Experiences of patients diagnosed with drug susceptible tuberculosis regarding lost to follow-up in Engela district, Ohangwena region
Notice bibliographique
Résumé
Lost to Follow-Up (LTFU) amongst Tuberculosis (TB) patients is referred to as a patient diagnosed with TB who interrupts treatment for two consecutive months or more. LTFU has been cited as a major risk factor for the re-emergence of TB strains resistant to first line anti-tuberculosis drugs. Namibia has been reporting increasing levels of patients LTFU over time, with some districts such as Engela reporting a 10% LTFU in quarter 4 of 2017 and 11% in quarter 1 of 2018 and constantly failing to attain the WHO recommended LTFU of below 5%. Patients diagnosed with drug-susceptible TB and registered for treatment after lost to follow up might have different experiences that can lead to them defaulting on treatment and being lost to follow up. Therefore, it was necessary to conduct a study aimed at exploring and describing the experiences of patients diagnosed with drug-susceptible and registered patients LFTU in Engela District, Ohangwena Region. Qualitative research with exploratory, descriptive and contextual designs were used in this study. The data was collected through in-depth interviews conducted at different sites in Ohangwena Region. A sample of 11 patients diagnosed with drug-susceptible TB and registered as patients LFTU were selected using a purposive sampling technique. The sample size was determined by saturation of data as reflected in repeating themes. Interviews were recorded and field notes were taken during the interview to ensure that all experiences of the participants were captured. The data was analysed using Tesch’s eight steps of coding. The results showed that patients diagnosed with drug-susceptible TB had different experiences that led to the patients being lost to follow up on TB treatment. Some patients experienced physical malaise prior to being diagnosed with TB, while others experienced chest pain. The participants iii became lost to follow up to their TB treatment for various reasons such as a lack of adequate information upon commencement of TB treatment and the importance of adherence to therapy, stigma at work and in the community, alcohol indulgence, a lack of proper nutrition and having travelled far away from the area where they initiated treatment. The study recommends the development of holistic LTFU mitigation strategies/interventions aimed at improving organisational and administrative health system challenges impeding health education delivery to patients and the communities and provision of patient-centred care by health care workers. Further, it is important to look into addressing stigma issues and changing labour policies and laws that disadvantage sick people in the workplace and lead them to default therapy.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,004 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».