Research Article

Investigating Integrity and Job Performance: A Quantitative Inquiry

147 reads
Psych Educ Multidisc J, 2026, 61 (9), 1153-1167, DOI: https://doi.org/10.70838/pemj.610904, ISSN 2822-4353
Verified on SciChain · token #9378 of SciMatic Articles (ERC-1155, 1,000,000 tokens)
Contract 0x0E596B4b…F05eF8 · mint transaction · verify the record

Abstract

This study examined the relationship between integrity and job performance among employees of Assumption College of Nabunturan. Specifically, it assessed employees integrity in terms of honesty, consciousness, and principles, and their job performance in terms of task performance, productive behavior, contextual performance, and adaptive performance. A quantitative descriptive-correlational research design was used involving 107 teaching and non-teaching employees selected through universal sampling. Data were collected using adapted and validated questionnaires and analyzed using mean, Pearson r correlation, and multiple regression analysis. The findings revealed that employees demonstrated high levels of integrity and job performance. Pearson correlation analysis showed no significant relationship between integrity and job performance (r = 0.167, p = 0.088). However, multiple regression analysis indicated that the domain of principles significantly predicted job performance (p = 0.018). The study concludes that while overall integrity was not significantly associated with job performance, adherence to ethical principles contributes to better employee performance. The findings highlight the importance of strengthening ethical values and principles to promote organizational effectiveness.
Keywords job performance integrity office administration universal sampling quantitative inquiry

The team behind this paper

5 authors, 2 institutions.

This paper Assumption College of Nabunturan (ACN) — Philippines Assumption College of N… 4 authors Assumption College of Nabunturan — Philippines Assumption College of N… 1 author Marrian Naypa — corresponding author MN Marrian Naypa ✉ Estiward Ly Banag EB Estiward Ly Banag Rean Joy Suarez RS Rean Joy Suarez Bermon Logronio BL Bermon Logronio Kimberly Jane Narvasa KN Kimberly Jane Narvasa

Readership

147 reads over 3 months.

August 2026 October 2026

On SciChain

This article is token #9378 of SciMatic Articles (ERC-1155): 1,000,000 tokens, minted once, never more. The chain also stores a fingerprint (SHA-256) of the article's record, so anyone can check that it has not been altered.

HolderWalletTokens
SciMatic 0xc35709…277732 100,000 (10%)
Marrian Naypa 0xDE8ef4…89383F 180,000 (18%)
Estiward Ly Banag 0x4c6aEa…89c2aD 180,000 (18%)
Rean Joy Suarez 0x78ACE5…B6954D 180,000 (18%)
Bermon Logronio 0xe5E83E…5e015F 180,000 (18%)
Kimberly Jane Narvasa 0x3E6E48…F440f5 180,000 (18%)
Content hash 0xcdb9e41460bf40127f8ff937a24ec3316dd8ffe1c27e67fcd28fd1934b277324

Bibliographic Information

Marrian Naypa, Estiward Ly Banag, Rean Joy Suarez, Bermon Logronio, Kimberly Jane Narvasa, (2026). Investigating Integrity and Job Performance: A Quantitative Inquiry, Psychology and Education: A Multidisciplinary Journal, 61(9): 1153-1167
Bibtex Citation
@article{marrian_naypa2026pemj,
author = {Marrian Naypa and Estiward Ly Banag and Rean Joy Suarez and Bermon Logronio and Kimberly Jane Narvasa},
title = {Investigating Integrity and Job Performance: A Quantitative Inquiry},
journal = {Psychology and Education: A Multidisciplinary Journal},
year = {2026},
volume = {61},
number = {9},
pages = {1153-1167},
doi = {10.70838/pemj.610904},
url = {https://scimatic.org/index.php/show_manuscript/9378}
}
APA Citation
Naypa, M., Banag, E.L., Suarez, R.J., Logronio, B., Narvasa, K.J., (2026). Investigating Integrity and Job Performance: A Quantitative Inquiry. Psychology and Education: A Multidisciplinary Journal, 61(9), 1153-1167. https://doi.org/10.70838/pemj.610904

Author Information

  • To change your profile photo, login to scimatic.org, go to your profile and change the photo.
  • Provide a face photo, and not full body.
  • It is better to remove the background from your photo. Go to Remove Background and then upload to profile
  • If you are unable to login, go to Reset My Password provide your email registered with the article and get new password.
  • In case of any other problem, contact your editor directly or write to us at info @ scimatic.org