Dataset Information

The Development and Psychometric Validation of the Diabetes Impact and Device Satisfaction Scale for Individuals with Type 1 Diabetes.

ABSTRACT:

Background

With the rapid development of new insulin delivery technology, measuring patient experience has become especially pertinent. The current study reports on item development, psychometric validation, and intended use of the newly developed Diabetes Impact and Device Satisfaction (DIDS) Scale.

Method

The DIDS Scale was informed by a comprehensive literature review, and field tested as part of two focus groups. The finalized measure was used at baseline and 6?months post-assessment with a large US cohort. Exploratory factor analyses (EFAs) were conducted to determine and confirm factor structure and item selection. Internal reliability, test-retest reliability, and convergent/divergent validity of the emerged factors were tested with demographics, diabetes-specific information, and diabetes behavioral and satisfaction measures.

Results

In all, 778 participants with type 1 diabetes (66% female, mean age 47.13?±?17.76?years, 74% insulin pump users) completed surveys at both baseline and post-assessment. EFA highlighted two factors-Device Satisfaction (seven items, Cronbach's ? = 0.85-0.90) and Diabetes Impact (four items, Cronbach's ? = 0.71-0.75). DIDS Scale demonstrated good concurrent validity and test-retest reliability.

Conclusion

The DIDS Scale is a novel and a brief assessment tool with robust psychometric properties. It is recommended for use across all insulin delivery devices and is considered appropriate for use in longitudinal studies. Future studies are recommended to evaluate the performance of DIDS Scale in diverse populations with diabetes.

SUBMITTER: Manning ML

PROVIDER: S-EPMC7196859 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The Development and Psychometric Validation of the Diabetes Impact and Device Satisfaction Scale for Individuals with Type 1 Diabetes.

Manning Michelle L ML Singh Harsimran H Stoner Keaton K Habif Steph S

Journal of diabetes science and technology 20200206 2

<h4>Background</h4>With the rapid development of new insulin delivery technology, measuring patient experience has become especially pertinent. The current study reports on item development, psychometric validation, and intended use of the newly developed Diabetes Impact and Device Satisfaction (DIDS) Scale.<h4>Method</h4>The DIDS Scale was informed by a comprehensive literature review, and field tested as part of two focus groups. The finalized measure was used at baseline and 6 months post-ass ...[more]

PMID: 32028790

Similar Datasets

Project description:BackgroundThe objective of this study was to develop the Chinese version of the biopsychosocial impact scale (BPIm-S) to assess functional limitation and psychosocial distress in orofacial pain (OFP) patients in mainland China, and investigate the factor structure, reliability and validity, measurement invariance, as well as scores differences across genders, age and educational status among OFP patients.MethodsThe BPIm-S was developed and evaluated in four stages: (1) concept selection and item generation; (2) a pilot study assessing face and content validity; (3) the factors structure, reliability, convergent validity, and measurement invariance; and (4) concurrent validity and clinical responsiveness. Exploratory (EFA) and confirmatory factor analyses (CFA) were performed on data gathered from 406 OFP patients to assess construct validity. Composite Reliability (CR) and the Average Variance Extracted (AVE) were used to assess internal convergent validity. CR, internal consistency, and split-half reliability were also performed to determine the reliability. Multigroup CFA (MGCFA) was used to assess measurement invariance across genders, age and educational status. Mann-Whitney test compared scores across different genders, age and educational status. Participants completed the BPIm-S, visual analog scale (VAS), brief pain inventory facial (BPI-F), General Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire-9 (PHQ-9), and spearman's correlation coefficient was used to evaluate the concurrent validity and item-total correlations. A total of 12 patients with OFP completed the BPIm-S twice to test clinical responsiveness. To conduct the CFA and measurement invariance analysis, Mplus 8.4 was used. IBM SPSS Statistics 21 software and SPSSAU, a web-based data science algorithm platform tool, were used for all additional studies.ResultsFor the preliminary version, 17 items were chosen. A total of four items were removed following the pilot research. The remaining 13 items of the BPIm-S comprised an overall summary scale. Excellent reliability (Item-to-total correlations ranged from 0.763 to 0.912) and strong internal consistency (Cronbach's α = 0.970, functional limitation, 0.962, and psychosocial distress, 0.977) were discovered. CFA also validated the structural validity of the 13-item scale. EFA was performed and a two-factor structure was investigated. In addition, MGCFA corroborated the measurement invariance of the BPIm-S across gender, age, and educational status. Patients over the age of 30, those with a medium level of education, and those with a low level of education showed substantially greater levels of functional limitation and psychological distress (Wilcoxon test, p < 0.001). Both concurrent validity and clinical responsiveness were assessed to be of good quality.ConclusionThe BPIm-S demonstrated good psychometric qualities and is a reliable tool that can now be used by clinicians to evaluate functional limitation and psychosocial distress among OFP patient.

Project description:ObjectiveAmid the COVID-19 pandemic, social stigma towards COVID-19 infection has become a major component of public discourse and social phenomena. As such, we aimed to develop and validate the COVID-19 Public Stigma Scale (COVID-PSS).Design and settingNational-based survey cross-sectional study during the lockdown in Thailand.ParticipantsWe invited the 4004 adult public to complete a set of measurement tools, including the COVID-PSS, global fear of COVID-19, perceived risk of COVID-19 infection, Bogardus Social Distance Scale, Pain Intensity Scale and Insomnia Severity Index.MethodsFactor structure dimensionality was constructed and reaffirmed with model fit by exploratory and confirmatory factor analyses and non-parametric item response theory (IRT) analysis. Psychometric properties for validity and reliability were tested. An anchor-based approach was performed for classifying the proper cut-off scores.ResultsAfter factor analysis, IRT analysis and test for model fit, we created the final 10-item COVID-PSS with a three-factor structure: stereotype, prejudice and fear. Face and content validity were established through the public and experts' perspectives. The COVID-PSS was significantly correlated (Spearman rank, 95% CI) with the global fear of COVID-19 (0.68, 95% CI 0.66 to 0.70), perceived risk of COVID-19 infection (0.79, 95% CI 0.77 to 0.80) and the Bogardus Social Distance Scale (0.50, 95% CI 0.48 to 0.53), indicating good convergent validity. The correlation statistics between the COVID-PSS and the Pain Intensity Scale and Insomnia Severity Index were <0.2, supporting the discriminant validity. The reliability of the COVID-PSS was satisfactory, with good internal consistency (Cronbach's α of 0.85, 95% CI 0.84 to 0.86) and test-retest reproducibility (intraclass correlation of 0.94, 95% CI 0.86 to 0.96). The proposed cut-off scores were as follows: no/minimal (≤18), moderate (19-25) and high (≥26) public stigma towards COVID-19 infection.ConclusionsThe COVID-PSS is practical and suitable for measuring stigma towards COVID-19 in a public health survey. However, cross-cultural adaptation may be needed.

Dataset Information

The Development and Psychometric Validation of the Diabetes Impact and Device Satisfaction Scale for Individuals with Type 1 Diabetes.

Background

Method

Results

Conclusion

Publications

The Development and Psychometric Validation of the Diabetes Impact and Device Satisfaction Scale for Individuals with Type 1 Diabetes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets