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Record W221763309

Satisfaction of Needs and Determining of Life Goals: A Model of Subjective Well-Being for Adolescents in High School.

2011· article· en· W221763309 on OpenAlexaboutno aff
Ali Eryılmaz

Bibliographic record

VenueEducational Sciences Theory & Practice · 2011
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsnot available
Fundersnot available
KeywordsDienerAffectionPsychologyFeelingLife satisfactionStructural equation modelingSubjective well-beingDevelopmental psychologyWell-beingSocial psychologyHappinessPsychotherapist
DOInot available

Abstract

fetched live from OpenAlex

Abstract The aim of this study is to develop and test a subjective well-being model for adolescents in high school. A total of 326 adolescents in high school (176 female and 150 male) participated in this study. The data was collected by using the general needs satisfaction questionnaire, which is for the adolescents' subjective well-being, and determining life goals questionnaire. The structural equation modeling method was used for analysis of the data. The results of the analysis showed that in the original model, the individual variables and the total effect of variables were directly and indirectly related to subjective well being of adolescents in high school. The direct and indirect effects of the independent variables to subjective well-being were found significant. The findings suggest that to enhance the subjective well-being of high school students, a combination of satisfaction of needs and determining of life goals are essential. Key Words Subjective Well-Being, Satisfaction of Needs, Determining Life Goals, Adolescents. Subjective well-being is considered to comprise three important dimensions: positive affection, negative affection and life satisfaction (Andrews & Whitney 1976; Diener, 1984). Positive affection includes positive feelings while negative affection includes negative feelings. The life satisfaction dimension is a cognitive component of subjective well-being (Myers & Diener, 1995). When literature is examined, the subjective wellbeing of children and adolescents were investigated based on three important domains such as demographic factors (Huebner, Suldo, Smith, & McKnight, 2004; Karatzias, Chouliara, Power, & Swanson, 2006; McCullough, Huebner, & Laughlin, 2002; Sarakauskiene & Bagdonas, 2010); psychological factors (Hartup & Stevens, 1997; Joronen & Kurki, 2005; Mcknight, Huebner, & Suldo, 2002; Rask, Kurki, & Paavilainen, 2003; Shek & Lee, 2007), and also academic factors (Ash & Huebner, 2001; Baker, 1998; Cheng & Furnham, 2002; Huebner, 1991; Huebner & Alderman, 1993; Huebner & Gilman, 2003; Suldo & Huebner, 2004). According to results of researches, when adolescents have higher level of subjective well-being, they become healthier (Huebner et al., 2004; Steinberg, 2004, 2005). To investigate of adolescents' subjective well-being with different variables is important for positive development of adolescents (Gilman & Huebner, 2006). Self determination theory points out that individuals want to satisfy three innate psychological needs such as competence, relatedness, and autonomy (Baard, Deci, & Ryan, 1998; Deci, 2008; Deci & Ryan, 1991; Deci, Vallerand, Pelletier, & Ryan, 1991; Ryan & Deci, 2000). According to studies on subjective well-being, satisfaction of psychological needs is important variable which affects subjective well-being of individuals (Baard, 2002; Ryan & Deci, 2000). If individuals satisfy their psychological needs, they feel better. On the other hand, if psychological needs are not satisfied, individuals develop more pathologies (Baard et al., 1998; Cole, Maxwell, & Martin, 1997; Crocker & Hakim-Larson, 1997; Deci et al., 2001; Ilardi, Leone, Kasser, & Ryan, 1993; Kasser & Ryan, 1999; Noom, Dekovic, & Meeus, 1999; Reis, Sheldon, Gable, Roscoe, & Ryan, 2000; Ryan & Deci, 2000; Ryan & Grolnick, 1986; Sheldon & Bettencourt, 2002; Sheldon, Ryan, & Reis, 1996; Veronneau, Koestner, & Abela, 2005; Wiest, Wong, & Kreil, 1998). Literature indicates that one of the most important factors to regulate and adapt individuals to their lives is goals (Diener & Seligman, 2002, 2004; Emmons, 1999; Kasser, 2002; Sheldon & Bettencourt, 2002; Sheldon & Elliot, 1999; Sheldon & Kasser, 1998; Sheldon, Ryan et al., 1996; Synder & Lopez, 2007). People behave to achieve various goals (Austin & Vancouver, 1996; Emmons, 1999; Emmons, Colby, & Kaiser, 1998; King, Richard, & Stemmerich, 1998; Lock & Latham, 1990; Yetim, 2001). …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.046
GPT teacher head0.352
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2011
Admission routes1
Has abstractyes

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