Spinal cord injury and quality of life: a systematic review of outcome measures
Notice bibliographique
Résumé
Study design: Systematic review. Study rationale: According to current estimates, there are more than 1 million people living with a spinal cord injury (SCI) in the United States alone. Given the potentially devastating impact of SCI on health-related quality of life (QoL), we sought to gain an improved understanding of QoL outcomes in SCI. Objective: To identify and describe common QoL outcomes measures in patients with SCI. Methods: A systematic review of the English-language literature was undertaken for articles published from 1998 through December 2010. Electronic databases and reference lists of key articles were searched to identify measures or indices used to evaluate QoL outcomes in patients with SCI. The titles and abstracts of the SCI peer-reviewed literature were searched to determine which of these outcome measures were most commonly used to evaluate QoL in patients with SCI. Results: We identified 27 outcome measures used to evaluate QoL in patients with SCI. In SCI literature, the six most commonly used objective outcome measures were the Short-form 36 (SF-36); Craig Handicap Assessment and Reporting Technique (CHART); Short-form 12 (SF-12); Sickness Impact Profile (SIP68); Reintegration to Normal Living Index (RNL); and Community Integration Questionnaire (CIQ). The six subjective measures that were most frequently used were the Satisfaction with Life Scale (SWLS); Quality of Life Index (QLI); Life Satisfaction Questionnaire (LISAT-9/-1); World Health Organization Quality of Life-BREF scale (WHOQOL-BREF); Perceived Quality of Life (PQOL); and global QoL. All six objective measures have been validated in an SCI population, and four of the six subjective measures have been similarly validated. Three of each of the objective and subjective measures have been reliability tested in a population with SCI. Conclusion: In addition to neurological and functional changes after SCI, QoL outcomes should be routinely assessed. Choice of appropriate QoL measure should be influenced by the study objectives and design, as well as the psychometric properties of the particular measure within the context of SCI. STUDY RATIONALE AND CONTEXT The World Health Organization’s International Classification of Functioning, Disability and Health encourages the incorporation of a comprehensive definition of health when examining patient-related outcomes after injury or disease 1. Accordingly, in evaluating recovery after spinal cord injury (SCI), there is increasing focus on evaluating patients’ changes in overall well-being, or quality of life (QoL), in addition to neurological and functional changes over time. To date, a QoL outcome assessment tool specific for and validated on patients with SCI remains elusive. One of the greatest challenges in achieving this goal remains creating a tool sensitive to the varied clinical spectrum of SCI, since the definition of QoL may vary dramatically depending on the level and severity of injury. Although we lack an SCI-specific QoL measurement tool, numerous QoL outcome measures intended for use on generic or disease-specific patient populations have been used in studies examining recovery after SCI. OBJECTIVES To identify and describe QoL outcome measures commonly used to assess patients with SCI and to evaluate which of these tools is most appropriate for the SCI population. MATERIALS AND METHODS Study design: Systematic review. Sampling: Search: PubMed; bibliographies of key articles. Dates searched: 1998 through December 2010. Inclusion criteria: (1) spinal cord injury (SCI); (2) adults 18 years and older; (3) studies reporting on QoL outcome measures. Exclusion criteria: (1) cancer; (2) infection; (3) children or adolescents. Outcomes: QoL stratified as „objective quality of life” or „subjective quality of life”2. Objective QoL refers to fulfilling the cultural and societal definitions of material wealth, social status, and physical well-being. Subjective QoL considers individuals‘ assessment of their emotions, happiness, or satisfaction with respect to their expectations and achievements. Analysis: identification of QoL outcome measures commonly reported in studies of patients with SCI and estimation of the frequency of their use in the SCI literature. Details about methods can be found in the web appendix at www.aospine.org / ebsj.
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 | 0,018 | 0,085 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,013 | 0,008 |
| Bibliométrie | 0,013 | 0,016 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».