STUDY 1
Sagone, Elisabetta & Indiana, Maria Luisa. (2017). The Relationship of Positive Affect with
Resilience and Self-Efficacy in Life Skills in Italian Adolescents. Psychology. 08. 2226-2239.
SAMPLE DETAILS

Total Sample Size: The sample consisted of 147 Italian healthy adolescents.

Gender Distribution
1. Boys: There were 60 boys in the sample.
2. Girls: There were 87 girls in the sample.

Age Range: The participants' age ranged from 15 to 19 years.

Mean Age: The average age of the participants was 17.3 years.

Class Distribution:
3. Third Class: There were 46 participants from the third class.
4. Fourth Class: There were 59 participants from the fourth class.
5. Fifth Class: There were 42 participants from the fifth class.

Location: The participants were recruited from High State Schools located in Catania, Eastern
Sicily, Italy.

Parental Consent: For the underage adolescents' participation in the study, parental consent
was requested and obtained. This is in accordance with the requirements of privacy and
anonymity laid down by Italian Law (Law Decree DL. 196/2003).
TEST USED:

Positive and Negative Affect Schedule (PANAS):
1. Purpose: The PANAS assessed the affective components of subjective well-being by
measuring the extent to which participants generally experienced positive and negative
affective states.
2. Description: Participants were asked to rate on a 5-point Likert scale (ranging from 1 =
very slightly to 5 = extremely) how much they experienced 20 adjectives describing
affective states, including 10 for positive affect (e.g., "strong," "proud," "interested")
and 10 for negative affect (e.g., "afraid," "ashamed," "nervous").
3. Internal Consistency: The Italian version of PANAS demonstrated satisfactory internal
consistency, with Cronbach's alpha coefficient being α = 0.74 for the positive affect scale
and α = 0.79 for the negative affect scale.

Resiliency Attitudes and Skills Profile (RASP):
4. Purpose: The RASP measured various dimensions of resilient profiles, including
adaptability, sense of humor, engagement, control, and competence.
5. Description: Participants responded to a 30-item self-report scale using a 6-point Likert
scale (ranging from 1 = strongly disagree to 6 = strongly agree). The items were grouped
into the five dimensions mentioned above.
6. Internal Consistency: The Italian version of RASP demonstrated satisfactory internal
consistency, with the total scale having a Cronbach's alpha coefficient of α = 0.83.

Perceived Self-Efficacy Scales in Life Skills (PSES):
7. Purpose: The PSES assessed participants' perceived self-efficacy in various life skills,
including regulating and managing positive and negative emotions, communication in
interpersonal and social relations, and problem-solving abilities.
8. Description: The PSES was divided into four subscales:
a. PSES_PE (Perceived Self-Efficacy in Positive Emotions): Consisting of 7 items.
b.
PSES_NE (Perceived Self-Efficacy in Negative Emotions): Consisting of 8 items.
c.
PSES_IC/SC (Perceived Self-Efficacy in Interpersonal and Social Communication):
Consisting of 19 items.
d.
PSES_PS (Perceived Self-Efficacy in Problem-Solving): Consisting of 14 items.
3. Response Scale: Participants rated their perceived efficacy on a scale from 1 (not
at all efficient) to 7 (completely efficient).
4. Internal Consistency: Each subscale of the PSES demonstrated satisfactory
internal consistency, with Cronbach's alpha coefficients being α = 0.82 for PSES_PE, α = 0.86 for
PSES_NE, α = 0.85 for PSES_IC/SC, and α = 0.84 for PSES_PS.
RESULTS:

Resilience: The adolescents showed high levels of competence and engagement,
moderate levels of control, and low levels of adaptability and sense of humor.

Correlations: The different aspects of resilience were positively related to each other.
For example, having a good sense of humor was linked to higher competence,
adaptability, and engagement. Competence was related to adaptability, control, and
engagement. Adaptability was connected to control and engagement. Lastly, control
was associated with engagement.

Gender Differences: Boys had higher levels of humor compared to girls. However, there
were no significant differences between boys and girls in other resilience aspects.

Class Differences: There were differences in competence and adaptability among
different classes. Specifically, the fourth class scored higher in competence and
adaptability compared to the fifth class.

Positive Affect: The adolescents generally felt more positive emotions than negative
emotions.

Gender Differences in Positive Affect: Boys reported higher levels of positive emotions
compared to girls.

Perceived Self-Efficacy: The adolescents felt confident in their abilities to handle
interpersonal communication and problem-solving, but they felt less confident in
managing negative emotions and regulating positive emotions.

Correlations in Perceived Self-Efficacy: The different aspects of perceived self-efficacy
were positively related to each other.

Gender Differences in Perceived Self-Efficacy: Boys felt more confident in managing
negative emotions, while girls felt more confident in regulating positive emotions.

Positive Affect and Resilience: Feeling positive emotions was linked to higher levels of
adaptability, control, engagement, and sense of humor.

Positive Affect and Perceived Self-Efficacy: Feeling positive emotions was associated
with higher self-efficacy in problem-solving, interpersonal communication, managing
negative emotions, and regulating positive emotions.
DISSCUSSION SIMPLIFIED:

Positive Affect and Perceived Self-Efficacy: The study found that adolescents who
experience positive emotions, such as enthusiasm and engagement, also have higher
levels of confidence in their abilities to handle life skills. This means that feeling positive
and energetic helps them believe they can solve problems, manage emotions, and
communicate effectively.

Positive Affect and Resilience: Adolescents with high positive affect showed higher
levels of resilience in terms of adaptability and engagement. This means that feeling
positive and active helps them cope with challenges and adapt to their surroundings.

Gender Differences: Boys tended to use humor more effectively to bounce back from
challenges compared to girls. Girls expressed higher levels of negative emotions, while
boys felt more confident in managing negative emotions.

Importance of the Study: The study is valuable because there are limited investigations
focused on the relationship between affect states, resilience, and perceived self-efficacy
in life skills in Italian healthy adolescents. Understanding these relationships can help in
promoting well-being and resilience during adolescence.

Educational Programs: The study suggests that educational programs focused on
developing life skills can be beneficial for adolescents. Such programs have been shown
to reduce risky behaviors and promote social interactions, autonomy, and personal
growth, which are crucial for psychological well-being and resilience during adolescence.
STUDY 2
Blanca, M. J., Ferragut, M., Ortiz-Tallo, M., & Bendayan, R. (2017). Life Satisfaction and
Character Strengths in Spanish Early Adolescents. Journal of Happiness Studies, 19(5),
1247–1260.
SAMPLE DETAILS

Total Sample Size: The sample comprised 457 students.

Gender Distribution:

Males: There were 238 male students in the sample.

Females: There were 219 female students in the sample.

Age Range: The students ranged in age between 11 and 14 years.

Mean Age: The average age of the students was 12.28 years.

Standard Deviation: The standard deviation of the students' ages was .068.

Recruitment Source: The students were recruited from 27 classrooms in eight schools located in
the province of Malaga, Spain.

Exclusion Criteria: The following criteria were used to exclude students from the sample:
1. Age older than 14 years.
2. Inadequate completion of the administered tests.
3. Specific psychological diagnosis by schools that would make it difficult for them to respond to
the questionnaires.
4. Difficulty speaking Spanish.

Nationality: Ninety percent of the sample were of Spanish nationality, while the remaining
students were mainly from Latin American countries.
TEST USED

Students' Life Satisfaction Scale (SLSS):
1. Purpose: Assesses life satisfaction in students.
2. Items: Consists of 7 questions (e.g., "My life is going well," "I have what I want in life").
3. Response Format: 4-point rating scale (1 = never; 4 = always).
4. Scoring: Total score is obtained, with higher scores indicating higher life satisfaction.
5. Reliability: The Cronbach’s alpha coefficient in the present sample was .76.

Values in Action Inventory of Strengths for Youth (VIA-Y):
1. Purpose: Assesses character strengths in youth.
2. Items: Consists of 198 items assessing 24 character strengths.
3. Response Format: 5-point rating scale (1 = not at all like me; 5 = very much like me).
4. Character Strengths: Appreciation of Beauty and Excellence, Authenticity (Honesty),
Bravery, Creativity, Curiosity, Fairness, Forgiveness, Gratitude, Hope, Humor, Kindness,
Leadership, Love of Learning, Love, Modesty (Humility), Open-mindedness (Judgment),
Persistence (Perseverance), Perspective, Prudence, Religiousness (Spirituality),
Self-regulation, Social Intelligence, Teamwork, and Zest.
5. Scoring: Higher scores indicate a stronger endorsement of each character strength.
6. Reliability: Adequate psychometric properties were reported for the Spanish version of
the VIA-Y in the present sample.
RESULTS

Correlations between Life Satisfaction (LS) and Character Strengths:
1. Eighteen strengths were positively and significantly correlated with LS.
2. The highest correlation coefficients were observed for love, hope, authenticity, and
persistence.

Regression Modelling for Boys:
3. Significant predictors of LS for boys were love and hope.
4. The model's R2 (explained variance) was 0.17, indicating that love and hope accounted
for 17% of the variance in LS for boys.

Regression Modelling for Girls:
5. Significant predictors of LS for girls were love, hope, and authenticity.
6. The model's R2 was 0.26, indicating that love, hope, and authenticity accounted for 26%
of the variance in LS for girls.

Interaction Analysis:
7. The only significant interaction observed was between gender and authenticity.
8. This interaction revealed that authenticity is a predictor of LS among girls.

Multiple Regression Analysis for Boys and Girls:
9. Love and hope were positively related to LS in both boys and girls.
10. Each point increase in the love score resulted in an increase of 0.30 in LS.
11. Each point increase in the hope score resulted in an increase of 0.14 in LS.
12. For girls, an increase of 0.16 in the authenticity score also led to an increase in LS.
DISSCUSION SIMPLIFIED:

The main aim of the study was to explore the relationship between character strengths
and life satisfaction in Spanish early adolescents and to see if there are any gender
differences in this association.

The study found that most of the character strengths were positively related to life
satisfaction in early adolescence. Specifically, love, hope, authenticity, and persistence
were the strengths with the highest correlation coefficients, indicating that adolescents
with higher scores on these strengths reported greater life satisfaction.

Girls showed higher correlations between character strengths and life satisfaction
compared to boys. Regression analysis was then conducted separately for boys and girls
to determine the best predictors of life satisfaction for each gender. The results showed
that love and hope were important predictors of life satisfaction for both boys and girls.
However, for girls, authenticity also played a significant role in predicting life
satisfaction.

Love and hope were identified as key strengths for promoting life satisfaction in
adolescents. Love, which reflects close relationships with others, was found to be
particularly important in fostering life satisfaction. Hope, which involves being optimistic
about the future and working towards goals, also had a positive impact on life
satisfaction.

The study also highlighted the importance of authenticity, which is the ability to be
sincere and take responsibility for one's feelings and actions, in predicting life
satisfaction among girls. This suggests that being true to oneself and having a strong
sense of identity are factors that contribute to greater life satisfaction for girls.
STUDY 3
Huebner, E. S., & Dew, T. (1996). "The interrelationships of positive affect, negative affect, and life
satisfaction in an adolescent sample." Social Indicators Research, 38(2), 129-137.
SAMPLE DETAILS

Total participants: 266 adolescents

Gender distribution: 92 males and 174 females

Racial distribution: 72 African-American, 181 Caucasian, and 13 categorized as "other"

Age range: Participants' ages ranged from 14 to 19 years old

Mean age: The average age of the participants was 16.22 years (SD = 1.28)

Social class rating: The mean social class rating was 3.58 (range = 1-7) based on the Revised
Occupational Rating Scale.
TEST USED:
1. Students' Life Satisfaction Scale (SLSS): A 7-item self-report scale designed to measure children
and adolescents' overall life satisfaction, independent of specific domains. Participants selected
one of six options ranging from "strongly disagree" to "strongly agree" to describe their life
satisfaction during the past several weeks.
2. Positive and Negative Affect Scale (PANAS): Comprised of two ten-item self-report scales
designed to measure positive and negative affect. Participants rated their mood on 20 adjectives
using a five-point scale, indicating the frequency of their mood during the past several weeks.
Both tests have been extensively validated, and their internal consistency estimates are high, indicating
their reliability in assessing life satisfaction and affect.
RESULTS:

Sample Size: The study included 266 adolescents from two secondary schools in an urban
Southeastern USA city. The participants consisted of 92 males and 174 females, with a mean age
of 16.22 years.

Measures Used:
1. Students' Life Satisfaction Scale (SLSS): A 7-item self-report scale to measure adolescents'
overall life satisfaction.
2. Positive and Negative Affect Scale (PANAS): Two ten-item self-report scales to measure positive
and negative affect.

Life Satisfaction Scores: The mean score on the Students' Life Satisfaction Scale was 34.65 (SD =
7.33).

Affect Scores: The mean scores on the PANAS Positive Affect and Negative Affect scales were
34.65 (SD = 7.33) and 22.62 (SD = 7.63) respectively.

Factor Analysis: The factor analysis resulted in a three-factor solution, representing global life
satisfaction, negative affect, and positive affect.

Relationship between Affect and Life Satisfaction: A hierarchical multiple regression analysis
showed that life satisfaction scores reflect more than just negative affect and include a positive
affect component as well. Affect, both positive and negative, explains only a modest proportion
(24%) of the variance in life satisfaction reports.

Demographic Variables: Age and life satisfaction scores were not significantly correlated.
Socioeconomic status was weakly related to negative affect.

Gender and Ethnicity: Female adolescents reported higher negative affect than male
adolescents. Black adolescents reported higher positive affect scores than white adolescents.
However, there were no significant gender, ethnicity, or interaction effects on life satisfaction
scores.
Overall, the study found that life satisfaction scores are influenced by both positive and negative
affect, and affect explains only a modest portion of the variance in life satisfaction reports among
adolescents. Gender and ethnicity had some influence on affect scores, but not on life satisfaction
scores.
DISSCUSION SIMPLIFIED:

The study examined subjective well-being in adolescents using a three-factor model that
included positive affect, negative affect, and global life satisfaction. The results showed that this
model is applicable across different age groups, from children to adolescents and adults.

The findings suggest that affective (emotional) aspects of well-being and cognitive aspects (life
satisfaction) are distinct and separate from each other. Adolescents may experience frequent
positive emotions but still report low life satisfaction, showing that these aspects of well-being
are not always aligned.

The study also revealed that the three constructs (positive affect, negative affect, and life
satisfaction) are independent of each other, questioning traditional unidimensional views of
well-being that simply focus on the absence of negative emotions.
STUDY 4
Altundag, Y., & Bulut, S. (2014). Prediction of Resilience of Adolescents Whose Parents Are Divorced.
Psychology, 5(10),1215–1223.
SAMPLE DETAILS

The study was conducted in Bolu during the academic year 2012-2013.

The participants were high school students from grades 9 to 12.

Initially, all high schools in Bolu were attempted to be included, but not all of them were
accessible for various reasons.

The researchers used a random sampling method to select the schools for the study.

The study included 11 high schools in total, which were categorized as follows:
1. Five Anatolian High Schools
2. One Teacher High School
3. One Regular High School
4. Four Vocational High Schools

The total number of students who participated in the study was 144.

All of these students had parents who were officially divorced.
TEST USED:

Demographic Information Form:
Used to collect personal information about adolescents, including sex, school, family status, number of
friends, and siblings.

Adolescent Resilience Scale:
1. Developed by Bulut, Doğan, and Altundağ (2013).
2. Consists of 29 items and six sub-dimensions: family support, peer support, determination of
struggle, adaptation, and empathy.
3. Validity: Exploratory Factor Analysis (EFA) was conducted, showing factor loadings between .51
and .82, explaining 56.99% of the total variance.
4. Criterion validity: Correlated with Problem Solving Inventory (-.47), Focus of Control Scale (-.46),
and Beck Despair Scale (-.61).
5. Reliability: Test-retest correlation of .87. Cronbach's Alpha internal consistency coefficients
were .87 for the whole scale, .89 for "family support," .84 for "peer support," .81 for "school
support," .70 for "adaptation," .67 for "determination of struggle," and .61 for "empathy."

Life Satisfaction Scale (LSS):
6. Developed by Diener, Emmons, Larsen, and Griffin (1985).
7. Measures life satisfaction of participating adolescents.
8. 7-grade Likert scale, higher points indicate higher life satisfaction.
9. Reliability: Cronbach's Alpha value was .84.

Loneliness Scale:
10. Revised form of the instrument developed by Russell, Peplau, and Ferguson (1978).
11. Validity: Significant correlations with UCLA Loneliness Scale (.62) and Beck Depression Scale
(.62).
12. Reliability: Internal consistency coefficient was .96, test-retest reliability was .73 after two
months interval.
RESULTS:

Pearson correlation analysis was used to examine the relationships between resilience, life
satisfaction, and loneliness levels of adolescents from divorced families and broken homes.

Correlation results:
1. Strong negative correlation (-0.70) between life satisfaction and loneliness.
2. Positive correlations between life satisfaction and empathy (0.40), determination of struggle
(0.71), adaptation (0.54), school support (0.17), peer support (0.68), and family support (0.64).

Multiple Regression analysis was performed to determine if life satisfaction and loneliness
levels predict resilience.

Regression results:
3. Positive relation (r = 0.65) between life satisfaction and resilience when controlling for other
variables.
4. Strong negative relation (r = -0.92) between loneliness and resilience.
5. Together, life satisfaction and loneliness variables explain 84% of the total variance in resilience.
6. Loneliness is a significant predictor of resilience, while life satisfaction does not have a
significant effect.
DISSCUSION SIMPLIFIED:

The study investigated the correlation between resilience, life satisfaction, and loneliness in
adolescents from divorced families. Previous research has focused on factors like self-respect,
coping ability, and emotional intelligence in relation to resilience. Some studies found positive
correlations between life satisfaction and resilience, while others found a stronger correlation
between life satisfaction and loneliness.

In this study, a strong negative correlation was found between life satisfaction and loneliness.
Additionally, there were positive correlations between life satisfaction and factors like empathy,
determination of struggle, adaptation, school support, peer support, and family support.

The results of multiple regression analysis indicated that life satisfaction and loneliness together
explain a significant amount of the variance in resilience. However, only loneliness was found to
be a significant predictor of resilience, suggesting that higher levels of loneliness are associated
with lower resilience.

The study highlighted the importance of social support in reducing feelings of loneliness and
social isolation in adolescents from divorced families. Close relatives and extended family
members play a significant role in providing social, financial, and emotional support to children
and adolescents in these situations.
STUDY 5
Garcia, A., Archer, T., 2012. Adolescent life satisfaction and well-being. J. Alternat. Med. Res. 4 (3),
271–279.
SAMPLE DETAILS
1. The study was conducted at a high school in the county of Blekinge, Sweden.
2. The whole population of the school, which consisted of 150 pupils, was contacted for
participation.
3. Out of the 150 pupils, 141 agreed to participate in the study.
4. Among the participants, there were 80 girls and the rest were boys.
5. The average age of the participants was 16.89 years, with a standard deviation (SD) of 0.97.
6. The adolescents obtained consent from their teachers to participate in the study.
7. All parents of the participants were informed about the study and other studies being
conducted among adolescents at the school.
8. The nature of the studies, including details about the instruments used and confidentiality
measures, was explained to the participants during a meeting.
9. The participants were assured that their involvement was voluntary and confidential.
10. The purpose of the studies was explained to be about how high school pupils think about their
lives.
11. The participants were given a battery of instruments, including measures of affect (PA and NA),
life satisfaction (LS), and psychological well-being (PWB).
12. The scores for positive affect (PA) and negative affect (NA) were divided into "high" and "low"
categories using specific cut-off points recommended in previous studies (low PA = 34 or less,
high PA = 35 or above, low NA = 22 or less, and high NA = 23 or above).
TEST USED:

Positive Affect and Negative Affect Schedule (PANAS):
1. Measures participants' experience of 20 different feelings or emotions over the last weeks.
2. Includes two scales: Positive Affect (PA) and Negative Affect (NA).
3. PA scale has 10 adjectives such as strong, proud, and interested.
4. NA scale has 10 adjectives such as afraid, ashamed, and nervous.
5. Responses are given on a 5-point Likert scale (1 = very slightly, 5 = extremely).
6. Cronbach's α reliability for PA scale is .84, and for NA scale is .81.

Satisfaction with Life Scale (SWLS):
7. Assesses participants' satisfaction with life through 5 items.
8. Participants rate their agreement on statements using a 7-point Likert scale (1 = strongly
disagree, 7 = strongly agree).
9. Example item: "I am satisfied with my life."
10. The LS score is computed by summarizing the 5 statements for each participant.
11. Cronbach's α reliability for SWLS is .83.

Ryff's Short Measurement of Psychological Well-Being:
12. Measures psychological well-being through 18 items, divided into six subscales.
13. Each subscale has three statements, and participants rate their agreement on a 6-point Likert
scale (1 = strongly disagree, 6 = strongly agree).
14. The six subscales are Self-acceptance, Positive Relations with Others, Autonomy, Environmental
Mastery, Purpose in Life, and Personal Growth.
15. The Self-acceptance subscale (e.g., "I like most aspects of my personality") is formed from three
items (Cronbach's α = .76).
16. The total Psychological Well-Being score is obtained by summing all 18 items (Cronbach's α =
.75).
RESULTS:
1. Gender did not have a significant effect on life satisfaction (LS) or psychological well-being
(PWB).
2. Temperaments (AFTs) had a significant effect on both LS and PWB. Self-actualizing, high
affective, and low affective adolescents reported higher LS and PWB compared to
self-destructive adolescents.
3. The interaction between AFTs and gender did not significantly affect LS or PWB, indicating that
the impact of AFTs on these variables was consistent across genders.
4. Psychological well-being (PWB) emerged as a significant predictor of LS for all temperaments.
5. Self-acceptance was significantly related to LS for all temperaments, suggesting that it plays an
important role in adolescents' life satisfaction regardless of their temperament.
DISSCUSION SIMPLIFIED:

The aim of this study was to explore differences in life satisfaction (LS) and psychological
well-being (PWB) among different temperaments (AFTs) in adolescents. The researchers also
wanted to understand the relationship between PWB and LS for each temperament. They
hypothesized that self-acceptance, a component of PWB, would be a significant predictor of LS
for all temperaments.

The results supported previous findings that self-actualizing, high affective, and low affective
adolescents reported higher LS and PWB compared to self-destructive adolescents. This
indicates that positive emotions, such as high positive affect (PA), can play a crucial role in
adolescents' well-being and adaptive responses to their environment.

The broaden and build theory suggests that positive emotions broaden an individual's thoughts
and behaviors, leading to more adaptive responses and enhanced well-being. In this study, high
positive affect in adolescents seemed to neutralize the negative effects of high negative affect,
making it more beneficial to be a high affective adolescent compared to a low affective one.

The researchers found that self-acceptance was a significant predictor of LS for all
temperaments. Adolescents who could accept themselves without judgment were more likely
to see their lives as satisfying and experience well-being. Fostering self-acceptance among youth
could be crucial for their overall well-being.
STUDY 6
Moksnes, U. K., Løhre, A., Lillefjell, M., Byrne, D. G., & Haugan, G. (2014). The Association
Between School Stress, Life Satisfaction and Depressive Symptoms in Adolescents: Life
Satisfaction as a Potential Mediator. Social Indicators Research, 125(1), 339–357.
SAMPLE DETAILS

The survey was conducted every fifth year since 1996 by the Norwegian University of Science
and Technology in Trondheim.

The survey targeted adolescents living in rural areas in the county of Sør-Trøndelag,
mid-Norway.

Convenience sampling was used to select participants from schools in inland to coastal areas in
five of the county's 25 municipalities.

A total of 1,924 students from 12 public lower and upper secondary schools were asked to
participate in the study.

The response rate was 67%, with 1,289 students completing the questionnaire.

Non-responses were mainly due to students being absent when the questionnaire was
administered or declining to answer.

Students younger than 13 or older than 18 (n = 50) were excluded from the study.

This left a final sample size of n = 1,239 (64%) adolescents aged between 13 and 18 years.

In the sample, 634 (51.2%) were girls, and 603 (48.7%) were boys, with gender unidentified for
two participants.

The distribution of participants in each age group was as follows: 13 years (n = 293, 23.6%), 14
years (n = 247, 19.9%), 15 years (n = 250, 20.2%), 16 years (n = 180, 14.5%), 17 years (n = 149,
12%), and 18 years (n = 120, 9.7%).

The mean age for the total sample was 15.00 (SD 1.62), with boys having a mean age of 14.99
(SD 1.63) and girls 15.02 (SD 1.63).
TEST USED

Adolescent Stress Questionnaire (ASQ-N): Used to assess school-related stress, including
stressors related to school performance and teacher interaction. It consists of a total of 11
items, with five items measuring stress of school performance and six items measuring stress of
teacher interaction.

Satisfaction with Life Scale (SWLS): Used to assess life satisfaction. It consists of five items, with
participants rating their agreement on a seven-point Likert scale.

Depression Scale: A short 15-item questionnaire specifically designed to assess nonclinical
depressive mood. Participants rate the extent to which they have experienced depressive
symptoms in the past week on a five-point Likert scale.

Confirmatory Factor Analysis (CFA): Used to evaluate the measurement models for the scales
and ensure that the items are valid and reliable indicators of the latent constructs they are
intended to measure.

Robust Maximum Likelihood (RML): A method used to correct for non-normality in the data
when applying structural equation modeling (SEM).

Structural Equation Modeling (SEM): Used to test the hypothesized relationships between
school stressors, life satisfaction, and depressive symptoms. SEM combines factor models with
regression models to assess overall model fit and evaluate the relationships between variables.
RESULTS

In the descriptive analysis:
1. Means, standard deviations, Cronbach's alpha, and Pearson's correlation matrix were presented
for the variables: stress of school performance, stress of teacher interaction, depressive
symptoms, and life satisfaction (LS).
2. The correlations between all variables were moderate to strong, significant, and in the expected
direction. Stress of school performance and stress of teacher interaction were positively
correlated with depressive symptoms and inversely correlated with life satisfaction.
3. Life satisfaction (LS) showed an inverse correlation with depressive symptoms.
4. The internal consistency of the various variables was good, with Cronbach's alpha coefficients
ranging between .83 and .89.

In the Structural Equation Modeling (SEM) analysis:
1. Model 1, which included stress of school performance, stress of teacher interaction, and
depressive symptoms, provided a good fit to the data. Stress of school performance showed a
strong positive association with depressive symptoms, while the association between stress of
teacher interaction and depressive symptoms was non-significant.
2. Model 2, which added life satisfaction (LS) to Model 1, also displayed a good fit. Stress of school
performance showed a significant inverse association with LS, but stress of teacher interaction
did not have a significant relation with LS.
3. There was a significant inverse association between LS and depressive symptoms.
4. LS partially mediated the association between stress of school performance and depressive
symptoms, but it did not act as a mediator between stress of teacher interaction and depressive
symptoms.
5. The total effect of stress of school performance on depression reduced slightly when LS was
included in the model, suggesting that LS has a weak additive value in explaining the association
between stress of school performance and depressive symptoms.
6. An indirect effect of stress of school performance on depression was found, indicating that this
association is affected by LS as an intervening variable. However, the total effect of stress of
school performance on depression remained significant even after considering LS.
Overall, the results suggest that school stress is associated with both depressive symptoms and life
satisfaction, and that life satisfaction partially mediates the association between stress of school
performance and depressive symptoms. Stress of teacher interaction, on the other hand, does not
appear to have a significant direct association with depressive symptoms or life satisfaction.
STUDY 7
Hughes, A. A., & Kendall, P. C. (2009). Psychometric Properties of the Positive and Negative
Affect Scale for Children (PANAS-C) in Children with Anxiety Disorders. Child Psychiatry and
Human Development, 40(3), 343–352.
SAMPLE DETAILS:
The sample consisted of 139 children with the following characteristics:

Age range: 7 to 14 years
1. Mean age: 10.40 years
2. Standard deviation (SD): 1.75 years

Principal Anxiety Disorder Diagnosis:
3. All children met DSM-IV diagnostic criteria for a principal anxiety disorder diagnosis.
4. Specific diagnoses were as follows: Generalized Anxiety Disorder (GAD): 46% of the sample
5. Social Phobia (SP): 32% of the sample
6. Separation Anxiety Disorder (SAD): 22% of the sample

Additional Diagnoses:
7. 76% of children had an additional anxiety disorder diagnosis.
8. 18% of children had a mood disorder.
9. 33% of children had attention deficit hyperactivity disorder (ADHD).
10. 9% of children had oppositional defiant disorder (ODD).
11. 4% of children had selective mutism.
12. 4% of children had functional enuresis.

Exclusion Criteria:
13. Children were excluded if they demonstrated psychotic symptoms.
14. Children were excluded if they were taking anti-anxiety or antidepressant medications.
15. Children were excluded if they were non-English-speaking or writing.

Gender and Ethnicity:
16. Male: 58% of the sample
17. Caucasian: 84% of the sample
18. African-American: 9% of the sample
19. Hispanic: 4% of the sample
20. Other: 3% of the sample

Family Income:
21. Below $20,000: 4% of the sample
22. Between $20,000 and $40,000: 12% of the sample
23. Between $40,000 and $60,000: 20% of the sample
24. Between $60,000 and $80,000: 28% of the sample
25. Above $80,000: 36% of the sample

Marital Status of Parents:
26. Married: 80% of the sample
TEST USED:

Demographic Questionnaire:
Purpose: Obtaining demographic information such as age, gender, ethnicity, and family income level
from children's caregivers.

Anxiety Disorders Interview Schedule for Children (ADIS-C/P):
Purpose: Semi-structured diagnostic interviews administered to parents and children independently to
assess the presence of DSM-IV anxiety disorders in children and adolescents. Also assesses
symptomatology and severity of anxiety, mood, and externalizing disorders in youth.

Positive and Negative Affect Scale for Children (PANAS-C):
Purpose: A 27-item self-report scale that measures positive affect (PA) and negative affect (NA) in
children and adolescents. Participants indicate how often they have felt this way over the past two
weeks.

Multidimensional Anxiety Scale for Children (MASC):
Purpose: A 39-item self-report measure of anxiety symptoms characteristic of children and adolescents.
Provides several subscales, including total anxiety scale (MASC-TS), social anxiety scale (MASC-SOC), and
separation anxiety scale (MASC-SEP).

Revised Children’s Manifest Anxiety Scale (RCMAS):
Purpose: A 37-item true-false self-report measure of trait anxiety. Provides a total anxiety scale
(RCMAS-TS) and subscales, such as the worry subscale (RCMAS-WOR).

The Children’s Depression Inventory (CDI):
Purpose: A self-report measure with 27 items assessing the cognitive, affective, and behavioral
symptoms of depression in children. Provides insights into depression severity.
RESULTS:
Descriptive Statistics:

PANAS-C subscales demonstrated good internal consistency.
1. MASC and RCMAS total scales and subscales exhibited good or adequate internal consistency.
2. CDI demonstrated adequate internal consistency.

Zero-Order Correlations between PANAS-C Subscales with Measures of Anxiety and
Depression:
3. NA (Negative Affect) showed significant positive correlations with measures of trait anxiety,
social anxiety, worry, separation anxiety, and depression.
4. PA (Positive Affect) showed significant negative correlations with depression, and negative
correlations (except for separation anxiety) with measures of trait anxiety, social anxiety, and
worry.
5. PA and NA were not significantly related to each other.

Differences in the Magnitudes of Correlations between PA and NA with Measures of Anxiety
and Depression:
6. NA was more strongly correlated with trait anxiety, worry, separation anxiety, and depression
than PA.
7. PA was more strongly correlated with social anxiety and depression than NA.

Hierarchical Multiple Regression Analyses for Measures of Anxiety and DepressionL:
For trait anxiety, worry, separation anxiety, and depression:
1. NA significantly predicted anxiety and depression scores, but not social anxiety.
2. PA significantly predicted social anxiety and depression scores, but not other anxiety measures.
These results indicate that negative affect (NA) was consistently related to various measures of
anxiety and depression, while positive affect (PA) was more strongly associated with social anxiety
and depression but not as much with other anxiety measures. This supports the tripartite model,
which suggests that NA is a common factor underlying both anxiety and depression, while PA is
specifically related to depression and some aspects of social anxiety.
DISSCUSION SIMPLIFIED:
1. Convergent and Discriminant Validity of PANAS-C:
2. The study provided evidence supporting the convergent validity of the Negative Affect (NA) and
Positive Affect (PA) scales of the PANAS-C (a measure of mood) in children diagnosed with
anxiety disorders.
3. NA was positively correlated with measures of anxiety (trait anxiety, social anxiety, worry, and
separation anxiety) and depression, as expected based on previous research and the tripartite
model.
4. PA was negatively correlated with depression and showed moderate negative correlations with
most anxiety measures (except separation anxiety). This was inconsistent with the tripartite
model's prediction, as PA was also moderately correlated with various anxiety measures.

Differentiating Social Anxiety and Depression:
5. The study found that PA was more strongly associated with social anxiety than with other
anxiety measures, contrary to the tripartite model's prediction.
6. PA was also positively correlated with depression, as expected from the tripartite model.
STUDY 8
Laurent, J., Catanzaro, S. J., Joiner Jr, T. E., & Rudolph, K. D. (2000). A measure of positive and
negative affect for children: Scale development and preliminary validation. Psychological
Assessment, 12(3), 326-338.
SAMPLE DETAILS
1. Sample: The study included 707 youngsters in Grades 4-8 from central Illinois.
2. Age: The mean age of the students in the sample was 11.67 years (SD = 1.48).
3. Grade Distribution: The sample consisted of 149 fourth graders, 144 fifth graders, 151 sixth
graders, 126 seventh graders, and 137 eighth graders.
4. Gender Distribution: The sample was 51% male and 49% female.
5. Ethnicity: Most children in the sample were Caucasian (95%), with African Americans, Asian
Americans, and those from other ethnic backgrounds representing 2%, 1%, and 2% of the
sample, respectively.
6. Family Structure: Sixty-three percent of the students lived with both biological parents, 11%
lived with only their biological mother, 2% lived only with their biological father, 13% lived with
their biological mother and stepfather, 4% lived with their biological father and stepmother, and
5% reported other living arrangements.
7. Special Education Status: Specific questions about special education status were not asked, but
based on school records, it was estimated that 12.2% of the students in Grades 4-8 received
special education services.
8. Sample Division: Due to the relatively large number of participants, the sample was divided into
two groups for data analysis based on the day of the month on which a child was born:
a. Sample 1 (n = 349): Composed of students born on the 1st-8th, 16th-21st, or 30th day of the
month.
b. Sample 2 (n = 358): Composed of students born on the 9th-15th, 22nd-29th, or 31st day of the
month.
Overall, the sample size for the study was 707, which provided sufficient variability and
representation from a general school population to examine the item performance of the PANAS-C.
RESULTS:

Positive Affect (PA) Scale:
1. In both the scale development and replication samples, the item "alert" on the PA scale did not
show a strong correlation with the total score.
2. The factor analysis for the PA scale revealed three factors, but only one factor had a significant
eigenvalue.
3. Items "fearless" and "daring" seemed to be problematic and were eliminated from the scale in
both samples.
4. The remaining 12 PA items were analyzed, and a two-factor solution emerged. However, the
correlation between the factors was strong, suggesting a unidimensional structure for the PA
scale.
5. The Schmid-Leiman transformation confirmed the unidimensional nature of the PA scale, with
two primary factors remaining.

Negative Affect (NA) Scale:
6. The item-total correlations for all 15 items on the NA scale exceeded the .30 criterion in both
samples, indicating good performance.
7. The factor analysis for the NA scale revealed a single robust factor, suggesting that all items
were cohesive and should be retained.

Overall PANAS-C Scale:
8. The final PANAS-C scale consisted of 12 items for Positive Affect and 15 items for Negative
Affect, showing distinct and reliable factors.
9. The PANAS-C demonstrated consistent results in both the scale development and replication
samples, supporting the validity and reliability of the measure.
In summary, the study established a reliable and valid PANAS-C scale consisting of 12 Positive Affect
items and 15 Negative Affect items, providing a useful tool to assess affect in children from a general
school population.
SUMMARY SIMPLIFIED:
1. Corrected Item-Total Correlations: All items on the Negative Affect (NA) scale had good
correlations with the total score, but the item "alert" on the Positive Affect (PA) scale did not
meet the criterion.
2. Factor Analysis for PA Scale: Initially, a two-factor solution emerged for the PA scale, but after
eliminating three items ("alert," "fearless," and "daring"), a second analysis suggested a
unidimensional structure for PA.
3. PA Scale Structure: The PA scale was best represented by 12 items, with all items contributing
to the general construct of positive affect. The Schmid-Leiman transformation confirmed the
unidimensional nature of the scale.
4. Factor Analysis for NA Scale: The NA scale showed robust loadings on a single factor, indicating
a strong relationship among all 15 items.
5. PANAS-C Scale Structure: A two-factor solution emerged in the final PANAS-C scale, with
separate robust factors for Positive Affect and Negative Affect, showing distinct characteristics
and a negative correlation between them (-0.25).
In summary, the study resulted in a 12-item Positive Affect scale and a 15-item Negative Affect scale.
The factor analyses confirmed the distinct nature of positive and negative affect, supporting the
validity and reliability of the PANAS-C as a measure of affect in children.
STUDY 9
Vera-Villarroel, P., Urzúa, A., Jaime, D., Contreras, D., Zych, I., Celis-Atenas, K., … Lillo, S.
(2017). Positive and Negative Affect Schedule (PANAS): Psychometric Properties and
Discriminative Capacity in Several Chilean Samples. Evaluation & the Health Professions,
016327871774534.
SAMPLE DETAILS:
Study 1:
1. Convenience sampling of 1,548 participants ranging in age from 18 to 60 years.
2. EFA subsample: n = 773 participants
3. CFA subsample: n = 775 participants
Study 2:
1. Evaluation of 1,044 teenagers aged between 13 and 17 years.
2. EFA subsample: n = 527 participants
3. CFA subsample: n = 517 participants
Study 3:
1. 964 adults aged between 18 and 60 years.
2. No subsamples were mentioned in Study 3.
Study 4:
1. Intentional sample of 307 young people aged between 18 and 29 years.
2. EFA subsample: n = 154 participants
3. CFA subsample: n = 153 participants
In summary, the total sample size across all four studies is 5,866 participants. Each study used
different sampling methods and divided the sample into subsamples for conducting exploratory factor
analyses (EFAs) and confirmatory factor analyses (CFAs).
TEST USED:
1. PANAS (Positive and Negative Affect Schedule): A self-report questionnaire with two scales
designed to measure Positive Affect (PA) and Negative Affect (NA).
2. BDI (Beck's Depression Inventory - revised version): Designed to measure the severity of
cognitive, affective, behavioral, and psychophysiological symptoms of depression.
3. STAI (State-Trait Anxiety Inventory): A questionnaire with two subscales - State Anxiety and
Trait Anxiety - used to measure anxiety as a temporary emotional condition and as a more
permanent emotional state of tension.
4. BFI (Big Five Inventory): Designed to assess personality using five factors - extroversion,
agreeableness, conscientiousness, neuroticism, and openness.
5. PHQ-9 Depression Scale (Patient Health Questionnaire-9): A questionnaire to measure the
presence of depressive symptoms based on Diagnostic and Statistical Manual of Mental
Disorders-IV criteria.
RESULTS:
Study 1:

EFA was performed with 1,548 participants, and both two- and three-factor solutions were
considered for PANAS.

The three-factor solution showed better fit indices but was not theoretically coherent, so the
two-factor solution (PA and NA) was chosen.

CFA confirmed the adequacy of the two-factor solution.

Reliability for both PA and NA was high (Cronbach's alpha = 0.91).
Study 2:

EFA was conducted with 1,044 teenagers, considering two- and three-factor solutions.

The three-factor solution separated NA into two factors: upset and afraid.

However, the two-factor solution was chosen as it had better fit indices and coherent factor
loads.

CFA confirmed the adequacy of the two-factor solution.

Reliability for both PA and NA was high (Cronbach's alpha = 0.85 and 0.83, respectively).
Study 3:

Convergent and divergent validity of the PANAS was assessed with 964 adult participants.

PANAS correlated significantly with depression, anxiety, neuroticism, and extroversion.

Both PA and NA were related to depression, anxiety, neuroticism, and extroversion.
Study 4:

EFA was performed with 307 young people with depressive symptomatology.

A two-factor solution was chosen, but the correlation between the factors was significant,
indicating they were not entirely independent.

CFA confirmed the adequacy of the two-factor solution.

Reliability for both PA and NA was high (Cronbach's alpha = 0.85 and 0.87, respectively).

PANAS scores differed significantly based on the degree of depressive symptomatology.
DISSCUSION SIMPLIFIED:

Reliability: The PANAS questionnaire showed high reliability in all three studies, with Cronbach's
alpha values over 0.80 for both Positive Affect (PA) and Negative Affect (NA) scales. This
indicates that the questionnaire consistently measures emotions effectively.

Factor Structure: The researchers confirmed a two-factor structure of the PANAS, with distinct
factors for PA and NA. However, in the clinical sample, there was a significant correlation
between PA and NA, likely because these constructs were measured at the state level
(temporary emotional condition) rather than the trait level (more permanent emotional state)
as seen in the general adult and adolescent populations.

Three-Factor Solution: Interestingly, a three-factor solution was found in the clinical sample,
showing a different distribution of items within the afraid and upset dimensions. This suggests
that the PANAS may have different factor structures depending on the study population and the
presence of depressive symptomatology.

Validity: The PANAS demonstrated adequate convergent and divergent validity, as it correlated
significantly with measures of depression, anxiety, neuroticism, and extroversion. It effectively
differentiated between individuals with and without symptoms of depression, particularly in
terms of the presence of negative affect (NA).

Limitations: The study had some limitations, including the sampling method, which may not
fully represent the entire population. Additionally, the sample with depressive symptomatology
consisted only of young patients from a university health center, limiting the generalizability of
the findings.

Implications: The study provides valuable information for researchers and clinicians, confirming
that the PANAS is a suitable and reliable instrument to assess emotions in different populations
in Chile. The findings also highlight the importance of considering the factor structure and
emotional experience in stressful situations when using the PANAS. Further research with larger
and more diverse samples is encouraged to strengthen these findings and generate population
normative data.
STUDY 10
Ramos-Díaz, E., Rodríguez-Fernández, A., Axpe, I., & Ferrara, M. (2018). Perceived Emotional
Intelligence and Life Satisfaction Among Adolescent Students: The Mediating Role of
Resilience. Journal of Happiness Studies.
SAMPLE DETAILS:

Sample size: 945 adolescent students

Gender distribution: 425 male, 520 female

Age: Average age (Mage) of 14.50 years, with a standard deviation (SD) of 1.82 years

Age range: Participants' ages ranged from 12 to 17 years

Location: The study was conducted in five secondary schools in the Basque Country, Spain.

Informed Consent: Students who wished to participate provided signed consent from their
parents/guardians.
TEST USED:

Perceived Emotional Intelligence:
1. Trait Meta-Mood Scale (TMMS) - 24-item version, adapted to Spanish by Fernández-Berrocal et
al. (2004)
2. Dimensions: Emotional Attention, Emotional Clarity, Emotional Repair
3. Response scale: Five-point Likert-style scale (totally disagree - totally agree)
4. Cronbach’s alpha reliability indices:
a. Emotional Attention: .89
b. Emotional Clarity: .87
c. Emotional Repair: .84
d. Composite reliability coefficient (CFC) of the questionnaire: .88
e. Average variance extracted (AVE): .50

Life Satisfaction:
1. Satisfaction with Life Scale (SWLS) - Spanish version, validated by Atienza et al. (2000)
5 items (e.g. "I am satisfied with my life", "If I could live my life over, I would change almost
nothing")
2. Response scale: Seven-point Likert-type scale (strongly disagree - strongly agree)
3. Cronbach’s alpha reliability: .82
a. Composite reliability coefficient (CFC): .83
b. Average variance extracted (AVE): .51

Resilience:
1. CD-RISC 10-item Resilience Scale by Campbell-Sills and Stein (2007)
2. Abbreviated version of the Connor-Davidson Scale (Connor and Davidson 2003)
10 statements (e.g., "Can deal with whatever comes", "Able to adapt to change")
3. Response scale: Five-degree Likert scale (0=strongly disagree, 5=strongly agree)
4. Internal consistency coefficients:
a. Cronbach’s alpha: .75
b. Composite reliability coefficient (CFC): .88
c. Average variance extracted (AVE): .50
RESULTS:
Preliminary Analysis:

The sample consisted of 945 adolescent students from five secondary schools in the Basque
Country, Spain.

Mean age of participants was 14.50 years (SD=1.82 years; range 12-17 years).

Participants completed questionnaires measuring Perceived Emotional Intelligence (PEI), Life
Satisfaction, and Resilience.

Reliability estimates (Cronbach’s alpha, CFC, and AVE coefficients) for the measures were as
follows:

Emotional Attention (TMMS): Cronbach's α = .89, CFC = .88, AVE = .50

Emotional Clarity (TMMS): Cronbach's α = .87, CFC = .88, AVE = .50

Emotional Repair (TMMS): Cronbach's α = .84, CFC = .88, AVE = .50

Life Satisfaction (SWLS): Cronbach's α = .82, CFC = .83, AVE = .51

Resilience (CD-RISC): Cronbach's α = .75, CFC = .88, AVE = .50

Bivariate zero-order correlation coefficients among variables were not provided in the given
information.
Measurement Model (CFA Analysis):

Confirmatory Factor Analysis (CFA) was conducted to test the measurement model.

The model included five interrelated latent variables: Emotional Attention, Emotional Clarity,
Emotional Repair, Satisfaction with Life, and Resilience.

The model showed a good level of model fit with the following indices:

χ² (512) = 1652.90, p < .001

CFI = .92

TLI = .91

SRMR = .062

RMSEA = .049 (90% CI = .046–.051)
Analysis of the Theoretical Model (Structural Equation Modeling - SEM):

Two models were tested to examine the relationships between the variables: a partial mediating
model and a full mediating model.

The partial mediating model included direct paths from the dimensions of PEI (Emotional
Attention, Emotional Clarity, Emotional Repair) to Life Satisfaction, as well as an indirect path
through Resilience.

The full mediating model proposed exclusively indirect effects of PEI factors on Life Satisfaction
through the mediating role of Resilience.

The results indicated that the partial mediating model had a better fit to the data compared to
the full mediating model.

The partial mediating model showed acceptable goodness-of-fit indexes: χ² (514) = 1660.30, p <
.01; CFI = .916, TLI = .908, SRMR = .062, RMSEA = .049 (90% CI = .046–.051).

All sub-scales of PEI (Emotional Attention, Emotional Clarity, Emotional Repair) indirectly
influenced Life Satisfaction through the mediator role of Resilience.
Model Comparison:

The Chi-squared test for the discrepancy between the two models (partial mediating vs. full
mediating) was statistically significant (Δχ² (1, N=945) = 16.36, p < .01), indicating that the two
models were significantly different.

The partial mediating model (M1) was found to have a better degree of replicability based on
the ECVI index.
Overall, the study suggests that Perceived Emotional Intelligence and Resilience play important roles
in determining Life Satisfaction in adolescent students. The partial mediating model, which considers
both direct and indirect effects, provides a better explanation for the relationships among these
variables.
DISSCUSION SIMPLIFIED:
The study focused on the relationship between Perceived Emotional Intelligence (PEI), Resilience, and
Life Satisfaction among adolescent students. It aimed to understand how emotional abilities and
resilience influence the students' overall satisfaction with life.
Key Findings:
Perceived Emotional Intelligence (PEI) and Life Satisfaction:

The study found that emotional clarity and emotional repair were positively related to both
resilience and life satisfaction. This means that students who had a better understanding of their
emotions and were able to manage them effectively tended to have higher levels of resilience
and life satisfaction.

Emotional attention, on the other hand, showed a weak negative direct effect on resilience and
an indirect inverse effect on life satisfaction. This means that excessive attention to emotions,
especially when students have difficulty understanding them, may negatively impact their
well-being and life satisfaction.
Mediating Role of Resilience:

The study revealed that resilience played a crucial role in determining students' life satisfaction.
Resilience partially mediated the relationship between PEI and life satisfaction. This means that
emotional intelligence, particularly emotional clarity and emotional repair, indirectly influenced
life satisfaction through its impact on resilience.

The findings suggest that emotional clarity, in particular, had a significant influence on
resilience, which, in turn, played a decisive role in students' life satisfaction during adolescence.
Practical Implications:

The study highlights the importance of developing emotional intelligence and resilience skills in
adolescents to improve their overall well-being and life satisfaction.

Schools can consider incorporating resilience-promoting programs into their standard
curriculum to enhance students' ability to cope with adversity and increase their life satisfaction.

The findings suggest that interventions targeting emotional intelligence and resilience can help
reduce stress and maladaptive behaviors and potentially improve mental health in adolescents.
STUDY 11
Eschenbeck, H., Kohlmann, C. W., & Lohaus, A. (2007). Gender differences in coping strategies in
children and adolescents. Journal of Individual Differences, 28(1), 18-26.
SAMPLE DETAILS:

Total participants: 1990 children and adolescents

Gender distribution: 957 boys and 1033 girls

Age range: 7 to 16 years

Mean age: 11.30 years

Standard deviation (SD) of age: 1.89 years

Grade distribution: The participants were from grades 3 to 8

Age groups: Participants were subdivided into three age groups reflecting important academic
transitions:
a. Late childhood: 644 third- and fourth-graders attending primary schools (338 boys, 306 girls)
b. Early adolescence: 672 fifth- and sixth-graders attending secondary schools (first level; 304
boys, 368 girls)
c. Middle adolescence: 674 seventh- and eighth-graders attending secondary schools (second
level; 315 boys, 359 girls)

School types for participants from secondary schools: The sample included students from
different school types representing various education levels:
d. Grammar schools: 35.4%
e. Lower and intermediate secondary schools: 49.9%
f.
Comprehensive schools: 14.7%
Overall, the sample size was relatively large, with a diverse representation of children and adolescents
across different age groups and school types in Germany.
TEST USED:

Revised German Stress and Coping Questionnaire for Children and Adolescents (Fragebogen
zur Erhebung von Stress und Stressbewältigung im Kindes- und Jugendalter, SSKJ 3–8):
Description: This is a stimulus-response inventory used to assess coping strategies in children and
adolescents. Participants rate how often they use various coping strategies in response to common
stressful situations. The questionnaire includes items related to seeking social support, problem-solving,
avoidant coping, palliative emotion regulation, and anger-related emotion regulation.
Subscales: The questionnaire consists of five dimensions of coping, with six items per dimension:
1. Seeking social support: e.g., "I ask someone for help."
2. Problem-solving: e.g., "I try to think of different ways to solve it."
3. Avoidant coping: e.g., "I tell myself it doesn't matter."
4. Palliative emotion regulation: e.g., "I try to relax."
5. Anger-related emotion regulation: e.g., "I get mad and break something."
Reliability: The alpha coefficients (α) indicate the internal consistency of the subscales for the
cross-situational coping and for each of the stress situations (argument with a friend and problems with
doing homework).

Factor analysis:
Description: Factor analysis is a statistical method used to identify underlying factors or dimensions in a
set of observed variables. In this study, factor analysis was used to determine the structure of coping
strategies and to identify the five factors representing seeking social support, problem-solving, avoidant
coping, palliative emotion regulation, and anger-related emotion regulation.

Factor congruence analysis:
Description: Factor congruence analysis is used to assess the similarity of factor structures across
different groups or situations. In this study, factor congruence analysis was used to confirm the
five-factor solution for coping strategies in different gender groups and for the two included stressful
situations (argument with a friend and problems with doing homework).
RESULTS:

Gender Differences in Coping Strategies:
1. Girls scored higher in seeking social support and problem-solving.
2. Boys scored higher in avoidant coping.
3. No gender differences were observed for palliative emotion regulation and anger-related
emotion regulation.

Grade Level Differences in Coping Strategies:
4. Primary school children (grades 3 and 4) scored lower in problem-solving compared to fifth and
sixth graders.
5. Fifth and sixth graders scored the lowest in avoidant coping.
6. Fifth and sixth graders scored lower in palliative emotion regulation compared to seventh and
eighth graders.
7. Seventh and eighth graders scored the highest in anger-related emotion regulation.

Situation Differences in Coping Strategies:
8. Children and adolescents reported higher scores in seeking social support, problem-solving,
avoidant coping, and anger-related emotion regulation in the social situation (argument with a
friend) compared to the academic situation (problems with homework).

Interaction Effects:
9. Gender differences in coping strategies (seeking social support, problem-solving, and avoidant
coping) were stronger for the social argument situation compared to the academic homework
situation.
10. The gender difference in seeking social support was strongest for older participants (grades 7
and 8).
11. Problem-solving strategies were reported the least by primary school children (grades 3 and 4)
in the social situation and by primary school children and adolescents (grades 7 and 8) in the
academic homework situation.
12. Avoidant coping was used the most by primary school children (grades 3 and 4) in the social
argument situation and by adolescents (grades 7 and 8) in the academic homework situation.

Three-Way Interaction:
13. The gender differences in seeking social support and avoidant coping were strongest for the
social argument situation in adolescents of grades 7 and 8.
DISSCUSION SIMPLIFIED:

Situational Differences: Children and adolescents used different coping strategies in response to
stressful situations. Specifically, they employed more problem-solving, avoidant coping, and
anger-related emotion regulation for social stressors (e.g., arguments with friends) compared to
academic stressors (e.g., problems with homework). Seeking social support was used more
frequently for social stressors as well.

Age Differences: Overall, there were only small age differences in coping strategies. However,
late primary school children used less problem-solving compared to adolescents, especially for
social stressors. Avoidant coping was lowest among early adolescents, implying a decrease in
avoidance with age.

Gender Differences: Gender differences were observed in three out of five coping strategies.
Girls reported using more seeking social support and problem-solving, while boys reported using
more avoidant coping. However, no gender differences were found for palliative emotion
regulation and anger-related emotion regulation.

Interaction Effects: The gender differences in seeking social support and avoidant coping were
stronger for the social stressor (argument with a friend) compared to the academic stressor
(problems with homework). Additionally, the gender differences were more pronounced in
middle adolescence (grades 7 and 8) than in late childhood (grades 3 and 4).
STUDY 12
Sánchez-Álvarez, N., Extremera, N., & Fernández-Berrocal, P. (2016). Maintaining life satisfaction in
adolescence: Affective mediators of the influence of perceived emotional intelligence on overall life
satisfaction judgments in a two-year longitudinal study. Frontiers in Psychology, 7, 1557.
SAMPLE DETAILS

The sample consisted of 269 adolescents from southern Spain.

The sample included 145 girls and 124 boys.

Participants were recruited from various high schools in the region.

All participants participated voluntarily and anonymously.

The data was collected at the beginning of the first academic semester in three successive years.

At the first assessment, participants' ages ranged from 12 to 16 years.

The mean age of the boys was 13.24 years (SD = 1.11).

The mean age of the girls was 13.28 years (SD = 1.10).

The study was conducted in accordance with the Declaration of Helsinki and ethical guidelines.

The Research Ethics Committee of the University of Málaga approved the study.
TEST USED:

Perceived Emotional Intelligence: Measured using the self-report Trait Meta-Mood Scale
(TMMS) - a shortened Spanish version (Fernández-Berrocal et al., 2004).
Three subscales were assessed:
a. Attention to Feelings
b. Mood Clarity
c. Emotional Repair.

Life Satisfaction: Measured using the Spanish version of the Satisfaction with Life Scale (SWLS)
(Diener et al., 1985).
The SWLS consists of five items rated on a seven-point Likert scale.

Positive Affect and Negative Affect: Measured using the Positive and Negative Affect Schedule
(PANAS) (Watson et al., 1988).
1. Twenty items in total, with 10 adjectives describing positive affect and 10 adjectives describing
negative affect.
2. Participants rated the extent to which they generally feel each way on a scale ranging from 1
(very slightly or not at all) to 5 (extremely).
RESULTS:

Descriptive Statistics:
1. Attention to feelings was positively correlated with negative affect at all three time points.
2. Mood clarity and emotional repair were positively correlated with positive affect and life
satisfaction at all three time points.

Structural Model:
3. A cross-lagged panel model was developed based on earlier research and mediation models
proposed by Baron and Kenny (1986).
4. The model included all measured variables and direct paths from TMMS dimensions to positive
affect, negative affect, and life satisfaction, as well as direct paths from positive affect and
negative affect to life satisfaction.
5. Two-way mediation was tested involving positive affect and negative affect.
6. The model was an acceptable fit to the data and accounted for 32% of the variance in life
satisfaction.

Indirect Associations:
7. There were indirect associations between TMMS dimensions (attention to feelings, mood clarity,
and emotional repair) and positive affect, negative affect, and life satisfaction.
8. The strongest indirect associations were found for attention to feelings and mood clarity, while
those involving emotional repair were weaker.
In summary, the study found significant relationships between perceived emotional intelligence
(measured using TMMS dimensions) and positive affect, negative affect, and life satisfaction.
Attention to feelings and mood clarity showed stronger indirect associations with positive and
negative affect and life satisfaction, while emotional repair had comparatively weaker associations.
DISSCUSION SIMPLIFIED:

Emotional Intelligence and Emotions:
1. Attention to feelings: Paying more attention to one's feelings was associated with experiencing
more negative emotions over time.
2. Mood clarity: Having better clarity about one's moods was linked to experiencing more positive
emotions and greater life satisfaction.
3. Emotional repair: Being good at repairing negative moods was connected to experiencing more
positive emotions and greater life satisfaction.

Emotional Intelligence and Life Satisfaction:
4. Adolescents with higher emotional intelligence tended to experience more positive emotions,
fewer negative emotions, and greater life satisfaction over a 2-year period.

Mediation of Emotions:
5. Positive and negative emotions partially mediated the relationship between emotional
intelligence and life satisfaction. This means that emotional intelligence influences life
satisfaction indirectly through its impact on positive and negative emotions.
6. Adolescents who paid less attention to their feelings experienced less negative emotion and
more positive emotion, leading to greater life satisfaction.
7. Those who had better mood clarity and emotional repair experienced less negative emotion and
more positive emotion, resulting in greater life satisfaction.

Causal Relationships:
8. The study's longitudinal design allowed researchers to suggest that emotional intelligence plays
a causal role in affecting positive and negative emotions, which, in turn, influence life
satisfaction.

Practical Implications:
9. Understanding and improving emotional intelligence in adolescents could lead to better
well-being and life satisfaction.
10. The study highlights the importance of emotional regulation and clarity of emotions in
promoting positive affect and life satisfaction.
STUDY 13
Cazan, Ana-Maria & Truța, Camelia. (2015). Stress, Resilience and Life Satisfaction in College
Students. Revista de Cercetare si Interventie Sociala. 48. 95-108.
SAMPLE DETAILS:

Total Sample Size: 341 Romanian students from several faculties participated in the study.

Gender Distribution:
1. Female Students: 260 (76.2% of the total sample).
2. Male Students: 81 (23.8% of the total sample).

Mean Age: The average age of the participants was 20.65 years.
NOTE: The sample was drawn using a convenience sampling procedure.
TEST USED

Adolescent Resilience Scale:
Description: Measures an adolescent's ability to cope with and adapt to challenges and
adversities. It consists of 21 items that assess three factors: Novelty Seeking (interest in various events),
Emotional Regulation (composure and control of emotions), and Positive Future Orientation (approach
to future goals).
Reliability Coefficients:
1. Novelty Seeking: .76
2. Emotional Regulation: .70
3. Positive Future Orientation: .82
4. Entire Scale: .81

Student-life Stress Inventory (SSI):
Description: Assesses academic stressors and reactions to stressors in students. It includes 51 items and
measures five stressor categories: frustrations, conflicts, pressures, changes, and self-imposed stressors.
Reactions to stressors are categorized into physiological, emotional, behavioral, and cognitive reactions.
Reliability Coefficients:
Academic Stressors: Ranging from .70 to .84

Satisfaction with Life Scale (SWLS):
Description: Measures subjective well-being and overall life satisfaction. It consists of five items rated on
a seven-point Likert scale, where higher scores indicate greater life satisfaction.
Reliability Coefficient: .82
(These tests were adapted and translated for the Romanian population, and previous studies have
reported good psychometric properties for them in this context).
RESULTS:

Adolescent Resilience Scale:
1. The Romanian version of the Adolescent Resilience Scale showed good psychometric properties
with high internal consistency (α = .81) across all three subscales: Novelty Seeking, Emotional
Regulation, and Positive Future Orientation.
2. A second order model with correlated errors provided the best fit for the scale.

Resilience, Stress, and Life Satisfaction:
3. Resilience was moderately and significantly correlated with academic stress dimensions and life
satisfaction.
4. Stressors mediated the relationship between resilience and life satisfaction.
5. The full mediation model, in which stressors fully mediate the relationship between resilience
and life satisfaction, provided the best fit to the data.

Specific Effects of Resilience Dimensions:
6. Novelty Seeking had a positive direct effect on life satisfaction.
7. Emotional Regulation had a negative direct effect on perceived stressors and a positive indirect
effect on life satisfaction while negatively impacting reactions to stress.
8. Positive Future Orientation had a positive direct effect on life satisfaction.

Stressors and Reactions to Stress:
9. Stressors had a negative indirect effect on life satisfaction and a positive direct effect on
reactions to stress.
DISSCUSION SIMPLIFIED:

Validity and Reliability of the Adolescent Resilience Scale:
1. The study demonstrated that the Adolescent Resilience Scale is a valid and reliable measure for
assessing resilience in Romanian college students.
2. It proved to be an efficient tool, especially considering that there are few similar scales available
in recent research in Romania.

Need for Further Research:
3. Further research is needed to investigate if the scale's measurement parameters are consistent
across different groups, such as gender, age, and cultural origin.
4. Studies with diverse subjects are essential to better understand the factor structure of the scale
and its implications.

Mediating Role of Stressors:
5. The study found that stressors mediate the relationship between resilience, reactions to stress,
and life satisfaction.
6. Emotion regulation had the most significant mediated effects on reactions to stress, suggesting
that stressors activate emotional resources for successful adjustment.
7. Positive future orientation had the most significant mediated effects on life satisfaction,
indicating that stressors can shape individuals' subjective perception of their own lives.

Importance of Resilience:
8. Resilience as a personality trait is crucial for understanding how adolescents and college
students react to stress in the academic context.
9. Highly resilient students perceive stressors as less demanding and cope better with them,
leading to more efficient adaptation to academic requirements.
10. Highly resilient students possess emotional regulation skills and utilize internal and external
resources effectively, contributing to higher life satisfaction.
STUDY 14
Azpiazu Izaguirre L, Fernández AR and Palacios EG (2021) Adolescent Life Satisfaction
Explained by Social Support, Emotion Regulation, and Resilience. Front. Psychol. 12:694183.
SAMPLE DETAILS:

Total Sample Size: 1,188 secondary school students participated in the study.

Gender Distribution:
1. Female Students: 546 (46% of the total sample)
2. Male Students: 642 (54% of the total sample)

Age Range: Participants' ages ranged from 12 to 16 years.

Mean Age: The average age of the participants was 14.24 years.

Standard Deviation: The standard deviation of ages was 1.0, indicating the spread of ages
around the mean.

Sampling Method: The incidental sampling method was used to select the participants. This
method involves selecting participants based on their availability and convenience rather than
using a random or systematic approach.

School Type:
3. 690 participants (58.1% of the total sample) attended public schools.
4. 498 participants (41.9% of the total sample) attended semi-private schools that receive some
state funding.

Academic Level:
5. 670 participants (56.4% of the total sample) were in the first 2 years of compulsory secondary
education.
6. 518 participants (43.6% of the total sample) were in the second 2 years of compulsory secondary
education.
Overall, the study included a diverse sample of secondary school students from different schools and
academic levels, providing valuable insights into the chosen research context in the Autonomous
Community of the Basque Country, Spain.
TEST USED:

Perceived Social Support from Family and Friends Questionnaire (AFA):
1. Purpose: Measures perceived social support from family and friends.
2. Dimensions: Family Support (8 items) and Support from Friends (7 items).
3. Response Scale: Five-point Likert-type scale ranging from 1 (never) to 5 (always).

Perception of the School Environment Questionnaire (Teacher Support Subscale):
4. Purpose: Measures perceived support from teachers in the school environment.
5. Items: Eight items assessing teacher kindness and friendliness.
6. Response Scale: Five-point Likert-type scale ranging from 1 (totally agree) to 5 (totally disagree).

Trait Meta Mood Scale-24 (TMMS-24):
7. Purpose: Measures emotion regulation abilities.
8. Items: Eight items assessing emotional traits, such as optimism.
9. Response Scale: Five-point Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly
agree).

Connor-Davidson Resilience Scale-10 (CD-RISC):
10. Purpose: Measures resilience, the ability to adapt to change.
11. Items: Ten items assessing self-reported resilience.
12. Response Scale: Likert-type scale ranging from 0 (not true at all) to 4 (true nearly all the time).

Satisfaction with Life Scale (SWLS):
13. Purpose: Measures life satisfaction.
14. Items: Five items assessing overall satisfaction with life.
15. Response Scale: Seven-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly
agree).
RESULTS:

Measurement Model: The researchers tested the measurement model, which assesses the
relationships between the variables in the study. The fit of the measurement model was found to
be satisfactory.

Final Model: After making some modifications to the initial model based on the results of
significance tests and modification indexes, the final model showed a good fit to the data. Family
support, emotion regulation, and resilience together explained 43.4% of the variance in life
satisfaction

Direct Effects: Among the types of support, only family support had a direct positive effect on
life satisfaction. The effect of support from friends and support from teachers on life satisfaction
was relatively weak.

Strongest Association: The strongest association was found between emotion regulation and
resilience, with resilience being associated with all the variables studied.

Emotional Regulation and Life Satisfaction: Emotion regulation had a stronger indirect effect on
life satisfaction through resilience compared to its direct effect.

Predictors of Life Satisfaction: Family support and resilience were strong predictors of life
satisfaction.

Variance Explained: The three types of support together explained 9% of the variance in
emotion regulation, and along with emotion regulation, they explained 30% of the variance in
resilience.
DISSCUSION SIMPLIFIED:

Shift in Focus: The study shifted its focus from identifying and addressing adolescent deficits to
exploring the psychological strengths that promote positive development in adolescence.

Aim of the Study: The aim of the study was to test a theoretical model of life satisfaction and
examine the psychological assets that contribute to well-being during adolescence.

Importance of Social Support: Social support, particularly from family, friends, and teachers,
plays a significant role in shaping adolescents' emotion regulation and resilience.

Impact of Family Support: Family support had the strongest prediction on emotion regulation
and also influenced resilience. Family support was found to be crucial for adolescents in
managing their emotions.

Role of Peer Support: Support from friends had a weak but significant prediction on resilience,
indicating that peers can also play a role in supporting adolescents during challenging times.

Emotion Regulation and Life Satisfaction: Emotion regulation directly predicts life satisfaction,
and it also indirectly influences life satisfaction through resilience. Good emotion regulation,
combined with resilience, leads to higher life satisfaction.

Explanation of Life Satisfaction: The study revealed that both emotion regulation and resilience
partially explain the association between social support and life satisfaction. These psychological
assets enhance the positive effect of support on life satisfaction.

Importance of Family Support: The study highlighted the key role of family support during
adolescence, with its influence being greater than that of support from friends and teachers.

Practical Implications: The findings suggest the need to create positive family environments and
focus on fostering resilience and emotional intelligence in educational settings to promote life
satisfaction among adolescents.

Limitations: The study acknowledges limitations, such as the use of self-report measures and the
cross-sectional nature of the research, which should be considered when interpreting the
results.
STUDY 15
Sun, R. C. F., & Shek, D. T. L. (2009). Life Satisfaction, Positive Youth Development, and
Problem Behaviour Among Chinese Adolescents in Hong Kong. Social Indicators Research,
95(3), 455–474.
SAMPLE DETAILS:

The study focused on the "Positive Adolescent Training through Holistic Social Programmes"
(P.A.T.H.S.), a positive youth development program in Hong Kong.

In the first year of the Full Implementation Phase (the 2006–2007 school year), the study
included a total of 48 schools: 24 were experimental schools, and 24 were control schools.

The sample consisted of junior secondary-school students in Hong Kong.

Prior to program implementation, all Secondary One students from the 48 schools were invited
to participate in the study.

The initial sample size for data collection (Wave 1) was 7,975 students.

Out of the total students, 4,121 were from experimental schools, and 3,854 were from control
schools.

Among the participants, 4,169 (52.3%) were boys, 3,387 (42.5%) were girls, and the remaining
5.2% did not report their gender.

The majority of students reported their age as 12 (60.5%), followed by 13 (14.9%) and 11
(12.5%).

Data were collected by trained research staff and/or school teachers with appropriate consent
from parents and schools.

Student consent was also obtained, and the confidentiality of the data collected was ensured.

All participants completed the questionnaires in a self-administration format, and no students
refused to participate in the study.
TEST USED:

Positive Youth Development Scale: The modified Chinese Positive Youth Development Scale
(Shek et al. 2008) was used to assess positive youth development. It consists of 15 subscales
measuring different aspects of positive development, such as bonding, social competence,
emotional competence, cognitive competence, behavioral competence, moral competence,
self-efficacy, prosocial norms, resilience, self-determination, spirituality, clear and positive
identity, beliefs in the future, prosocial involvement, and recognition of positive behavior.

Life Satisfaction Scale: The Life Satisfaction Scale (Diener et al. 1985) was used to assess
participants' overall life satisfaction. It consists of five items measured on a 6-point rating scale,
where respondents provide their global judgment of their quality of life.

Problem Behavior Scales: Problem behavior was measured using three subscales.
1. Substance Abuse Scale: It includes eight items measuring the frequency of alcohol, tobacco,
ketamine, cannabis, cough mixture, organic solvent, pills, and narcotics use, rated on a
seven-point scale.
2. Delinquency Scale: It includes 12 items measuring the frequency of engaging in antisocial
behaviors, such as stealing, cheating, truancy, running away from home, damaging property,
assault, having sexual relationships with others, gang fighting, speaking foul language, staying
away from home without parental consent, strong-arming others, and breaking into residences,
rated on a seven-point scale.
3. Intention to Engage in Problem Behavior Scale: It includes five items measuring the intention to
engage in problem behaviors, such as consuming alcohol, smoking, consuming illicit drugs,
engaging in sexual behavior, and gambling, rated on a four-point scale.
RESULTS:

Reliability: All scales and subscales, except the self-efficacy subscale, were found to be highly
reliable, with alpha coefficients above .75.

Prevalence of Problem Behavior: The prevalence of problem behavior among Chinese early
adolescents was relatively low. More than 90% of the respondents reported that they had never
smoked or abused drugs (other than alcohol) in the previous 6 months. While about half of the
respondents reported that they had engaged in behaviors like cheating or using foul language,
the majority had not been involved in more serious delinquent behaviors, such as sexual
relationships. However, some respondents expressed intentions to engage in problem behaviors
like drinking alcohol (20.8%), gambling (6.3%), smoking (4.4%), having sex (3.1%), and using illicit
drugs (1.4%) in the subsequent 2 years.

Correlations: Pearson correlation analyses showed that all variables were correlated in the
expected directions. Life satisfaction was positively correlated with measures of positive youth
development, while being negatively correlated with substance abuse, delinquency, intention to
engage in problem behavior, and overall problem behavior.

Normal Distribution: Most variables were normally distributed, except for drug and delinquency
variables in problem behavior, which showed positive skewness and kurtosis.

Measurement Models: The measurement models for positive youth development and problem
behavior showed good fit to the data. However, the initial five-indicator life satisfaction model
did not fit well. After removing one item (item 5) that had lower loading and measured a
hypothetical situation different from other items, the four-indicator life satisfaction model
showed good fit, indicating that it better represented life satisfaction in similar contexts.
DISSCUSION SIMPLIFIED:

The present study aimed to investigate the relationships between positive youth development,
life satisfaction, and problem behavior among Chinese early adolescents. Several unique
features of the study were highlighted, including its focus on Chinese adolescents, a large
sample size, and the use of validated assessment tools.

The study confirmed that positive youth development consists of fifteen inter-related
constructs, such as bonding, social competence, emotional competence, resilience, and beliefs
in the future. Beliefs in the future and spirituality had the strongest influence on positive youth
development. The study also revealed that a modified version of the Life Satisfaction Scale,
excluding one item, resulted in a better measurement of life satisfaction.

Regarding problem behavior, three indicators were identified: substance abuse, delinquency,
and intention to engage in problem behavior. Delinquency had the strongest loading. Life
satisfaction and positive youth development were found to be positively correlated, while both
were negatively associated with problem behavior.

The most important finding was the proposed predictive model (Model 6), which indicated that
positive youth development directly predicts life satisfaction and problem behavior.
Additionally, there is a bidirectional relationship between life satisfaction and problem behavior.
Adolescents with poorer positive development tend to have lower life satisfaction and engage in
more problem behavior. Conversely, lower life satisfaction can lead to increased problem
behavior, creating a cycle.

While the study did not fully support certain mediating or bidirectional models, the
non-recursive model, showing a direct influence of positive youth development on life
satisfaction and problem behavior, was deemed the most meaningful and supported by the
data.

The study's limitations include the need for replication in different contexts, caution in drawing
causal inferences from the cross-sectional design, the potential inclusion of other variables in
the model, and the consideration of social desirability and self-serving biases due to
self-reporting.
Overall, the study provides valuable insights into the importance of positive youth development in
promoting life satisfaction and mitigating problem behavior among Chinese early adolescents. The
findings highlight the need to focus on fostering positive youth development as a means to enhance
adolescents' well-being and reduce risk-taking behaviors.
STUDY 16
Tu, Y., & Zhang, S. (2014). Loneliness and Subjective Well-Being Among Chinese
Undergraduates: The Mediating Role of Self-Efficacy. Social Indicators Research, 124(3),
963–980.
SAMPLE AND PROCEDURE DETAILS:

The survey was conducted in a business school at a high-prestige university in central China.

The participants were all sophomores in the business school.

Questionnaires were distributed to all the sophomores with the help of research assistants.

Participants were informed that the investigation was voluntary to reduce concerns.

Each participant received a small unsealed envelope containing the questionnaire and a cover
letter explaining the purpose and anonymity of the survey.

Participants were asked to evaluate their loneliness, self-efficacy, depression, stress, and life
satisfaction.

After the distribution and return process, 486 questionnaires were returned, resulting in a
response rate of 81%.

Out of the returned questionnaires, 444 were considered valid, leading to a valid response rate
of 91.36%.

The male participants constituted 38.4% of the student sample.

The average age of the respondents was 19.02 years, with a standard deviation of 1.26.
TEST USED:

Loneliness: Revised version of the UCLA Loneliness Scale (R-UCLA) - 20-item scale measuring
feelings of loneliness. Reliability: .884.

Self-efficacy: General Self-Efficacy Scale - 10-item scale assessing one's belief in their ability to
handle different situations. Reliability: .946.

Stress: Perceived Stress Scale - 14-item scale measuring the degree to which situations in a
person's life are appraised as uncontrollable and overloaded. Reliability: .711.

Depression: Seven-item version of the Center for Epidemiological Studies Depression Scale
(CES-Dm) - Assessing the frequency of unpleasant symptoms of depressed mood and
physiological malaise. Reliability: .953.

Life Satisfaction: Satisfaction with Life Scale - Five-item scale evaluating cognitive-judgmental
aspects of general life satisfaction. Reliability: .857.
RESULTS:

Common Method Bias (CMB) was assessed using Harman's single-factor test, and the results
showed that CMB was not significant enough to influence the relationship between variables.

The study examined the relationships between loneliness, self-efficacy, stress, depression, and
life satisfaction.

The correlations between the variables were consistent with the hypotheses: loneliness was
positively related to stress and depression, and negatively related to self-efficacy and life
satisfaction.

Hypothesis 1 was supported: loneliness positively influenced students' stress.

Hypothesis 2 was supported: loneliness positively influenced depression.

Hypothesis 3 was supported: loneliness negatively influenced life satisfaction.

Hypothesis 4a, 4b, and 4c were supported: self-efficacy partially mediated the relationship
between loneliness and stress, depression, and fully mediated the relationship between
loneliness and life satisfaction.

The Sobel test and MCMAM confirmed the significant indirect effects in the mediation models,
supporting the role of self-efficacy in mediating the relationships.
In summary, the study found that loneliness has significant associations with stress, depression, and
life satisfaction, and these relationships are partially mediated by self-efficacy. The results highlight
the importance of self-efficacy in understanding how loneliness impacts mental well-being and life
satisfaction in students.
DISSCUSION SIMPLIFIED:

The study aimed to understand how loneliness impacts subjective well-being in the Chinese
context, considering the cultural influences of Confucianism and collectivism.

The results showed that loneliness has significant effects on individual stress and depression,
leading to increased feelings of stress and depression.

On the other hand, loneliness was found to be negatively related to individual life satisfaction,
meaning that feeling lonely is associated with lower levels of life satisfaction.

The study also explored the psychological mechanism between loneliness and subjective
well-being. It found that self-efficacy, which refers to one's belief in their ability to handle
challenges, plays a crucial role in mediating the relationship between loneliness and stress,
depression, and life satisfaction.

Specifically, self-efficacy partially mediates the impact of loneliness on stress and depression,
and it fully mediates the impact of loneliness on life satisfaction. This means that self-efficacy
acts as a key factor that explains how loneliness affects individual well-being.
In conclusion, this study extends our understanding of how loneliness influences subjective well-being
in the Chinese cultural context, and it sheds light on the cognitive processes involved in this
relationship. By identifying the role of self-efficacy, the study provides valuable insights into how to
support Chinese students in managing loneliness and enhancing their well-being.
STUDY 17
Jovanović, V. (2016). The validity of the Satisfaction with Life Scale in adolescents and a
comparison with single-item life satisfaction measures: a preliminary study. Quality of Life
Research, 25(12), 3173–3180.
SAMPLE AND PROCEDURE DETAILS:
FOR STUDY 1

The sample consisted of 481 high school students.

54.9% of the participants were female.

The mean age of the participants was 17.01 years.

The standard deviation (SD) of the participants' age was 0.72.

The age range of the participants was from 16 to 18 years.

The participants were recruited from four mixed-sex public schools in Serbia.

The schools were selected based on accessibility and convenience for the researcher.

The measures were administered in a standard paper-and-pencil format in a group setting
during class time at their schools.

Participation in the study was anonymous and voluntary.

Participants did not receive any compensation for their participation.
FOR STUDY 2:

Sample size: 283 high school students

Gender distribution: 64% females, 36% males

Number of schools: 4 mixed-sex public schools in Serbia

Mean age: 17.34 years

Standard deviation (SD) of age: 0.49 years

Age range: 16 to 18 years
FOR STUDY 3:

Total sample size: 220 high school students

Gender distribution: 79.5% females, 20.5% males

Number of schools: 2 mixed-sex public schools in Serbia

Mean age: 16.73 years

Standard deviation (SD) of age: 0.72 years

Age range: 16 to 18 years
TEST USED:
FOR STUDY 1:
Satisfaction with Life Scale (SWLS): A 5-item measure of global life satisfaction.
1. Example item: "If I could live my life over, I would change almost nothing."
2. Response scale: 7-point scale, ranging from 1 (strongly disagree) to 7 (strongly agree).
3. Internal consistency reliability (Cronbach's alpha): .82.
Note: The SWLS is a well-established measure of life satisfaction and has been previously validated in
a Serbian version with favorable psychometric properties. In the present study, it demonstrated
adequate internal consistency reliability.
FOR STUDY 2:

Satisfaction with Life Scale (SWLS): A 5-item scale measuring global life satisfaction. Responses
are rated on a 7-point scale from 1 (strongly disagree) to 7 (strongly agree). Internal consistency
reliability (Cronbach's alpha) was .82.

Single-item measure of life satisfaction: Participants were asked to rate their overall life
satisfaction on a 10-point scale from 1 (not at all satisfied) to 10 (completely satisfied).

Depression Anxiety and Stress Scale (DASS-21): A 21-item scale measuring depression, anxiety,
and stress. Each subscale consists of 7 items, and respondents rate their feelings over the past
week on a 4-point scale from 0 (did not apply to me at all) to 3 (applied to me very much, or
most of the time). Internal consistency reliabilities were .80 for Depression, .75 for Anxiety, and
.78 for Stress subscale.

Positive and Negative Affect Schedule (PANAS): A 20-item scale measuring positive affect (PA)
and negative affect (NA). PA includes 10 items (e.g., interested, excited), and NA includes 10
items (e.g., distressed, upset). Participants rate their feelings over the last month on a 5-point
scale from 1 (very slightly or not at all) to 5 (extremely). Internal consistency reliabilities were
.83 for PA subscale and .82 for NA subscale.
FOR STUDY 3:

Satisfaction with Life Scale (SWLS): A 5-item scale measuring global life satisfaction. Internal
consistency reliability (Cronbach's alpha) was .81.

Positive and Negative Affect Schedule (PANAS): A 20-item scale measuring positive affect (PA)
and negative affect (NA). Internal consistency reliabilities were .78 for PA subscale and .79 for
NA subscale.

Depression Anxiety and Stress Scale (DASS-21): A 21-item scale measuring depression, anxiety,
and stress. Internal consistency reliabilities were .84 for Depression, .81 for Anxiety, and .82 for
Stress subscale.

Single-item measure of life satisfaction: Participants were asked to rate their overall life
satisfaction on an 11-point scale from 0 (not at all satisfied) to 10 (completely satisfied).

Mental Health Continuum-Short Form (MHC-SF): A 14-item measure assessing general
well-being, including emotional, social, and psychological components. Participants rated how
often they felt a certain way during the past month on a 6-point scale. Internal consistency
reliability (Cronbach's alpha) for the overall score was .88.

School success: Participants reported their grade point average (GPA) at the end of the prior
semester on a five-point grading scale, ranging from 1 (the lowest possible grade) to 5 (the
highest possible grade).
RESULTS:
Study 1:

The original one-factor model of the Satisfaction with Life Scale (SWLS) showed a good fit,
except for RMSEA, which was still considered acceptable.

There was no evidence of correlated residuals between certain items of the SWLS, so no
modification was made.

Measurement invariance of the SWLS across gender was supported, allowing for a comparison
of latent means between boys and girls.

No significant gender differences were found in life satisfaction based on the SWLS scores.
Study 2:

Girls reported higher life satisfaction than boys, both on the SWLS and a single-item measure of
life satisfaction.

The SWLS and single-item measure of life satisfaction showed a strong correlation, indicating
good convergent validity.

Both scales had moderate negative correlations with measures of depression, anxiety, stress,
and negative affect, and moderate positive correlations with positive affect.

No significant differences were observed between the two measures of life satisfaction in
relation to convergent measures.
Study 3:

There were no significant gender differences in life satisfaction based on the SWLS and
single-item measure.

The SWLS and single-item measure of life satisfaction showed a strong correlation, indicating
good convergent validity.

Both scales had moderate negative correlations with depression and negative affect, low
negative correlations with anxiety, and moderate positive correlations with positive affect.

The SWLS had a low negative correlation with stress, while the single-item measure had a
moderate negative correlation with stress. They differed significantly only in their associations
with stress, but not with other convergent measures.
DISSCUSION SIMPLIFIED:

The present research had two main objectives: (1) to assess the validity and reliability of the
Satisfaction with Life Scale (SWLS) among adolescents, specifically examining whether the scale
is consistent across genders, and (2) to investigate the relationship between the SWLS and
single-item life satisfaction measures with various indicators of mental health and well-being in
adolescents.

The results of the study supported the original one-factor model of the SWLS, indicating that the
scale is valid and reliable for assessing life satisfaction in adolescents. The scale performed
equally well for both boys and girls, suggesting that it is culturally unbiased and provides
meaningful comparisons between genders.

Regarding gender differences in life satisfaction, the study found that in most cases, there were
no significant differences between boys and girls in their reported life satisfaction. However, in
one of the studies (Study 2), girls reported higher life satisfaction than boys on both the SWLS
and the single-item measure. This aligns with some previous studies but contradicts others,
indicating that gender differences in adolescent life satisfaction are not well understood and
may vary based on cultural and other factors.

Furthermore, the study compared the SWLS with single-item life satisfaction measures and
found that both approaches demonstrated similar results. The correlations between the SWLS
and single-item measures were strong, suggesting that single-item scales are also valid for
assessing life satisfaction in adolescents. Both the SWLS and single-item measures showed good
convergent validity, meaning they correlated well with other indicators of mental health and
well-being.

However, it's essential to acknowledge some limitations of the study. The samples were limited
to late adolescents from Serbia, which may limit the generalizability of the findings. Future
research should consider including diverse adolescent populations and cross-cultural validation
of life satisfaction measures. Additionally, the study was cross-sectional, and longitudinal
research could further assess the stability and consistency of life satisfaction measures over
time.
In conclusion, the findings suggest that both the SWLS and single-item life satisfaction measures are
valid and reliable tools for assessing adolescent well-being. Researchers can confidently use
single-item measures, as they provide results consistent with the SWLS, making them a practical and
effective choice in adolescent research on life satisfaction.
STUDY 18
Suldo, S. M., & Huebner, E. S. (2004). The role of life satisfaction in the relationship between
authoritative parenting dimensions and adolescent problem behavior. Social Indicators Research,
66(1-2), 165-195.
SAMPLE DETAILS:

Total number of students enrolled in grades 6 to 12: 4,140

Number of students with parental consent (participating students): 1,258

Number of students included in the final sample after excluding outliers: 1,188

Subsample of early adolescents (ages 11 and 12): 314 students (26% of the final sample)

Subsample of middle adolescents (ages 13 to 15): 510 students (43% of the final sample)

Subsample of late adolescents (ages 16 to 19): 364 students (31% of the final sample)
Demographics of the final sample:

African American: 58%

Caucasian: 34%

Hispanic: 2%

Asian: 2%

Native American: 1%

Mixed-race: 3%

Female: 64%

Living with both biological parents: 49%

Living with mother only: 24%

Living with mother and stepfather: 15%

Living with father and stepmother: 3%

Living with father only: 3%

Living with other adults (e.g., extended family member): 6%

Qualifying for school lunch at free or reduced rate (low SES): 58%

Qualifying for paid lunches (average and above-average SES): 42%
TEST USED:

Students' Life Satisfaction Scale (SLSS):
1. 7 items assessing global life satisfaction
2. 6-point response format (1 = "strongly disagree" to 6 = "strongly agree")
3. Items 3 and 4 are reverse scored
4. Scores averaged to yield a mean life satisfaction score between 1 and 6
5. Coefficient alpha for current study: 0.83
6. Test-retest stability coefficients for early adolescents: 0.74 (two-week) and 0.64 (four-week)
7. Test-retest stability coefficient for late adolescents: 0.53
8. Strong evidence for construct validity, with convergent and discriminant validity supported in
previous research

Family Support Scale (FSS):
9. 11 items assessing perceived availability of emotional and instrumental parental support
10. 5-point response format (1 = "not at all true" to 5 = "very true")
11. Emotional and instrumental subscales highly correlated (r = 0.78), merged into a total parent
social support variable
12. High scores indicate high parental support
13. Coefficient alpha for Emotional Support subscale: 0.81
14. Coefficient alpha for Instrumental Support subscale: 0.74
15. Validity supported by expected relationships with adolescent outcome variables

Psychological Autonomy Granting (PAG) subscale of the Authoritative Parenting Measure:
16. 9 items assessing noncoercive, democratic discipline and encouragement of adolescent
individuality
17. 4-point response format (1 = "strongly disagree" to 4 = "strongly agree")
18. Reverse scoring for most items, with higher scores indicating increased parental psychological
autonomy granting
19. Validity supported by relationships with theoretically expected adolescent outcome variables

Strictness/Supervision subscale of the Authoritative Parenting Measure:
20. 8 items assessing parental supervision and strictness via imposed curfews
21. Responses indicate latest time allowed out on school nights and weekends
22. Some items are reverse scored, with higher total scores indicating high levels of parental
supervision
23. Validity supported by relationships with adolescent outcome variables, such as substance abuse
and academic performance

Youth Self Report (YSR) form of the Child Behavior Checklist:
24. 118 items assessing problem behavior in eight areas, with focus on internalizing and
externalizing behavior domains
25. 3-point response format (0 = "not true," 1 = "somewhat or sometimes true," 2 = "very true or
often true")
26. Summed scores for internalizing and externalizing domains, with higher scores indicating higher
problem behavior
27. Validity supported by relationships with other measures and significant correlations with
teacher and parent reports.
RESULTS:

Descriptive Analysis:
1. Means and standard deviations for the entire adolescent sample and each age group (early,
middle, late) on various measures, including life satisfaction, parental social support,
psychological autonomy granting, strictness-supervision, and adolescent externalizing and
internalizing behavior.
2. Skewness and kurtosis values for all measures were within acceptable limits (-1.0 to +1.0).

Correlational Analysis:
3. Pearson correlations between all continuous variables for the entire sample and each age group.
4. Significant positive relationships between authoritative parenting dimensions and adolescent
life satisfaction.
5. Significant negative relationships between life satisfaction and both internalizing and
externalizing behavior.
6. Negative relationships between authoritative parenting dimensions and adolescent
externalizing behavior, as well as between parental social support and psychological autonomy
granting and adolescent internalizing behavior.
7. Strong relationship between internalizing and externalizing behavior.

Multiple Regression:
8. Simultaneous multiple regression analysis to determine the total variance explained in life
satisfaction by authoritative parenting dimensions.
9. Authoritative parenting dimensions (social support, psychological autonomy granting,
strictness-supervision) accounted for 26% of the variance in life satisfaction.
10. Social support demonstrated the largest unique contribution to life satisfaction (17% of
variance), followed by psychological autonomy granting and strictness-supervision (1% each).

Adolescent Age as a Moderator:
11. Interaction analysis to evaluate age as a moderator in the relationship between parenting and
life satisfaction.
12. Age was a significant moderator for the relationship between parental social support and life
satisfaction.
13. The influence of parental social support on life satisfaction decreases as adolescents age.

Mediator Model:
14. Path model testing life satisfaction as a mediator between authoritative parenting dimensions
and adolescent problem behavior.
15. Initial model fit indices were substandard, but a revised model that included direct paths from
strictness-supervision to externalizing behavior and from psychological autonomy granting to
internalizing behavior provided an adequate fit to the data.
16. Life satisfaction appears to fully mediate the relationship between parental social support and
problem behavior and partially mediate the influence of strictness-supervision and psychological
autonomy granting on problem behavior.
DISSCUSION SIMPLIFIED:

The study found that there is a strong relationship between the way parents parent and
adolescents' life satisfaction (LS). Specifically, three crucial aspects of authoritative parenting
(strictness-supervision, social support/acceptance-involvement, and psychological autonomy
granting) were significantly related to adolescents' life satisfaction, regardless of their age (early,
middle, or late adolescence).

However, the study also revealed that not all aspects of authoritative parenting were equally
important in predicting life satisfaction. Among them, social support from parents appeared to
be the most critical factor in determining adolescents' life satisfaction. In other words, when
parents provide emotional and instrumental support to their children, it has a significant impact
on their overall life satisfaction.

The study also found that the influence of parenting behaviors on adolescents' life satisfaction
changes as they grow older. As children age, factors outside of parental influence may start to
play a more significant role in their evaluation of life satisfaction. Additionally, the importance of
social support from parents in relation to life satisfaction decreases as adolescents get older.

Furthermore, the study highlighted the role of life satisfaction as a mediator between
authoritative parenting and adolescent problem behavior. Life satisfaction acts as a cognitive
mechanism through which parenting influences adolescents' behavior. It was found that life
satisfaction partially mediates the relationship between parenting behaviors and adolescent
problem behaviors.
STUDY 19:
Usán Supervía, P., Salavera Bordás, C., & Murillo Lorente, V. (2020). Exploring the
Psychological Effects of Optimism on Life Satisfaction in Students: The Mediating Role of Goal
Orientations. International Journal of Environmental Research and Public Health, 17(21),
7887.
SAMPLE DETAILS:

Total Participants: The study included a total of 1602 students from 9 public secondary schools.

Gender Distribution: The participants consisted of both male (N = 871; 54.36%) and female (N =
731; 45.63%) students.

Age Range: The age of the participants ranged from 12 to 17 years.

Mean Age: The average age of the participants was 14.11 years.

Age Standard Deviation: The standard deviation of the participants' ages was 1.47 years.

Sampling Method: The participants were selected using a simple random sampling method.

Inclusion Criteria: The inclusion criteria for the study were the ability to read and communicate
in perfect Spanish. This was to ensure that the participants could understand and respond to the
questionnaire accurately.

Exclusion Criteria: Participants with incomplete questionnaires were discarded from the study.
Additionally, students with cognitive disorders who could not fully understand the questionnaire
were also excluded from the study.
TEST USED:

Life Orientation Test Revised (LOT-R):
1. Purpose: Measured the level of optimism among participants.
2. Description: Consisted of six items, three positive and three negative statements.
3. Response Scale: 5-point Likert scale, ranging from "Strongly disagree" (1) to "Strongly agree" (5).
4. Internal Consistency (Cronbach's α): 0.78 in this study.

Perception of Success Questionnaire (POSQ):
5. Purpose: Measured the goal orientations of the participants.
6. Description: Comprised 12 items reflecting task orientation (6 items) and ego orientation (6
items).
7. Response Scale: 5-point Likert scale, ranging from "Strongly disagree" (1) to "Strongly agree" (5).
8. Internal Consistency (Cronbach's α): Task subscale = 0.85, Ego subscale = 0.84 in this study.

Satisfaction with Life Scale (SWLS):
9. Purpose: Measured the life satisfaction of the participants.
10. Description: Included 5 items assessing the degree of life satisfaction.
11. Response Scale: 5-point Likert scale, ranging from "Strongly disagree" (1) to "Strongly agree" (5).
12. Internal Consistency (Cronbach's α): 0.86 in this study.
RESULTS:

Descriptive Variables:
1. Males scored higher in optimism, ego orientation, and life satisfaction.
2. Females scored higher in task orientation.

Correlational Analysis:
3. All variables (optimism, task orientation, ego orientation, and life satisfaction) are
positively correlated.
4. Optimism is strongly correlated with life satisfaction (r = 0.523).
5. Optimism is somewhat more strongly correlated with task orientation (r = 0.304).

Mediation Effects of Goal Orientation:
6. Task orientation mediates the relationship between optimism and life satisfaction.
7. Optimism has a significant effect on task orientation (VI = 0.23), and task orientation has
a significant effect on life satisfaction (VD = 0.19).
8. Ego orientation does not mediate the relationship between optimism and life
satisfaction.
9. The direct effect of optimism on life satisfaction is positive (0.50, p < 0.001).
10. The total effect (direct effect + indirect effect) of optimism on life satisfaction is also
positive (0.55, p < 0.001).
11. The model explains a significant proportion of variance in life satisfaction (R2 = 0.52).
In summary, the study found that optimism has a direct positive effect on life satisfaction in
adolescents. Additionally, task orientation partially mediates the relationship between
optimism and life satisfaction, meaning that the influence of optimism on life satisfaction is
partly explained by task orientation. However, ego orientation does not play a mediating role
in this relationship. The overall model suggests that optimism and task orientation together
account for a substantial portion of the variance in life satisfaction among adolescents.
DISSCUSION SIMPLIFIED:

Relationship between Optimism and Life Satisfaction:
1. The study confirmed that there is a positive relationship between optimism and life
satisfaction in adolescents.
2. Optimistic students tend to have higher scores in variables reflecting life satisfaction.

Mediating Role of Task and Ego Orientations:
3. The study explored whether task and ego orientations play a mediating role in the
relationship between optimism and life satisfaction.
4. It was found that task orientation plays a positive mediating role, meaning that the
positive effect of optimism on life satisfaction is partly explained by task orientation.
5. On the other hand, ego orientation did not play a mediating role in this relationship.
Previous Studies:
1. Previous research also supports the idea that optimism and life satisfaction are related
to various positive outcomes, such as social adaptability, resilience, happiness, and
academic performance.
2. Some studies have shown that task orientation is associated with positive variables,
such as persistence, academic engagement, and overall well-being.
In conclusion, the study provides evidence that optimism is linked to greater life satisfaction
in adolescents. Task orientation partially explains this relationship, suggesting that optimistic
individuals with a task-oriented mindset tend to experience higher life satisfaction. However,
ego orientation was not found to have an impact on the relationship between optimism and
life satisfaction in this study. These findings contribute to our understanding of the factors
influencing adolescents' well-being and highlight the importance of fostering a positive and
task-oriented mindset to promote life satisfaction in this age group.
STUDY 20
Liu, W. J., Zhou, L., Wang, X. Q., Yang, B. X., Wang, Y., & Jiang, J. F. (2019). Mediating role of
resilience in relationship between negative life events and depression among Chinese
adolescents. Archives of Psychiatric Nursing.
SAMPLE DETAILS:

Study Design: Cross-sectional study.

Sample Size: Initially, a convenient sample of 301 junior and senior high school students from
different districts of Wuhan was recruited.

Eligibility Criteria: Adolescents aged 12–18 years old who were able to cooperate in completing
the data collection were eligible to participate.

Informed Consent: Informed consent was obtained from eligible participants and their
guardians.

Response Rate: Out of the 301 students initially recruited, only 278 students completed all the
questionnaires and were included in the analysis.

Response Rate Calculation: The response rate for the study was 92.36% (278/301). This means
that 92.36% of the initially recruited participants provided complete data for analysis.
TEST USED:

Psychological Impact of Negative Life Events: Adolescent Self-Rating Life Event Checklist
(ASLEC)
1. Purpose: Assess the psychological impact of negative life events during the prior 6 months on
adolescents.
2. Components: Covers six components, including interpersonal relationships, study pressure,
being punished, bereavement and property loss, health and adaptation, and others.
3. Scoring: Each item is scored from 1 (=not at all) to 5 (=extremely severe), with a higher total
score indicating a greater impact of negative life events.
4. Reliability: Cronbach α coefficient was 0.87 in this study.

Resilience: Chinese version of the Connor-Davidson Resilience Scale (CD-RISC)
1. Purpose: Measure resilience based on participants' feelings over the previous month.
2. Items: Contains 25 items on a 5-point Likert scale, ranging from 0 (not true at all) to 4 (true
nearly all of the time).
3. Scoring: Total score ranges from 0 to 100, with higher scores reflecting higher levels of
resilience.
4. Reliability: Cronbach α was 0.935 in this study.

Depressive Symptoms: Chinese version of the Center for Epidemiological Studies Depression
Scale (CES-D)
1. Purpose: Evaluate participants' depressive symptoms.
2. Items: Consists of four components (depressed affect, positive affect, somatic and retarded
activity, and interpersonal), including 20 items.
3. Scoring: Structured on a 4-point scale, rated from 0 (rarely or none of the time – < 1 day) to 3
(most or all of the time – 5 to 7 days), with higher scores indicating more symptoms.
4. Cutoff: A total score of 16 or above indicates depressive symptoms.
5. Reliability: Cronbach α was 0.89 in this study.
These tests were used to assess the psychological impact of negative life events, measure resilience,
and evaluate depressive symptoms among the participants in the study.
RESULTS:

Sample Characteristics: The study included 278 junior and senior high school students from
different districts of Wuhan. The sample consisted of 153 males (55%) and 125 females (45%).
The majority of participants (87.6%) were junior high school students, and 63% were the only
child in the family.

Differences in Depression, NLE, and Resilience Scores:
1. Female students had higher depression scores than male students.
2. Junior high school students had higher negative life events (NLE) scores but lower resilience
scores compared to senior high school students.
3. Family income was related to differences in NLE and resilience scores, with participants from
higher-income families showing lower impact from NLEs and higher levels of resilience.

Levels of Negative Life Events, Depression, and Resilience:
4. 55% of participants had scores indicating depressive symptoms.
5. The average total depression score was 17.14, indicating mild to moderate depression.
6. Interpersonal relationships and study pressure had higher scores among negative life events.
7. The average resilience score was 52.52, indicating a medium level of resilience.

Correlation Analysis:
8. Depression was positively correlated with all dimensions of negative life events and overall
NLEs.
9. Depression was negatively correlated with resilience.
10. Resilience was negatively correlated with all dimensions of negative life events and overall NLEs.

Mediating Role of Resilience:
11. A structural equation model was used to analyze the mediating role of resilience in the
relationship between negative life events and depression.
12. Negative life events had a positive direct effect on depression, indicating that higher NLEs led to
increased depression.
13. Negative life events were negatively associated with resilience, meaning that more NLEs were
linked to lower resilience.
14. Resilience was negatively associated with depression, suggesting that higher resilience was
associated with lower depression.
15. Resilience partially mediated the relationship between negative life events and depression,
accounting for 21.9% of the total effect.
DISSCUSION SIMPLIFIED:

High Incidence of Depression: The study found that 55% of Chinese junior and senior high
school students experienced depressive symptoms, which is consistent with previous research.
Depression is a significant issue affecting adolescents' mental health globally.

Gender Differences: Female students had higher levels of depression compared to male
students. This gender difference is consistent with other studies and may be influenced by
physiological factors, cognitive styles, and stress exposure.

Age Differences: Junior high school students had higher depression scores than senior high
school students. Younger adolescents may be more vulnerable to depression due to significant
physiological and psychosocial changes during this developmental period.

Stressors and Depression: Interpersonal relationship issues and study pressure were major
stressors associated with depression. The pressure to excel academically and conflicts with
peers and teachers can contribute to depressive symptoms.

Resilience as a Protective Factor: Resilience, the ability to bounce back from challenges, played
a crucial role in preventing depression. Higher levels of resilience acted as a buffer against the
negative impact of stressors and helped individuals adapt and manage emotional responses.

Implications: Promoting resilience among adolescents is essential to reduce the likelihood of
stress-related depression. Interventions could include cognitive reappraisal training, active
coping strategies, emotional regulation techniques, and interpersonal communication skills.

Limitations: The study's sample was limited to students from a specific city, so the findings may
not be generalizable to all adolescents in China. Further research with larger and more diverse
samples is needed.