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Enregistrement W2887766048 · doi:10.1093/pch/pxy101

A mother’s fear from Uganda: A story told and lessons to be learned

2018· article· en· W2887766048 sur OpenAlexfundno aff
Teddy Kyomuhangi

Notice bibliographique

RevuePaediatrics & Child Health · 2018
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueHIV/AIDS Impact and Responses
Établissements canadiensnon disponible
Organismes subventionnairesMicroResearch
Mots-clésPsychologyMedicineDevelopmental psychology

Résumé

récupéré en direct d'OpenAlex

The story of a mother, Mirembe (not her real name) This is a real-life story of one mother’s experience as she sought health care services to save the life of her child. The story provides a spectrum of lessons to health care providers as it brings out the expectations of both patients and caregivers. At age 23, Mirembe had had four pregnancies. However, she had only one living child who was 3 years old. There is a strong belief in witchcraft in Mirembe’s community, related to school completion. Mirembe stopped school in grade three as she believed that she would have been harmed by neighbours if she had completed grade seven. She lived with her husband who earned his income through tea growing. When I visited Mirembe at home, she shared her story about the recent death of her child. Omwana wangye akazarwa aine amagara marungi (My child had good health at birth); she looked like any other normal child. She suddenly got sick; I tried to take her to clinic but there was no improvement. She got worse when she started vomiting everything and developed diarrhea at the same time. Finally, my husband and I decided to take her to a government health centre where we met doctors from a higher-level hospital and they offered to refer and take us with them to hospital. This raised some hope that our child would get better. I went with my husband. I knew doctors were going to use a scan and tell me what my child was suffering from. This was important because I had a feeling that my child had been bewitched. My husband had a quarrel with someone who claimed that we had stolen his UGX 50,000 (20 Canadian dollars). This happened the past Saturday and the following Wednesday, the health of my child became worse, so I thought this man could be the cause. When we reached the hospital, my child was admitted, started feeding in a tube and was put on oxygen. Before the baby got fine, a nurse came and removed the oxygen, yet the baby’s condition was not improving. The doctor came later and asked who removed the oxygen. I did not know the name of the nurse because I could not read her tag. The doctor put back the oxygen. I started asking myself if my baby was in safe hands. Another nurse took a blood sample but did not bring the results. The doctor asked me where the results were but I could not remember the name of the nurse. Remember, this was my first time to go outside my village. Everything was new to me. It was as if I was abroad. On top of a lot of learning, I was always asked which nurse did this and that, as if these are people I stay with and therefore know their names. Young nurses speak in English which was so hard for me. At least senior nurses spoke in my language and are more close to us, but they are not many. In hospital, there are no supplies. One is asked to buy everything otherwise, you keep waiting. When my husband went home to look for money, I stayed alone and was asked to buy some things which I could not afford. My child missed treatment three times, which made me lose hope that she would get fine. I accepted to come to hospital because I knew they were going to tell me the problem of my child but no one told me. I wanted someone to do a scan of the stomach of my child and tell me what the problem was. I decided to go back home before my child died in the hospital. I fear dead bodies, and here I was alone in the hospital. At least at home my mother-in-law could help when the baby dies. I got up very early and hired a motorcycle and driver and went back home. I could not go by taxi; taxis can be slow and I feared the baby could die on the way in case of delays. At home everybody saw that the baby was too ill to get well and therefore advised me not to go to any other health facility. In the evening of the same day I arrived home, my child passed on. This problem is common in children in my community. Even my neighbour’s child has the same condition. Most children here are dying of the ‘disease of wounds’. You can see the wounds in the mouth and they are also in the stomach. A lot of children have died of this problem here. We need help! Not everyone can go to hospital. Our clinics are good; they treat our children and accept payments in bits, but here we produce a lot of children and treatment is very expensive. We fear using family planning due to its side effects. The experience can be bad and when you do not produce children, your husband will marry other wives. There are many lessons here for all of us who provide care, regardless of the setting. This mother and this village need help and understanding. We in the formal health system all too often do not explain what is going on in terms that mothers such as this can understand. This is not just a low-income country problem. Variations can be seen around the globe and across health systems. Trust is only built through good communication—the best care can fail to be accepted and followed if trust is not built. We are grateful that this mother agreed to have her story told so that we and others may learn. We acknowledge the help of MicroResearch in preparing the manuscript.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,018
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,024
Score d'incertitude au seuil0,061

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,018
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0220,011
Communication savante0,0080,010
Science ouverte0,0020,008
Intégrité de la recherche0,0150,032
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

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.

Tête enseignante Opus0,045
Tête enseignante GPT0,289
Écart entre enseignants0,244 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations6
Publié2018
Routes d'admission1
Résumé présentnon

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