International Journal of Healthcare Simulation

Introduction

During the perinatal period many women experience suboptimal mental health; from mild mood changes to more serious anxiety (13%) and depressive disorders (12%) [1]. In addition to the impact poor mental health can have on a woman during her pregnancy, birth and transitioning to parenthood, the evidence shows that reduced maternal mental health is also related to suboptimal infant development [2]. That is, infants whose mothers have experienced a mental health issue are also more likely to demonstrate poorer social adaptation, including emotional and behavioural problems [3]. However, Stein et al [4] argues that the adverse effects on infants and children are not inevitable and that with early and effective care the negative impact on families can be significantly minimized.

Effective care requires an educated and connected workforce who can provide a local, integrated and specialist mental healthcare service to women who become unwell [5]. To meet this requirement in Northern Ireland, the first interprofessional, postgraduate perinatal mental health module was commissioned. The educational remit was to provide a learning experience that would enable practitioners such as midwives, mental health nurses and health visitors (specialist community public healthcare professionals) to work together to design optimal and integrated care for women experiencing a deterioration in their perinatal mental health. Although interdisciplinary learning is recognized as an effective educational design for healthcare professionals caring for women and their families [6], providing interdisciplinary education is not without its challenges. For example, healthcare students bring into the learning environment their different discourses and epistemologies that can make it difficult for them to engage in interdisciplinary learning [7,8].

Research shows that interprofessional simulations can positively impact the knowledge, skills and attitudes of all disciplines [9,10], whether delivered face-to-face or via an immersive technology [11,12]. Immersion in simulation is important as it enhances the realism for the students [13] and, therefore, has the potential to influence the degree of motivation they experience. According to key theorists such as Sansone and Harackiewicz [14] and Keller [15], when students are motivated to learn, they experience an energy that leads to greater interest, persistence and effort, self-regulation and confidence to achieve. Interestingly, immersion, in terms of presence and agency, is seen to influence aspects of students’ motivation to learn via simulation [16]. In Makransky and Peterson’s model [16], the authors propose that presence and agency (immersion) can influence students’ situational interest, intrinsic motivation, self-efficacy, embodiment, cognitive load and self-regulation. To understand how these factors and others such as curiosity, information seeking, attribution and self-worth interact to influence a student’s intrinsic and extrinsic motivation to learn, Sansone and Harackiewicz [14] take our understanding beyond the motivational impact of a particular modality to a theoretical understanding of learning goals. Integrating multiple theories of motivation, the authors challenge educators to consider the role and nature of the learning goals, as a catalyst for learner motivation within a learning environment. It follows that for students to experience optimal motivation to achieve (outcome related to the goals) their motivational and self-regulatory processing (process related to achieving the goals) should be systematically and theoretically influenced. To assist educators in knowing what an optimal goal is and how to frame and set it, theories related to human motivation (achievement psychology) have been integrated into the broader practice of instructional design.

The applied motivational design model

In his book on Motivation and Learning Performance, Keller [15] provides a useful classification of motivational design models as a subset of instructional design. Most motivational design models are grounded in psychological theories and their systematic implementation within education. Depending on what group of psychological theories the educators apply to guide their design, these models can be classified as person-centred, environmentally centred or interaction-centred (persons interacting with their environment). A fourth group of models are referred to as omnibus models and are those where no distinction is made between instructional design and motivational design. Although successful practices can result from the implementation of an omnibus model, psychological theories are not systematically applied.

Classified as an interaction-centred model, the ARCS-V model [15] is underpinned mainly by expectancy-value theory and more recently incorporating social learning theory [26]. Considering that the learning environment is where students experience the challenge associated with the learning goals, the model from an expectancy-value position can be understood in terms of how students’ ‘values and innate abilities both influence and are influenced by the learning environment’ [15, pg 33]. While it is beyond the remit of this paper to provide detailed insight into the ARCS-V model, a summary of what it offers educators is provided in Figure 1:

Figure 1:

Summary of what the ARCS-V offers educators to guide their motivational design.

Details of the ARCS-V model and its theoretical underpinning, synthesis and design process are provided by Keller [15]; however, in summary there are two opportunities to apply the model. First, as described in this paper, to apply, in principle, the ARCS-V dimensions (Figure 2) to guide the development of new educational programmes and activities. Second, to solve specific problems related to learners’ motivation with an already existing learning design (enhancement).

Figure 2:

The dimensions of the ARCS-V meta-synthesis that guides the design process.

Although Keller’s model has had mixed levels of success [27,28], it remains one of the most widely used and preferred interactionist models, demonstrating validity and reliability [29,30]. Applications include enhancement of completion rates of pharmacy undergraduates in online self-study [31], motivating netizen students to learn transferable skills and learning through gamification [26,32]. Although applying the ARCS-V model to simulation maybe advantageous, little evidence of the model’s implementation to simulation is available [33].

Method

The following method describes each of the phases described in the objectives above.

Phase 1 (Learning Needs Analysis ) – as motivation is carried into the learning environment via the learning goals, a number of co-diagnostic workshops were facilitated to identify the nature and structure of the learning goals. Experts in perinatal psychiatry, psychology, obstetrics, midwifery, health visiting and family nursing were challenged to identify and agree on the key learning goal[s] associated with the module. Through collaborative discussion interdisciplinary caring emerged as a higher-order learning goal that influenced all other learning goals, including learning about common perinatal mental health conditions. Subgoals directly related to achieving interdisciplinary learning included team-working and decision-making. Determining the goals and how they relate to each other (goal structure) is important from a motivational perspective, in that, it can motivate students to create strong associations to and between the learning goals [34]. A subsequent diagnostic workshop with women who had lived experience of poor perinatal mental health, confirmed the importance of effective and safe interdisciplinary care.

Although the learning goal structure related to interdisciplinary caring was well developed through the co-design workshops, Keller [15] recommends consideration is given to what is known about the students. As the MSc module was being developed for practising midwives, health visitors and mental health nurses, it was anticipated that the students would have some shared values and previous experience related to caring for perinatal women with deteriorating mental health. Understanding the students’ shared valences (audience information) can be useful when selecting motivational tactics (phase 2). It was also anticipated that the majority of the students would be on commissioned places and may not have studied for some time. It was not known if the students practised as healthcare professionals together or not. When applying the ARCS-V to existing courses and classes, an audience analysis is recommended to ascertain the students’ attention readiness, perceived relevance, felt confidence and satisfaction potential. Students had not yet enrolled, so a systematic audience analysis was not possible.

Phase 2 (Motivational Design of the Simulations and Integration of Motivational Tactics) – the educational design team met to develop the learning experiences related to the learning goal structure, with particular emphasis on the goals related to interdisciplinary care. Team experts included those with knowledge of motivational learning design, simulation, drama, learning technology, midwifery and mental health. Through discussion it was agreed that simulated scenarios recorded as 360° videos could provide the opportunity to experience interdisciplinary caring and team-based decision-making. Two conditions taught on the course (bipolar affective disorder and obsessive-compulsive disorder) were selected as content for the scenarios, with the plan to use the video resources as part of the overall motivationally designed learning experience about interdisciplinary caring. As the team discussed the overall learning design, they aimed to apply the principles of the ARCS-V model. Table 1 provides examples of how motivational tactics were incorporated into the simulation design, including the pre-brief, simulated challenge set and post brief:

Table 1:

Summary and examples of the applied motivational tactics to the simulation design

ARCS components	Examples of the ARCS motivational tactics incorporated into the design
Capture & sustain Attention	Variability, perceptual and inquiry arousal aims to capture and hold attention through direct sensory stimuli and the motivational role of curiosity, which is supported by variation in style and sequence. That is, perceptual arousal is activated when there are changes within the learning environment; while inquiry arousal focuses on encouraging learners to seek out information, ask questions and solve problems in order to satisfy their own curiosity. Variability, however, is associated with attention maintenance.
	Examples of attention tactics used to design the simulated scenarios included:
	– Two women’s stories related to two different conditions and levels of deterioration were used to create and maintain inquiry arousal.
	– Variability across the scenarios was incorporated; for example, in one scenario, the woman was home alone (no visible support), while in the other a supportive partner was present in one of the scenes.
	– Sensory stimuli that related to the woman’s clinical condition, such as a crying baby, were also incorporated (perceptual arousal)
Communicate goal Relevancy	To communicate relevancy, three related theoretical tactics were applied: motive matching, goal orientation and familiarity. Examples of the relevancy tactics included:
	– Connecting the current learning experience to previous experiences as clinicians were achieved by co-designing scenarios that would be familiar with their work experiences
	– A key part of the pre-brief was to link the challenge that the students were about to experience with their personal interest as healthcare professionals (motive matching). This open discussion created relevancy as students shared the common challenges experienced when caring for women with deteriorating mental health.
	– Goal orientation was clearly framed as a ‘pause and ponder’ activity (see Figure 3). This enabled simulation of the interdisciplinary discussion and skills that the students would need to visualize and imitate in their future practice (interdisciplinary, team-based decision-making)
	– Mastery goal orientation enables students to engage in the right level of difficulty and cognitive challenge, therefore, increasing their ongoing persistence, effort and development.
	– In addition to using positive language related to mastering interdisciplinary caring, competitive language related to performance-orientated, motive matching was minimized. Instead, those more likely to be performance-orientated were able to represent satisfy their need during the debrief session. This design decision was based on the lack of available information as to whether students were high or low in achievement motivation.
Build Confidence	Confidence building occurs when the challenges are set appropriately, and students are encouraged to have a positive expectation for success. Another motivational tactic is to encourage students to own their successes and failures (attribution moulding). Examples of confidence building tactics included:
	– During the pre-brief the interdisciplinary team challenge and sequence were explained and set (see Figure 3). The main challenge was to identify the women’s deterioration and create an immediate care plan. As the students were also going to be experienced practitioners, the challenge was increased by placing cues around the room that provided subtle indicators of each woman’s condition. For example, a Christmas tree with one decoration still in the window weeks after the season pointed to disorganized thinking as a symptom of bipolar affective disorder; as a single empty wine glass suggested alcohol consumption while breastfeeding.
	– Attribution moulding included providing the students with the opportunity as a team to create their own interdisciplinary care plan. Each team talked through their plan (student-led debrief), demonstrating their competency, which in turn positively reinforces their expectancy, and ongoing effort to master successful identification of deterioration and decision-making as an interdisciplinary team.
Influencing intrinsic Satisfaction	Satisfaction indicates the relationship between the students’ expectations and outcomes achieved. The two main sources of satisfaction are intrinsic motivation (enjoyment related to taking part in the experience) and the rewarding consequences (extrinsic rewards). Intrinsic and extrinsic motivation can positively influence persistence, effort and learning, and off course satisfaction. Equity can also affect satisfaction, on the basis that if students perceive any unfairness, this will negatively affect their satisfaction with the learning experience. Examples of satisfaction tactics included:
	– Prior to participating in the simulated challenges, it was important that students had access to the required knowledge; otherwise, the challenge would feel unfair (equity). Lectures Consultant Psychiatrists and a tutorial that focused on the conditions were timetabled ahead of the simulations.
	– The post-simulation debrief aimed to provide motivating feedback. The student-led approach provided across-team encouragement via verbal reinforcement (stimulating intrinsic pride as a less obvious performance goal) for achieving the challenge set (present an interdisciplinary care plan with rationale for the team-based decision-making). The educators contributed to the feedback by recognizing related interests.
	– In addition to reinforcing the intrinsic satisfaction, public recognition of good performances aimed to act as an extrinsic motivator to the students. Effort attributions were also used to frame setbacks as challenges as opposed to evaluative threats.

Figure 3:

Outline of the pause and ponder simulation activities within a 2-hour class.

The two scenarios were recorded using a 360° camera and an additional spatial audio recorder. As described by Rizzo et al [35], 360° videos provide a panoramic view with all-round access to a ‘photorealistic’ view of the environment, for example, Google Street View. An advantage of 360° video footage is that it can be experienced via head-mounted display (HMD), as computer-generated virtual reality. While 360° video is a low-cost alternative to virtual reality, it has nonetheless shown equal potential in attaining ‘spatial presence’ (the degree to which learners feel the immersive environment is real to them). Young women capable of depicting deteriorating perinatal mental health as standardized patients were not available, so third-year drama students were coached in portraying the two women. A mental health nurse lecturer played the role of a ‘healthcare professional’. Each scenario was recorded as three acts, with each act representing a stage in the overall interaction. An interdisciplinary pause and ponder simulation activity was design and implemented as outlined in Figure 3. Taking time to pause and ponder as an interdisciplinary group facilitated the intersubjectivity that occurs when people who have different conceptualizations, commence a task together, and through the process adapt, until they have a shared understanding.

The idea of designing a pause and ponder approach as a means of initiating interdisciplinary discussion and learning amongst the students was created specifically for this study by the educational team. As students engaged in the co-design of a care plan for the women portrayed in the videos, it was anticipated that interdisciplinarity would be achieved.

Evaluation Phase : Although ARCS-V studies can include comprehensive evaluations [36], the main purpose is to provide the educators with a descriptive view that illustrates the degree of attention, relevance, confident and satisfaction experienced as a result of the motivational tactics applied. Through this process, educators can identify motivational problems and/or direct the next iteration in the students’ learning. To explore the potential impact of immersion on student motivation, the scenarios were experienced via either 360° flat screen videos or virtual reality headsets. In summary, a comparative approach was used to evaluate the motivational impact and the degree of immersion according to the modality (scenarios experienced via 360° flat screen videos versus virtual reality headsets). Participants were randomly allocated to one of two groups:

• Group A - engaged with the scenarios 360° immersive videos on virtual headsets
• Group B - engaged with the scenarios as a 360° video displayed on a flat screen monitor (computer screen) with headphones.

Ethical permission was granted by the Faculty of Health and Life Science’s Ethical Committee [Reference Number: MHLS 20_22].

Randomization

Participants were randomly allocated into Group A or B using Microsoft Excel’s random number generator by a member of the research team who was not involved in the module teaching. To ensure students experienced an interdisciplinary learning experience, the students were randomized to Group A or B according to their profession. Table 2 presents the student allocation to the groups following randomization. As there was not an equal number of students per profession, some within-group variation was unavoidable.

Table 2:

Randomization of professions to Groups A and B

Randomized to Group A	Randomized to Group B
Team 1 2 Midwives, 1 Health Visitor, 1 Mental Health Nurse	Team 1 1 Midwife, 1 Health Visitor, 1 Mental Health Nurse
Team 2 2 Midwives, 1 Health Visitor, 1 Mental Health Nurse	Team 2 2 Midwives, 1 Health Visitor, 1 ER Nurse
Team 3 2 Midwives, 1 Health Visitor, 1 Mental Health Nurse, 1 ER Nurse	Team 3 2 Midwives, 1 Health Visitor

Group A viewed both scenarios using 360° videos via virtual reality headsets, whereas Group B viewed the same scenarios on a computer screen display that could be viewed 360° using the computer mouse (Table 3):

Table 3:

Modality for viewing according to group

Group	OCD (Time 1)	BPD
A	360° video via VR headsets	360° video via VR headsets
B	360° video via computer display screen	360° video via computer display screen

Results

A total of 23 students completed the study. Participant demographics are listed in Table 4:

Table 4:

Demographics of students participating in the study

Variables	Frequency	Percent	Cumulative percent
Age: 21–30	4	17.4	17.4
31–40	10	43.5	60.9
41–50	9	39.1	100.0
Used Learning Videos Before: Yes	7	30.4	30.4
No	16	69.6	100.0
English First Language: Yes	20	87.0	87.0
No	3	13.0	100.0

Motivational Results : the mean for each of the four ARCS dimensions were calculated for the study population, as indicators of how well the video-based simulations motivated students to learn about interdisciplinary care planning for two women whose perinatal mental health was deteriorating. Table 5 is a summary of the descriptive statistics related to Attention, Relevance, Confidence and Satisfaction:

Table 5:

Descriptive statistics including composite means for the four dimensions of motivation to learn

Dimensions of motivation	Min.	Max.	Mean	Standard deviation	Composite means
Attention  Quality of videos held my Attention	3.00	5.00	4.56	0.6623
Pause and Ponder held my Attention	3.00	5.00	4.52	0.6653
Variety of the videos for care planning held my Attention	3.00	5.00	4.43	0.6623	Attention: 4.5
Relevance  Clear P&P videos helped me learn about interdisciplinary care planning	2.00	5.00	4.30	0.8221
Content and style conveyed the relevancy of PMH knowledge	4.00	5.00	4.86	0.3443
The content of the videos was useful to me	3.00	5.00	4.56	0.6623	Relevance: 4.6
Confidence  As we watched the video, I was confident I could learn	3.00	5.00	4.39	0.8387
After watching, I was confident I could listen to similar women	3.00	5.00	4.34	0.7140
Organization of the videos and discussion helped my confidence to lead caring in an interdisciplinary team	2.00	5.00	4.21	0.9513	Confidence: 4.3
Satisfaction  I enjoyed working with the P&P videos; they stimulated me to keep on learning	2.00	5.00	4.60	0.7223
I really enjoyed learning using the videos and the P&P approach	1.00	5.00	4.30	1.105
It was a pleasure to watch and discuss such well-designed videos	2.00	5.00	4.47	0.8458	Satisfaction: 4.6

To explore if motivational differences existed between those who viewed the videos in headsets versus computer display screen, a Chi-square test was conducted in relation to each of the ARCS dimensions. No significant differences were noted between groups (Attention X² 3.23, NS 0.198), (Relevance X² 2.85 NS 0.414), (Confidence X² 2.85, NS 0.239), (Satisfaction X² 5.79, NS 0.215).

Immersive Results: four items explored the degree of immersion experienced by the participating students (n = 23), including a comparison between groups (Table 6):

Table 6:

Descriptive statistics for the items measuring immersion

Immersive items	Min	Max	Mean	Standard deviation	Significant group difference
I felt I was standing in her room	1.00	7.00	4.78	1.832	0.165
I think of the space as a place similar to others I have been in	2.00	7.00	5.34	1.300	0.281
During the video, I had strong sense of being in place/elsewhere	1.00	7.00	5.30	1.819	0.202
Think back on experience, think of image or somewhere visited	2.00	7.00	5.26	1.514	0.093
Times during experience, woman’s room felt real	3.00	7.00	5.65	1.300	0.247
I had real sense of being in the room	4.00	7.00	5.95	1.106	0.204

No significant differences were noted in the level of immersion experienced between the groups.

Visualizing the results

The findings related to attention, relevance, confidence and satisfaction were discussed and mapped onto an inverted U (Figure 4). Based on Yerkes Dodson Law [1908] as cited by Keller [15] the inverted U respects the curvilinear relationship between motivation and performance. For example, in relation to arousal (psychological basis for attention), a low level tends to result in low performance, yet as arousal increases, the quality and quantity of performance also increases. The effect is only beneficial to an optimal level, in that performance will deteriorate if arousal increases beyond the optimal as a result of stress. The same principle of optimization applies to relevancy, confidence and satisfaction. For example, if confidence is too low, students’ performance will be hindered by their feelings of helplessness, while if it is too high, their overconfidence can result in learning gaps, in that what they actually know does not enable them to adopt the challenge set. Keller [15, pg 211] points out that this exercise is heuristic, ‘as the methods for measuring motivational levels are not sufficiently precise or stable for creating rigorous mathematical models’. Immersion was not plotted as it does not have the same inverse relationship with performance. However, both groups reported a positive level of immersion, suggesting that the motivation was related to the motivational tactics which both groups experienced equally, and not the level of immersion that was experienced differently between the groups.

Figure 4:

Heuristic mapping of the ARCS components onto an inverted U.

In this ARCS-V application, the findings were plotted in the upper aspect of the inverted U as an acceptable level of motivation, indicating that the learning design achieved an optimal level for the groups of students. Deciding that the ARCS components should be plotted as motivationally acceptable, as opposed to too high, was based on the fact that all four components were reported at a similar level. Variation between the components would have indicated a motivational problem.

Discussion

The main purpose of an ARCS-V application is to direct the educator in embedding motivational tactics into the learning design, so that the student audience experiences optimal motivation. Designing motivating simulations is important, as students who are optimally motivated are more likely to experience intrinsic motivation to learn and therefore, feel psychologically safer. Psychological safety within simulation proposes that over-challenging students leads to stress (over arousal so suboptimal attention ) therefore, interfering with their knowledge recall and performance [40]. Likewise, if psychological safety is achieved, students are more likely to engage in self-correcting behaviours, which is also reflective of students’ volition as a result of optimal attention, relevance, confidence and satisfaction. As such, the application of a motivational design model, namely the ARCS-V model to perinatal mental health scenarios, has several benefits for interprofessional simulation and learning.

In this implementation of the ARCS-V model, the results were achieved by creating mainly a mastery-orientated group challenge. Simulation-based mastery learning (SBML) is already well documented, especially within medical education. As an omnibus approach, SBML includes key instructional design aspects, such as determining baseline diagnostics, setting scaffolded goals, engaging in supportive learning activities and ongoing assessment and feedback until the standards are met [41]. Although motivation may occur, theorists such as Barron and Harackiewicz [42] make an evidence-based argument for carefully considering the motivational impact that the types of goals set can have. For example, although SBML argues for mastery orientation, the instructional design by default includes a performance measure which students are challenged to adopt as their goals (assessments). Likewise, while the main emphasis of the ARCS tactics in this study aimed to create a mastery-orientated learning environment, it was recognized that mastery orientation alone could not meet the motivational needs of all students, especially those who were high in achievement motivation. Butler [43] therefore recommends that a multiple-goal approach is taken, where mastery goals are combined with performance goals to influence student motivation. This discussion draws out the importance of framing the learning goals both as mastery and performance goals, so most participants can feel optimally motivated.

Mastery goals are defined as those that enable the development of an ability. Performance goals are those that enable the ability to be demonstrated. According to Molden and Dweck [44] performance goals are motivated by a desire to ‘approach success’ and/or ‘avoid failure’. This subtle difference is critical when it comes to adding meaning to how learning is experienced. For example, students who are motivated to approach a performance goal (demonstrate their competency), when successful, can enjoy, value the task and in doing so experience the benefits of intrinsic motivation. In turn, their intrinsic motivation enables them to maintain their mastery-orientated pattern, even if faced with a performance failure. Exposed to these motivational influences, student groups who adopt mastery and performance-orientated goals alongside each other are, therefore, more likely to learn through effort while remaining psychologically safe. However, when students approach a challenge mainly from a motivational basis of wanting to avoid failure (performance avoidance-goal), they become vulnerable, risk-avoidant, defensive and have low intrinsic interest and performance [44]. It is because of this possibility that mastery-orientated learning goals tend to take centre-stage when educators are designing new learning experiences; yet for students high in achievement motivation, an opportunity to demonstrate their competency as an approach performance goal is equally important.

In this study, the simulated activity was being designed for a new student cohort; therefore, the aim of the design team was to emphasize mastery orientation, supported by a less obvious performance orientation. Taking a multiple-goal orientation where strong mastery goals are paired with less predominant performance goals [44] is a good starting point when students’ motivation is unknown. For example, the pause and ponder aspect of the learning experience was designed as a stronger group-based, mastery goal (pause and ponder) combined with a weaker performance-approach goal (student-led debriefing, enabling those high in achievement motivation to demonstrate their ability and generate intrinsic pride). The presence of the performance goal opportunity within the mastery-orientated context was further managed by designing the group-based challenge. Underpinned by Datt and Aspden when applying the ARCS model to skill development in netizens, group-based activity can engage students as natural collaborators, who enjoy learning through co-constructed social learning experiences [26].

In summary, the findings confirmed that for this group of students, the applied motivational tactics guided the goal structuring and resulted in optimal motivation to learn about perinatal mental health and how to provide interdisciplinary care. It follows that the pragmatism of Keller’s ARCS-V model [15] can enable educators to design optimally simulating learning activities, even when the motivational response of the students to simulated learning is not previously known.

Conclusion

Designing interdisciplinary simulations related to interdisciplinary perinatal mental healthcare is known to be challenging. Yet, this study supported the concept that an interdisciplinary learning simulation about perinatal mental health that was designed using the ARCS-V motivational design model [15] can be optimally motivating. Whether viewed via flat screen and earphones or virtual reality headsets, the recorded scenarios created optimal attention, relevance, confidence and satisfaction for the student groups. Although the results are situational, the potential for further research into the use of the ARCS-V model related to simulation design and evaluation exists.