In today’s corporate environment, a "one-size-fits-all" approach is no longer a valid strategy, especially when discussing mental health and psychosocial risks. Understanding workplace well-being requires precision, context, and rigor. Under this premise, MentallyPro is proud to announce a key advancement: the expansion of our sectoral benchmarks. MentallyPro anunciamos un avance clave: la expansión de nuestros baremos sectoriales.
Beyond Generic Evaluation: The Value of Specialization
One of the primary advantages of MentallyPro is its design, which tailors assessments to the unique reality of each sector. The cognitive and emotional challenges faced in a call center are not the same as those in a bank office. To provide reliable results, comparing specific elements is essential.
Until today, our platform has successfully operated across 14 sectors. Today, we are raising that standard by incorporating 5 new sectoral benchmarks, reaching a total of 19 areas of specialization.This expansion allows organizations to obtain a much clearer picture of their psychosocial health by comparing their results against metrics built specifically for their industry.
The new additions respond to sectors with very specific dynamics:
- Public Administration
- Pharmaceutical Sector
- Water Management and Treatment
- Security and Access Control
- Legal Firms
Each field has its own benchmarks, allowing for scale adjustments using different criteria
even when the administration occurs within the same organization. This option ensures that results are adjusted to the diverse activities that coexist within a company.
Psychometric Rigor: Eliminating Bias
This is not the only leap that positions MentallyPro as a leading reference tool. What differentiates a simple climate survey from a professional diagnostic tool is scientific rigor. This is where MentallyPro stands out, thanks to its legal and psychometric validation,grounded in an ipsative methodology.
Unlike traditional questionnaires (where it is easy to consistently select the "socially correct" option), our system requires the individual to rank items based on their level of identification. This design is crucial because it drastically reduces social desirability bias or prompted responses. By eliminating these distortions, along with age or gender biases, we guarantee that the data collected are not just opinions, but valid indicators of risk probability.