**Yes. The strongest natural grouping is `Overall_Impact`, which splits students into three clearly separated segments.** The results of both queries are shown above. The segments differ steadily on every measure, and Daily_Usage_Hours moves in step with the impact label. | Segment | Share of students | Daily hours | Sleep (hrs) | Stress | Mental health | GPA | Late-night share | |---|---|---|---|---|---|---|---| | **Beneficial** | 3,681 (81.8%) | 4.42 | 7.03 | 11.16 | 84.26 | 3.55 | 0.54 | | **Neutral** | 654 (14.5%) | 8.50 | 5.48 | 22.30 | 63.42 | 3.00 | 0.82 | | **Negative** | 165 (3.7%) | 12.25 | 4.23 | 31.12 | 47.13 | 2.54 | 0.82 | - **The segments are well separated.** Moving from Beneficial to Neutral to Negative, average daily usage rises from 4.4 to 8.5 to 12.3 hours. Sleep falls from 7.0 to 4.2 hours and sleep quality from 2.72 to 1.04. Stress climbs from 11 to 31, mental health drops from 84 to 47, and GPA drops from 3.55 to 2.54. - **Usage hours look like the main driver.** The groups are ordered by daily hours, so usage bands (low, moderate, heavy) would likely recreate the same three segments without needing the label. - **Late-night use only separates the first group.** The share of late-night users is 0.54 for Beneficial and 0.82 for both Neutral and Negative. It marks the break from Beneficial but does not tell Neutral and Negative apart. - **The segments are very uneven in size.** The Negative group has only 165 students, so comparisons that cut it further, for example by platform or gender, will rest on small counts. **Caveats** - `Overall_Impact` looks like an outcome label, probably derived from the other measures rather than independently observed. The clean separation may partly reflect that, so treat it as a descriptive grouping, not proof that usage causes the differences. The data is observational. - I did not check whether the demographic columns (age, gender, academic level) or platform and device type form groupings of their own. They are the next candidates, but this evidence does not show whether they separate students as clearly.