Kidney Week

Abstract: PUB153

Self-Efficacy Predicts Patient-Reported Outcomes Measurement Information System (PROMIS) Health-Related Quality of Life Outcomes in Turkish Patients on Dialysis Better than the 36-Item Short Form Health Survey (SF-36)

Session Information

• Publication Only

Category: Dialysis

• 801 Dialysis: Hemodialysis and Frequent Dialysis

Authors

• Cromm, Krister, Fresenius Medical Care Deutschland GmbH, Bad Homburg, Hessen, Germany

Krister Cromm, MA, MS, MSc, MBA

• Pham, Ngoc, Fresenius Medical Care Deutschland GmbH, Bad Homburg, Hessen, Germany

Ngoc Pham, MSc

• Tunçel, Özlem Kuman, Ege Universitesi, Izmir, İzmir, Turkey

Özlem Kuman Tunçel, MD, PhD

• Humpert, Mirja, Fresenius Medical Care Deutschland GmbH, Bad Homburg, Hessen, Germany

Mirja Humpert

• De los Ríos, Tatiana, Fresenius Medical Care Deutschland GmbH, Bad Homburg, Hessen, Germany

Tatiana De los Ríos

• Stauss-Grabo, Manuela, Fresenius Medical Care Deutschland GmbH, Bad Homburg, Hessen, Germany

Manuela Stauss-Grabo, PhD

• Asci, Gulay, Ege Universitesi, Izmir, İzmir, Turkey

Gulay Asci, MD

• Ok, Ercan, Ege Universitesi, Izmir, İzmir, Turkey

Ercan Ok, MD

• Elbi, Hayriye, Ege Universitesi, Izmir, İzmir, Turkey

Hayriye Elbi, DrMed

Background

Recent research has emphasized the importance of psychosocial factors on health-related quality of life (HRQL). Self-efficacy (SE) and social support (SS) emerged as particularly relevant. The purpose of this study was to understand the degree to which these two variables are also useful in predicting HRQL in Turkish patients using standard SF-36 and new PROMIS-29 measures.

Methods

177 patients (mean age: 55.5±13.4) on in-center or home hemodialysis in Izmir, Turkey filled out electronic surveys. A series of ANCOVA models was employed to examine the relationship between HRQL scores and domains as dependent variables, and SE and SS as predictor variables. HRQL was measured by SF-36 mental (MCS) and physical composite scores (PCS), PROMIS mental (MHS) and physical health (PHS) composite scores as well as 7 PROMIS-29 domain scores. SE and SS were measured with the MOS-SSS and GSE scales. Covariates included demographic characteristics and disease impact (KDQOL-36 burden, symptoms, and effects of kidney disease scales).

Results

SE was a significant predictor for MHS (F(1,138)=19.57, p<.0001; R²=.60 for whole MHS model) as well as MCS (F(1,138)=5.84, p=0.02; R²=.47 for whole MCS model) over and above the covariates. SE was related to PHS (F(1,138)=5.52, p=0.02; R²=.43 for whole PHS model) but not to PCS. SS was not significantly related to any composite scores. SE was a significant predictor for all PROMIS-29 domains except for Physical Function and Pain Intensity. The Tangible Support domain of SS was a significant predictor for Sleep Disturbance only (F(1,138)=4.27, p=0.04; R²=.42 for whole Sleep Disturbance model).

Conclusion

In line with previous research, our results show that SE is a significant predictor for mental health. PROMIS includes a broader range of HRQL subdomains than SF-36, leading to more explained variance of SE on physical health. This suggests that PROMIS may provide a more sensitive assessment of HRQL. The Social Support domains appear to be less useful for predicting HRQL, though the Tangible Support domain does show a relationship with the PROMIS-29 Sleep Disturbance domain.

Funding

• Commercial Support – Fresenius Medical Care