The Relationship Between Physical Activity, Depression and Symptom Burden in individuals With Persistent Post Concussion Symptoms : a Chart Review
Notice bibliographique
Résumé
INTRODUCTION: Individuals with Persistent Post Concussion Symptoms (PPCS) are at greater risk for depression and often experience exercise intolerance contributing to increased sedentary activity. Physical activity (PA) alone has been shown to reduce symptoms of mild to moderate depression to the same extent as standard treatments. Additionally, people who are regularly physically active assign higher ratings to their mental health. In Canadian youth, both physical inactivity and sedentary activity were significantly related to symptoms of depression. While there is increasing evidence that aerobic exercise following concussion can improve recovery, the relationship between depression, PA and symptom burden in individuals with PPCS has not been characterized. OBJECTIVE/HYPOTHESIS: This study seeks to shed light on the relationship between depression, PA and symptom burden in adults with PPCS. We anticipate those with increased sedentary behavior and lower levels of PA will have greater depressive scores. Additionally, we hypothesize that those with greater symptom burden will have higher rates of depression, participate in less PA, and engage in more sedentary behaviors. METHODS: A prospective cohort chart study of adult patients referred to the Calgary Brain Injury Program at Foothills Medical Centre in Calgary, Alberta, CAN between 2012-2017 was conducted. Inclusion criteria was a diagnosis of both concussion and persistent concussion symptoms (i.e., greater than 3 months). Patient demographics and injury characteristics were collected. The Patient Health Questionnaire-9 (PHQ-9) was used to screen for depression. PA levels were measured using the Godin Leisure Time Exercise Questionnaire (GLTEQ), while sedentary behaviors were accessed using the Rapid Assessment Disuse Index (RADI). Symptom burden was quantified using The Rivermead Post Concussion Symptoms Questionnaire. Descriptive statistics were applied for patient demographics. Spearman correlations were run between the RADI inactivity risk index and PHQ-9 scores/ Rivermead scores and between the GLTEQ and PHQ-9 scores/ Rivermead scores. Spearman correlations were also run between PHQ-9 scores and Rivermead scores. RESULTS: Of the 604 records reviewed, 46 individuals (43% male, 57% female) met inclusion criteria. Participants had a mean age of 35.6 (13) years at time of injury with 46% having a history of prior head injury. Spearmanu2019s correlation analyses revealed no significant correlation between PA and depression or symptom burden. A significant positive correlation was found between the RADI inactivity risk index, and depression scores, rs (46) = .389, p = .008. Additionally, increased symptom burden was positively correlated with increased depression scores, rs (46) = .531, p < .001.CONCLUSION: These findings provide insight into the contribution of sedentary behavior to levels of depression in individuals with PPCS. This suggests that while the benefits of physical activity may be abundant, although not observed in this population, focus on decreasing sedentary behaviors should also be emphasized.
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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 | 0,003 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,011 | 0,012 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».