Evaluation of an advance care planning training program for practice professionals in Japan incorporating shared decision making skills training: a prospective study of a curricular intervention

Study design

This prospective study of a curricular intervention collected and used data from those who completed the 2020 Practical ACP Professions Development Education Program (the Aichi ACP Project) led by the Aichi Prefectural Government.

Evaluation framework

This study validated the effectiveness of an educational program for developing professionals who will practice ACP incorporating SDM skills training using the New World Kirkpatrick Model [22,23,24]. The New World Kirkpatrick Model assesses the effectiveness of training programs at the following four levels: level 1, the trainee’s response to the training experience (including training experience); level 2, the learner’s learning outcomes and increases in knowledge, skill, and attitude toward the attendance experience (i.e., how much attendees learned the content after training, typically measured using a pretest and posttest); level 3, the students’ change in behavior and improvement (whether the learning transfers into practice in the workplace); and level 4, results (the ultimate impact of training).

Since the evaluation took place immediately after the training it was based on the first to the third level of Kirkpatrick’s model: reaction (level 1), learning (level 2), and behavior (level 3).

Development of a new Japanese educational program for professionals who can practice ACP

The Aichi ACP Project is a training program “completed” via participation in two venue workshops and submitting before each workshop. The training was conducted at eight sites adopted by the Aichi Prefecture for the Aichi ACP Project. Each training site recruited participants and enrolled individuals from among medical, nursing, or welfare specialists in the field to support patient decision making. Enrolled participants completed preliminary learning via e-learning to allow for knowledge acquisition before the first training session. In the first workshop, SDM skills training was conducted using a dialog on ACP through lectures and role-playing.

The first workshop conducted role-playing for practical training of SDM with a small number of people. In addition, various professionals teamed up to discuss how to support difficult patient decisions in groups. There were two main instructors at the workshop, and four sub instructors provided participant support at each training site.

In the role-playing, we set up scenes in which some kind of health trouble occurred, with fictitious patients consisting of an older person with mild dementia living alone and an older person with dementia living with an unemployed and withdrawn family. Sets of three participants formed a team at random, and were divided into the roles of provider (decision supporter), patient, and observer. They then role-played SDM using the scenes. The individual who played the role of provider (decision supporter) drew on their own profession and expertise during the role-play to perform SDM. Immediately after role-playing, the three members evaluated the role-playing using the SDM measures [25, 26]. The participant playing the patient role evaluated the SDM received from the decision supporter role from the patient’s point of view. Three members then provided feedback on decision support and discussed ideas for improvement.

We set the target of group discussion as bedridden older patients with dementia who were receiving home care and family caregivers who could not tolerate the stress of long-term care. We set up a scene in which a patient had pneumonia and discussed the ACP practice with the collaboration of multiple professionals. The duration of the first workshop was 6 h.

In the questionnaire after the first workshop, we collected the respondents’ expertise, years of clinical experience, satisfaction with the Aichi ACP Project to date, and responses regarding the project’s difficulty as compared with their own prior predictions. To practice what was learned and learn from this experience before the second workshop, participants made efforts to practice ACP using SDM and perform regional and organizational development to enable practicing ACP in the organization or region to which they belonged. A report was then compiled, which was submitted at the second workshop.

Participants received SDM skills training during the second workshop using role-playing and group discussion. The second workshop was a 3-h session with two main instructors; no support sub instructor was included. The patient settings and scene settings for the role-playing in the second workshop were the same as for the first session of role-playing. As in the first workshop, three members formed a team at random and then role-played SDM using one situation by playing the roles of provider (decision supporter), patient, and observer. They evaluated their SDM skills, using SDM measurements and discussing improvement methods. The individual who played the provider (decision supporter) performed SDM using their own profession and expertise. Immediately after role-playing, the three members independently evaluated the role-playing using the SDM measure, provided feedback on decision support, and discussed improvements, as in the first workshop.

During the second workshop, participants presented practical reports on ACP and organizational development activities using SDM, which they had submitted as their assignment. They then drew up a draft ACP activity plan for the group. During the group discussion, the workshop participants then shared their ACP activity plans and devised an ACP practice plan on which the participants would work as a team in the future (Fig. 1).

Fig. 1figure 1

Aichi ACP Project educational program and data collection points

In the questionnaire administered after the second workshop, we collected information on the respondents’ expertise, years of clinical experience, responses regarding the difficulty of the Aichi ACP Project compared with their advanced expectations, frequency of seeing the ACP practiced by other specialists, the possibility of using the Aichi ACP Project, and recognition of the necessity of continued learning regarding ACP in the future.

Data collection

We collected data for usage anonymously from eight training sites of the Aichi ACP Project, which a government agency held in Aichi Prefecture, Japan, from July 2020 to February 2021. The eight training sites (seven hospitals and one organization promoting medical and long-term care coordination) completed all Aichi ACP Project programs. An individual in charge of information processing but not involved in this study entered the collected and anonymized data. The data included results of the questionnaire anonymously administered to participants after two sessions of venue workshops, SDM measurement data at workshops, and information on activity reports (Fig. 1).

Immediately after the first workshop, the participants provided the answers to the following items on the anonymous questionnaire: satisfaction with training, the frequency of seeing about patients’ ACP in the information provided by the liaison organizations, and frequency of seeing other people’s ACP practice. Answers were obtained using six-point Likert-type scales.

Immediately after the second workshop, the participants provided answers to the following items on an anonymous questionnaire at the venue: degree of confidence in ACP practice, frequency of seeing about patients’ ACP in the information provided by the liaison organizations, frequency of seeing other people’s ACP practice, the possibility of using the training content in their ACP practice, and the need for continuous ACP learning in the future. Answers were obtained using six-point Likert-type scales, and each result was replaced with a dummy variable ranging from 0 to 5.

SDM measurement

In order to evaluate SDM skills in this study, the SDM measure used in this study, namely, the SDM-Q-9 (patient) [25]/SDM-Q-Doc (physician) [26], was developed by the Department of Medical Psychology, University Medical Center Hamburg Eppendorf, Germany. It is the world’s first bidirectional SDM scale. The scale includes nine items that help visualize the degree of SDM (Figs. 23, and 4). As of 2021, the measure had been translated into 29 languages [27]. Its reliability and validity are confirmed in various cultures and languages. The nine items of the SDM scale comprise a one-factor structure measuring the concept of SDM, and the Japanese version of the SDM-Q-9 (patient) [28]/Japanese version of the SDM-Q-Doc (physician) [29] has already been confirmed to be reliable and valid in clinical practice in Japan. Furthermore, the Japanese version of the SDM-Q-9 (patient)/Japanese version of the SDM-Q-Doc (physician) was adapted to create an SDM-C–Patient/SDM-C–Provider for use by health care professionals other than physicians. In addition, the configural and measurement invariance of the Japanese version of the SDM-Q-9(patient)/Japanese version of the SDM-Q-Doc (physician) and the SDM-C–Patient/SDM-C–Provider for use by care professionals has been confirmed [30]. All nine items are rated on a six-point Likert-type scale, where 0 corresponds to completely disagree and 5 corresponds to completely agree; a perfect score is 45 points.

Workshop participants were asked to fill out an anonymous SDM measurement form at the workshop venue.

Fig. 2figure 2

Nine items of SDM: components of the SDM-Q-9/SDM-Q-Doc

Fig. 3figure 3 Fig. 4figure 4

SDM-Q-Doc, English version

Statistical and qualitative analysesSDM skills data and analysis

We compiled data from the two questionnaires from all training sites of the two workshops and analyzed the descriptive statistics. The evaluation of SDM skill was analyzed descriptively by substituting the scores for the SDM-Q-9/SDM-Q-Doc and the SDM-C–Patient (care patient)/SDM-C–Provider (care provider) from a perfect score of 45 to a perfect score of 100. We compared SDM skills between O1 and O2 (observation points in Fig. 1), with Wilcoxon rank-sum tests because the team members and roles in the role-play differed between O1 and O2, and we set p ≤ 0.05 as the level of significance. The sample size was calculated as an unpaired sample using a Wilcoxon rank-sum test [31]. With α = 0.05 and power = 0.8, the test being two-sided, and the effect size is set at a moderate d = 0.5 because there were no prior studies, we calculated the number in each group as 67.

Analysis of questionnaire immediately after training

We confirmed the difference between the difficulty levels after the first and second workshops using a chi-squared test, and the level of statistical significance was set as p ≤ 0.05. We analyzed the data from the questionnaire results after the second workshop using a covariance structure analysis. The perceptions from the training and environmental factors influencing the trainees were clarified. Using chi-squared values, we evaluated the model’s goodness-of-fit with the root mean square error of approximation (RMSEA), goodness-of-fit index (GFI), the adjusted goodness-of-fit index (AGFI), and the comparative fit index (CFI).

Analysis of SDM reports and organizational/regional development activity reports enabling the practice of ACP

In the SDM reports, we extracted key concepts related to promoting and inhibitory factors for clinical practice of SDM; in turn, key concepts with a number and frequency of occurrence > 10% of the total were also extracted.

The key concepts of the activity were extracted from the organizational/regional development activity reports enabling the practice of ACP, and, in turn, the key concepts with an appearance frequency > 10% were extracted. In addition, we also extracted the promoting and inhibitory factors and key concepts exceeding 10% of the total.

For statistical analysis, we used IBM SPSS Statistics 28 and IBM SPSS Amos Graphics 28

We performed a computerized lexical analysis of free text from the SDM reports and organizational/regional development activity reports enabling the practice of ACP, using the Japanese version of SPSS Text Analytics for Surveys 4.0.1. The participants’ reports were imported into the software, which extracts key terms used to categorize the responses. To create categories for this project, we combined both linguistic and frequency algorithms in the software. Once the data were categorized, the individual reports responses and the associated categorized data were exported for subsequent data analysis by several researchers. Through this process, the core sentences containing frequently occurring words were extracted, and the participants’ description contents were analyzed to create categories for this project.

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