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Record W2974840559 · doi:10.5539/jel.v8n5p57

Investigation of the Relationship Between Dispositional Flow State, Sensation Seeking and Ski Resort Preference of Skiing and Snowboarding Participants

2019· article· en· W2974840559 on OpenAlexvenueno aff
Sırrı Cem DİNÇ, Mustafa Demircan

Bibliographic record

VenueJournal of Education and Learning · 2019
Typearticle
Languageen
FieldPsychology
TopicAdventure Sports and Sensation Seeking
Canadian institutionsnot available
FundersManisa Celal Bayar Üniversitesi
KeywordsSensation seekingPsychologyKurtosisSkewnessNormalityPearson product-moment correlation coefficientStructural equation modelingSocial psychologyPreferenceDemographyStatisticsMathematicsPersonality

Abstract

fetched live from OpenAlex

The aim of this study is to investigate the relationship between was to examine dispositional flow state, sensation seeking and ski resort preference of skiing and snowboarding participants. The sample of this study constituted 510 (126 female x̄ = 23.94 ± 5.79 years; 384 male x̄ = 27.33 ± 7.87 years) skiers and snowboarders from varied ski resort between the years 2018–2019. A demographic questionnaire, The Contextual Sensation Seeking Questionnaire for Skiing and Snowboarding (CSSQ-S) Ski Resort Preference Scale (SRPS) and Dispositional Flow Scale-2—Short Form (DFS2-SF) were used to collect data. Before the statistical analysis, coefficient of kurtosis, coefficient of skewness and test of normality (Kolmogorov-Smirnov Test) of the data were examined and the deviation from the normal distribution was determined meaningless (p > .05). Pearson Product-Moment Correlation Coefficient was used to determine the relationship between variables. The mediator effect of sensation seeking in the relationship between ski resort preference and flow of participants were examined with Structural Equation Modeling (SEM). The correlation value between the variables was determined between 0.196–0.549. (P < 0.01). There is causal relationship between; SRPS and DFS2-SF (β = .187, p < .01), SRPS and CSSQ-S (β = .932, p < .01), CSSQ-S and DFS2-SF (β = .581, p < .01) respectively. It was found that when SRPS variable was included in the model as a mediating variable, causal relationship between SRPS and DFS2-SF was eliminated (β = 7.067, p > .05) and causal relationship between CSSQ-S and DFS2-SF was significantly increased (β = .722, p < .01). When the fit indexes of the models were examined, all values in all four models indicated acceptable/perfect fit. The results show that ski resort preference has a significant causal relationship on flow state and sensation seeking in skier and snowboarders. However, when sensation seeking is included in the model as a mediating factor, effect of the ski resort preference on the flow state disappears, while the effect level of sensation seeking increases.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.018
Threshold uncertainty score0.207

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.075
GPT teacher head0.330
Teacher spread0.254 · 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 teacher head, 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

Citations4
Published2019
Admission routes1
Has abstractyes

Explore more

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