Enhancing self‐care, adjustment and engagement through mobile phones in youth with HIV.
Bibliographic record
Abstract
AIM: To evaluate the effectiveness of mobile phones in enhancing self-care, adjustment and engagement in non-disclosed youth living with HIV. BACKGROUND: Youth aged 15-24 years represent 42% of new HIV infections globally. Youth who are aware of their HIV status generally do not disclose it or utilize HIV-related facilities because of fear of stigma. They rely on the Internet for health maintenance information and access formal care only when immune-compromised and in crisis. INTRODUCTION: This study shows how non-disclosed youth living with HIV can be reached and engaged for self-management and adjustment through mobile phone. STUDY DESIGN: One-group pre-test/post-test experimental design was used. METHODS: Mobile phones were used to give information, motivation and counselling to 19 purposively recruited non-disclosed youth with HIV in Calabar, South-South Nigeria. Psychological adjustment scale, modified self-care capacity scale and patient activation measure were used to collect data. Data were analysed using PASW 18.0. RESULTS: Scores on self-care capacity, psychological adjustment and engagement increased significantly at post-test. HIV-related visits to health facilities did not improve significantly even at 6 months. Participants still preferred to consult healthcare providers for counselling through mobile phone. DISCUSSION: Mobile phone-based interventions are low cost, convenient, ensure privacy and are suitable for youth. Such remote health counselling enhances self-management and positive living. CONCLUSION AND IMPLICATIONS FOR HEALTH POLICY: Mobile phones enhance self-care, psychological adjustment and engagement in non-disclosed youth living with HIV, and can be used to increase care coverage. Findings underline the importance of policies to increase access by locating, counselling and engaging HIV-infected youth in care.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".