Skip to main content

Knowledge and Protective Practice Towards Love Scam Among Female Facebook Users in Malaysia

Original title: Pengetahuan dan Amalan Perlindungan Pengguna Facebook Wanita Terhadap Penipuan Cinta di Malaysia

Document language: Malay. English title supplied by the publisher.

Norazlina Zainal Abidin ; Mohammad Rahim Kamaluddin ; Azianura Hani Shaari ; Norazura Din ; Saravanan Ramasamy (2018) — Jurnal Komunikasi: Malaysian Journal of Communication

What do these research terms mean?
Preprint
A manuscript shared before formal peer review and publication. Check whether a later published version is available.
Dataset
A collection of data or examples for others to inspect or reuse. It can appear in Library search and topic mapping, but RSRC does not use dataset records as evidence in Research Insights.
Dissertation or thesis
Research submitted for an academic degree. This describes its format, not its reliability.
Journal article
An article published in a journal. This label alone does not establish peer review, study quality, or how well the findings apply elsewhere.
Qualitative research
Examines experiences, meanings, or processes, often through interviews or observations. It can explain how something happens without estimating how common it is.
Quantitative research
Uses numerical measurements to describe patterns or test relationships. A relationship between two measurements does not by itself show that one causes the other.
Systematic review
Uses a planned, documented method to find and assess research addressing a question. Its conclusions still depend on the included studies and what the search covered.
Meta-analysis
Statistically combines results from multiple studies. Combining studies does not remove weaknesses in their design or make unlike populations interchangeable.
Not classified
This record has no recognized label in this filter. It does not mean the publication used no method, or that no research exists.

Definitions draw on DataCite resource types; Cochrane review methods; NLM: association and causation. RSRC’s dataset and classification rules are explained in our methodology.

Citation tools


              
              

Transparency

Evidence and review status

This page contains AI-generated content. No human content review or subject-matter-expert review is recorded.

Source basis
Downloaded PDF
Source updates
No notice found at last check
AI-generated page content
Yes
Automated checks
Passed
Administrative approval
Yes
Human content review
Not recorded
Subject-matter-expert review
Not recorded
How this was prepared
Source basis

RSRC downloaded and privately stored a copy of the paper for internal analysis. The PDF is not offered to viewers from this page.

  • PDF added to RSRC:
Source updates

No incoming update notice was found in the dated Crossref response. Coverage is incomplete, particularly for corrections and expressions of concern; this is not a guarantee that the source is valid or unchanged.

  • Last source-status attempt:
AI-generated page content

AI-generated research notes displayed on this page: Synopsis, Identified gaps, Methods, Limitations, Future work. The paper itself is not described as AI-generated.

  • Document analysis recorded:
  • Synopsis generation recorded:
  • Page record updated:
Automated checks

The current, source-bound synopsis passed the recorded versioned publication checks.

  • Checks completed:
View passed checks (3)
  • Length, completeness, repetition, refusal, boilerplate, and active-markup screening
  • Numerical claims checked against the available source text
  • English-source lexical grounding check
Administrative approval

The record is approved for public display, but a complete historical administrator action is not recorded.

Human content review

No human review is recorded for the AI-generated content displayed on this page.

Subject-matter-expert review

RSRC has not recorded review of this content by a subject-matter or methods expert.

Review-state definitions
Found a possible error? Request a correction.

Synopsis

This study examines what Malaysian women who use Facebook know about love scams and how they protect themselves online. The authors describe love scams as fraudulent romantic schemes used to induce financial or sexual exploitation, and they focus on female Facebook users in Malaysia. A quantitative approach was used, distributing questionnaires to a purposive sample of 609 women. The researchers assessed two domains: knowledge of love scams and protective practices, reporting that most respondents demonstrated high levels in both areas. Analyses indicate a positive and statistically significant relationship between knowledge and protective practices (Pearson r = 0.30, p < 0.05). The study also reports subgroup differences. There were no significant differences in knowledge or protective practices between women who had personally been victims of love scams and those who had not. However, there were significant differences when comparing respondents who had a close family member, friend, or colleague who had been a victim with those without such a history: those with a close contact who had been a victim scored higher on both knowledge and protective practices. Additional descriptive findings describe the emphases of respondents’ knowledge and practices, such as recognizing scams and avoiding sharing sensitive information or funds with unknown or recently acquainted online contacts. The authors suggest that these findings can serve as benchmarks for measuring and monitoring knowledge and protective behavior among female social media users in Malaysia. They imply that heightened awareness and careful online conduct contribute to protective practices, though the study does not present causal conclusions or broad generalizations beyond the sample.

Identified Gaps

The paper identifies an absence of Malaysian research on knowledge of, and protective practices against, love scams despite many domestic incidents. It positions the study as an initial Malaysian baseline and indicates a need to determine which sociodemographic groups are more vulnerable.

Methods

Quantitative cross-sectional survey of 609 Malaysian female Facebook users aged 19–50, recruited through purposive non-probability sampling. A researcher-developed questionnaire measured demographics, love-scam knowledge (17 items), and protective practices (23 items). Face/content validity and internal consistency were assessed (Cronbach’s alpha .79 and .87). SPSS descriptive analyses, Pearson correlation, and independent-samples t-tests examined levels, associations, and differences by victimisation history.

Limitations

The purposive, non-random sample comprised only female Facebook users aged 19–50, limiting generalisability beyond this population. Measures were researcher-developed self-report agreement scales, so reported protective practices may not reflect actual behaviour. The cross-sectional survey and correlational/t-test analyses establish associations and group differences but cannot determine whether knowledge causes protective practices or victimisation outcomes.

Future Work

Use the developed questionnaire to compare knowledge and protective practices across sociodemographic groups, to identify groups more vulnerable to love scams. The authors also urge women, particularly prior victims, to take the issue seriously and strengthen protective practices to reduce recurrence.

See how this publication connects to RSRC's living evidence syntheses through current citations and research-topic mapping.