This document discusses a study that examined the relationship between daily perceived stress and distress levels in dreams. The study found that daily perceived stress significantly positively correlated with the level of distress in dreams. Specifically, individuals experiencing higher levels of daily stress reported higher levels of distress in their dreams. The document provides background on stress, dreams, and prior research examining relationships between stressors, trauma, and dream content.
Estudio de investigacion Centro Walton de Neurología y Neurocirugía de Liverp...Ana Liébanas Serrano
Desarrollo y validación de medidas de auto-informe de la fatiga y las necesidades basadas en la calidad de vida en enfermedades neurológicas
http://www.polioconference.com/Power%20points.php
Relationship between Leisure Constraints, Leisure Motivation, and Leisure Sat...inventionjournals
This study aimed to investigate the relationships between leisure motivation, leisure constraints, and leisure satisfaction in junior college students participating in leisure activities. The research was conducted at junior colleges in southern Taiwan. A total of 500 questionnaires were distributed, of which 358 were returned. After eliminating ineffective responses, an effective sample of 21 questionnaires was collected, representing an effective recovery rate of 66%. Descriptive statistical analysis, confirmatory factor analysis, and structural equation modeling were conducted for returned questionnaires. The results indicated that among junior college students participating in leisure activities, (1) leisure motivation significantly and negatively affects leisure constraints and (2) leisure constraints significantly affect leisure satisfaction.
Parent-infant interactions in families with women diagnosed with postnatal depression: a longitudinal study on the effects of a psychodynamic treatment
Estudio de investigacion Centro Walton de Neurología y Neurocirugía de Liverp...Ana Liébanas Serrano
Desarrollo y validación de medidas de auto-informe de la fatiga y las necesidades basadas en la calidad de vida en enfermedades neurológicas
http://www.polioconference.com/Power%20points.php
Relationship between Leisure Constraints, Leisure Motivation, and Leisure Sat...inventionjournals
This study aimed to investigate the relationships between leisure motivation, leisure constraints, and leisure satisfaction in junior college students participating in leisure activities. The research was conducted at junior colleges in southern Taiwan. A total of 500 questionnaires were distributed, of which 358 were returned. After eliminating ineffective responses, an effective sample of 21 questionnaires was collected, representing an effective recovery rate of 66%. Descriptive statistical analysis, confirmatory factor analysis, and structural equation modeling were conducted for returned questionnaires. The results indicated that among junior college students participating in leisure activities, (1) leisure motivation significantly and negatively affects leisure constraints and (2) leisure constraints significantly affect leisure satisfaction.
Parent-infant interactions in families with women diagnosed with postnatal depression: a longitudinal study on the effects of a psychodynamic treatment
Presentación sobre Términos Básicos en EstadísticaLombardJr
Presentación sobre Términos Básicos en Estadística
1.La Estadística Se considera una herramienta que, hoy por hoy, permite dar luz y obtener resultados, y por tanto beneficios, en cualquier tipo de estudio.
2.Las variables Una variable estadística es cada una de las características o cualidades que poseen los individuos de una población. Las Variables se dividen en: Cualitativa Cualitativa Nominal Cualitativa Ordinal No pueden ser medidas con números. Presentan modalidades no numéricas, no admiten un orden. Presentan modalidades no numéricas, y admiten un orden.
3.Cuantitativa Discreta Continua Expresada por números, se prestan para operaciones aritméticas. Toma valores aislados, no admite valores intermedios entre uno específico. Se pueden tomar valores intermedios entre 2 específicos. CUALITATIVA NOMINAL: El estado civil, con las siguientes modalidades: soltero, casado, separado, divorciado y viudo. CUALITATIVA ORDINAL: Medallas de una prueba deportiva: oro, plata, bronce. CUANTITATIVA DISCRETA: El número de hermanos de 5 amigos: 2, 1, 0, 1, 3. CUANTITATIVA CONTINUA: La altura de los 5 amigos: 1.73, 1.82, 1.77, 1.69, 1.75. Ejemplos de las Variables
4. La Población Se precisa como un conjunto finito o infinito de personas u objetos que presentan características comunes. Finita Infinita Se forma de un número limitado de elementos. No se puede cuantificar por ser muy extensa.
5. 5. La Muestra Es una representación significativa de las características de una población, que bajo un % de error, no mayor al 5%, nos describe como es la población global. La muestra se dividen en dos tipos: El muestreo aleatorio es cuando se selecciona la muestra al azar, donde todos los elementos de la población pueden ser escogidos; y El muestreo no aleatorio se aplica en una previa experiencia con la población, para luego seleccionar una muestra aleatoria.
6. Ejemplo de Población: Por ejemplo estudiamos los valores sociales de una población de 5000 habitantes aprox., entendemos que sería de gran dificultad poder analizar los valores sociales de todos ellos, por ello, la estadística nos dota de una herramienta que es la muestra para extraer un conjunto de población que represente a la globalidad y sobre la muestra realizar el estudio. Una muestra representativa contiene las características relevantes de la población en las mismas proporciones que están incluidas en tal población. Ejemplo de Muestra: Continuando el ejemplo de los 5000 habitantes, una muestra aleatoria incluirían 100 habitantes seleccionados al azar.
7. Parámetros Estadísticos Un parámetro estadístico es aquel formado por una función establecida sobre los valores numéricos de una comunidad. Se trata, por lo tanto, de una cifra representativa que permite modelizar un plano real.
Hadi Alnasir
Research Proposal
Independent variable 1: Sex
Independent variable 2: anxiety
Dependent variable: Stress
Question #1
My first independent variable (sex) and my dependent variable (stress) are related. Men and
women tend to experience stress differently. Similarly, men and women react differently to
stress.
I expect women to score higher than men on the dependent variable. Women suffer more stress
compared to men. A 2010 study discovered that women are more likely to experience an
increase in stress levels as compared to men. Women are also more likely to report emotional
and physical symptoms of stress compared to men (APA, 2012). The stress gap between men
and women is because their stress response is different. Women have a different hormonal
system that usually causes them to react more emotionally and become more fatigued.
Similarly, women are exposed to more stress-related factors since they assume several roles in
their daily life.
Question #2
My second independent variable (anxiety) is related to my dependent variable (stress). Anxiety
and stress can both cause severe physical and mental health issues, such as depression, muscle
tension, substance abuse, personality disorders, and insomia (Powell & Enright, 2015). Both are
emotions and normal responses that can become disruptive and overwhelming to day-to-day
life. They can interfere with important aspects of life, such as work, relationships,
responsibilities, and school.
An increase in anxiety can increase stress levels. Research indicates that excessive anxiety can
lead to stress-related symptoms such as difficulty concentrating, insomnia, irritability, muscle
tension, and fatigue. Individuals can manage their anxiety and stress with relaxation techniques.
This includes breathing exercises, yoga, physical activity, art therapy, meditation, and massage.
References
APA. (2012). 2010 Stress in America: Gender and Stress. Retrieved from:
https://www.apa.org/news/press/releases/stress/2010/gender-stress
Powell, T., & Enright, S. (2015). Anxiety and stress management. Routledge.
Running Head: GENDER AND STRESS AS PREDICTORS OF DEPRESSION
Gender and Stress as Predictors of Depression
Zae’Cari Nelson
California Baptist University
Gender and Stress as Predictors of Depression 1
Gender and Stress as Predictors of Depression
More than 17 million adults in the United States experience the ill effects of depression,
making it perhaps the most well-known mental illness in the U.S.A. Depression influences an
expected one out of 15 adults. What's more, one out of six individuals will encounter depression
in their life (What is Depression?). There are a mind-boggling number of elements that can
prompt depressive symptoms in male and female individuals, one of which is held to be a rise in
stress hormone disturban ...
Bullying and PTSD SymptomsThormod Idsoe & Atle Dyregrov & .docxcurwenmichaela
Bullying and PTSD Symptoms
Thormod Idsoe & Atle Dyregrov & Ella Cosmovici Idsoe
Published online: 6 March 2012
# Springer Science+Business Media, LLC 2012
Abstract PTSD symptoms related to school bullying have
rarely been investigated, and never in national samples. We
used data from a national survey to investigate this among
students from grades 8 and 9 (n0963). The prevalence
estimates of exposure to bullying were within the range of
earlier research findings. Multinomial logistic regression
showed that boys were 2.27 times more likely to be exposed
to frequent bullying than girls. A latent variable second-
order model demonstrated an association between frequency
of bullying exposure and PTSD symptoms (beta00.49).
This relationship was not moderated by gender. However,
the average levels of PTSD symptoms as well as clinical
range symptoms were higher for girls. For all bullied stu-
dents, 27.6% of the boys and 40.5% of the girls had scores
within the clinical range. A mimic model showed that youth
who identify as being both a bully and a victim of bullying
were more troubled than those who were victims only. Our
findings support the idea that exposure to bullying is a
potential risk factor for PTSD symptoms among students.
Future research could investigate whether the same holds for
PTSD through diagnostic procedures, but this will depend
on whether or not bullying is decided to comply with the
DSM-IV classification of trauma required for diagnosis.
Results are discussed with regard to their implications for
school interventions.
Keywords Bullying . Victimization . PTSD symptoms .
School
Even though there has been discussion whether exposure to
bullying complies with the classification of trauma required
for diagnosis of Posttraumatic Stress Disorder (PTSD) as
defined within the DSM–IV–TR (APA 2000), practitioners
often report PTSD symptoms in victims of bullying (Scott
and Stradling 1992; Weaver 2000). Research focusing on
workplace bullying has established a relationship with
PTSD symptoms that appears to be quite strong
(Björkqvist et al. 1994; Leymann and Gustafsson 1996;
Matthiesen and Einarsen 2004; Mikkelsen and Einarsen
2002). Few studies have investigated this in relation to
school bullying (McKenney et al. 2005; Mynard et al.
2000), and none in national samples. The aim of our study
was to examine the relationship between being bullied and
PTSD symptoms in a representative sample of Norwegian
pupils.
Bullying
Bullying is regarded as a subtype of aggressive behavior
(Berkowitz 1993) in which an individual or a group repeat-
edly and over time direct negative actions against individu-
als who are not able to defend themselves, meaning there is
an imbalance of power between perpetrators and victims
(Bowes et al. 2009; Herba et al. 2008; Olweus 1994;
Salmivalli 2010). The prevalence among children and
young people varies depending on the defining criteria used
and the population studied. Estimates indicating peer mal-
treatm.
Influential Determinants of Capacity Building to Cope With Stress among Unive...iosrjce
This study is a survey to find out the influential determinants of capacity building to cope with stress
among university students. Descriptive survey research design was employed for the study while self-structured
modified questionnaire was used to elicit information from the respondents. A total of nine hundred and five
(905) respondents participated in the study forming the sample size for the study. The statistical tools used for
the study includes; percentage counts, frequency, mean, regression analysis, spearman rank andMann-Whitney
U test. The statistical results of the multiple regression analysis showed that the predictors (age, sex, religion,
college, family financial status and academic performance) had 92% (adjR
2=.092, F(7,896)=14.02, P=.000,
P<0.05) joint contribution in the dependent variable (perceived ability to cope with stress). The linear
regression analysis showed that only age (β=-.112, p=.001), sex (β=.124, p=.000), religion (β=.084, p=.009),
college (β=-.088, p=.007) and academic performance (β=.249, p=.000) had significant relative contribution to
the dependent variable.The Mann-Whitney U results showed that there is significant difference in the perceived
ability to cope with stress between both male and female (H=84552, Z=-3.78, p=.000). The result of the
findings revealed that age, sex, religion, college of study, academic performance could significantly predict
perceived ability to cope with stress.And also showed that the way male and female perceived their abilities to
cope with stress differ
Medicine and Health Literature Review Capstone Project SampleCapstone Project
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Quantitative Analysis Template !Instructions When analyzing.docxamrit47
Quantitative Analysis Template !
Instructions: When analyzing a journal article, first focus on the title of the article and/or the abstract.
Determine the independent variables (IVs) or the dependent variables (DVs) from these sections. If the
IVs and DVs are what you are looking for, then go ahead and read the whole article and fill out the following
information below. The purpose of filling out this template is to organize the most relevant information in a
journal article.
Reference (APA style) !!!
Background of the problem {e.g., According to Jonson et al. (2008), low self-esteem is correlated to lower
academic performance and behavioral problems in young adolescents.} !!!!!
Rationale (Key phrase: …few studies…) !!!!
Purpose (Key phrase: to determine or to examine…) !!!!
Past Studies{i.e., facts that are relevant to the IV and DV with citations (APA style)} !!!!!
Participants !
Age group(s) !
Gender !
Ethnic group(s)
SES !!
Quantitative Methods (survey, causal-comp, experimental, single-subject, mixed)
Assessments !
IV:
Measure !
Example question !
Likert-scale !
Reliability !
DV:
Measure !
Example question !
Likert-scale !
Reliability !!
(If there are more IVs and DVs that you feel are relevant, then you may note them here) !!
Treatment (Intervention) !!!
Hypothesis or research question(s) (Focus on the IVs and DVs from your definitions section) !!!!
What was significant (results) in the study? Focus on the IVs and DVs that you have picked. You don’t have
to state all the IVs and DVs from the article. What reasons do the authors give for the significant data (key
phrase in the discussion section: may be, might be)? !!!!!!!
Implications (What is the study recommending to educators? How can educators apply what they have
learned to their children/students/clients?)
RESEARCH ARTICLE
Mental Health and the Life Span
Depression and Retirement in Late
Middle-Aged U.S. Workers
Jalpa A. Doshi, Liyi Cen, and Daniel Polsky
Objective. To determine whether late middle-aged U.S. workers with depression are
at an increased risk for retirement.
Data Source. Six biennial waves (1992–2002) of the Health and Retirement Study, a
nationally representative panel survey of noninstitutionalized 51–61-year-olds and their
spouses started in 1992.
Study Design. Workers aged 53–58 years in 1994 were followed every 2 years there-
after, through 2002. Depression was coded as lagged time-dependent variables mea-
suring active depression and severity of depression. The main outcome variable was a
transition to retirement which was measured using two distinct definitions to capture
different stages in the retirement process: (1) Retirement was defined as a transition out
of the labor force in the sample of all labor force participants (N 5 2,853); (2) In addition
a transition out of full time work was used as the retirement definition in the subset of
labor force participants who were full time workers (N 5 2,288).
Princip ...
2Relationship Between Depression (from heartbreak)simisterchristen
2
Relationship Between Depression (from heartbreak) and Reaction Time
Jenna Lantrip
October 2nd, 2022
Relationship Between Depression (from heartbreak) and Reaction Time
There are many reasons that can cause depression and a cognitive developmental delay, but this review is going to be looking at depression that comes from a relational breakup (heartbreak) and how this effects their reaction time. When an individual undergoes emotional distress that was caused by heartbreak it can lead the individual to negative effects such as, having an increased risk of physical illness and stress-related diseases (Izzati & Takwin, 2018). Young-adults, according to Erikon’s theory are going thothe developmental stage of intimacy versus isolation (Izzati & Tawkin, 2018; Erikson 1968). This emphasizes that young adults are either developing intimate relationships with other individuals or they are being isolated from society. Naturally when an individual is actively pursuing an intimate relationship with another individual and this fails, heartbreak is expected. One should never underestimate the effects that a heartbreak can cause to an individual. Heartbreak can result into emotional distress and even in grief responses (Izzati & Takwin, 2018; Kaczmarek et al., 1990 in Lepore & Greenber, 2002). There can be different levels of heartbreak, an extreme level can cause emotional distress from a heartbreak that can link a person to horrid scenes, such as psychopathology or even death (Izzati & Takwin, 2018; Field, 2011).
The aim of this study was to explore the relationship between depression from heartbreak and the effects of cognitive development, more specifically, reaction time in individuals who range from 14-24 years of age. The participants were assessed by using the Beck Depression Inventory Scale (Streiner, 2002) and The Taylor Competitive Reaction Time Test (TCRTT). Results from this study could be beneficial to mental health professionals and individuals of these ages in understanding why they have a slower or faster reaction time than others.
Background of the Study
When an individual goes through a breakup from a relationship, this can cause many different negative experiences to happen. Whenever there is an increase of stress coming from an event, there is an increased risk for developing depression (Verhallen et al., 2019). Conducting research studies on stressful and emotional upsetting events can provide for great insight as to why there are individual differences when talking about stress-related coping and the link for stress and depression. Previous research has shown that the breakup from a romantic relationship can have such a strong emotional upsetting there can be multiple symptoms that are related to sadness, grief, and depression (Verhallen et al., 2019). There can even be a result of having an increased risk of developing a depressive episode (Verhallen et al., 2019). Women have reported for a h ...
2Relationship Between Depression (from heartbreak)pearlenehodge
2
Relationship Between Depression (from heartbreak) and Reaction Time
Jenna Lantrip
October 2nd, 2022
Relationship Between Depression (from heartbreak) and Reaction Time
There are many reasons that can cause depression and a cognitive developmental delay, but this review is going to be looking at depression that comes from a relational breakup (heartbreak) and how this effects their reaction time. When an individual undergoes emotional distress that was caused by heartbreak it can lead the individual to negative effects such as, having an increased risk of physical illness and stress-related diseases (Izzati & Takwin, 2018). Young-adults, according to Erikon’s theory are going thothe developmental stage of intimacy versus isolation (Izzati & Tawkin, 2018; Erikson 1968). This emphasizes that young adults are either developing intimate relationships with other individuals or they are being isolated from society. Naturally when an individual is actively pursuing an intimate relationship with another individual and this fails, heartbreak is expected. One should never underestimate the effects that a heartbreak can cause to an individual. Heartbreak can result into emotional distress and even in grief responses (Izzati & Takwin, 2018; Kaczmarek et al., 1990 in Lepore & Greenber, 2002). There can be different levels of heartbreak, an extreme level can cause emotional distress from a heartbreak that can link a person to horrid scenes, such as psychopathology or even death (Izzati & Takwin, 2018; Field, 2011).
The aim of this study was to explore the relationship between depression from heartbreak and the effects of cognitive development, more specifically, reaction time in individuals who range from 14-24 years of age. The participants were assessed by using the Beck Depression Inventory Scale (Streiner, 2002) and The Taylor Competitive Reaction Time Test (TCRTT). Results from this study could be beneficial to mental health professionals and individuals of these ages in understanding why they have a slower or faster reaction time than others.
Background of the Study
When an individual goes through a breakup from a relationship, this can cause many different negative experiences to happen. Whenever there is an increase of stress coming from an event, there is an increased risk for developing depression (Verhallen et al., 2019). Conducting research studies on stressful and emotional upsetting events can provide for great insight as to why there are individual differences when talking about stress-related coping and the link for stress and depression. Previous research has shown that the breakup from a romantic relationship can have such a strong emotional upsetting there can be multiple symptoms that are related to sadness, grief, and depression (Verhallen et al., 2019). There can even be a result of having an increased risk of developing a depressive episode (Verhallen et al., 2019). Women have reported for a higher dis ...
This study aimed to assess the nature of stress, and
coping styles among rural and urban adolescents. Methods: 200
students in 10+2 and graduation first year of both genders in the
age range of 16-19 years were assessed with the Adolescent Stress
Scale, and a self-report coping scale. Results: The Result of
present study reveals that in both environmental settings male
reported more stress than their counterparts girls, however, to
utilize coping strategies female adolescents are in higher in
number than male adolescents. Conclusions: It is important for
research to examine how adolescents suffering from typical
stressors such as school examination, family conflict and poor
peer relations. Social support is likely one of the most important
resources in their coping process.
This study aimed to assess the nature of stress, and
coping styles among rural and urban adolescents. Methods: 200
students in 10+2 and graduation first year of both genders in the
age range of 16-19 years were assessed with the Adolescent Stress
Scale, and a self-report coping scale. Results: The Result of
present study reveals that in both environmental settings male
reported more stress than their counterparts girls, however, to
utilize coping strategies female adolescents are in higher in
number than male adolescents. Conclusions: It is important for
research to examine how adolescents suffering from typical
stressors such as school examination, family conflict and poor
peer relations. Social support is likely one of the most important
resources in their coping process.
5Relationship Between Depression (from heartbreak).docxstandfordabbot
5
Relationship Between Depression (from heartbreak) and Reaction Time
Jenna Lantrip
September 18th, 2022
Relationship Between Depression (from heartbreak) and Reaction Time
There are many reasons that can cause depression and a cognitive developmental delay, but this review is going to be looking at depression that comes from a relational breakup (heartbreak) and how this effects their reaction time. When an individual undergoes emotional distress that was caused by heartbreak it can lead the individual to negative effects such as, having an increased risk of physical illness and stress-related diseases (Izzati&Takwin, 2018). Young-adults, according to Erikon’s theory are going thought the developmental stage of intimacy versus isolation (Izzati&Tawkin, 2018; Erikson 1968). This proves that young adults are either developing intimate relationships with other individuals or they are being isolated from society. Naturally when an individual is actively pursuing an intimate relationship with another individual and this fails, heartbreak is expected. One should never underestimate the effects that a heartbreak can cause to an individual. Heartbreak can result into emotional distress and even in grief responses (Izzati&Takwin, 2018; Kaczmarek et al., 1990 in Lepore &Greenber, 2002). There can be different levels of heartbreak, an extreme level can cause emotional distress from a heartbreak that can lead a person to horrid scenes, such as psychopathology or even death (Izzati&Takwin, 2018; Field, 2011). Comment by user: Headings are very important. You would have started by illutrating this is an introduction of your work. Comment by user: I did not understand this point. Did you mean through or thought?
The aim of this study was to explore the relationship between depression from heartbreak and the effects of cognitive development, more specifically, reaction time in individuals who range from 14-24 years of age. In addition, the participants gender was also investigated and taken into account when examining the relationship between depression from heartbreak and reaction time. The participants were assessed by using the Beck Depression Inventory Scale (Streiner, 2002), the Everyday Cognitive Instrument (Farias et al., 2008), and a sex assigned at birth questionnaire. Results from this study could be beneficial to mental health professionals and individuals of these ages in understanding why they have a slower or faster reaction time than others.
Background of the Study
When an individual does through a relationship breakup this can cause many different negative experiences to happen. Whenever there is an increase of stress coming from an event, there is an increased risk for developing depression (Verhallen et al., 2019). Conducting research studies on stressful and emotional upsetting events can provide for great insight asa to why there are individual differences when talking about stress-related coping and the .
5Relationship Between Depression (from heartbreak).docx
Final Paper
1. RUNNINGHEAD: Daily Stresses and Dreams 1
The Relationship Between Daily Stresses and Dreams
Alex Turner
Baldwin Wallace University
2. Daily Stresses and Dreams 2
Abstract
Prior research on stress has focused mainly on causes of stress as well as some potential effects
and relationships with other factors. One main correlation that has not been studied heavily is
dream distress and dream content. Previous research has studied the relationship between
traumatic situations and dreams, but not the stress of daily life. The objective of this study was
to gain knowledge in the relationship between daily perceived stress and distress levels in
dreams. The sample consisted of 292 participants between the ages of 18 and 80. Subjects
completed a survey containing a demographic questionnaire, a Perceived Stress Scale, and a
Dream Motif Scale. The results indicated that daily perceived stress significantly positively
correlated with the level of distress in dreams (r = .222, p < .001). This main hypothesis was
followed by multiple other significant demographic findings including sex and age.
3. Daily Stresses and Dreams 3
The Relationship Between Daily Stress and Dreams
Adults experience a variety of situations in their lives that can be good or bad. These
experiences may vary from social situations to test grades, which result in stress. Stress is
important to consider in each experience, as it can affect people in both psychological and
physical ways (e.g., Yang et al., 2014). In the Diagnostic and Statistical Manual, Fifth Addition,
stress disorders range from short term adjustment disorders as a reaction to a stressor, to long
term post-traumatic stress disorders (American Psychiatric Association, 2013). There are both
beneficial and detrimental forms of stress (e.g., Fernandez-Gonzalez, Gonzalez-Hernandez &
Trianes-Torres, 2015; Wang, Wang, Gaskin & Wang, 2015). This includes circumstances from
receiving ‘good’ grades to getting fired from a job. In daily life, stress can cause small
biological changes like increased heart rate, and even changes sleep patterns (Yang et al., 2014).
Past research (Kron, Hareven & Goldzweig, 2015) has even shown that extreme stress and high
levels of trauma can impact the content of dreams. For example, the most common dream theme
consists of the dreamer meeting the person they wish to see (Yu, 2015). These typical dream
themes can be greatly altered by the impact of major stress or trauma on an individual (Erlacher,
Ehrlenspiel & Schridel, 2011). However, more research is needed in the area of possibly
smaller, everyday stressors and their impact on dreams. It is hypothesized that there will be a
significantly higher level of distress in dreams of individuals experiencing life stress.
Although personal perceptions of stress may vary, there are a few things that are
important to consider. Environmental demands or events that happen in one’s life are crucial to
examine when considering stress and physiological outcomes (Munoz, Sliwinski, Scott & Hofer,
2015). Depending on the age or chosen activities of an individual, the environmental factors can
be different, causing different stressors. Culture and different traditions can also greatly affect
4. Daily Stresses and Dreams 4
the causes of stress in one’s daily life (Persike & Seiffge-Krenke, 2012). Younger individuals
are more vulnerable to stressors and traumatic events that occur in life in comparison to adults
(Kron et al., 2015). Individuals experiencing these stressors from the environment have an
increase in cortisol release as well as higher heart rates (Yang et al., 2014). This shows that there
is a physiological, not just psychological, bodily reaction to stress.
College students have been tested for major stressors in life (Beiter, Nash, McCrady,
Rhoades, Linscomb, Clarahan & Sammut, 2015). Adapting to changes in location or
environment can be a stressful situation for some people. For example, in college students, the
transition can be difficult enough that stress can arise from it (Kaya, Tansey, Melecoglu &
Cakiroglu, 2015). Amounts of stress also vary between different groups of college students. For
transfer students, stress levels were significantly higher than those who did not transfer (Beiter et
al., 2015).
There are also grade level differences to take into consideration. Upperclassmen may be
considering preparing for the workforce and are concerned with meeting requirements for their
majors. Underclassmen are concerned with transitioning into college life. Beiter et al. (2015)
tested upperclassmen stress levels versus underclassmen stress levels. In their study,
upperclassmen scored higher on the given stress test when compared to underclassmen.
Specifically, seniors scored higher than sophomores, while juniors scored higher than freshmen
(Beiter et al., 2015). Age can also correlate to the severity of how a person is affected by
stressors or trauma. Younger individuals often become more negatively affected from traumatic
experiences (Kron et al., 2015). Young adults, however, have the greatest ability to cope with
trauma or stressors (Kron et al., 2015). Reactivity by any individual to minor stressors is
correlated with depressed mood (Felsten, 2002).
5. Daily Stresses and Dreams 5
According to Nonterah et al. (2015), many students have a fear of negative evaluation,
which can include exams, presentations, and other academic stressors. In this study, Nonterah et
al. (2015) explored how the fear of negative evaluation in academic situations affected students.
Fear of negative evaluation played both beneficial and harmful roles for students in the study
(Nonterah et al., 2015). One harmful role this fear plays in students’ lives included creating a
large amount of stress. The beneficial role, in contrast, was that students studied harder due to
the fear of negative evaluation, sometimes resulting in higher grades (Nonterah et al., 2015).
Fear of negative evaluation is just one of many stressors in the college life.
The number one stressor for students, without question, is academic stress (Persike &
Seiffge-Krenke, 2012). Reaffirming the results of Persike and Seiffge-Krene (2012) concerning
the number one stressor for students, Beiter et al. (2015) found the top ten causes of stress in
college students. These sources of concern, in order of severity, include academic performance,
the pressure to succeed, post-graduate plans, financial concern, quality of sleep, relationships
with friends, relationships with family, overall health, body image, and self-esteem (Beiter et al.,
2015). Many of the stressors listed as the top ten stressors for college students are similar,
especially the top four, which all relate significantly to college life (Beiter et al., 2015). These
results suggest that major stressors correspond to a person’s priorities in their current phase of
life. Academic performance is the highest ranked cause of stress in college students according to
Beiter et al. (2015). The stress of academic performance can come from various sources,
including procrastination and poor time management skills (Moore, Burgard, Larson & Ferm,
2014). Procrastination and poor time management skills have been found to be linked with stress
(Moore et al., 2014), and can also impact academic performance.
6. Daily Stresses and Dreams 6
Academic stressors have a large impact on students, but they are not the sole stressors in
an adult life. Emotional stress is another type of stressor that heavily impacts individual lives.
Optimism and pessimism are two traits that have an effect on emotional stress (Fernandez-
Gonzalez et al., 2015). Higher pessimism, and therefore lower optimism, is often correlated with
higher stress (Fernandez-Gonzalez et al., 2015). With emotional stress being significant more so
in some lives than others, Holinka (2015) tested emotional intelligence with the hopes of finding
a correlation between the two. Emotional intelligence has multiple sub-divisions within it
(Holinka, 2015). Each sub-division was tested, as well as overall emotional intelligence. Results
showed that there is only one sub-division significantly correlated to emotional stress: the
interpersonal one (Holinka, 2015). This sub-division deals with establishing relationships that
are cooperative, beneficial, and satisfying (Holinka, 2015). The correlation was found to be
significantly negative; as interpersonal skills increased, life satisfaction decreased (Holinka,
2015).
Personality traits have also been tested in correlations to stress. Neuroticism is one trait
that has been tested (Felsten, 2002). Those with higher scores of neuroticism had a higher
reactivity to stress, with reactivity being synonymous with how much a person responds to a
stressor (Felsten, 2002). This means that there is a positive correlation; the more neurotic one is,
the more stress. Neuroticism also significantly predicted drug use (Coleman & Trunzo, 2015).
This suggests that psychostimulant use increases significantly during higher stress times at
college as a reaction to stressors (Moore et al., 2014).
Negative personality traits such as neuroticism and pessimism have both been found to
correlate with stress (Felsten, 2002). Studies, such as that of Kaya et al. (2015), show that
students experiencing higher levels of stress may have other significant sources of stress as well.
7. Daily Stresses and Dreams 7
These sources can include high personal threat in one’s environment, as well as not having a
solid emotional support system (Kaya et al., 2015). This is shown in the example of workplace
violence, where workplace violence correlates to occupational stress (Yao, Wang, Wang & Yao,
2014). In an attempt to avoid stressors, many choose to try to suppress the stressful thoughts by
eliminating them from their minds. Although intentions can be to push away the stressful
situations or feelings, data shows that thought suppression leads to significantly more psychiatric
symptoms (Kroner-Borowik et al., 2013).
Beiter et al. (2015) included a general sample of adults, eleven percent of people
reported severe or extremely severe levels of stress, fifteen percent reporting moderate stress,
and twelve percent having mild stress. With approximately thirty-eight percent of people
surveyed reporting higher than normal stress levels, coping strategies must be developed in order
to handle the levels of stress. Some coping strategies are beneficial to users, while others can be
destructive, harming the individuals and their health. Students who indicate having more stress
may simply have less beneficial coping strategies (Kaya et al., 2015). Optimism, which is
known to negatively correlate with stress, is one characteristic that can moderate emotional
manifestations of stress (Fernandez-Gonzalez et al., 2015). According to Fernandez-Gonzalez et
al. (2015), the higher the level of optimism, the fewer emotional and behavioral manifestations
of stress. This is a positive coping mechanism, as it is not potentially harmful to the individual
who is optimistic.
Coping mechanisms have the potential to work in different ways. Optimism generally
works in most situations, such as dealing with academic stressors or work related stressors, but
other strategies may not work as well so broadly (Fernandez-Gonzalez et al., 2015).
Psychological resilience has been reported to help with overcoming psychological distress (Rees,
8. Daily Stresses and Dreams 8
Breen, Cusack & Hegney, 2015). However, ego resilience specifically buffers academic stress
(Cole et al., 2015). Both ego resilience and another protective factor called mindfulness
mediates the association between academic stress and poor mental health symptoms (Cole et al.,
2015). Much like ego resilience, mindfulness buffers for academic stress, but does not buffer
anxiety as an off-shoot of stress (Cole et al, 2015).
As videogames, internet, and other technologies become more popular, new destructive
coping mechanisms are being formed. Smartphone use has become especially problematic in
recent years, and has been shown to be a possible coping strategy for life’s problems (Wang et
al., 2015). Gaming has also become a potentially overused and harmful cognitive diversion from
real life issues in recent years (Wang et al., 2015). Social support systems have been shown to
be a far more effective coping strategy (Fernandez-Gonzalez et al., 2015). Older students and
adults have significantly less satisfaction with these instrumental support systems for coping
(Fernandez-Gonzalez et al., 2015). Fernandez-Gonzalez et al. (2015) hypothesized that older
students and adults prefer to solve their own stressors due to a higher level of autonomy and self-
confidence. Regardless of the coping mechanisms, stress and life satisfaction and are negatively
correlated (Holinka, 2015).
Younger adults, such as college students, with especially low life satisfaction and high
stress levels may choose to make unexpected, and poor life decisions in an attempt to change
their unsatisfactory life (Kaya et al., 2015). For example, Kaya et al. (2015) found that college
students which have high levels of stress are more likely to make the decision to leave school
due to the stress. In studies by De Koninck (1975) and Nonterah et al. (2015), academic stress as
well as stress in general has been found to have significant positive correlations with both
9. Daily Stresses and Dreams 9
depression and anxiety. Emotional state, especially after trauma, influences mental imagery
related to stress (Hartmann, Kunzendorf, Rosen & Grace, 2001).
One biological factor that plays a role in the effects of stress is sex. In many
circumstances, men and women find different aspects of life to be more stressful (Beiter et al.,
2015). Gender differences on PSS-10 (for perceived stress) scores are not significant, meaning
that both sexes have relatively similar stress levels (Kaya et al., 2015). Females are known to
show more physiological as well as emotional manifestations of stress compared to men
(Fernandez-Gonzalez et al., 2015). For example, the study done by Beiter et al. (2015) shows
that a greater portion of females compared to males reported some qualities of life to be more
stressful than males do. These qualities include sleep, academic stressors, self-esteem, and body
image. In contrast to all of the qualities that females find more stressful about life, they also
have a significantly higher reported satisfaction with life (Kaya et al., 2015). These results
demonstrate that sex is a precursor to life stress.
Regardless of sex, when shown a stressful film, De Koninck (1975) found that
participants had a significant increase in sleep latency, the length of time it takes to fall asleep.
The ability to sleep can be affected by stress (De Koninck, 1975). Once individuals are able to
fall asleep and wake up in the morning, according to Yu (2015), approximately 11.9% of people
report remembering their dreams from the night before the study was done. This is where stress
and dreams connect. A study done by Domhoff (2015) argued that dreams are what is called
embodied simulations. Embodied simulations are one’s mind creating an image or story relating
to present times, emotions, or feelings.
The feelings and emotions embodied in dreams represent and become what are known as
common dream themes (Yu, 2015). Common dream themes have been compiled into a list in the
10. Daily Stresses and Dreams 10
Dream Motif Scale (DMS; Yu, 2015). Although typical dream themes sometimes vary between
cultures (Yu, 2015), evidence supports cross-cultural stability of many dream characteristics
(Mazandarani, Aguilar-Vafaie & Domhoff, 2013). Dreams that are more intense are had by
‘thin’ boundaried subjects, creating more contextual images (Hartmann et al., 2001). Dreams
that have more contextual images are more vivid and ‘dreamlike’ (Hartmann et al., 2001). The
boundary of the mind is so thin that it can let in those images, whereas individuals with ‘thick’
boundaries are not able to do so (Hartmann et al., 2001).
According to Hartmann et al. (2001), dreams when asleep also contain more
contextualizing images than do day dreams when awake. Emotions reported when dreaming are
often very similar to emotions had when in an awake state during actual events of a day (Nielsen,
Deslauriers & Baylor, 1991). This means that the emotions while awake may impact emotions
had in dreams (Nielsen et al., 1991). Emotions are as important in dreams as they are in real life
when experiencing them (Nielsen et al., 1991). Bad dreams have more emotional references,
while nightmares have more contextual images (Fireman, Levin & Pope, 2014). In regards to
negative dream types, bad dreams happen four times more often than nightmares (Fireman et al.,
2014).
Arousal affects dreams, no matter if the dream is pleasant or a nightmare (Hartmann &
Basile, 2003). Being threatened when in an awake state increase the incidence of threats in
dreams (Valli, Revonsuo, Palkas & Punamaki, 2006). After watching a stressful video, those
with anxiety from the video incorporated the film into their dreams (De Koninck, 1975).
Traumatic events such as the terrorist attack on 9/11/01 has affected a great number of people
involved in the event, as well as throughout the nation of the Unites States. In the United States,
after 9/11/01, dreams began to trend towards increased inclusion of fear and/or terror, as well as
11. Daily Stresses and Dreams 11
increased intensity of dream imagery (Hartmann & Basile, 2003). Dreams that relate to some
sort of trauma, such as the 9/11 attack, were found to be longer than the control group’s dreams
(Valli et al., 2006). Not only are the dreams themselves different in length with stress or trauma
involved, but trauma also improves dream recall after the fact (Valli et al., 2006). This means
that once a person is exposed to a stressor or traumatic event, the dreams which that individual
has after the fact will be remembered more easily in comparison to individuals who did not
undergo stressors or trauma.
People who have undergone traumatic experiences have prevalent dream themes, which
include situational stress, fear, anxiety, and helplessness (Kron et al., 2015). For women, the
most prevalent were togetherness and active ego, possibly as strategies to cope with the trauma
(Kron et al., 2015). There is a theory called Disruptive Avoidance Adaptation (DAA) in regards
to dreams after a stressful event (Stewart & Koulack, 1993). The DAA theory involves
oscillation between mastery dreams and pleasant avoidant dreams. Mastery dreams are typically
more upsetting for the person involved, and are composed of situations in which the individual
attempts to learn or ‘master’ specific areas of life, or stressors (Stewart & Koulack, 1993). This
implies that avoidance dreams provide the dreamer with brief times of relief between the
disruptive and negative mastery dreams in which the mind attempts to master the stress (Stewart
& Koulack, 1993).
Even though trauma greatly affects individuals in a number of ways, they do not have to
have a traumatic event in order to affect dreams. For example, a study done by Erlacher et al.
(2011) of German athletes shows that stressful situations can also cause dream changes. In this
study, athletes reported a significant likelihood of having a bad dream or nightmare the night
before a big game in whatever sport they were participating in. The exact statistic is that fifteen
12. Daily Stresses and Dreams 12
percent of all German athletes included in the survey have had a nightmare the night before a big
game in the past year (Erlacher et al., 2011). Females were more likely to succumb to this than
men (Erlacher et al., 2011). These nightmares often presented distressing content for the
individual dreaming that was predominantly related to the upcoming game (Erlacher et al.,
2011). According to Erlacher et al. (2011), common themes of these nightmares included
athletic failure or losing the game.
In the presence of stress, recurrent dreams are more present in an actively recurrent group
(Duke & Davidson, 2002). The group that was actively having recurrent dreams recalled more
recurrent dreams than the group who was not currently active in the presence of stress (Duke &
Davidson, 2002). When participants were found to suppress thoughts on stressors, they had a
significant amount of more target-related dreams than those who did not suppress their stressful
thoughts (Kroner-Borowik et al., 2013). In those dreams, there was also a higher level of dream
distress due to the negative thoughts in the dream. In a case study done by Domhoff (2015), a
recently widowed man continued to dream of his deceased wife. The dreams that followed her
death consisted of all of the emotions and feelings he had towards her, as well as sexual
frustrations from their relationship. As the dreams continued, there were diminishing
occurrences of his wife coming back to life or of her illness and death (Domhoff, 2015). From
survey studies to case studies, previous research on the variables of stress and dreams have
shown significant correlations. In this study, the researcher predicts that there will be a
significantly higher level of distress in dreams of adult individuals experiencing stress.
13. Daily Stresses and Dreams 13
Methods
Participants
Participants were obtained in two ways. The final survey of all tests were displayed in
Qualtrics for the students of Baldwin Wallace University’s Spring 2016 semester taking the
Intorduction to Psychology – 100 course to potentially choose for extra credit. The survey link
was also posted in a Facebook event open to the public. Potential subjects were invited and
encouraged to also invite their friends in a snowball effect. Using both methods, the total number
of participants was 292. There were a total of 91 male participants and 200 female participants
recorded, while the remaining one participant chose to omit this information.
Materials
In the survey, three measures were used to account for the main hypothesis as well as all
ex post facto variables. Perceived stress was measured using the Perceived Stress Scale (PSS;
Cohen, Kamarck & Mermelstein, 1983). Distress during dreams was measured using the Dream
Motif Scale (DMS; Yu, 2011). Age, sex, year in school, race, and family income were all
measured using the Demographic Survey in Appendix A.
Procedures
All subjects completed the survey provided to them online using a device that can access
the internet. The first page shown on the survey was the informed consent agreement. By
clicking the ‘next’ button, the research participant agreed to the terms of the study. After the
14. Daily Stresses and Dreams 14
informed consent, this survey first consisted of the demographic survey provided in Appendix A.
Following that was the Percieved Stress Scale (PSS; Cohen, Kamarck & Mermelstein, 1983).
The final part of the survey was the Dream Motif Scale (DMS; Yu, 2011).
15. Daily Stresses and Dreams 15
Results
In this study, the main hypothesis tested perceived stress scores with distress levels in
dreams using a Correlation Regression. The Pearson Correlation revealed that there is a
significant relationship between perceived stress and distress in dreams, r = + .222, p < .001. See
Figure 1 for a scatter plot of this relationship. The Linear Regression demonstrated that one can
significantly predict a person’s distress level in dreams from his/her level of perceived stress
(F1,290 = 15.036, p < .001). The Regression equation is:
Distress in Dreams = Perceived Stress (.279) + 89.574
(r2 = .046, t = 30.705, p < .001)
Figure 1: Scatterplot of Distress in Dreams and Perceived Stress.
The age of participants in this study ranged from eighteen to eighty. A Pearson
Correlation evinced that there is a significant relationship between perceived stress and age, r = -
.320, p < .001. See Figure 2 for a scatter plot of this relationship. A Linear Regression
16. Daily Stresses and Dreams 16
demonstrated that one can significantly predict a person’s perceived stress from his/her age
(F1,275 = 31.455, p < .001). The Regression equation is:
Perceived Stress = Age (-.182) + 45.131
(r2 = .099, t = 44.221, p < .001)
Figure 2: Scatterplot of Perceived Stress and Age.
According to a One-Way F-Test, there was a significant difference among the perceived
stress scores of the given five school groups: Freshmen, Sophomores, Juniors, Seniors, and Not
Currently in School (F1,4 = 4.646, p = .001). In a post-hoc Tukey analysis, the only two groups
with significant differences were Freshmen who were significantly more stressed than those not
currently in school at p = .001. See Figure 3 for a graph of this finding.
17. Daily Stresses and Dreams 17
Figure 3: Bar Graph of Perceived Stress and Year in School.
Differences in sex were also examined in this study. First, an Independent Samples T-
Test indicated that women have a higher level of perceived stress than men, t289 = - 2.686, p =
.004. See Figure 4 for a graph of this finding.
Figure 4: Bar Graph of Sex and Perceived Stress.
18. Daily Stresses and Dreams 18
However, an Independent Samples T-Test indicated that men and women do not have
significantly different levels of distress in dreams (see Table 1 for Group Statistics), t289 = -
1.283, p = .1005.
Table 1: Group Statistics of Sex and Distress in Dreams.
Two other demographics were tested in this study; race and income level. A One-Way F-
Test revealed that there was not a significant difference in distress in dreams among the five
given races: White, Multiracial, Black/African American, Asian, Hispanic, and Other (F1,5 =
1.400, p = .224). Another One-Way F-Test discovered that there was not a significant difference
in perceived stress among the four listed income levels: less than $50,000, $50,001-$75,000,
$75,001-$100,000, and greater than $100,000 (F1,3 = .802, p = .493).
19. Daily Stresses and Dreams 19
Discussion
This study strengthened prior research dealing with stress. According to Kron et al.
(2015), extreme stress and traumatic events can impact the content of dreams. In this study,
perceived daily stress was considered instead, and was predicted to positively correlate with level
of distress in dreams as the main hypothesis. As hypothesized, higher daily perceived stress
significantly positively correlated with distress in dreams. The main null hypothesis was rejected
as the correlation had a significance above what was needed for the set alpha level of five
percent. This study had other significant findings dealing with demographics listed in the survey
as well. One demographic that was tested with perceived stress was age.
Age was found to significantly negatively correlate with daily perceived stress. This
means that eighteen year old freshmen in college were significantly more stressed than the
participant of eighty years old. The variable age relates to the variable of year in school, as
younger individuals were typically in lower years in school, such as freshmen and sophomores.
A post-hoc comparison of year in school with daily perceived stress also determined that the
only significant finding when considering the college level groups was between freshmen in
college and those not currently in school. The findings of both age and year in school relating to
stress have the same result in this study, increasing its relevance.
However, the findings pertaining to year in school contradict previous research stating
that juniors were more stressed than freshman, and seniors more stressed than sophomores
(Beiter et al., 2015). This could be due to issues with the number of participants (i.e., power) in
the study. This study had fewer upperclassmen college students than underclassmen, specifically
freshmen. Also, although this study had a wide age range, there were many more participants
20. Daily Stresses and Dreams 20
that were in the age range of eighteen to twenty-five than many other groups (i.e., 25-35, or 40-
50). The lack of power in other age ranges and years in school may have an effect on the
outcome of their correlations. In the future, closer to equal amounts of subjects in each age
range should be considered.
Another demographic in question was sex. According to previous research, females have
a greater physiological and emotional manifestations of stress (Fernandez-Gonzalez et al., 2015).
This study has strengthened that known finding. According to the data from the current study,
females have significantly higher perceived stress compared to men. Past research also found
that females were more likely to succumb to bad dreams compared to men (Erlacher et al.,
2011). In contradiction, this study found that there was no significant difference in level of
distress in dreams between the two sexes. With that being said, future studies should focus on
which result is indeed significant when considering sex and dreams.
The remaining two demographics studied were race and income level. Despite personal
preconceptions, income level did not lead to significantly different perceived stress levels. Also,
differences in race did not lead to significantly different levels of distress in dreams. As with
age, both findings could pertain to lack of power in these demographics, or simply in the number
of subjects. Concerning income level, each category had a similar number of participants. With
race, a strong majority of subjects were Caucasian, while many other groups were
underrepresented in the sample. In future research, correlations between race and distress in
dreams, as well as between income level and perceived stress, should be investigated further.
21. Daily Stresses and Dreams 21
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25. Daily Stresses and Dreams 25
Appendix A
Demographic Survey
1. What is your age? ________
2. What sex do you identify with?
a. Male
b. Female
3. Year in school?
a. Freshman
b. Sophomore
c. Junior
d. Senior
e. Not currently in school
4. What is your race? ________
5. In what range is your best estimate of your household/family income?
a. Less than $50,000
b. $50,001-$75,000
c. $75,001-$100,000
d. Greater than $100,000