社会心理的
三级护理
相(物质)
医学
材料科学
口腔正畸科
化学
家庭医学
精神科
有机化学
作者
Maria Hietaharju,Ida Kivimäki,Henriikka Heikkilä,Ritva Näpänkangas,Tuija Teerijoki‐Oksa,Johanna Tanner,Pentti Kemppainen,Mimmi Tolvanen,Tuija Suvinen,Kirsi Sipilä
摘要
Abstract Background The Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) and Diagnostic Criteria for TMD (DC/TMD) include Axis II instruments for psychosocial assessment. Objectives The aims were to compare the Finnish versions of Axis II psychosocial assessment methods of the RDC/TMD and DC/TMD and to study their internal reliability. Methods The sample comprised 197 tertiary care referral TMD pain patients. The associations between RDC/TMD [Graded Chronic Pain Scale (GCPS) 1.0, Symptom Check List 90‐revised (SCL‐90R)] and DC/TMD (GCPS 2.0, Patient Health Questionnaire‐9 (PHQ‐9), PHQ‐15) assessment instruments were evaluated using Spearman correlation coefficients, Wilcoxon Signed Rank s, chi‐squared test and gamma statistics. The internal reliability and internal inter‐item consistency of SCL‐90‐R, PHQ‐9, PHQ‐15 and Generalized Anxiety Disorder‐7 (GAD‐7) were evaluated using Cronbach's alpha coefficient values. Results The DC/TMD and RDC/TMD Axis II psychosocial instruments correlated strongly ( p < .001). GCPS 1.0 and GCPS 2.0 grades were similarly distributed based on both criteria. The RDC/TMD psychological instruments had a higher tendency to subclassify patients with more severe symptoms of depression and non‐specific physical symptoms compared to DC/TMD. The internal reliability and internal inter‐item consistency were high for the psychological assessment instruments. Conclusion The Finnish versions of the RDC/TMD and DC/TMD Axis II psychosocial instruments correlated strongly among tertiary care TMD pain patients. Furthermore, the Axis II psychological assessment instruments indicated high validity and internal inter‐item consistency and are applicable in Finnish TMD pain patients as part of other comprehensive specialist level assessments, but further psychometric and cut‐off evaluations are still needed.
科研通智能强力驱动
Strongly Powered by AbleSci AI