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Silver Lining: Grit and Well-Being of Working Students in a Private University

Rona Esther Banlasan Suizo, Baby Rose Robles
Psychology and Education: A Multidisciplinary Journal · 2026-08-18 · DOI 10.70838/pemj.610910
Token #9386
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Token#9386 of SciMatic Articles (ERC-1155), fixed supply 1,000,000
Contract0x0E596B4bb924937aA35D9b342A90347ed6F05eF8
Mint transaction0x82adb6670b76b04ec1c83bfa0832ecca88138ccfd1933a3ba66a3f0b68ee9bc7 · block 12112838
Minted2026-10-02 15:25 UTC
Hash on chain0xe76ba2fe052ab5df2808cd5ee58970eda934e73c19918424dcac006765724f30
SHA-256 of the record0xe76ba2fe052ab5df2808cd5ee58970eda934e73c19918424dcac006765724f30
Article today Matches the anchored record.

Allocation at minting

HolderWalletMintedHolds now
SciMatic (10%) 0xc35709AB…277732 100,000 100,000
Rona Esther Banlasan Suizo 0x15e246aD…2Cd8Ce 450,000 450,000
Baby Rose Robles 0x8046494f…3Af0e1 450,000 450,000

The anchored record

Canonical JSON (keys sorted, no spaces, UTF-8). Its SHA-256 is the hash on chain.

{"abstract":"Working students represent a unique population that simultaneously manages academic responsibilities and employment while coping with financial and personal challenges. Despite increasing interest in positive psychology, limited empirical evidence has examined the relationship between grit and well-being among working students in collectivist contexts. This mixed-methods study investigated the levels of grit and well-being, examined differences according to sex, age, and general weighted average (GWA), identified the predictors of grit and well-being, and explored the lived experiences of working students in a private university. An explanatory sequential mixed-methods design was employed. Quantitative data were collected from 39 working students through the researcher-developed Triarchic Model of Grit (TMOG) and Well-being Outcomes Scale (WBOS), both of which demonstrated excellent internal consistency (Cronbach's α = .916 and .914, respectively). Descriptive statistics, independent-samples t-test, Kruskal–Wallis test, Pearson correlation, and multiple linear regression were used for quantitative analysis, while thematic analysis was conducted on in-depth interviews with two purposively selected participants. Results revealed that working students exhibited high levels of both grit and well-being. No significant differences were found across sex, age, and GWA. Adaptability to situations significantly predicted well-being, whereas positive affect significantly predicted grit. Qualitative findings showed that financial hardship, family responsibilities, academic pressures, and personal adversities strengthened participants' perseverance, adaptability, optimism, and commitment to long-term educational goals. Family support, gratitude, and the desire to improve their family's socioeconomic condition further reinforced their persistence. The findings extend the application of the Triarchic Model of Grit within a collectivist context by demonstrating the importance of adaptability as a culturally relevant dimension of grit. The study recommends that higher education institutions implement evidence-based positive psychology and student wellness programs that cultivate grit, resilience, adaptability, and psychological well-being among working students.","abstract_source":"original","authors":["Rona Esther Banlasan Suizo","Baby Rose Robles"],"date":"2026-08-18","doi":"10.70838/pemj.610910","id":9386,"issue":9,"journal":{"issn":"2822-4353","name":"Psychology and Education: A Multidisciplinary Journal"},"pdf_sha256":"028d08e4bae6ac0f7e29e3854140c612b1884bf1699c32be233419081a935b77","schema":"scimatic-article/1","title":"Silver Lining: Grit and Well-Being of Working Students in a Private University","volume":61}

Check it yourself

1. The record, from the token's own metadata:

printf '%s' "$(curl -s https://scimatic.org/nft/articles/9386.json | jq -r .canonical_record)" | sha256sum

2. The hash stored on chain (contentHash(9386)):

curl -s https://rpc.scimatic.net -H 'content-type: application/json' \
  -d '{"jsonrpc":"2.0","id":1,"method":"eth_call","params":[{"to":"0x0E596B4bb924937aA35D9b342A90347ed6F05eF8","data":"0xf3e0c29000000000000000000000000000000000000000000000000000000000000024aa"},"latest"]}'

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