances among emerging adulthood Shirly Khoh (29636779) Monash University Malaysia

PSY3062 Milestone 2 Tutor: Ms. Genevieve Wong Class: Tuesday, 9 - 11 am Word Count: 3000

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Family Risk Factor and Depression predicts Sleep disturbances Emerging adulthood between the age 18 to 24 associates with distinct changes in their normal sleep-wake cycles (Patten, Choi, Gillin, & Pierce, 2000) usually facing a developmental reduction in their sleep cycles and encounters phases of delay in the timing of sleep and these are the source on the rise of family risk factor and depression which associates lower quality of sleep among individuals. It has been reported that sleep disturbance has a higher prevalence in approximately one-third of the emerging adult populations. It has been examined that sleep disturbances are categorized differently where chronic sleep disturbances usually last for years to decades. Epidemiological surveys indicated between 9% to 15% of the adult’s population fussed about their chronic insomnia which often associates with frequent sleep difficulties and individuals constantly report having psychological disorders such as depression, anxiety, and these psychological factors has increased the vulnerability of individuals to develops insomnia (Bastien & Morin, 2000). A longitudinal study of an eight-year UK examined one-third of the individuals who still reporting insomnia symptoms in 1985 continually predicts symptoms after 4 years later, 1989 (Dregan, 2010). Sleep disturbance is often unnoticed, and rarely scrutinize its component of illness which affecting one’s health status. Individuals who experienced poor sleep may respond to certain psychological distress which leads them to perceive negative health outcomes. According to research, sleep disturbance has constituted an important contributor to health disparities among Black individuals in the United States, (US) (Pigeon et al., 2011). In the US, the majority of the black community are facing common chronic stress such as chronic insomnia which approximately 10% of the populations encountered and resulting in poor health due to lack of social advantages and these US-born Americans are forced into enslavement and its

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consequences precipitate increase of sleep disturbances and low quality of periods of sleep (Pigeon, 2011). Findings also examined 35% of patients who seek their insomnia incidence at a sleep disorders clinic generally have a positive family history of sleep disorders (76%) and this common type of sleep disturbances are usually genetically affecting mother in the family member (Bastien & Morin, 2000). Individuals with depression often encountered difficulties falling asleep and stay asleep during the night. According to research, females are more prevalent at high risk of depression compared to males, and this pattern continues to arise in adolescence and adulthoods (Morris, Mcgrath, Goldman, & Rottenberg, 2013). Depression and sleep disturbances typically associate with emerging adult’s sleeping disorders (Ford & Kamerow, 1989), and risk indicators are usually linked to parental loss, family, loss, physical and sexual abuse, and these are further internalized the problems to sleep disturbances among individuals. Research determined depression have strong correlations with sleep disturbances which are the core symptoms that result from depressing moods and required to seek helps to prevent further risk factor of suicidal ideations among adulthoods (Wilson & Nutt, 2008). Besides, depression levels usually increased because of perceived chronic stressful life situations that individuals experienced which leads to the risk of developing depression when individuals unable to cope with the stress which speculates irregular sleep-wake cycles. The exposures of individuals to the severity, repetitive and uncontrollable stressor may precipitate the development of psychopathologies which are referred to as mental illness which involved psychological impairment, and individuals with depressive symptoms tend deficits in their hippocampus functioning. Research determines the reduction of the hippocampal volume are consequences of major depressive disorder which lead individuals to experience cognitive impairments and individual who developed insomnia often

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predicts depressive episodes (Riemann and Voderholzer, 2003). Sleep deprivation mostly affects an individual’s hippocampal-dependent memory formation and it interfered with the reductions of an individual’s neurogenesis because of the insufficient sleep that may indirectly result from stress (Mirescu et al., 2006). Additionally, the precipitating factor of sleep disturbance is also associated with significant stress in a family that results in individuals obtained a low quality of sleep. Sleep difficulties are commonly reported by individuals where the symptoms can prolong for years from the current or past event which occurred (Tavernier et al., 2019). About two and a half million populations of United States died each year, where individuals experienced the recent loss of their loved ones or past which are distinguished into two forms of normative reactions of death, protest of despair (Schwartz, Howell, & Jamison, 2018). Therefore, it is likely individuals perceived health problems which eventually affecting their sleep disturbances after the onset of severe illness events occurring in the family (Vahtera, Pentti, Helenius, & Kivimäki, 2006). However, they will be experiencing maladaptive grief which includes sadness, insomnia, tearfulness, and decreased in their appetite and this predicts them having a significant amount of distress and impairment, decreased quality of life, the rise of suicidal ideations, and excess of medical morbidity. Hence, individuals who perpetrate psychological distress tends to undergo momentous distressing incidence that involves traumatic events such “the death of a family member or close friends”, separation or divorce among their parents, and traumatic sexual or physical experienced which have impacted their life (Schwartz et al., 2018). Moreover, research determined between 16% and 65% of homeless emerging adults comorbid with illicit drugs like cracks and cocaine usage where they facing severe family history; parental substance misuse, family abuse, and hence, this promotes them leaving home and the presence of drugs and

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alcohols able to cope and escapes from the intrusive thoughts with their past and present situations which influenced their sleep cycles (Tyler & Johnson, 2006). Family Stress Theory can be implemented to explore how acute stressors happen within a family and this can help families to deal better with their problems and continue to nurture their children despite to upbringing of chronic and acute stressors. Past research has indicated the increased of the social and emotional problem have taken a psychological toll for both children and adolescence when parental conflicts occur in the family; divorce, separation, etc, and these burden of stress contributing to their sleep disturbances and buffering against the emotional and behavioral during their developmental life span. (Wadsworth & Berger, 2006). This theory is important in reducing the stress which individuals perceived within the family’s environment and can help to improve their sleep from the acute stressors. More, depression is extremely comorbid with sleep disturbance among emerging adults such as insomnia and a model aimed to help reduce the severity of insomnia and depression by using Cognitive Behavioural Therapy (CBT) (Cheng et al., 2018). CBT approach can be done online, and the accessibility increases as participants have access to primary care settings where they experienced depression and encounter higher sleep disturbance which involved low sleep quality. Therefore, CBT is important in a primary healthcare setting for everyone to have access to it and helps to reduce health disparities in accessing mental healthcare. (Cheng, 2018). The present study aimed to determine how family risk and depression predict sleep disturbances among emerging adults. It is hypothesized, the higher the level of family risk factor and depression will have positive correlations of sleep disturbances. It is crucial to examine in depths on the findings of family risk factors, and depression which predicts a high risk of sleep disturbance among individuals. It is hypothesized that both family risk and depression factors

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highly predict sleep disturbances among emerging’s adults' sleep cycles and rhythm and life span’s development. The lower the family risk factor and depression will predict lower degrees of sleep disturbances. Method Participants The study utilized data from the general community of ecological momentary assessment to investigates the behavioral and psychological what was implement from April to December 2019. Participants who participate meet the inclusionary criterion, aged between 19 to 40 years. All participants are required to own a smartphone (IOS or Android), able to comprehend in English, and not experiencing any major physical health conditions. A total number of 191 emerging adults (29 males, 79 females, and 83 others; Age: M = 22.55 years, SD = 4.12) are participants who are chosen and individuals who did not obtain consent are removed from the study. Before performing the study, informed consent is obtained. Materials The Activity, Coping, Emotions, Stress, and Sleep (ACES) written in the codebook, a 12day diary that was associates with the variables were administered. The variables are measured based on The Patient-Reported Outcomes Measurement Information System (PROMIS) in determining the scales for depression (“I felt depressed”, “I felt like a failure”, “I felt hopeless” and employ a 5-point Likert scale (1 = Never, 2 = Rarely, 3 = Sometimes, 4 = Often, 5 = Always). Sleep disturbance’s variable (“I had problem with my sleep”, I tried hard to get to sleep”) utilized a 5-point Likert scale (1= Not at all, 2 = A little bit, 3 = Somewhat, 4 = Quite a bit, 5 = Very much) (Cella et al., 2010). The family Risk factor is measured using the Risky

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Family Questionnaire (e.g., “how often would you say there war quarreling, arguing, or shouting between your parents”) with items 1,3,6 was reverse and summed to create a total score utilized 5-point Likert Scale (1= Not at all, 2 = Rarely, 3 = Occasionally, 4 = Often, 5= Very often) (Repetti, Taylor, & Seeman, 2002). Procedure All participants are provided with questionnaires that can be completed online on Qualtrics and the durations have given to attempts a single phase is 30 minutes. This study goes through ethical approval granted by the Monash University Human Research Ethics Board (project number: 2017-8245). Design This study utilizing correlational research, cross-sectional design to determine the associations between the variables. The dependent variable for this study is sleep disturbances and the independent variables are family risk factor and depression. It is hypothesized that, as a family risk factor and depression increase, sleep disturbance among emerging adulthood will increase. Results Primary Analyses The R Commander statistical software (Version 2.6-0) is utilized when performing the data analysis. Winsorization of data (Winsor 1951) is performed to all dataset purposed to reduce the extreme values which known as outliers and the cleaned data are made up of a total of 185 emerging adults (29 male, 79 female, 77 others) who between the age 19 to 40 years old. As

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shown in Table 1, a descriptive statistic for the three variables in the study; family risk factor, depression, and sleep disturbance are tabulated. Moreover, a Pearson correlation coefficient is run to determine the relationship between the variables. The Cronbach’s Alpha, α was computed to measure the internal consistency of the scales in the study. The coefficient alphas for the measures of each of the variables are as the following: Depression Subscale (α = .94), Family Risk Factor Subscale (α = .80), and Sleep Disturbance (α = .45). The standardized scores are calculated to determine the outliers in the study which are further known as z-scores that falls within the range of 3.29 and -3.29. All the relevant of the R’s script outputs are attached in the Appendix section. To determine the relationship between family risk factors and depression predicting sleep disturbance among emerging adults, a multiple regression analysis is conducted. It is shown that the concentration of significance values of 5% is performed with shown that it is statistically significant with a value of p < 0.05. Several assumptions are assessed before running the results of the analysis. Firstly, a scatterplot is generated to measure the form of relationship of direction between the two independent variables; family risk factor and depression for its linearity and residuals of data against the dependence variable; sleep disturbance. The scatterplot showed that family risk factors and depression are a positive correlation with sleep disturbance as shown in Figure 1 and Figure 2. For the second assumption, a Shapiro-Wilk test is performed in the study aimed to test the normality between the variables indicating three of the value in the study shows p > 0.05. Therefore, interpreting the statistical or whether it is a normal distribution of data in this analysis are determined based on the generated QQ plots, Boxplots, and Histogram. The third assumption, the Variance Inflation Factor (VIF) is measured to calculate the ratio for each independent variable that helps to interpret whether it is collinear with another

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variable in the analysis. Hence, both predictors in this regression model indicate low tolerances of multicollinearity because VIF values must greater than 10 to indicate the presence of multicollinearity (Thompson, Kim, Aloe, & Becker, 2017). Next, depression and family risk factor accounted for a non-significant 2.5% variability of the sleep disturbance perceived among emerging adults, with medium effect size f ² = 0.12, R² = .13, adjusted R² = .12, F(2, 182) = 27.89 , p < .001. The unstandardized (B) and standardized and (β) regression coefficients values for each predictor in the regression model of the study are as tabulated in Table 2.

Table 1 Descriptive Statistics with cleaned data Variables Depression Family Risk Factor Sleep disturbance

Mean

SD

n

52.24 26.26 46.79

8.99 6.21 8.09

185 185 185

Note. Descriptive Statistics with cleaned data for depression, family risk factor, and sleep disturbance, n = total emerging adult (female + male)

Table 2

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Unstandardized (B) and Standardized (β) Regression Coefficients for each of the predictors in the regression model predicting Sleep Disturbance Predictors

Unstandardized coefficients Standardized coefficients B β Depression 0.28 [0.15,0.40] 0.31 Family Risk Factor 0.17 [-0.01,0.35] 0.13 Note. The Unstandardized and Standardized Regression Coefficients each predictor

Figure 1 Scatterplot

FAMILY

NCE

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Note. Depression (DEP) against Sleep Disturbance (SDI) Figure 2 Scatterplot

Note. Family Risk Factor (RF) against Sleep Disturbance (SDI)

Discussion This study aimed in determining family risk factors and depression which predicts sleep disturbances among emerging adults aged 18 to 24 years old. It is hypothesized that the higher

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the psychological distress of individual with depression which triggered by stressful life events depression will have higher sleep disturbances because the total sleep time of an individual is reduced in their both sleep onset latency and wake rhythm and this strongly indicates emerging adulthood will have trouble falling asleep at night and awaken after the initial sleep onset (Cousins, Bootzin, Stevens, Ruiz, & Haynes, 2007). However, based on the result, the hypothesis of the study has been rejected. Results indicated a non-significant 2.5% variability between depression factor and family risk factor which predicts sleep disturbance among emerging adults. Therefore, this study has failed to determine the associations between depression factor and family factor predicting sleep disturbance that occurs among emerging adults in the study because of several limitations in the study. The strength of the study is cost-effective because it is conducted online, and it helps to reduce the cost of research before researchers needed to put much effort to collect new data or travel from place to another to carry out the study. Additionally, online questionnaires also quick to analyze with the simple coding system provided for each question and answer and there will be a greater chance of accessibility for each every participant who participate in the study, and the study only required shorter duration for participants to complete the questionnaires which only takes up to 30 minutes. Although past research examines that depressed patients often display increased Rapid Eye Movement sleep (REM) and often reported symptoms are insomnia, nightmares, and frequent nocturnal panic attacks which can predict high sleep disturbance (Cukrowicz et al., 2006), hence, lack of correlations between the family risk factor and depression been examined which predict the symptoms of sleep disturbance by individual’s low quality of sleep cycle. In contrast, the study has few limitations. Firstly, both depression and family risk variables are only

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utilized based on one questionnaire to determine emerging adults encounter the disorders, the Patient-Reported Outcomes Measurement Information System (PROMIS), and Risky Family Questionnaires (RFQ) where it is insufficient to determine whether individuals have predicting symptoms. According to PROMIS measurement for depression factor, the questionnaire only focusses on individual’s predicting depression indications such as “I felt helpless” and “I felt depressed” the past seven days and according to the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition, DSM-5 (American Psychiatric Association [APA], 2013) of depression, the individual must be experiencing five or more symptoms for durations of two weeks with one symptom must possess depressed mood or loss of interest or pleasure. Therefore, the indications of individuals having depression based on the PROMIS measures limited to justify whether individuals encounter depression symptoms positively predict their sleep disturbance. Consequently, future studies should have more than one measurement for each variable to obtain consistency of results by comparing the result with the results from different questionnaires to ensure individuals who participate in the study having depression, family risk factors, and sleep disturbance. For example, DSM-5 can be utilized in a future study to examine the accurate assumption criterion for each diagnosis of mental health disorders and this can helps to obtain a valid result based on the manual which provides the full descriptions of symptoms individuals must have to be diag...