Dataset Information

The National Institutes of Health measure of Healing Experience of All Life Stressors (NIH-HEALS): Factor analysis and validation.

ABSTRACT: Two hundred patients with severe and/or life-threatening disease were recruited form the NIH Clinical Center and participated in the validation of the NIH-HEALS, which included exploratory factor analysis, principal component analysis, reliability, convergent validity, and divergent validity analyses. Item-reducing principal components analysis and internal consistency and split-half reliability demonstrated excellent internal consistency and split-half reliability (Cronbach's alpha = 0.89, split-half reliability = 0.95). Exploratory factor analysis revealed a three-factor structure, namely Connection (including religious, spiritual, and interpersonal), Reflection & Introspection, and Trust & Acceptance. Seven items were not retained. Convergent and divergent validity of 35-item NIH-HEALS against other validated measures of healing and spirituality provided strong evidence for its validity. As predicted, the Healed factor of the Self-Integration Scale (SIS), and Meaning, Peace, and Faith factors of the Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being-12 Scale (FACIT-SP12) were all positively and significantly correlated with the NIH-HEALS and its three factors. Divergent validity was also confirmed by the significant negative correlation between the NIH-HEALS and the Codependent factor on the SIS. Confirmatory Factor Analyses revealed good model fit by GFI (0.96), adjusted GFI (0.95), SRMR (0.077), and RMSEA (0.065), supporting the use of the NIH-HEALS with 35 items.

SUBMITTER: Ameli R

PROVIDER: S-EPMC6291293 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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The National Institutes of Health measure of Healing Experience of All Life Stressors (NIH-HEALS): Factor analysis and validation.

Ameli Rezvan R Sinaii Ninet N Luna María José MJ Cheringal Julia J Gril Brunilde B Berger Ann A

PloS one 20181212 12

Two hundred patients with severe and/or life-threatening disease were recruited form the NIH Clinical Center and participated in the validation of the NIH-HEALS, which included exploratory factor analysis, principal component analysis, reliability, convergent validity, and divergent validity analyses. Item-reducing principal components analysis and internal consistency and split-half reliability demonstrated excellent internal consistency and split-half reliability (Cronbach's alpha = 0.89, spli ...[more]

PMID: 30540764

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Project description:BackgroundCancer is associated with trauma and stress which impacts the physical, psychological, and spiritual/existential well-being of patients. Psychological/behavioral healing may help alleviate this distress and the associated health-related suffering. Psycho-Social-Spiritual healing outcome measures are thus needed to stimulate service development. The NIH Healing Experiences in All Life Stressors (NIH-HEALS), is a novel 35-item measure of psycho-social-spiritual healing, developed in USA and is yet to be validated and adapted for use in African countries.ObjectivesThis study aimed to assess the face and content validity of the NIH-HEALS in the population of cancer patients in Uganda and to culturally adapt this measure.MethodsCross-sectional study using cognitive interviewing alongside standard piloting. We recruited adult (18 years and above) patients with advanced cancer from Hospice Africa Uganda. Interviews were conducted in two phases, using the think aloud technique and concurrent probing and were audio recorded. Phase 1 was used to identify initial concerns around clarity of the statements, and phase 2 further explored whether the issues of clarity had been addressed, alongside the standard cognitive interview parameters. The transcripts were imported into NVivo-12 analyzed using the content analysis technique and categorized using Tourengeau's information processing model.ResultsWe recruited thirty-five (35) patients: phase one (n = 5) two (n = 30). The median completion time was 20 minutes. Problems identified included comprehension of some statements, words, and phrases, suggestions to include local examples, highlighting of potentially sensitive statements that lean towards difficult conversations, and some cultural differences in the construction of the "Trust and Acceptance" construct, our sample showed less emphasis on family/friend relations. This feedback was used to adapt the NIH-HEALS for the local context.ConclusionThe NIH-HEALS has sufficient face and content validity properties to be used among palliative cancer patients in Uganda. We propose some changes to inform the adaptation of this measure for the local context.

Project description:The National Institutes of Health (NIH) Health Care Systems Research Collaboratory (NIH Collaboratory) seeks to produce generalizable knowledge about the conduct of pragmatic research in health systems. This analysis applied the PRECIS-2 pragmatic trial criteria to five NIH Collaboratory pragmatic trials to better understand 1) the pragmatic aspects of the design and implementation of treatments delivered in real world settings and 2) the usability of the PRECIS-2 criteria for assessing pragmatic features across studies and across time.Using the PRECIS-2 criteria, five pragmatic trials were each rated by eight raters. For each trial, we reviewed the original grant application and a required progress report written at the end of a 1-year planning period that included changes to the protocol or implementation approach. We calculated median scores and interrater reliability for each PRECIS domain and for the overall trial at both time points, as well as the differences in scores between the two time points. We also reviewed the rater comments associated with the scores.All five trials were rated to be more pragmatic than explanatory, with comments indicating that raters generally perceived them to closely mirror routine clinical care across multiple domains. The PRECIS-2 domains for which the trials were, on average, rated as most pragmatic on the 1 to 5 scale at the conclusion of the planning period included primary analysis (mean?=?4.7 (range?=?4.5 to 4.9)), recruitment (4.3 (3.6 to 4.8)), eligibility (4.1 (3.4 to 4.8)), setting (4.1 (4.0 to 4.4)), follow-up (4.1 (3.4 to 4.9)), and primary outcome (4.1 (3.5 to 4.9)). On average, the less pragmatic domains were organization (3.3 (2.6 to 4.4)), flexibility of intervention delivery (3.5 (2.1-4.5)), and flexibility of intervention adherence (3.8 (2.8-4.5)). Interrater agreement was modest but statistically significant for four trials (Gwet's AC1 statistic range 0.23 to 0.40) and the intraclass correlation coefficient ranged from 0.05 to 0.31. Rating challenges included assigning a single score for domains that may relate to both patients and care settings (that is, eligibility or recruitment) and determining to what extent aspects of complex research interventions differ from usual care.These five trials in diverse healthcare settings were rated as highly pragmatic using the PRECIS-2 criteria. Applying the tool generated insightful discussion about real-world design decisions but also highlighted challenges using the tool. PRECIS-2 raters would benefit from additional guidance about how to rate the interwoven patient and practice-level considerations that arise in pragmatic trials.Clinicaltrials.gov trial registrations: NCT02019225 , NCT01742065 , NCT02015455 , NCT02113592 , NCT02063867 .

Project description:Readmissions are a common problem in cardiac surgery. The goal of this study was to examine the frequency, timing, and associated risk factors for readmission after cardiac operations.A 10-center cohort study prospectively enrolled 5,158 adult cardiac surgical patients (5,059 included in analysis) to assess risk factors for infection after cardiac operations. Data were also collected on all-cause readmissions occurring within 65 days after the operation. Major outcomes included the readmission rate stratified by procedure type, cause of readmission, length of readmission stay, and discharge disposition after readmission. Multivariable Cox regression was used to determine risk factors for time to first readmission.The overall rate of readmission was 18.7% (number of readmissions, 945). When stratified by the most common procedure type, readmission rates were isolated coronary artery bypass grafting, 14.9% (n = 248); isolated valve, 18.3% (n = 337); and coronary artery bypass grafting plus valve, 25.0% (n = 169). The three most common causes of first readmission within 30 days were infection (17.1% [n = 115]), arrhythmia (17.1% [n = 115]), and volume overload (13.5% [n = 91]). More first readmissions occurred within 30 days (80.6% [n = 672]) than after 30 days (19.4% [n = 162]), and 50% of patients were readmitted within 22 days from the index operation. The median length of stay during the first readmission was 5 days. Discharge in 15.8% of readmitted patients (n = 128) was to a location other than home. Baseline patient characteristics associated with readmission included female gender, diabetes mellitus on medication, chronic obstructive pulmonary disease, elevated creatinine, lower hemoglobin, and longer operation time. More complex surgical procedures were associated with an increased risk of readmission compared with the coronary artery bypass grafting group.Nearly 1 of 5 patients who undergo cardiac operations require readmission, an outcome with significant health and economic implications. Management practices to avert in-hospital infections, reduce postoperative arrhythmias, and avoid volume overload offer important targets for quality improvement.

Project description:On August 6th, 2019, a two-day trans-agency scientific meeting was convened by the United States (U.S.) National Institute of Allergy and Infectious Diseases (NIAID/NIH) on the research and development of medical countermeasures (MCMs) and treatment strategies to mitigate synthetic opioid-induced toxicities. This trans-agency meeting was an initiative of the Chemical Countermeasures Research Program (CCRP) and organized by the NIAID in collaboration with the National Institute of Drug Abuse (NIDA), the Biomedical Advanced Research and Development Authority (BARDA), the Food and Drug Administration (FDA), and the Defense Threat Reduction Agency (DTRA). The CCRP is part of the larger NIH biodefense research program coordinated by NIAID, which also includes MCM research and development programs against biological, radiological, and nuclear threats. Its overarching goal is to integrate cutting-edge research and technological advances in science and medicine to enhance the nation's medical response capabilities during and after a public health emergency involving the deliberate or accidental release of toxic chemicals. The potential of a mass casualty public health event involving synthetic opioids is a rapidly growing concern. As such, the overall goals of this trans-agency meeting are to better understand opioid-induced toxicities and advance the development of MCMs to mitigate and reverse opioid-induced respiratory depression (OIRD) to prevent consequential mortality. The primary objectives of the meeting were (1) highlight the latest research on mechanisms of OIRD and related toxicities, animal models, diagnostics, delivery technologies, and emerging new treatment options to prevent lethality; (2) identify current knowledge gaps to advance medical countermeasure development; (3) hear from the U.S. FDA on regulatory considerations to support new technology and treatment approaches; and (4) provide a forum for networking and collaborative partnerships. To accomplish this, a diverse group of almost 200 US domestic and international subject matter experts spanning fundamental and translational research from academia, industry, and government came together in-person to share their collective expertise and experience in this important field. This report briefly summarizes the information presented throughout the meeting, which was also webcast live in its entirety to registered remote attendees.

Dataset Information

The National Institutes of Health measure of Healing Experience of All Life Stressors (NIH-HEALS): Factor analysis and validation.

Publications

The National Institutes of Health measure of Healing Experience of All Life Stressors (NIH-HEALS): Factor analysis and validation.

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