Integrated Care: A PTSD diagnostic mechanism for a refugee reception centre
Notice bibliographique
Résumé
IntroductionWithin the 65 million displaced people, many are dealing with post-traumatic stress disorder (PTSD). According to the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV), PTSD derives from witnessing of violence and crime. Among the symptoms are avoidance of trauma-related stimuli, negative thoughts and alterations in arousal and reactivity. PTSD seriously affects functionality and transition to the new society and therefore, thorough screening is highly recommended. Assessment solely through a PTSD-related questionnaire cannot be satisfactory to reveal the difficulties faced and the intervention needed. A possible way to provide a holistic approach in dealing with PTSD, is to conduct a battery of tests in combination with simple technological aids.Theory/Methods Assessment and treatment of PTSD requires the coordination of a multi-disciplinary group that is usually lacking in refugee reception centres. The suggested set of assessments does not require application by a clinician and may serve as a solid base upon which to build the treatment plan. The aim is to explore whether the use of a battery of tests along with a smart band and a Galvanic Skin Response (GSR) sensor will provide more accurate diagnostic results, allowing a thorough assessment of the mental, functional and occupational state for refugees living in reception centers and thus, multi-disciplinary intervention planning. The Davidson Trauma Scale (DTS), the Stressful Life Events Screening Questionnaire and the Canadian Occupational Performance Measure (COPM) will be applied to adult refugees residing at Kofinou Reception Center in Cyprus. Occupational therapy students supervised by a professional will apply the tests to approximately 100 participants. This will be a within-subjects design, meant to empower the diagnostic phase of intervention. In Stage A: Participants will be wearing a wrist band for one week to record the number of steps, hours of sleep (deep / light) and heart rate. In Stage B: A Questionnaire application will be conducted, while participants will be wearing a GSR sensor to determine their relative stress levels. Results will be uploaded on a cloud-based Electronic Health Record (HER) to be further processed by a multidisciplinary group.Results / DiscussionsTreatment for PTSD involves psychotherapy, medication and occupational therapy, each of which requires a thorough assessment beforehand to design a client-centered intervention strategy. Treatment may focus on dealing with negative thoughts, learning ways to cope with symptoms, minimizing depression, anxiety, or misuse of alcohol or drugs and engaging in meaningful occupations.ConclusionsCombining a battery of tests along with introducing smart wearable technologies will provide a thorough assessment and further intervention for refugees living in reception centers. This is a critical process given the vast number of refugees arriving on a daily basis in Cyprus and Greece .Suggestions for future research Application of the assessment battery by non-clinicians may be one of the next steps. Furthermore, Machine Learning / Artificial Intelligence techniques may be used to process results stored on the cloud in order to provide early stage indications of PTSD.
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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 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,034 | 0,002 |
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 ».