Emptiness Inside: Languishing as Experienced by Generation Z Students
Bibliographic record
Abstract
Languishing, characterized by a lack of vitality, motivation, and engagement, has gained significant attention during the COVID-19 pandemic due to its impact on mental health. This study investigates the underlying factors and impacts of languishing among Generation Z students at Lipa City Colleges, exploring their experiences, daily life challenges, and coping mechanisms. Using a phenomenological design, participants aged 24 and below, identified through the Mental Health Continuum-Short Form and were purposefully selected. Thematic analysis, following Braun and Clarke's model, revealed four emerging themes: life transitions, emotional distress, apathy, and coping strategies (positive coping and avoidance). The findings indicate that life transitions contribute to feelings of languishing, leading to emotional distress and apathy, which affect their daily functioning. Participants employ both positive coping mechanisms and avoidance strategies. The study recommends collaboration among parents, instructors, program heads, and the institution's Guidance and Counseling Department to prioritize mental health support for Gen Z students. Future research should expand to include different age groups and generations, such as Generation X and Y, to provide a more comprehensive understanding of this phenomenon.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".