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Enregistrement W754774650 · doi:10.1044/leader.ftr2.14152009.23

Lost and Found After 40 Years: An SLP’s Determination Helps a Man with Aphasia Find His Family

2009· article· en· W754774650 sur OpenAlexaboutno aff
Kellie Rowden-Racette

Notice bibliographique

RevueASHA Leader · 2009
Typearticle
Langueen
DomaineHealth Professions
ThématiqueInterpreting and Communication in Healthcare
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAphasiaPsychologyAshaMedicineLinguisticsPsychiatryPhilosophy

Résumé

récupéré en direct d'OpenAlex

You have accessThe ASHA LeaderFeature1 Nov 2009Lost and Found After 40 Years: An SLP’s Determination Helps a Man with Aphasia Find His Family Kellie Rowden-Racette Kellie Rowden-Racette Google Scholar More articles by this author https://doi.org/10.1044/leader.FTR2.14152009.23 SectionsAbout ToolsAdd to favorites ShareFacebookTwitterLinked In When state police found 80-year-old Bob Lance wandering along the side of Interstate 90 in Montana last May, he was unable to talk or communicate even the most basic information—his name, where he was from, or where he was going. Not knowing what to do, officers brought him to a hospital in Billings, Mont., where he had a brain scan. After doctors determined that Lance had a hematoma and suffered from global aphasia, he was released from the hospital, admitted to a nearby skilled nursing facility, and placed in the care of speech-language pathologist Jonalyn Brown. “I had worked with other patients with aphasia before,” Brown said. “But he was different. It was his personality that struck me. He was so friendly and so determined to work with me. I’d work with him and he’d go away, but come back for more. He really wanted to communicate and was determined to get to where he was going.” Luckily for Lance, Brown was equally determined to help and didn’t stop working with him even when his sessions were up. Although Lance’s speech was beginning to come along, much of what he told her was in pieces as he regained his cognitive function. She also wanted him to get to where he was going but needed to gather more clues. “He kept talking about a tourist destination near the Canadian border, but when I’d ask if that’s where he was going, he’d insist that it wasn’t,” Brown said. “Finally after a few weeks of working with him, the city of Toronto came up and he said, ‘Oh, yes!’” So Brown looked up phone numbers under the name “Lance” in Toronto and started calling. The first person she reached hung up but the second person to answer the phone turned out to be Lance’s older brother, Arthur. Not able to hear well, Arthur gave Brown the number of his younger sister. She, too, had trouble hearing and passed Brown on to yet another younger sibling. Finally, after several passes, Brown spoke with a family member who could both hear her and understand what she was saying: She had found their brother, Bob, whom they had not heard from in 20 years. He had been living in Seattle for the past 40 years and now he wanted to come home. The reaction, said Brown, was tremendous. They wanted him home, too. “I felt like a social worker, but because it was so easy for me to do this research and I was invested in his outcome, I just did it,” said Brown. “I wanted him to find his home.” Once Lance rediscovered where he was going, Brown helped him get his passport and medical records in order, which had many therapeutic benefits. “We went everywhere in the community to get his documents,” she said. “We filled out all the paperwork, and he made phone calls to confirm who he was. It was actually really good therapy for him.” And all is well that ends well. Lance has been reunited with his brothers and sisters and has returned to Toronto. As for Brown, she has gone back to business as usual, but she will always remember her determined patient who wouldn’t give up. “He was unique. Even though he had typical global aphasia, his personality and history were compelling,” she said. “I guess I’ll never meet another patient like him, but you never know!” Author Notes Kellie Rowden-Racette, print and online editor for The ASHA Leader, can be reached at [email protected]. Advertising Disclaimer | Advertise With Us Advertising Disclaimer | Advertise With Us Additional Resources FiguresSourcesRelatedDetails Volume 14Issue 15November 2009 Get Permissions Add to your Mendeley library History Published in print: Nov 1, 2009 Metrics Current downloads: 90 Topicsasha-topicsleader_do_tagasha-article-typesleader-topicsCopyright & Permissions© 2009 American Speech-Language-Hearing AssociationLoading ...

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)0,001
score de la tête « metaresearch » (Gemma)0,006
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Étude de cas · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,155
Score d'incertitude au seuil0,518

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,006
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0060,001
Communication savante0,0030,005
Science ouverte0,0010,004
Intégrité de la recherche0,0030,005
Charge utile insuffisante (le modèle a refusé de juger)0,1550,064

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 Opus0,067
Tête enseignante GPT0,418
Écart entre enseignants0,351 · 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'étudeÉtude de cas
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

Citations0
Publié2009
Routes d'admission1
Résumé présentoui

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