MétaCan
Menu
Back to cohort
Record W2476009077 · doi:10.1007/s10899-016-9633-7

The Candy Crush Sweet Tooth: How ‘Near-misses’ in Candy Crush Increase Frustration, and the Urge to Continue Gameplay

2016· article· en· W2476009077 on OpenAlexafffund
Chanel J. Larche, Natalia Musielak, Mike J. Dixon

Bibliographic record

VenueJournal of Gambling Studies · 2016
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNear missFrustrationPsychologyArousalSocial psychologyCognitive psychologyForensic engineeringEngineering

Abstract

fetched live from OpenAlex

Like many gambling games, the exceedingly popular and lucrative smartphone game "Candy Crush" features near-miss outcomes. In slot machines, a near-miss involves getting two of the needed three high-paying symbols on the pay-line (i.e., just missing the big win). In Candy Crush, the game signals when you just miss getting to the next level by one or two moves. Because near-misses in gambling games have consistently been shown to invigorate play despite being frustrating outcomes, the goal of the present study was to examine whether such near-misses trigger increases in player arousal, frustration and urge to continue play in Candy Crush. Sixty avid Candy Crush players were recruited to play the game for 30 min while having their Heart Rate, Skin Conductance Level, subjective arousal, frustration and urge to play recorded for three types of outcomes: wins (where they level up), losses (where they don't come close to levelling up), and near-misses (where they just miss levelling up). Near-misses were more arousing than losses as indexed by increased heart rate and greater subjective arousal. Near-misses were also subjectively rated as the most frustrating of all outcomes. Most importantly, of any type of outcome, near-misses triggered the most substantial urge to continue play. These findings suggest that near-misses in Candy Crush play a role in player commitment to the game, and may contribute to players playing longer than intended.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.035
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.079
GPT teacher head0.405
Teacher spread0.326 · 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

Citations39
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Gambling StudiesSame topicGambling Behavior and TreatmentsFrench-language works237,207