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Record W4413499875 · doi:10.3389/fpsyt.2025.1576323

Commentary: Prediction of problem gambling by demographics, gaming behavior and psychological correlates among gacha gamers: A cross-sectional online survey in Chinese young adults

2025· letter· en· W4413499875 on OpenAlexaff
Leon Y. Xiao, Nick Ballou, Charlotte Eben

Bibliographic record

VenueFrontiers in Psychiatry · 2025
Typeletter
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsGreo
FundersHORIZON EUROPE Marie Sklodowska-Curie ActionsHORIZON EUROPE Framework ProgrammeEuropean CommissionCity University of Hong Kong
KeywordsDemographicsPsychologyCross-sectional studyNeural correlates of consciousnessClinical psychologyPsychiatryMedicineDemographyCognition

Abstract

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1. IntroductionTang et al. (1) purported to report that ‘problem gambling,’ as they defined it, is associated with monetary spending on video game mechanics that involve randomisation (e.g., gacha mechanics (2,3) and loot boxes (4)) amongst young Hong Kong players of games containing such mechanics. At face value, that assertion is not surprising as a consistent line of research has previously established that relationship in Western countries (5–7), which has been relied upon in policymaking (8,9). Research conducted subsequent to Tang et al. in Mainland China has also replicated the relationship (10).However, unfortunately, Tang et al. suffered from a fundamental flaw. That study did not, in fact, measure ‘problem gambling’ as traditionally defined because Tang et al. significantly modified the measurement scale. Instead, Tang et al. measured only ‘problematic participation in gacha mechanics’ and proved various relationships existed between that construct and other variables, which arguably is less meaningful (11,12). The development of that new scale lacked transparency and evidence of reliability and validity. It is unclear whether that new measure is related to ‘problem gambling’ and, if so, to what extent. In any case, it is not, and cannot be used as, a direct replacement without further validation.Tang et al. could not in fact have been able to report on any issues concerning ‘problem gambling’ because by definition, they did not measure ‘problem gambling.’ They should not have claimed to have been able to test or comment on any psychological relationships concerning ‘problem gambling.’ The current framing of that paper and its conclusions are misleading to readers whose attention are not specifically drawn to this highly significant measurement modification. This comment intends to correct that misimpression. Simply put, Tang et al. did not prove what its title suggested. That paper must be treated with due caution and considered for exclusion from meta-analyses.2. DiscussionSpecifically, when purporting to measure ‘problem gambling,’ Tang et al. used a significantly modified version of the Chinese version of the Problem Gambling Severity Index (PGSI). The PGSI was originally created in English (13) but has since been translated and validated in Chinese (14). Therefore, the use of the Chinese language version of the PGSI instead of the English version is not at issue. In fact, the Chinese PGSI has been used with success in other loot box studies in China (10,15).The problem was that Tang et al. modified the wording of the PGSI beyond a mere translation: references to ‘gambling [赌博]’ were all converted to ‘spending money on gacha mechanics [課金抽蛋],’ as the authors revealed in a personal response to L.Y.X.’s query and as shown in Table 1. This modification was disclosed at page 4 of the original paper only very vaguely and not sufficiently prominently (‘As PGSI-C was originally developed for screening general gambling activities, the authors had modified a few words on some items to fit the context of gacha games’) (1). All modifications made should have been fully disclosed in detail.Table 1The Problem Gambling Severity Index compared to the Tang et al. problematic participation in gacha mechanics scale (with changes marked with red italics)ItemProblem Gambling Severity Index (PGSI)Tang et al. problematic participation in gacha mechanics scaleDifferences and potential issues (besides changing the subject matter)1Have you bet more than you could really afford to lose?你有沒有向手機遊戲內的抽蛋活動投下超出你能力可承受的金額?[Have you ever bet more money than you can afford in a gacha event in a mobile game?]N/A2Have you needed to gamble with larger amounts of money to get the same feeling of excitement?你需要藉由課更多金錢去抽蛋,來得到你所想要的興奮程度嗎?[Have you needed to spend more money on gacha to get the level of excitement you want?]The ‘same feeling’ was substituted with ‘the level of excitement you want’3When you gambled, did you go back another day to try to win back the money you lost?如果你課金後抽不到你想要的東西,你會為了不浪費之前投下的金錢,再次課金嗎?[When you could not obtain your desired rewards from paying for gacha mechanics, did you pay money again to participate more because you did not want to waste the money you previously invested?]The additional explicit justification of ‘did not want to waste the money you previously invested’ and the omission of the reference that the subsequent activity should occur at a later date.4Have you borrowed money or sold anything to get money to gamble?你會因課金抽蛋而去借錢或賣東西嗎?[Have you borrowed money or sold things to spend money on gacha mechanics?]N/A5Have you felt that you might have a problem with gambling?你有沒有覺得你課金抽蛋的行為可能存在問題?[Have you felt that you might have a problem with spending money on gacha mechanics?]N/A6Has gambling caused you any health problems, including stress or anxiety?課金抽蛋的行為曾給你帶來過健康問題嗎?包括壓力或焦慮?[Has your behavior of spending money on gacha mechanics caused you any health problem? Including stress or anxiety?]N/A7Have people criticized your betting or told you that you had a gambling problem, regardless of whether or not you thought it was true?有沒有人曾指責或告訴過你課金抽蛋的行為有問題,無論你認為這是正確的還是錯誤的?[Have people criticised your behavior of spending money on gacha mechanics or told you that you had a problem, regardless of whether you thought it was true or false?]The additional explicit mention of the suggestion potentially being ‘false.’8Has your gambling caused any financial problems for you or your household?你曾試過因課金抽蛋而導致你或你的家庭出現經濟問題嗎?[Has your spending on gacha mechanics caused any financial problems for you or your household?]N/A9Have you felt guilty about the way you gamble or what happens when you gamble?你有沒有對自己課金抽蛋的行為感到過內疚?[Have you felt guilty about your behaviour of spending money on gacha mechanics?]The clause ‘or what happens when you gamble’ was omitted.In theory, making such modifications to create a new scale is not problematic in and of itself, although when not done properly and transparently, it might constitute so-called ‘measurement schmeasurement’ or ‘questionable measurement practices’ that ‘raise doubts about the validity of the measures, and ultimately the validity of study conclusions’ (16). Other constructs, whose developments were much better detailed, have sought to measure potentially problematic engagement with loot boxes, e.g., the ‘Risky Loot Box Index’ (RLI) (10,17–19) and the ‘Problematic Use of Loot Boxes Questionnaire’ (PU-LB) (20,21). However, Tang et al.’s continued representation of the modified scale as if it measured ‘problem gambling’ as traditionally understood was misleading because following the modification, the scale instead measured ‘problematic participation in gacha mechanics’ – a completely different construct. The modification effectively created a new and, importantly, unvalidated problematic gacha engagement scale more comparable to the RLI (10,17,18). This means Tang et al. misrepresented their construct of ‘problematic participation in gacha mechanics’ as a measure of ‘problem gambling’ throughout the paper, from title to abstract through the results and into the conclusion.Other substantive changes were also made to the PGSI. For example, the third item of the PGSI was not just slightly amended by having a few words modified but completely replaced, causing its meaning to change. The original question was: ‘When you gambled, did you go back another day to try to win back the money you lost?’ (13). The third question in the modified scale used by Tang et al. was: ‘When you could not obtain your desired rewards from paying for gacha mechanics, did you pay money again to participate more because you did not want to waste the money you previously invested?’ It is obvious that Tang et al. tried to replicate a similar sentiment of ‘loss chasing’ in both contexts (22), but there is a conceptual difference between (a) more actively wanting to win back past losses and (b) more passively not wanting to waste previous investments referenced by Tang et al.’s new item, which is more akin to entrapment and the sunk cost fallacy (23). The explicit reference to wasting previous investments could have been omitted in the modified scale, which could have just asked whether the participant tried to win the desired reward again by spending more money at a later date. Again, the question that was asked may have been perfectly acceptable at measuring the underlying behaviour. However, there was a lack of transparent disclosure of the modification and the justifications thereof, which casts doubt on the reliability of the measurement construction, its validity, and resultant findings (16).3. ConclusionResearch conducted in Mainland China after Tang et al. has confirmed that spending on loot boxes is associated with problem gambling as traditionally understood (10), thus alleviating concerns that the relationship may not be replicable beyond Western samples (15,24). Nonetheless, it must be clarified that Tang et al. did not measure ‘problem gambling’ but ‘problematic participation in gacha mechanics’ instead, which is a possibly related but substantially different construct. Readers must be informed that they ought to approach Tang et al. by mentally amending all references to ‘problem gambling’ in the paper (including title and abstract) to the new, unvalidated construct of ‘problematic participation in gacha mechanics’ instead, which is incredibly burdensome. Tang et al. must be corrected to ensure the accuracy and integrity of the scientific record. Attempts should also be made to validate the modified scale used by Tang et al. to better understand how that new construct is related to the traditional ‘problem gambling’ construct and whether the modified scale may have future utility as an alternative to the RLI (10,17–19) and the PU-LB (20,21).

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)0.011
metaresearch head score (Gemma)0.095
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.052
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.095
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.002
Science and technology studies0.0040.004
Scholarly communication0.0020.004
Open science0.0100.002
Research integrity0.0310.022
Insufficient payload (model declined to judge)0.0210.011

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 head0.040
GPT teacher head0.353
Teacher spread0.312 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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