Health managers’ views on the status of national and decentralized health systems for child and adolescent mental health in Uganda: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Robust health systems are required for the promotion of child and adolescent mental health (CAMH). In low and middle income countries such as Uganda neuropsychiatric illness in childhood and adolescence represent 15-30 % of all loss in disability-adjusted life years. In spite of this burden, service systems in these countries are weak. The objective of our assessment was to explore strengths and weaknesses of CAMH systems at national and district level in Uganda from a management perspective. METHODS: Seven key informant interviews were conducted during July to October 2014 in Kampala and Mbale district, Eastern Uganda representing the national and district level, respectively. The key informants selected were all public officials responsible for supervision of CAMH services at the two levels. The interview guide included the following CAMH domains based on the WHO Assessment Instrument for Mental Health Systems (WHO-AIMS): policy and legislation, financing, service delivery, health workforce, medicines and health information management. Inductive thematic analysis was applied in which the text in data transcripts was reduced to thematic codes. Patterns were then identified in the relations among the codes. RESULTS: Eleven themes emerged from the six domains of enquiry in the WHO-AIMS. A CAMH policy has been drafted to complement the national mental health policy, however district managers did not know about it. All managers at the district level cited inadequate national mental health policies. The existing laws were considered sufficient for the promotion of CAMH, however CAMH financing and services were noted by all as inadequate. CAMH services were noted to be absent at lower health centers and lacked integration with other health sector services. Insufficient CAMH workforce was widely reported, and was noted to affect medicines availability. Lastly, unlike national level managers, lower level managers considered the health management information system as being insufficient for service planning. CONCLUSION: Managers at national and district level agree that most components of the CAMH system in Uganda are weak; but perceptions about CAMH policy and health information systems were divergent.
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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 | 0.018 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.009 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".