Understanding the health context for implementation of a new digital psychosocial intervention for improvement of the mental health in North Macedonia
Bibliographic record
Abstract
The aim of this study was to identify the contextual attributes in North Macedonia and their characteristics relevant to the implementation of a new digital intervention to improve mental health, called DIALOG+. This research is the first of its kind in North Macedonia due to the analysis of contextual attributes that may affect the effectiveness of the intervention and its acceptability in various settings of mental health care. Some of the data processed in this paper were provided and analyzed by the National Mental Health Strategy 2018-2025 and other relevant accompanying documents from the World Health Organization and action plans, as well as through interviews with stakeholders (patients, carers, clinicians and policy makers) for their opinion before introducing the DIALOG + intervention and the report on the assessment of the situation in the centers where the implementation of the intervention should have started. The collected data were then mapped to a framework developed by the Ottawa Implementation Group, which included 14 contextual attributes. The results are summarized in 2 subgroups, and are presented as facilitators and barriers to implementation, specific to the mental health system in North Macedonia. The characteristics of DIALOG + (widely applicable psychosocial intervention) are in accordance with modern assumptions for psychosocial rehabilitation of patients with psychosis. Hence, we can conclude that it is a useful tool for professionals in monitoring and achieving the true vision and mission of these institutions. It will help patients reintegrate into society, become more independent and use their full potential in the pursuit of healthy and functional living.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".