What do psychological test reports look like and what do they convey? What information does Starcheck extract from tests completed online by candidates or employees?
Below are some examples of psychological test reports and a work profile. On competencies, or the underlying items such as personality, intelligence, and motivations.
This is usually where it starts. In any case, the work profile indicates the behavioral competencies that are important to successfully perform a job.
This can be done based on an interview, but there are also various expert systems that can compile such a profile in a highly structured way. Starcheck works with the expert system HRorganizer.
After a candidate or employee completes an online assessment, an expert system generates a report identifying the candidate’s potential in job-relevant competencies.
The test score report is also generated from an online assessment. The test score report includes all underlying items that can explain potential behaviors (competencies).
The personal report is also generated from the online assessment. It is a report specifically intended for a candidate or employee. It concerns mainly instructional information. The report gives more insight into “who am I” and “what can I do”.
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This fact sheet provides an overview of the most commonly used (psychological) selection methods, both classical and modern. The figures are based on meta-analyses and dominant scientific literature.
| Method | Predictive validity (r) | Typical reliability |
|---|---|---|
| Cognitive ability (GMA test) | .51 | High (.85-.95) |
| Work test | .54 | High (inter-rater ≥.70) |
| Structured interview | .51 | Medium-high (.60-.75) |
| Unstructured interview | .18-.38 | Low-medium (.40-.55) |
| Integrity test | .41 | High (α ≥.80) |
| Conscientiousness (Big Five) | .31 | Medium-high (α ~.75-.85) |
| Job knowledge test | .48 | High (≥.80) |
| Years of service | .18 | Not applicable |
| Video/asynchronous interview (incl. AI) | .30-.40 | Good at structuring; algorithmically variable |
| Machine learning / algorithmic models | .20-.50 | Depends on dataset; generalizability limited |
| Serious games / game-based work samples | .35-.50 | High on objective metrics |
| Social media screening | .00-.20 | Low and variable |
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