Examples of mental health campaigns targeted at men
Bibliographic record
Abstract
Men commit suicide more frequently than women in nearly all parts of the world. This is due to a number of factors, including the fact that women tend to seek mental help relatively more often than men. Many developed countries have attempted to implement suicide prevention programmes and initiatives, but only a small proportion of these have targeted men directly. The aims of this paper are to highlight preventive measures focusing on mental problems experienced specifically by men, and provide a detailed description of these measures. Consequently, the paper has both theoretical and practical dimensions, outlining the challenges and presenting potential solutions. The study discusses selected examples of mental health actions targeting men which were carried out in several countries around the world including Japan (“Daddy, have you slept well?”), UK (“Heads Up” campaign), United States (“Real men. Real depression”), Canada (“HeadsUpGuys” campaign), and Australia (Movember), as well as social media campaigns (Instagram: #HereForYou). Men are often reluctant to reveal their mental problems (stress, low mood, insomnia, suicidal ideation), which can be attributed to the so-called macho culture existing in societies. The man is traditionally considered head of the family, a guardian and leader, a strong personality, and a person to rely on. This perception contributes to the fact that men tend not to admit their weaknesses in front of family or friends. It is recommended that preventive actions take into account such aspects as the transfer of knowledge, skills and competences in the areas of identification of mental problems, and abilities to cope with a crisis situation. Mental health actions should be launched in areas frequently visited by men including workplaces, buses, pubs, bars, sports clubs, stadiums or other meeting places, so that the information can reach the largest possible target group.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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; both teacher heads agree on what is shown here.
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".