iManage Program: Decision Coaching Guide to Promote Audiology Care
Bibliographic record
Abstract
Noting the large proportion of adults with unaddressed hearing loss, audiologists often look to hearing screenings as an opportunity to educate individuals about their hearing loss and to motivate them to seek help.1 Unfortunately, no post-screening intervention has been successful in increasing the uptake of audiology care to date.2,3 As such, in 2012, the U.S. Preventive Services Task Force did not recommend that primary care physicians screen for hearing loss in asymptomatic adults aged 50 and older.4 The task force's 2020 draft recommendation is unchanged; there is still insufficient evidence to show that hearing screenings improve outcomes in adults over 50 because, typically, the screening does not trigger the uptake of hearing healthcare services.5 In 2017, our research team began the task of designing a post-hearing screening intervention that would increase the percentage of adults who seek audiology care following a failed hearing screening. Previous researchers have tried to solve this conundrum. For example, Milstein and Weinstein2 developed an intervention to increase post-screening follow-up based on the Health Belief Model (HBM).6 We attempted to build on the work of previous researchers by developing an intervention based on health psychology (such as the HBM) while using the principles of Participatory Design (PD).Shutterstock/Pixel-Shot, hearing loss, patient, care, audiologyFigure 1: Sample summary screen in Part 1, where the user considers whether it is important to do something about his/her hearing loss. Hearing loss, patient, care, audiology.Figure 2: An example of the final screen in Part 3, where the user considers the benefits and drawbacks of seeking audiology care. Hearing loss, patient, care, audiology.FRAMEWORK & PROGRAM DEVELOPMENT PD is a creative and collaborative process that aims to include developers, previous research, and most importantly, end-users, in the design of an intervention.7 In the first step, the research team developed a framework for the internet-based intervention based on self-management and social support literature.8 We created online activities for individuals to recognize their communication problems related to hearing loss and to develop achievable goals and action plans to meet those goals. Using an iterative process, we held four stakeholder focus groups; following each focus group we modified the program framework and content and presented the modified design to the next group. Focus groups 1, 3, and 4 included people with hearing loss (n & #xF03D; 14) and communication partners (n & #xF03D; 6). Focus group 2 included five audiologists who spent part of their practice doing adult hearing aid work. The program framework and activities then went through additional modifications following an evaluation by three expert panels. Panel 1 included seven eHealth experts who worked for a hearing aid-related research institute, Panel 2 included local leaders from the Hearing Loss Association of America, and Panel 3 included six experts who worked for a major hearing aid manufacturer. A final phase of program development involved validation groups with the target end-users (people with hearing loss who were not hearing aid users) and one group of audiologists to evaluate and select final program content (recorded testimonials and informational recordings). The final program was quite different from the original vision; we created a program to help participants decide whether or not they want to visit an audiologist based on the principles of decision coaching.9 Coaching guides can help individuals prepare for an appointment by giving them information about their condition, flesh out their thoughts about seeking treatment, and prepare them to engage in shared decision-making with their clinician. We followed the Ottawa Personal Decision Guide,10 which leads users through the following steps: Clarify the decision. In our case, the decision is “Should I visit an audiologist?” In this step, participants consider what is at stake in regards to the decision and consider where they are in the decision-making process. For example, an individual may not have thought about the decision, they may be thinking about the decision, they may be close to a decision, or they may have made a choice. Explore the decision. This may include content to: Educate the user about their management options (e.g., What happens during an audiology appointment? If I go to the audiologist will the audiologist insist that I need hearing aids? What are the drawbacks if I do nothing about my hearing problems?) Evaluate the benefits and barriers of the management options (e.g., Do I want others to see me wearing hearing aids? Can I really afford a hearing aid? If I wear hearing aids will it make it easier to enjoy dinner in a restaurant? What is the value of getting a baseline audiologic evaluation?) Help the user to clarify his/her values (e.g., do the benefits of seeking audiology care outweigh the drawbacks?) Identify decision-making needs. In this case, the user considers the following: Knowledge: Do I know the benefits and drawbacks of my management options? Values: Which benefits and drawbacks are most important to me? Support: Should I discuss my options with a communication partner? If I discuss these options with a communication partner, will I be more certain of my decision? Certainty: Am I sure that I am making the right decision? PROGRAM COMPONENTS & NEXT STEPS The final program was named “iManage (my hearing)” because we aim to give individuals the knowledge and tools to decide whether or not to seek audiology care. We also aim to give the user enough information to enable shared-decision making with their audiologist.11 The final iManage program is divided into three parts:12 Part 1: The user learns about the impact of hearing loss on activities and participation areas (e.g., communicating with family and friends), and rates how important it is to improve his/her hearing for each situation. The user is presented with up to 10 activity and participation areas until she/he rates three items at least a & #x2018;3’ on a 1 to 5 scale, with 1 being & #x2018;Not Important’ and 5 being & #x2018;Important’. Figure 1 shows a summary screen of Part 1. Part 2: The user and a communication partner work together to identify situations where each one is impacted by the HL. In this module, partners watch videos of a couple going through the Goal-Sharing for Partners Strategy with an audiologist.13 This is a step-by-step process during which the partners consider where they experience good communication, how each one is affected by the hearing loss, and propose steps to improve their communication. In Part 2, each partner has the opportunity to answer questions about their communication; this is an opportunity for the person with hearing loss to get support from a communication partner. (A modification is available if the user does not have a communication partner available while completing the iManage program.) Part 3: The user considers the benefits and drawbacks of seeking audiology care via a values clarification exercise. Figure 2 shows an example of the final screen after a user clarified her values regarding the benefits and drawbacks of seeking audiology care. Does the iManage program increase the uptake of audiology services in individuals who fail a hearing screening? In March of 2020, we began a feasibility study to answer this question. After running our second subject, the research was shut down due to the COVID-19 pandemic. We look forward to continuing our research when participants are comfortable with an in-person hearing screening. Stay tuned. Author acknowledgments: This work was funded by a grant from the William Demant Foundation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".