Computer-based Decision Aid Research Articles

Computer-based patient decision aid in interventions for patients with chronic disease.

Computer-based patient decision aid in interventions for patients with chronic disease.

Effectiveness of computerised decision aids for patients with chronic diseases in shared decision-making: A systematic review and meta-analysis.

To synthesise the composition and effectiveness of computer-based patient decision aid (PDAs) in interventions for patients with chronic diseases. A systematic review with meta-analysis. Five databases were searched, and only randomised controlled trials (RCTs)were included. This review was conducted with the PRISMA guidelines. The JBI Appraisal Tools for randomised trials were used to assess the risk of bias. We used the random-effects model to conduct meta-analyses. Evidence from RCTs was synthesised using standardised mean differences or mean differences. The GRADE system was employed to assess the certainty of evidence and recommendations. This study was registered on PROSPERO (number: CRD42022369340). PubMed, Embase, Web of Science, CINAHL and Cochrane Library were searched for studies published before October 2022. The review included 22 studies, and most computer-based PDAs reported information on the disease, treatment options, pros and cons and risk comparison and value clarification. The use of computer-based PDAs showed a significant effect on decision conflict and knowledge, but not on decision regret, satisfaction, self-efficacy, anxiety and quality of life. The overall GRADE certainty of evidence was low. Although the quality of evidence was low, however, using computer-based PDAs could reduce decision conflict and enhance knowledge when making medical decisions. More research is needed to support the contention above. Computer-based PDAs could assist health-care providers and patients in the shared decision-making process and improving the quality of decision-making. This study adhered to PRISMA guidelines. NO PATIENT OR PUBLIC CONTRIBUTION.

Development and testing of "Is Lung Cancer Screening for You?" A computer-based decision aid.

To reduce lung cancer mortality, individuals at high-risk should receive a low-dose computed tomography screening annually. To increase the likelihood of screening, interventions that promote shared decision-making are needed. The goal of this study was to investigate the feasibility, acceptability, usability, and preliminary effectiveness of a computer-based decision aid. Thirty-three participants were recruited through primary-care clinics in a small southeastern-US city. Participants used a computer-based decision aid ("Is Lung Cancer Screening for You?") during a clinic appointment. Paper surveys collected self-reported feasibility, acceptability, and usability data. A research coordinator was present to observe each patient's and health-care provider's interactions, and to assess the fidelity of shared decision-making. The decision aid was feasible, acceptable for use in a clinic setting, and easy for participants to use. Patients had low decisional conflict following use of the decision aid and had high screening intention and actual screening rates. Shared decision-making discussions using the decision aid were nearly 6min on average. Computer-based decision aids are feasible for promoting shared lung cancer-screening decisions. A more robust study is warranted to measure the added value of a computer-based version of this aid versus a paper-based aid.

User Experience of a Computer-Based Decision Aid for Prenatal Trisomy Screening: Mixed Methods Explanatory Study.

BackgroundMobile health tools can support shared decision-making. We developed a computer-based decision aid (DA) to help pregnant women and their partners make informed, value-congruent decisions regarding prenatal screening for trisomy.ObjectiveThis study aims to assess the usability and usefulness of computer-based DA among pregnant women, clinicians, and policy makers.MethodsFor this mixed methods sequential explanatory study, we planned to recruit a convenience sample of 45 pregnant women, 45 clinicians from 3 clinical sites, and 15 policy makers. Eligible women were aged >18 years and >16 weeks pregnant or had recently given birth. Eligible clinicians and policy makers were involved in prenatal care. We asked the participants to navigate a computer-based DA. We asked the women about the usefulness of the DA and their self-confidence in decision-making. We asked all participants about usability, quality, acceptability, satisfaction with the content of the DA, and collected sociodemographic data. We explored participants’ reactions to the computer-based DA and solicited suggestions. Our interview guide was based on the Mobile App Rating Scale. We performed descriptive analyses of the quantitative data and thematic deductive and inductive analyses of the qualitative data for each participant category.ResultsA total of 45 pregnant women, 14 clinicians, and 8 policy makers participated. Most pregnant women were aged between 25 and 34 years (34/45, 75%) and White (42/45, 94%). Most clinicians were aged between 35 and 44 years (5/14, 36%) and women (11/14, 79%), and all were White (14/14, 100%); the largest proportion of policy makers was aged between 45 and 54 years (4/8, 50%), women (5/8, 62%), and White (8/8, 100%). The mean usefulness score for preparing for decision-making for women was 80/100 (SD 13), and the mean self-efficacy score was 88/100 (SD 11). The mean usability score was 84/100 (SD 14) for pregnant women, 77/100 (SD 14) for clinicians, and 79/100 (SD 23) for policy makers. The mean global score for quality was 80/100 (SD 9) for pregnant women, 72/100 (SD 12) for clinicians, and 80/100 (SD 9) for policy makers. Regarding acceptability, participants found the amount of information just right (52/66, 79%), balanced (58/66, 88%), useful (38/66, 58%), and sufficient (50/66, 76%). The mean satisfaction score with the content was 84/100 (SD 13) for pregnant women, 73/100 (SD 16) for clinicians, and 73/100 (SD 20) for policy makers. Participants thought the DA could be more engaging (eg, more customizable) and suggested strategies for implementation, such as incorporating it into clinical guidelines.ConclusionsPregnant women, clinicians, and policy makers found the DA usable and useful. The next steps are to incorporate user suggestions for improving engagement and implementing the computer-based DA in clinical practice.

Differential diagnosis of COVID-19 and influenza.

This study uses two existing data sources to examine how patients' symptoms can be used to differentiate COVID-19 from other respiratory diseases. One dataset consisted of 839,288 laboratory-confirmed, symptomatic, COVID-19 positive cases reported to the Centers for Disease Control and Prevention (CDC) from March 1, 2019, to September 30, 2020. The second dataset provided the controls and included 1,814 laboratory-confirmed influenza positive, symptomatic cases, and 812 cases with symptomatic influenza-like-illnesses. The controls were reported to the Influenza Research Database of the National Institute of Allergy and Infectious Diseases (NIAID) between January 1, 2000, and December 30, 2018. Data were analyzed using case-control study design. The comparisons were done using 45 scenarios, with each scenario making different assumptions regarding prevalence of COVID-19 (2%, 4%, and 6%), influenza (0.01%, 3%, 6%, 9%, 12%) and influenza-like-illnesses (1%, 3.5% and 7%). For each scenario, a logistic regression model was used to predict COVID-19 from 2 demographic variables (age, gender) and 10 symptoms (cough, fever, chills, diarrhea, nausea and vomiting, shortness of breath, runny nose, sore throat, myalgia, and headache). The 5-fold cross-validated Area under the Receiver Operating Curves (AROC) was used to report the accuracy of these regression models. The value of various symptoms in differentiating COVID-19 from influenza depended on a variety of factors, including (1) prevalence of pathogens that cause COVID-19, influenza, and influenza-like-illness; (2) age of the patient, and (3) presence of other symptoms. The model that relied on 5-way combination of symptoms and demographic variables, age and gender, had a cross-validated AROC of 90%, suggesting that it could accurately differentiate influenza from COVID-19. This model, however, is too complex to be used in clinical practice without relying on computer-based decision aid. Study results encourage development of web-based, stand-alone, artificial Intelligence model that can interview patients and help clinicians make quarantine and triage decisions.

Reduction of cardiovascular risk factors among young men with hypertension using an interactive decision aid: cluster-randomized control trial

BackgroundCoronary heart disease (CHD) mortality among young men is very high and the prevention methods usable in family practice (FP) settings are limited (1,2). The objectives of this study were to investigate the cardiovascular risk profile among young males (18–50) visiting their family doctor (FD) and to find out if using an interactive computer-based decision aid (DA) has advantages in reducing cardiovascular risk factors compared to usual counselling at the FD’s office.MethodsThe study was a cluster-randomized controlled trial including hypertensive male patients aged 18–50 recruited by their FD in 2015–2016. Patients with cardiovascular complications were not included. FDs were randomly divided into intervention groups (n = 9) and control groups (n = 11). Altogether, FDs recruited 130 patients, 77 into the intervention group (IG) and 53 into the control group (CG). IG patients were counselled about cardiovascular risk factors using a computer-based DA. CG patients received usual counselling by their FD. Data was collected with questionnaires, clinical examinations and laboratory analyses at the baseline and at the follow-up visit three months later. We compared the cardiovascular risk factors of the IG and CG patients.ResultsBaseline characteristics of the IG and CG patients were comparable. Of the whole study group, 51.5% (n = 67) of the patients had hypertension grade 1, 45.4% (n = 59) had grade 2 and 3.1% (n = 4) had grade 3. Twenty-seven per cent (n = 21) of the IG and 42% (n = 22) of the CG patients were smokers. We found that shared decision making with the DA was more effective in smoking reduction compared to usual FD counselling: 21 smoking patients in the IG reduced the number of cigarettes per day which is significantly more than the 22 smoking patients in the CG (− 3.82 ± 1.32 (SE Mean) versus + 2.32 ± 1.29; p = 0.001). Systolic blood pressure (SBP), diastolic blood pressure (DBP) and the number of cigarettes per day, all showed a statistically significant reduction among patients who were using the DA. Male patients with hypertension grade 2 had a significantly greater reduction in their SBP (− 6.003 ± 2.59 (SE Mean) versus + 1.86 ± 2.58; p = 0.038) grade 1. Reduction of DBP, cigarettes per day and CVD risk in general were nearly significant in the IG whereas the CG showed an increase in all of these parameters.ConclusionUsing interactive DAs at FD’s offices for counselling of young hypertensive male patients is one possibility to help patients understand their risk factors and make changes in their treatment choices. DAs can be more effective in achieving behavioural changes like reducing smoking or blood pressure compared to normal counselling.

Development and preliminary evaluation of tablet computer-based decision aid for patients participating in cancer clinical trials

ObjectivesPatients often consent to participate in cancer clinical trials despite misunderstanding the trial content. We developed a tablet-based clinical trial decision aid and tested its use with the usual discussion at the time of clinical trial registration. MethodsParticipants were individuals considering participating in a breast cancer clinical trial. The control participated in usual discussions; the intervention group participated in discussion using the decision aid. Pre- and post-discussion, we investigated knowledge, decision-making conflict, and discussion length. ResultsWe enrolled 54 patients, 27 in the control group and 27 in the intervention group. Post-discussion clinical trial knowledge was significantly higher in the intervention group than in the control group (p = 0.003). No significant difference was found in decisional conflict, but the intervention group tended to have lower post-discussion conflict than the control group. There was no between-group difference in the length of discussions with physicians and clinical research coordinators. ConclusionFor women considering participation in cancer clinical trials, a tablet-based decision aid may promote clinical trial understanding without increasing discussion length or patient burden. This pre-learning decision aid incorporating a quiz and bidirectional question prompt lists may improve participants’ understanding of clinical trials.

Evaluation of a computerized contraceptive decision aid: A randomized controlled trial

ObjectiveTo evaluate the effectiveness of a contraceptive decision aid in reducing decisional conflict among women seeking reversible contraception. Study DesignWe conducted a randomized trial of a computer-based decision aid compared to a control group for women presenting for reversible contraception at two clinics affiliated with an academic medical center. The primary outcome was change in decisional conflict, measured before and after the healthcare visit using the validated Decisional Conflict Scale. We hypothesized the decision aid would reduce the decisional conflict score by 10 points on a 100-point scale (0 = no conflict, 100 = high conflict) compared to the control group. Secondary outcomes included contraceptive method chosen and satisfaction with the healthcare visit. ResultsWe enrolled and randomized 253 women, and 241 had complete data for our primary outcome. Overall, pre-visit decisional conflict scores were low, reflecting low levels of decisional conflict in our sample; median score 15 (range 0–80) in the decision aid and 10 (0–85) in the control group (p = 0.45). Both groups had a similar reduction in median decisional conflict after the healthcare visit: −10 (−80 to 25) and −10 (−60 to 5) in the decision aid and control groups respectively (p = 0.99). Choice of contraception (p = 0.23) and satisfaction with healthcare provider (p = 0.79) also did not differ by study group. ConclusionsDecisional conflict around contraception was low in both groups at baseline. Use of a computerized contraceptive decision aid did not reduce decisional conflict, alter method choice, or impact satisfaction compared to the control group among women choosing reversible contraception. ImplicationsUse of a computerized contraceptive decision aid did not reduce decisional conflict or alter method choice compared to the control group among women choosing reversible contraception. Future studies could focus on testing the decision aid in different clinical settings, especially where barriers to providing comprehensive contraceptive counseling exist.

Patients With Advanced Cancer Choose Less Aggressive Medical Treatment on Vignettes After Using a Computer-Based Decision Aid.

Although patients often prefer less rather than more treatment at the end of life, in the absence of contrary instructions, the medical profession's de facto position is to treat aggressively. It is unknown whether a computer-based decision aid can affect treatment choices. Secondary analysis of a single-center, single-blind randomized controlled trial of an advance care planning (ACP) intervention among 200 patients with stage IV cancer. Participants were randomized to intervention (Making Your Wishes Known, a values-neutral, educational, computer-based decision aid) or control (standard living will + brochure). After reading a hypothetical clinical vignette, participants were asked whether they would want 11 medical/surgical treatments in that situation (dialysis, cardiopulmonary resuscitation [CPR], ventilator, feeding tube, etc). The median number of treatments wanted by participants was compared between groups, and logistic regression was used to compare between-group likelihood of not wanting each specific treatment. The median number of treatments wanted was 1 in the intervention group versus 5 in the control (P < .001). For 6 of 11 treatments, the intervention group was significantly less likely than control to want aggressive treatment. Most notably, compared to control, intervention participants were less likely to want CPR (odds ratio [OR] = 0.31), short-term mechanical ventilation (OR = 0.34), short-term dialysis (OR = 0.38), surgery (OR = 0.37), and transfusion (OR = 0.21). Individuals using an educational ACP decision aid were less likely to want aggressive medical treatment than those completing standard living wills. These findings have implications not only for how to respect patient's wishes but also potentially for reducing costs at the end of life.

Development and Usability Testing of a Decision Support App for Women Considering Breast Reconstruction Surgery.

Women with breast cancer have difficulty deciding whether to undergo breast reconstruction when mastectomy is necessary. A computer-based decision aid that can be individualized to provide both surgery information and value clarification may be helpful for women considering breast reconstruction surgery. The objectives of this study are to program a prototype of an application (app) with a value clarification exercise and to evaluate the pilot usability, feasibility, and efficacy of the app. In phase 1, a prototype app called Pink Journey for use on the iPhone OS (IOS) platform was created following the framework of shared decision making. In phase 2, 11 women who were given the option of reconstruction by a breast surgeon were recruited from July 2017 to December 2017. A pretest-posttest design was adopted to test the usability and feasibility of the app. The results showed that the women who used the app reported significantly less decisional conflict after intervention on each subscale of the Decision Conflict scale, i.e., "being informed", "uncertainty", "social support", "effective decision", and "value clarification". This research provides preliminary data indicating that Pink Journey holds promise for decreasing decision conflict. Most women felt that the app was both helpful and user-friendly. The app increased their participation in decision making, helped them obtain more accurate risk perceptions, and clarified their values. It also helped the women make decisions regarding breast reconstruction more confidently.

Development and initial psychometric evaluation of the computer-based prostate Cancer screening decision aid acceptance scale for African-American men

BackgroundTo reliably evaluate the acceptance and use of computer-based prostate cancer decision aids (CBDAs) for African-American men, culturally relevant measures are needed. This study describes the development and initial psychometric evaluation of the 24-item Computer-Based Prostate Cancer Screening Decision Aid Acceptance Scale among 357 African-American men.MethodsExploratory factor analysis (EFA) with maximum likelihood estimation and polychoric correlations followed by Promax and Varimax rotations.ResultsEFA yielded three factors: Technology Use Expectancy and Intention (16 items), Technology Use Anxiety (5 items), and Technology Use Self-Efficacy (3 items) with good to excellent internal consistency reliability at .95, .90, and .85, respectively. The standardized root mean square residual (0.035) indicated the factor structure explained most of the correlations.ConclusionsFindings suggest the three-factor, 24-item Computer-Based Prostate Cancer Screening Decision Aid Acceptance Scale has utility in determining the acceptance and use of CBDAs among African-American men at risk for prostate cancer. Future research is needed to confirm this factor structure among socio-demographically diverse African-Americans.

Development and pilot-testing of a colorectal cancer screening decision aid for individuals with varying health literacy levels

ObjectiveMaking an informed decision about colorectal cancer screening requires health literacy. Our aim was to develop and pilot-test a computer-based decision aid to support informed decision making about whether or not to participate in colorectal cancer screening for individuals with varying health literacy levels in the Netherlands. MethodsFirst, we designed and adapted the decision aid prototype among 25 individuals with low (n = 15) and adequate (n = 10) health literacy. Second, we used a before/after study to assess changes in knowledge, attitude, intention, decisional conflict, deliberation, anxiety and risk perception in an online survey among 81 individuals eligible for colorectal cancer screening with low (n = 35) and adequate (n = 46) health literacy. ResultsThe decision aid was acceptable, comprehensible, reduced decisional conflict, increased deliberation and improved knowledge about colorectal cancer screening, but not about colorectal cancer, among individuals with adequate and low health literacy. Usability was slightly higher for participants with adequate health literacy compared to those with low health literacy. ConclusionThe decision aid is promising in supporting informed decision making about colorectal cancer screening, also among individuals with lower health literacy. Practice implicationsFurther refinement of interactive features, such as videos, animations and the values clarification exercise, is needed to increase the usability of the decision aid.

Evaluation of a Computer-Based Decision Aid for Promoting Informed Prostate Cancer Screening Decisions Among African American Men: iDecide.

To evaluate the effects of iDecide on prostate cancer knowledge, informed decision-making self-efficacy, technology use self-efficacy, and intention to engage in informed decision-making among African American men. One-group, pretest/posttest. Community settings in South Carolina. African American men, ages 40 years +, without a prior prostate cancer diagnosis (n = 354). iDecide, an embodied conversational agent-led, computer-based prostate cancer screening decision aid. Prostate cancer knowledge, informed decision-making self-efficacy, technology use self-efficacy, and intention to engage in informed decision-making. Descriptive statistics, paired t tests, general linear modeling, Spearman correlations. On average, participants experienced significant improvements in their prostate cancer knowledge ( P ≤ .001), informed decision-making self-efficacy ( P ≤ .001), and technology use self-efficacy ( P ≤ .001), postintervention. Additionally, 67% of participants reported an intention to engage in informed decision-making. Given the significant improvements across all measures, this research demonstrates that embodied conversational agent-led decision aids can be used to enhance the capacity for making informed prostate cancer screening decisions among African American men and increase their technology use self-efficacy. One critical limitation of this study is that most men had received prostate cancer screening prior to engaging in our intervention, so the implications of this intervention may be different for men who do not have a history of screening. Additionally, actual engagement in informed decision-making postintervention was not assessed.

An Iterative Process for Developing and Evaluating a Computer-Based Prostate Cancer Decision Aid for African American Men.

The disproportionate burden of prostate cancer (PrCA) among African American (AA) men amplifies the need for informed decisions about PrCA screening. To create a computer-based decision aid (CBDA) for increasing prostate knowledge, decision self-efficacy, and intention to make an informed decision, the study implemented an iterative approach to develop a culturally appropriate CBDA. A short CBDA prototype containing PrCA information and interactive activities was developed. A sample of 21 AA men aged 37 to 66 years in South Carolina participated in one of seven 90-minute focus groups and completed a 36-item survey. Updates were made to the CBDA based on participant feedback. The CBDA and heuristic evaluation surveys were then distributed to six expert reviewers. Ten men were also randomly selected from our sample population to participate in interviews regarding usability of the CBDA. Participants and expert reviewers expressed consensus on many features of the CBDA, but some suggested changes to the format and graphics in order to enhance the CBDA's effectiveness. Development and evaluation processes and implications are discussed. Using CBDAs for informed decision making may be appropriate for AA men. It is important to engage the community and experts in an iterative development process to ensure that a CBDA is relevant for priority populations.

Impact of computer-based pregnancy-induced hypertension and diabetes decision AIDS on empowering pregnant women.

ObjectivesWe designed a computer-based decision aid (CDA) for use by pregnant women at home to investigate and participate in solving their pregnancy problems related to pregnancy-induced hypertension (PIH) and gestational diabetes (GD). The system cannot and is not intended to replace visits to physicians; rather it can help women focus on the most important symptoms and provides guidance on when to see a doctor.MethodsThe study is a randomized controlled trial, which is performed among Iranian pregnant women. For subjects, 420 healthy pregnant women have been recruited from two private and two public prenatal centers. The intervention group will receive the CDA for use at home, and the control group will receive care as usual. The CDA relies on knowledge extracted from the national guidelines on PIH and GD.ResultsThe two primary outcomes for the study are self-efficacy and knowledge. Self-efficacy will be measured by the Stanford self-efficacy scale and knowledge will be evaluated by 15 binary (true/false) questions provided by the researchers. Secondary outcomes include type and frequency of doctor and/or medical center visits; blood pressure and blood sugar changes based on the national guidelines and according to pregnancy records, and anxiety will be assessed by the state component of the short Spielberger anxiety scale.ConclusionsThis paper describes the design of a CDA and a protocol for a randomized controlled trial to study the effects of the CDA on self-efficacy and knowledge of pregnant women pertaining to PIH and GD. Differences in the primary outcomes will be analyzed using 'intention-to-treat' principles.

Reliability of a computer-based decision aid for advance care planning

One of the concerns with advance directives as a means for promoting advance care planning is that advance directives are unreliable as a mechanism for articulating and documenting an individuals...

Advance care planning decision aid improves clinician understanding of wishes of patients with ALS

This study examined whether a computer-based decision aid for advance care planning (ACP) could help improve communication about end-of-life treatment wishes between patients with amyotrophic lateral sclerosis (ALS) and the...

Patients with CHF find decision aid for ACP helpful and computer-generated advance directive accurate

The fluctuating clinical course of congestive heart failure involves recurrent medical crises and readmission rates of ∼50% within 6 months following hospital discharge. The consequent focus on acute care measures...

Accuracy of a Decision Aid for Advance Care Planning: Simulated End-of-Life Decision Making

Advance directives have been criticized for failing to help physicians make decisions consistent with patients' wishes. This pilot study sought to determine if an interactive, computer-based decision aid that generates an advance directive can help physicians accurately translate patients' wishes into treatment decisions. We recruited 19 patient-participants who had each previously created an advance directive using a computer-based decision aid, and 14 physicians who had no prior knowledge of the patient-participants. For each advance directive, three physicians were randomly assigned to review the advance directive and make five to six treatment decisions for each of six (potentially) end-of-life clinical scenarios. From the three individual physicians' responses, a "consensus physician response" was generated for each treatment decision (total decisions = 32). This consensus response was shared with the patient whose advance directive had been reviewed, and she/he was then asked to indicate how well the physician translated his/her wishes into clinical decisions. Patient-participants agreed with the consensus physician responses 84 percent (508/608) of the time, including 82 percent agreement on whether to provide mechanical ventilation, and 75 percent on decisions about cardiopulmonary resuscitation (CPR). Across the six vignettes, patient-participants' rating of how well physicians translated their advance directive into medical decisions was 8.4 (range = 6.5-10, where 1 = extremely poorly, and 10 = extremely well). Physicians' overall rating of their confidence at accurately translating patients' wishes into clinical decisions was 7.8 (range = 6.1-9.3, 1 = not at all confident, 10 = extremely confident). For simulated cases, a computer-based decision aid for advance care planning can help physicians more confidently make end-of-life decisions that patients will endorse.

The Impact of a Novel Computer-Based Decision Aid on Shared Decision-Making for Colorectal Cancer Screening: A Randomized Trial (Running head: SDM for CRC Screening)

The Impact of a Novel Computer-Based Decision Aid on Shared Decision-Making for Colorectal Cancer Screening: A Randomized Trial (Running head: SDM for CRC Screening)