COVID-19 Pandemic: Age-Related Differences in Measures of Stress, Anxiety and Depression in Canada
Bibliographic record
Abstract
BACKGROUND: The spread of COVID-19 along with strict public health measures have resulted in unintended adverse effects, including greater levels of distress, anxiety, and depression. This study examined relative presentations of these psychopathologies in different age groups in a Canadian cohort during the COVID-19 pandemic. METHODOLOGY: Participants were subscribers to the Text4Hope program, developed to support Albertans during the COVID-19 pandemic. A survey link was used to gather demographic information and responses on several self-report scales, such as Perceived Stress Scale (PSS), Generalized Anxiety Disorder 7-item (GAD-7) scale, and Patient Health Questionnaire-9 (PHQ-9). RESULTS: There were 8267 individuals who completed the survey, giving a response rate of 19.4%. Overall, 909 (11.0%) respondents identified as ≤25 years, 2939 (35.6%) identified as (26-40) years, 3431 (41.5%) identified as (41-60) years, 762 (9.2%) identified as over 60 years, and 226 (2.7%) did not identify their age. Mean scores on the PSS, GAD-7, and PHQ-9 scales were highest among those aged ≤25 and lowest amongst those aged >60 years old. CONCLUSIONS: The finding that the prevalence rates and the mean scores for stress, anxiety, and depression on standardized scales to decrease from younger to older subscribers is an interesting observation with potential implications for planning to meet mental health service needs during COVID-19.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".