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Decision Support for the Renal Replacement Therapy With End-stage Renal Disease

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ClinicalTrials.gov Identifier: NCT03921437
Recruitment Status : Recruiting
First Posted : April 19, 2019
Last Update Posted : May 6, 2019
Sponsor:
Collaborator:
Tri-Service General Hospital
Information provided by (Responsible Party):
Tsae Jyy, Wang, National Taipei University of Nursing and Health Sciences

Brief Summary:
Patients often need more comprehensive information and clearer communication in order to to understand the complications, risks, cost and impacts on life quality associated with different treatment options. The purpose of this study is to investigate the efficacy of a decision support intervention on reducing conflict and improving satisfaction in making the renal replacement therapy decision among patients with end-stage renal disease. This study will be a randomized controlled trail. They will be randomly assigned to the experimental or the control group. Participants in the experimental group will receive the decision support intervention provided by the patient educators through using a decision support tool. The control participants will receive the routine care. Independent t-tests will be used to analyze between-group differences in autonomy preference index, renal replacement therapy knowledge, decision self-efficacy, decision conflict, decision regret, and decision satisfaction at different data collection points.Generalized Estimating Equations will be used to analyze between group differences in the changes of renal replacement therapy knowledge, decision self-efficacy, and decision conflict across time.

Condition or disease Intervention/treatment Phase
Chronic Renal Disease Radiation: decision support intervention Not Applicable

Detailed Description:

I. Research object: In the outpatient department of a medical center in a medical center in the north, the case was collected, and the sample was selected conveniently. The patients who met the following sample selection conditions were selected, and 128 patients who agreed to participate in the study and filled out the consent form were studied by Random Allocation. The software software generates a random assignment list, which is then assigned to the experimental group and the control group.

2.The number of samples is calculated The number of samples required is calculated by G power (version 3.1.9.2) statistical software (Faul, Erdfelder, Buchner, & Lang, 2009), and the repeated measures ANOVA of the F test is used to compare the difference between the two groups (between factors) due to lack of intervention. The reference data of the effect size of the measure, the estimated measure should be moderately beneficial for the degree of decision-making, so according to the cohen's rule (Cohen, 1988) f2 is 0.30, the significant level α is 0.05, and the statistical power value is 0.05. It is 0.80, repeated measurement 3 times, the correlation between repeated measurements is 0.5, the total number of samples is estimated to be 86, each group is 43, and in addition, in order to make the secondary effect variable, there are enough samples, and consider The exit and omission values were about 20%. Therefore, 128 end-stage renal patients were selected from the hospital outpatient nephrology case management database. About 64 people in the experimental group and the control group participated in the study.

3. Intervention measures The intervention measures in this study were discussed with the nephrologist and CKD health teachers. Based on theoretical considerations, both the experimental group and the control group can accept the introduction and selection of renal replacement therapy, but the decision support measures are different, and the experimental group provides decision support. Measures include the use of CKD Guardian as a decision-maker and the development of medical decision aids by e-book software, and the application and decision-directed model complemented by introduction and selection. The implementation steps include team discussion, option discussion and decision making. The conversation is conducted while the control group is introduced with traditional care care.


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Study Type : Interventional  (Clinical Trial)
Estimated Enrollment : 128 participants
Allocation: Randomized
Intervention Model: Parallel Assignment
Intervention Model Description: A random 1:1 assignment was made using a random number table to generate a sequence, and the participants were randomly divided into an experimental group and a control group.
Masking: Single (Outcomes Assessor)
Masking Description: Adopting the method of unnamed, the analysis uses de-named coding, who will not know who the respondent is.
Primary Purpose: Supportive Care
Official Title: The Efficacy of a Decision Support Intervention on Reducing Conflict and Improving Satisfaction in Making the Renal Replacement Therapy Decision Among Patients With End-stage Renal Disease
Actual Study Start Date : November 29, 2018
Estimated Primary Completion Date : December 31, 2019
Estimated Study Completion Date : December 31, 2020

Resource links provided by the National Library of Medicine


Arm Intervention/treatment
Experimental: decision support intervention
The intervention measures in this study were discussed with the nephrologist and CKD health teachers. Based on theoretical considerations, the experimental group provides decision support. Measures, including CKD Guardian as a decision-maker, and the use of e-book software to develop medical decision-assist tools, and the application and decision-making mode complemented by introduction and selection, including team discussions, option discussions, and decision-making conversations. The control group is introduced with traditional care instructions for routine care. The experimental group and the control group were referred to the CKD health teacher for the introduction of renal replacement therapy by the physician. The experimental group was guided by CKD Health Education to guide the patients to participate in the discussion, discuss the advantages and disadvantages of each treatment and guide patients to explore preferences. And value, supplemented by discussion and final decision.
Radiation: decision support intervention
CKD Guardian is the decision-maker and uses the e-book software to develop medical decision-assist tools, and applies this tool and decision-directed mode to introduce and select. The implementation steps include team discussion, option discussion and decision-making. The group is introduced with traditional care instructions for routine care.
Other Name: routine care

No Intervention: routine care
According to the nursing routine provide paper education.



Primary Outcome Measures :
  1. Control Preferences Scale [ Time Frame: 10 minutes ]
    The control preferences construct is defined as "the degree of control an individual wants to assume when decisions are being made about medical treatment." The CPS consists of five cards that each portrays a different role in treatment decision-making using a statement and a cartoon. A and B represent the individual making the treatment decisions, C represent the individual making the decisions jointly with the physician, and D and E represent the physician making the decisions.

  2. Scale of knowledge [ Time Frame: 10 minutes ]
    To measure the patient's relevant disease knowledge, dialysis modalities and items that should be tracked over time. The scale mainly applied a dichotomy response (right/wrong), but to prevent patient guessing, add the choice of 'I don't know' as well. There are 20 questions in total with a total possible score ranging from 0-20. The higher the subject's score, the more knowledge he/she was presumed to possess.

  3. Decision Self-Efficacy: Decision Self-Efficacy Scale [ Time Frame: 10 minutes ]
    Using the Decision Self-Efficacy Scale developed by O'Connor (1995) to measure self-confidence or belief in decision-making ability, including joint decision making, the scale has a total of 11 questions, 0-4 points. Scored by 5 points, 0 points means no confidence at all, and 4 points means very confident. In order to help explain the score more easily, the scale multiplies the score by 25, and the score ranges from 0 (nothing at all). Confidence) to 100 points (very confident). The 0 point is expressed as "very low self-efficacy" and the 100 points means "very high self-efficacy" (O'Connor, 1995). The internal consistency of the scale is 0.92 with a correlation with the knowledge (r = 0.47) and support (r = 0.45).

  4. Decisional Conflict [ Time Frame: 10 minutes ]
    A total of 16 questions, 5 points method Sub-(0-4), which is used to measure the decision-making disturbances of patients involved in treatment decision-making, including uncertainty, feelings, lack of relevant information, unclear personal values, feelings of lack of support, and decision satisfaction. Table (O'Connor, 1995). The summary score is converted to 0-100 points. According to the manual, the higher the total score, the higher the decision-making trouble, and the score greater than 37.5 is the relevant decision delay. The scale was originally used in patients who received influenza vaccine or breast cancer screening. The decision was made on whether or not to treat 909 patients. The internal consistency coefficient of the scale ranged from 0.78 to 0.92 with good reliability and validity. O'Connor, 1995).


Secondary Outcome Measures :
  1. Decisional Satisfaction: Satisfaction with Decision (SWD) [ Time Frame: 10 minutes ]
    It is proposed to adopt the Satisfaction with Decision (SWD) developed by Holmes-Rovner (1996) for a total of 6 questions, mainly to discuss the patient's subjective feelings of participation in the decision-making process, 5 points (1-5) The scores of each question are summed up and then averaged. The higher the score, the higher the satisfaction of the decision. This scale has been widely used by international scholars to assess the satisfaction of menopausal women in receiving hormonal treatment decisions with good reliability (Cronbach's alpha = 0.86) (Holmes-Rovner et al., 1996). Since there is no Chinese version of this scale, it is expected to be translated by the original author. After translation into the Chinese version of the scale, 8-10 patients will be pre-tested to understand the language readability of the scale to confirm the final Chinese version.

  2. Decisional Regret [ Time Frame: 10 minutes ]
    A total of 5 questions, the decision-making regret scale measures pain or regret after a medical decision. It mainly discusses the negative psychological feelings of patients who participate in the treatment decision-making process and related results. 5-point scoring (1-5), in which the second and fourth questions are reverse questions, and the average score after summing the questions is obtained. After subtracting 1 and multiplying by 25, the score range of 0-100 is obtained. Higher scores indicate a higher level of regret (O'Connor, 1996). This scale has been translated into multiple languages and is available in Chinese for breast cancer patients. The original scale was determined by the medical decision-making psychological test test tool reliability, showing its internal consistency (Cronbach's alpha) = 0.81 to 0.92, and Spearman's correlation and DCS correlation score was (rS = .56, p <.0001) (Brehaut et Al., 2003)



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Ages Eligible for Study:   20 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
Criteria

Inclusion conditions:

  1. The fifth stage of chronic renal failure diagnosed by a physician.
  2. The physician advises and informs the patient who has to undergo renal replacement therapy but has not yet decided what treatment to take.
  3. Being able to communicate in Mandarin and Taiwan.
  4. Ages over 20 years old.

Exclusion conditions:

  1. Cognitive impairment: The MMSE of the above-mentioned educators was 26 points, and the national minimum was < 21 points, those who are not educated are <16 points, and the case is excluded.
  2. Patients who have received non-emergency dialysis treatment.
  3. Patients with severe cardiopulmonary dysfunction, severe shock, low blood pressure, and large bleeding are not controlled.
  4. Patients with chronic active hepatitis, cirrhosis or liver failure.
  5. A history of cancer that may be transferred.
  6. Severe bleeding tendency.
  7. Loss of peritoneal function or extensive peritoneal adhesion, unable to use peritoneal dialysis.
  8. Unable to correct physiological defects, may interfere with peritoneal dialysis, or increase the chance of infection, such as umbilical hernia.
  9. The patient is unable to operate the fluid change, hand shake, and no family members can assist.
  10. Patients who are blind, have poor eyesight, and have difficulty operating.

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03921437


Contacts
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Contact: Tasw Jyy Wang, PhD +886911246130 tsaejyy@ntunhs.edu.tw
Contact: Shu Yen Lee, PhD +886922743555 leey1108@mail.ndmctsgh.edu.tw

Locations
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Taiwan
Tri-Service General Hospital, National Defense Medical Center Recruiting
Taipei, Taiwan, 886
Contact: Shu -Yen Lee, PhD    +886922743555    leey1108@mail.ndmctsgh.edu.tw   
Sponsors and Collaborators
National Taipei University of Nursing and Health Sciences
Tri-Service General Hospital
Investigators
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Principal Investigator: Tasw Jyy Wang, PhD National Taipei University of Nursing and Health Sciences

Publications:
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Responsible Party: Tsae Jyy, Wang, RN PhD Professor, National Taipei University of Nursing and Health Sciences
ClinicalTrials.gov Identifier: NCT03921437     History of Changes
Other Study ID Numbers: 1-1-7-05-114
First Posted: April 19, 2019    Key Record Dates
Last Update Posted: May 6, 2019
Last Verified: May 2019
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No

Keywords provided by Tsae Jyy, Wang, National Taipei University of Nursing and Health Sciences:
Chronic Renal Diseases
Decision-making

Additional relevant MeSH terms:
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Kidney Diseases
Kidney Failure, Chronic
Renal Insufficiency, Chronic
Urologic Diseases
Renal Insufficiency