orisma_indicators: ORISMA bibliometric indicators

In orisma: Occupational Risk Integrated Systematic Mapping and Analysis

ORISMA bibliometric indicators

Description

ORISMA implements five original bibliometric indicators designed specifically for occupational health and safety (OHS) evidence mapping. Three are corpus-level indicators (WRDI, RCS, MGP) and two are record-level indicators (ASS, Bridge Score).

1. Worker-Risk Disconnection Index (WRDI)

Definition

The WRDI measures the proportion of studies in a corpus that characterise an occupational risk without including direct worker exposure data. A study is considered to have worker exposure data if its abstract contains terms indicating real measurement of exposure in actual workers under real working conditions (e.g. "worker exposure", "occupational exposure", "breathing zone", "personal sampling", "field study", "workplace measurement").

Formula

For a given risk category c:

WRDI_c = 1 - \frac{N_{workers,c}}{N_{total,c}}

where N_{workers,c} is the number of studies in category c that include worker exposure data, and N_{total,c} is the total number of studies in that category.

The global WRDI is computed across all records:

WRDI_{global} = 1 - \frac{N_{workers}}{N_{total}}

Interpretation

• WRDI = 0: All studies include direct worker exposure data. The body of evidence is fully connected to real workplace conditions.

• WRDI = 1: No study includes worker exposure data. The entire literature characterises the risk technically (e.g. in simulated environments, chambers, or in vitro) without measuring real exposure in workers.

• WRDI >= 0.8: Critical alert. The evidence has very low direct preventive transferability. On-site risk assessment is essential.

• WRDI 0.5-0.8: Attention required. More than half the evidence lacks worker data.

• WRDI < 0.3: Reasonable coverage. Most studies include worker data.

Important limitation

WRDI detection is based on abstract text, not full text. Studies that measured worker exposure but did not mention it in the abstract may be misclassified. Manual validation via orm_validate() is recommended.

2. Risk Category Saturation Index (RCS)

Definition

The RCS measures the relative dominance of a risk category in the corpus compared to a hypothetical uniform distribution across all categories. It identifies which categories are over-represented (saturated) and which are under-represented (gaps) in the literature.

Formula

RCS_c = \frac{pct_c}{pct_{uniform}}

where pct_c is the percentage of records assigned to category c, and pct_{uniform} = 100 / K is the percentage each category would have under a uniform distribution across all K categories.

Equivalently:

RCS_c = \frac{N_c \cdot K}{N_{total}}

where N_c is the number of records in category c, K is the total number of categories, and N_{total} is the total number of records.

Interpretation

• RCS > 1: The category is over-represented relative to a uniform baseline. The literature has concentrated disproportionately on this risk type.

• RCS = 1: The category has exactly the representation expected under a uniform distribution.

• RCS < 1: The category is under-represented. This risk type has received less attention than a balanced literature would suggest.

• RCS = 0: No studies address this category. Complete evidence gap.

Note

RCS is a relative measure. A category can have RCS > 1 with very few absolute studies if the corpus is small or highly specialised. Always interpret RCS together with the absolute number of records (N).

3. Material-Gap Profile (MGP)

Definition

The MGP is a domain-specific indicator designed for corpora where the corpus can be stratified by material, substance, or agent. It measures the ratio between a material's known hazard potential and its coverage in the occupational health literature, identifying materials that are dangerous but understudied.

Formula

MGP_m = \frac{hazard\_proxy_m}{coverage_m}

where hazard\_proxy_m is an estimate of the material's hazard potential (based on the number of distinct risk categories detected in studies involving that material), and coverage_m is the proportion of corpus records that address that material.

Interpretation

• High MGP: The material is associated with multiple risk categories but appears in few studies. Priority material for future research and on-site risk assessment.

• Low MGP: The material is well-covered in the literature relative to its known hazard profile.

• MGP requires a material column: The material_col parameter in orm_analyse() must point to a column classifying each record by material or agent. If not available, MGP is not computed.

4. Abstract Sufficiency Score (ASS)

Definition

The ASS is a cumulative hierarchical index (0-5) measuring how much preventively useful information an abstract contains for an occupational health practitioner. It is not a measure of study quality, but of abstract informativeness for preventive purposes.

The score is strictly cumulative: a record cannot reach level N without satisfying all previous levels.

Levels

0 - Non-informative

The abstract contains no hazard or risk terms relevant to OHS. No useful preventive information.

1 - Hazard without context

The abstract mentions a hazard or risk agent (e.g. nanoparticles, noise, vibration) but provides no occupational or workplace context. Could be an environmental or laboratory study.

2 - Occupational context

The abstract mentions workers, employees, operators, or workplace/occupational setting. The study is clearly situated in a work context.

3 - Exposure measurement

The abstract reports quantitative exposure data: concentrations, levels, measurements, or monitoring results. Implies some form of exposure quantification.

4 - Worker exposure with result

The abstract explicitly reports exposure in workers (not just in the environment) with a result (e.g. exceeded a limit, found significant association, detected at breathing zone).

5 - Complete preventive abstract

The abstract addresses all four dimensions: worker population + exposure measurement + study method/design + preventive recommendation or control measure. This is the highest OHS informative level.

Computation

Each level is detected via regular expression patterns applied to the abstract text. Detection is strictly cumulative: the algorithm tests each level in sequence and stops at the first level not satisfied.

Interpretation

• Mean ASS < 2: The corpus is predominantly technical with very little preventive context. High priority for on-site investigation.

• Mean ASS 2-3: Mixed corpus. Some workplace context but limited quantitative exposure data.

• Mean ASS > 3: Good preventive evidence base. Substantial proportion of studies report actual worker exposure data.

• ASS = 5 articles: These are the most valuable abstracts for practitioners and should be read in full first.

5. Bridge Article Score

Definition

A bridge article is a study that connects technical science with applied OHS prevention. It simultaneously addresses five dimensions that are rarely all present in a single study:

Criterion 1 - Technology/process

The study involves a specific technology, industrial process, or work task (e.g. additive manufacturing, welding, construction, healthcare).

Criterion 2 - Hazardous agent

The study characterises a specific hazardous agent (chemical, physical, biological, or psychosocial).

Criterion 3 - Workers (MANDATORY)

The study involves a real worker population in a real workplace setting. This criterion is mandatory for bridge classification.

Criterion 4 - Exposure measurement (MANDATORY)

The study quantitatively measures exposure (air sampling, biological monitoring, dosimetry, etc.). This criterion is mandatory for bridge classification.

Criterion 5 - Prevention/recommendation

The study includes preventive recommendations, control measures, or intervention results.

Classification

Strong bridge (score 4-5)

Meets criteria 3+4 (mandatory) plus 2 or 3 additional criteria. Highest priority for full-text reading. These articles have already done the translation from laboratory science to workplace prevention.

Partial bridge (score 3)

Meets criteria 3+4 (mandatory) plus 1 additional criterion. Valuable but incomplete bridge.

Technical study (score 0-2, or missing C3/C4)

Does not meet the mandatory criteria. Contributes technical knowledge but lacks direct preventive applicability.

Priority score

The overall priority reading score used in orm_ranking() combines all record-level indicators:

Priority = (Bridge \times 2) + (ASS \times 1.5) + (N_{cats} \times 0.5)

where N_{cats} is the number of risk categories detected in the record. Bridge score is weighted highest because it reflects the most direct preventive relevance.

References

The WRDI, RCS, and MGP indicators were first described in:

Aguilar-Elena, R. & Delgado-Garcia, A. (2025). Mapping the Safety Landscape of Emerging Technologies: A Bibliometric Analysis of Occupational Risks in Metal Additive Manufacturing. (Under review)

The ORISMA methodological framework is described in:

Aguilar-Elena, R. & Delgado-Garcia, A. (2025). orisma: A Framework for Occupational Risk Integrated Systematic Mapping and Analysis. R package version 0.1.0. Universidad Internacional de Valencia (VIU) & Universidad de Salamanca (USAL).

See Also

orm_analyse() to compute WRDI, RCS, and MGP. orm_ass() to compute the Abstract Sufficiency Score. orm_bridge() to detect bridge articles. orm_ranking() to generate a priority reading list. orm_validate() to validate automatic classification with Cohen's Kappa.

orisma documentation built on May 19, 2026, 1:07 a.m.