Article

Efficiency of static and computer adaptive short forms compared to full-length measures of depressive symptoms.

Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
Quality of Life Research (Impact Factor: 2.86). 11/2009; 19(1):125-36. DOI: 10.1007/s11136-009-9560-5
Source: PubMed

ABSTRACT Short-form patient-reported outcome measures are popular because they minimize patient burden. We assessed the efficiency of static short forms and computer adaptive testing (CAT) using data from the Patient-Reported Outcomes Measurement Information System (PROMIS) project.
We evaluated the 28-item PROMIS depressive symptoms bank. We used post hoc simulations based on the PROMIS calibration sample to compare several short-form selection strategies and the PROMIS CAT to the total item bank score.
Compared with full-bank scores, all short forms and CAT produced highly correlated scores, but CAT outperformed each static short form in almost all criteria. However, short-form selection strategies performed only marginally worse than CAT. The performance gap observed in static forms was reduced by using a two-stage branching test format.
Using several polytomous items in a calibrated unidimensional bank to measure depressive symptoms yielded a CAT that provided marginally superior efficiency compared to static short forms. The efficiency of a two-stage semi-adaptive testing strategy was so close to CAT that it warrants further consideration and study.

0 Bookmarks
 · 
84 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: BACKGROUND Supportive oncology practice can be enhanced by the integration of a brief and validated electronic patient-reported outcome assessment into the electronic health record (EHR) and clinical workflow.METHODS Six hundred thirty-six women receiving gynecologic oncology outpatient care received instructions to complete clinical assessments through Epic MyChart, an EHR patient communication portal. Patient Reported Outcomes Measurement Information System (PROMIS) computer adaptive tests (CATs) were administered to assess fatigue, pain interference, physical function, depression, and anxiety. Checklists identified psychosocial concerns, informational and nutritional needs, and risk factors for inadequate nutrition. Assessment results, including PROMIS T scores with documented severity thresholds, were immediately populated in the EHR. Clinicians were notified of clinically elevated symptoms through EHR messages. EHR integration was designed to provide automated triage to social work providers for psychosocial concerns, to health educators for information, and to dietitians for nutrition-related concerns.RESULTSFour thousand forty-two MyChart messages sent, and 3203 (79%) were reviewed by patients. The assessment was started by 1493 patients (37%), and once they started, 93% (1386 patients) completed the assessment. According to first assessments only, 49.8% of the patients who reviewed the MyChart message completed the assessment. Mean PROMIS CAT T scores indicated a lower level of physical function and elevated anxiety in comparison with the general population. Fatigue, pain, and depression scores were comparable to those of the general population. Impaired physical functioning was the most common basis for clinical alerts and occurred in 4% of the patients.CONCLUSIONSPROMIS CATs were used to measure common cancer symptoms in routine oncology outpatient care. Immediate EHR integration facilitated the use of symptom reporting as the basis for referral to psychosocial and supportive care. Cancer 2014. © 2014 American Cancer Society.
    Cancer 11/2014; · 5.20 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Background: The Internet is used increasingly for both suicide research and prevention. To optimize online assessment of suicidal patients, there is a need for short, good-quality tools to assess elevated risk of future suicidal behavior. Computer adaptive testing (CAT) can be used to reduce response burden and improve accuracy, and make the available pencil-and-paper tools more appropriate for online administration. Objective: The aim was to test whether an item response–based computer adaptive simulation can be used to reduce the length of the Beck Scale for Suicide Ideation (BSS). Methods: The data used for our simulation was obtained from a large multicenter trial from The Netherlands: the Professionals in Training to STOP suicide (PITSTOP suicide) study. We applied a principal components analysis (PCA), confirmatory factor analysis (CFA), a graded response model (GRM), and simulated a CAT. Results: The scores of 505 patients were analyzed. Psychometric analyses showed the questionnaire to be unidimensional with good internal consistency. The computer adaptive simulation showed that for the estimation of elevation of risk of future suicidal behavior 4 items (instead of the full 19) were sufficient, on average. Conclusions: This study demonstrated that CAT can be applied successfully to reduce the length of the Dutch version of the BSS. We argue that the use of CAT can improve the accuracy and the response burden when assessing the risk of future suicidal behavior online. Because CAT can be daunting for clinicians and applied scientists, we offer a concrete example of our computer adaptive simulation of the Dutch version of the BSS at the end of the paper. (J Med Internet Res 2014;16(9):e207) doi:10.2196/jmir.3511
    Journal of Medical Internet Research 09/2014; 9. · 4.67 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Objective Total knee replacement (TKR) is the treatment option of choice for the millions of individuals whose osteoarthritis pain can no longer be managed through non-invasive methods. Over 500,000 TKRs are performed annually in the United States. Although most patients report improvement in pain and functioning following TKR, up to 30% report persistent pain that interferes with daily function. However, the reasons for poor outcomes are not clear. To best determine which patients are at risk for pain post TKR, a detailed and comprehensive approach is needed. In this article, we present the methodology of a study designed to identify a set of genetic, proteomic, clinical, demographic, psychosocial, and psychophysical risk factors for severe acute and chronic pain post TKR.DesignProspective longitudinal observational study.SettingUniversity Hospital System.SubjectsPatients scheduled for unilateral TKR with a target number of 150.Methods Prior to surgery, we collect demographic, psychosocial, and pain data. Biological data, including blood samples for genetic analyses, and serum, urine, and joint fluid for cytokine assessment are collected intraoperatively. Pain assessments as well as medication use are collected during each of the three days postsurgery. Additionally, pain and psychosocial information is collected 6 and 12 months following surgery.Conclusions This study, for the first time, captures the information on both genetic and “environmental” risk factors for acute and chronic pain post-TKR and has the potential to lead to the next step—multicenter large-scale studies on predictors and biomarkers of poor TKR outcomes as well as on tailored interventions and personalized medicine approaches for those at risk.
    Pain Medicine 08/2014; · 2.24 Impact Factor

Full-text (2 Sources)

Download
31 Downloads
Available from
May 29, 2014