Feasibility of the Mio-Training: A metacognitive training for children and adolescents

doi:10.21203/rs.3.rs-8163350/v1

Background: The Mio-Training is a novel multicomponent mobile serious game designed to strengthen cognitive development of children and adolescents. By combining intensive working memory training, mnemonic strategy training, coordinative challenges, and metacognitive reflection, the Mio-Training addresses the shortage of effective cognitive training programs for children and adolescents. This article reports on the development of the Mio-Training and presents results from a feasibility study with healthy children and adolescents.

Methods: We included 21 healthy children and adolescents (aged 8-16 years) who underwent 5 weeks of Mio-Training and filled out a feasibility questionnaire (enjoyment, usability, level of autonomy, perceived impact, preferences and potential improvements) after using the Mio-Training. Within-training performance data was collected during the use of the multimodal Mio-Training.

Results: The Mio-Training was perceived as feasible, with a high compliance rate of 95%. The usability, the enjoyment of the training, the level of autonomy and the perceived impact were rated as positive. The compliance and the socioeconomic status correlated significantly with enjoyment of the training, design, perceived flexibility, perceived difficulty, subjective duration of the training, motivation and self-efficacy (r = .455 to .698, p <.001 to .044). Within-training performance improved significantly after acquiring a new mnemonic strategy (p<.001 to .005, g = .327 to .881). Data from the intensive working memory training revealed strong variability in performance gains, with approximately half of the users showing improvement in their working memory performance.

Conclusion: This study gives insight into the feasibility of a novel digital, game-based, multimodal training program focusing on metacognition. The combination of feasibility data and within-training performance essentially contributes to the development and revision of the Mio-Training. We conclude that the Mio-Training is feasible and users show high compliance. However, there is large inter-individual variance in within-training performance, and an evaluation of individual progress patterns is needed. With the insights of this feasibility study the Mio-Training will be evaluated in young patients with an increased risk for atypical cognitive development such as children after cancer or with AD(H)D and will hopefully lead to cognitive far transfer effects in everyday and school life.

Trial registration: Clinicaltrials.gov (NCT06464237, date of registration: 12.06.2024)

cognitive training

metacognitive abilities

childhood

mnemonic strategies

motor coordination

working memory training

Cognitive development in children and adolescents is shaped by a complex interplay of genetic and environmental factors (1–3). Strengthening cognitive performance in atypical cognitive developing children and adolescents is essential, as it supports academic achievement and everyday functioning (4–6). In light of the shortage of qualified professionals and long waiting times for therapy, digital interventions offer a promising approach to fostering cognitive abilities in children and adolescents, hence serving as a transitional or complementary resource to traditional therapy (7, 8).

Different approaches are used to address the strengthening of cognitive performance. Most common are programs that focus on the intensive training of a specific cognitive function such as for example the crucial domain of working memory (9–12). However, these trainings have only limited, often short-term effectiveness and lack a transfer effect to non-trained tasks (13), meaning that they only train a specific function (i.e. working memory) without a benefit for other cognitive domains. Besides intensive training of a specific cognitive function, applying mnemonic strategies might have an effect on cognitive long-term outcomes of children and adolescents (10, 14, 15). Mnemonic strategies are effective in promoting better encoding and enhancing both short-term and long-term memory functions. Research shows that applying mnemonic strategies entails a far transfer to untrained tasks, such as an improvement in reading ability or attention performance (10, 11, 16). The acquisition of mnemonic strategies further enables the promotion of metacognitive thinking (17, 18) as the use of cognitive strategies asks for self-reflection, reflection on the task’s demands, and monitoring as well as adaptation of one's own performance. Recent studies show that metacognitive interventions enhance children’s self-efficacy and have a positive effect on executive functions (19). Well established metacognitive skills can serve as a regulator of cognitive processes and may assist children in reflecting on and managing their own learning (20, 21).

Metacognition comprises two main components: metacognitive knowledge and metacognitive regulation (18). Metacognitive knowledge refers to the awareness and understanding of one’s own cognitive processes. It includes knowledge of the use and application of cognitive strategies, about oneself as a learner (e.g., knowing one’s strengths and weaknesses), and about task demands (e.g., recognizing which strategies are suitable for certain tasks). This knowledge may positively influence the approach to new tasks and through this has an impact on performance. Metacognitive regulation, in contrast, refers to the active control and management of one’s cognitive processes. This includes planning how to approach tasks, monitoring one’s understanding and progress, and evaluating the effectiveness of the chosen strategies (18). Multicomponent approaches that combine metacognitive reflections, mnemonic strategy use, and the training of specific cognitive functions show promising results, as they lead to improvements in cognitive and psychosocial functions, such as social skills (22).

Multicomponent cognitive interventions ideally should include physical training, as evidence suggests that cognitive outcomes can be enhanced through physical activities (17). Short and long-term physical activity can have a positive effect on cognition, particularly when physical tasks involve cognitive challenges (17, 23–27). A recent systematic review and meta-analysis showed that physical activities with cognitive engagement promote the development of executive functions (28). ໿Regarding long-term physical activity, cognitively challenging physical activity was found to have superior effects than non-cognitively challenging physical activity across core executive function outcomes (29).

There is growing research interest in digital intervention programs, which have been shown to positively influence cognitive development (30). Gamification and especially serious games aim to enhance user motivation and increase engagement (31, 32). Gamified trainings can support the users to change aspects of their behaviour to support learning (33). A meta-analysis by Ren et al. (2023; (34) showed that the task content and game features of digital interventions can contribute to training effects. The potential for effectiveness and training-related benefits, as well as adherence is particularly enhanced when game-based interventions are co-designed with and for the target group and developed within an interdisciplinary team (35, 36).

To sum up, there are cognitive trainings that show a certain effectiveness but address specific aspects of cognition. In order to offer a holistic training with a far transfer effect to other tasks, school performance and everyday life, a multicomponent approach is needed that combines the various training approaches. Further, we envision a training that is motivating, easily accessible, easy to use and can be implemented without the need for specialized staff. Therefore, we developed a playful, digital multicomponent cognitive training approach combining intensive working memory, learning of strategies, as well as physical and metacognitive training to strengthen cognition of children and adolescents in the long-term – the Mio-Training.

This study aims to assess the feasibility of the Mio-Training in healthy children and adolescents, before conducting clinical trials in patients with atypical development such as children after cancer and with Attention-Deficit/Hyperactivity Disorder (AD(H)D). The comprehensive feasibility study will combine qualitative metrics to (1) assess the enjoyment of the training (2) evaluate the usability (3) determine the level of autonomy of the users (4) assess the perceived impact of the training (5) document the preferences, motivation and suggestions for potential improvement and will include quantitative metrics to (6) evaluate the compliance and (7) analyse the within-training performance. We hypothesize that the Mio-Training will be perceived as feasible and will induce changes in within-training performance in children and adolescents.

This study is a sub study of the Mio-Study, a randomized clinical trial performed at the Children’s University Hospital, Inselspital Bern, Switzerland. Details of the study procedure are presented in Salzmann et al. 2025 (under review; (37)).

2.1. Participants

In total, 21 healthy Swiss children and adolescents aged 8 to 16 years underwent the Mio-Training in the framework of the Mio-Study. Excluded were participants with a known neurological, psychiatric or other chronic disease influencing their cognitive development. One participant decided to terminate the study due to a lack of time for the training. The final sample compromised 20 children and adolescents. Written consent was obtained from one parent or legal guardian. Participants aged 14 years or older additionally provided their own written consent. The study was approved by the ethics committee of the University of Berne (2023-12-05).

2.2 Study Design

The study was conducted between October 2024 and July 2025. The training group used the Mio-Training for 5 weeks, 3 sessions per week with 15 training sessions in total. After the completion of the Mio-Training, the participants filled out a questionnaire aiming to evaluate their experience with the Mio-Training. During the Mio-Training, within-training user data was assessed.

2.3. Outcome Measures

Baseline characteristics (age, sex, socioeconomic status and intelligence) were assessed. Socioeconomic status included parental education (categorized into eight levels from secondary education to doctorate) and net annual income (1 = unemployed to 10 = over CHF 110,001). A total socioeconomic status score was calculated including the highest education and the yearly net salary of both parents. These scores were z-standardized and summarized to a mean value. General intelligence was assessed with the Wechsler Intelligence Scale for Children – Fifth Edition (WISC- V; (38).

Feasibility Questionnaire

To assess the feasibility of the Mio-Training, participants completed a study-specific feasibility questionnaire adapted from existing validated scales such as the system usability scale (39), the game experience questionnaire (40) and the intrinsic motivation inventory (41) as well as newly developed items tailored to the study context (see supplementary material S1). The questionnaire evaluates the experience regarding (1) the enjoyment of the training program (2) the usability (3) the level of autonomy of the users while using the training program (4) the perceived impact of the training program and (5) the preferences, motivation and suggestions for potential improvement received from the feedback of the users by identifying challenges and make adjustments (see Figure S1). The questionnaire comprises 68 items on a 4-point Likert scale (1 = strongly disagree to 4 = strongly agree; negative evaluation < 2, positive evaluation > 2) and open questions.

User data

During the 5-week training, we constantly assessed user data including the objective session duration (per session), the compliance (session completion after 5 weeks) and the use of the difficulty levels. Further, within-training performance was assessed, namely performance in the cognitive games (% correct) and the answers to the metacognitive questions (depending on question: range from 0-100; yes = 1; no = 0). No within-training performance data for the coordinative challenges is available.

2.4. Development of Mio-Training

The Mio-Training was conceptualized and developed between October 2023 and March 2024 at the Divison of Neuropediatrics, Development and Rehabilitation at the Inselspital in Bern in collaboration with the software development company Pioneo GmbH. The thematic framework was developed in a co-creation workshop with all partners, including neuropsychologists, a developmental psychologist, a sport scientist, and two app developers. The workshop addressed practicability, technical feasibility, search for common interfaces of existing programs, performance tracking, program adjustment, and the implementation of a reward system. To ensure user-centered design, workshops with healthy children and adolescents were conducted to explore relevant factors for engaging training programs, including gaming preferences and ideas for the narrative, design, protagonists and their tolls and reward elements. As the Mio-Training will be evaluated in the specific population of cancer survivors, interviews with specialized staff (e.g., nurses, sport scientists, teachers, neuropsychologists) were carried out to identify key considerations for study design and App development.

2.5. Mio-Training

The Mio-Training is a new multicomponent training approach that intends to be easily accessible and feasible in everyday life without the need of specialized staff. It is designed as a mobile serious game (App) – a game with a purpose beyond fun (42) – for children and adolescents with the aim to strengthen the cognitive development in the long-term in a multimodal manner. The training includes (1) teaching and practicing of five mnemonic strategies via games, (2) coordinative challenges, (3) visual and auditive intensive working memory training games, and (4) metacognitive reflections. The Mio-Training takes the user on a journey through space. During the 5-week training, the users complete 15 training sessions on five different planets, three training sessions on each planet. Through a chatbot, the users are guided through the training sessions. Each planet has its own characteristics and inhabitants which teach and train mnemonic strategies and help the users through the Mio-Training. The training provides motivating feedback, is rich in variety and fosters self-efficacy and self-confidence. Additional game elements such as a reward system, a narrative, different difficulty levels, challenges and a repeat function keep the users motivated and engaged in the training.

Mnemonic strategies

Five mnemonic strategies are taught and practiced in the framework of 24 minigames.

In the first session of each planet a cognitive game (without the introduction of a mnemonic strategy) followed by an introduction of a mnemonic strategy via the chatbot and a repetition of the game using the mnemonic strategy is presented. At the end of the training session the same cognitive game is played again by autonomously recalling the mnemonic strategy learned beforehand (Fig. 1). The cognitive games are based on the principles of the “Memo-Training” (10, 11, 16) and adapted for digital implementation.

“Similarity trick” (“free association, elaborative encoding”): New information is associated with familiar concepts, either auditorily (linking a sound to a similar tone), or visually (relating shapes to a familiar object). This facilitates the memorization of corresponding terms.
“TV-trick” (“visualization/mental imagery”): Forming vivid mental images of the material being learned (e.g. closing eyes and visualizing it as if on a TV screen), enhances memory retention through the use of mental imagery.
“Story trick” (“chaining”): Connect individual pieces of information into a coherent narrative. This storytelling approach may improve recall by remembering the overarching narrative.
“Symbol trick” (“dual coding/symbolic representation”): Use symbols or notes that represent the material to be learned, supporting deeper information processing and improving long-term retention.
“Echo-trick” (“inner rehearsal”): Practicing repeating words (i.e. such as vocabulary in a foreign language) multiple times. This repetition, analogous to an echo, strengthens memory consolidation and recall.

Three difficulty levels are implemented (easy, moderate, difficult) according to the question “How cognitively fit do you feel today?” presented via the chatbot.

Coordinative challenges

One of 15 different coordinative tasks is presented in every session via a video tutorial aiming to stimulate cognitive flexibility by means of coordinative challenges (Fig. 1). The coordinative challenges such as ball, dance and balance challenges, were created in collaboration with sport scientists. Via the chatbot, the participants are encouraged to repeat the exercises in their daily routines.

Working memory training

15 adaptive minigames (eight visuospatial and seven auditory working memory games) aiming to extend the short term and working memory span are presented (Fig. 1). In the visuospatial working memory games, various objects illuminate in a specific sequence and are replicated in the same order, targeting short-term memory. The task is repeated by reproducing the sequence in reverse order, engaging working memory. The auditive working memory games present five colored dots, each of which can be repeatedly tapped to familiarize with the associated sounds. Subsequently, sequences of sounds, are reproduced by tapping the corresponding-colored dots.

Metacognitive reflections

Before and after the minigames and the coordinative challenges, 139 metacognitive reflections were implemented in the chatbot. Via specific questions children and adolescents are encouraged to reflect on their cognitive processes and strategies during task completion (Fig. 1). The purpose of these metacognitive reflections is to foster awareness on strategy use and thereby enhance the management of difficult tasks.

Different answer types are implemented in the chatbot such as yes or no answers (Do you know a trick that could help you with this task?), ranges adjustable via sliders (How difficult was this task for you?: not difficult to very difficult) and open space for own text. The questions are based on the metacognitive cycle adapted from Ambrose et al. 2010 ((43)Figure S2). We focused on (1) prospective questions on assessing the task demand, evaluate own strength and weaknesses in respect to the task demands and plan the approach and (2) retrospective questions focusing on cognitive reflections and adjustments of cognitive strategies after finishing the games and challenges.

Hardware and software

The Mio-App is available for Android and iOS and can be used on the Smartphone or a tablet. The App will be updated for new regulations and technical changes in a frequent manner.

In total 15 sessions are implemented in the Mio-Training on five different planets. In the first session on each planet a new mnemonic strategy is introduced. Metacognitive questions are answered via the chatbot (yes/no or with graded responses (not at all to very much)).

2.6. Statistical analysis

Statistical analyses were conducted using R Studio (Version 2024.12.1 + 563). Initially, the data was tested for normal distribution using visual inspection and the Shapiro-Wilk Test. The alpha level was set to .05 for all tests. Descriptive statistics were reported for demographics, feasibility questions and user data. To assess common themes, recurring issues and specific areas requiring attention within the open questions, a systematic examination of the feasibility questionnaire was conducted. Reverse items in the feasibility questionnaire were recoded so that higher scores indicate a positive evaluation. Means and standard deviations were calculated for all the feasibility subscales. To assess if the age, sex, intelligence, the socioeconomic status and the compliance influence the ratings of the participants’, spearman correlations and independent t-test were applied. For the within-training performance the mean and ranges were calculated and visualized. Absolute and relative change scores were calculated for the mnemonic strategy games. Group differences between the mean scores of the performance before the teaching and practicing of mnemonic strategies and the performance after learning the mnemonic strategies and the long-term recall using a Mann-Whitney-U test were calculated. The effect size was determined with the Hedge’s g (small effect g = 0.2, moderate effect g = 0.5, large effect g = 0.8). The mean working memory performance of the first two sessions and the last two sessions was compared using a Mann-Whitney-U test, and Hedge’s g was calculated to estimate the effect size. The mean, median and ranges were calculated for the metacognitive reflections before and after teaching and practicing mnemonic strategies.

3.1. Demographics

In total 21 participants (10 females) were included in the study, all aged 8 to 16 years (M = 10.57, SD = 1.72). One participant withdrew from the study and therefore 20 participants were included in the analysis. Demographics are presented in Table 1.

Table 1

*Demographics of the study population (N = 20)*
	Mean (SD/ N (%))	Range
Female sex	10 (50.00%)	-
Age	10.57 (1.72)	8–14
Body mass index (BMI)	18.25 (3.23)	13–29
Education participant (years)	5.00 (1.73)	3–8
Mean socioeconomic status	0.01 (0.76)	-0.99-1.17
Mother: Highest education	5.24 (1.97)	2–8
Net salary	5.14 (2.69)	2–10
Father: Highest education	4.18 (1.99)	2–7
Net salary	7.30 (2.23)	2–10
Intelligence (IQ)	112.95 (10.57)	93–127
Note. Data presented as mean (standard deviation) or incidence (%).

3.2. Feasibility of the Mio-Training

The enjoyment of the training, the usability, the level of autonomy and the perceived impact were rated as positive (Table 2). No significant correlations occurred between feasibility scores and age and intelligence (see Table S1. Correlations between feasibility, age, intelligence, socioeconomic status and compliance). The ratings of the perceived duration of the training and self-efficacy differed significantly between female and male with higher ratings in males (see Table S2. Sex differences in feasibility ratings). The socio-economic status correlated significantly with the perceived design of the training (r = .467, p = .038), the perceived flexibility (r = .532, p = .016) and self-efficacy (r = .565, p = .015). Compliance was significantly associated with enjoyment of the training (r = .457, p = .043), perceived difficulty (r = .500, p = .025), motivation (r = .515, p = .024), perceived design of the training (r = .652, p = .002), design of the physical activity tasks (r = .698, p < .001), evaluation of the duration of the training (r = .565, p = .009), perceived flexibility (r = .455, p = .044) and self-efficacy (r = .590, p = .010). Therefore, higher socioeconomic status and compliance related to better feasibility ratings.

Compliance

16 out of 20 (80%) participants completed the whole Mio-Training (15 out of 15 sessions). 19 out of 20 (95%) participants, who finished the Mio-Training were scored as compliant (> 80% of the sessions completed). Reasons for not completing the training were a lack of time (N = 3) and/or technical problems (N = 2).

Enjoyment

The enjoyment of the Mio-Training was rated as positive (> 2 points on the Likert scale). The training was perceived as interesting (N = 15, 75%), fun (N = 16, 80%), not frustrating (N = 18, 90%) and enjoying (N = 16, 80%) by most of the users. Most of the users did not feel pressure (N = 20, 100%) or felt tense (N = 17, 85%) during the training and the difficulty level was perceived as manageable (N = 17, 85%; not too easy not too difficult) and were motivated (N = 14, 70%). For some participants (N = 5, 25%) it was difficult to combine the training and everyday life tasks (i.e. hobbies, homework). The overall design (N = 20, 100%) and narrative (N = 15, 75%) of the training was rated as positive (> 2 points on the Likert scale).

Usability

The usability was rated as positive (> 2 points on the Likert scale). The users easily understood how to use the training (N = 19, 95%) without further help (N = 18, 90%) whereas some rated the duration of the training as too long (N = 7, 35%). The mean objective session duration was 19.28 minutes (SD 8.73, range 14.28 to 23.30 minutes).

Level of autonomy and perceived flexibility

All of the user easily understood the tasks and explanations (N = 20, 100%). Most of the users reported that the performed the training without help of someone else (N = 16, 80%) and appreciated the flexibility to autonomously choose the training days (N = 19, 95%), whereas half of the users liked the autonomous choice of difficulty level (N = 10, 50%). Some of the users chose varying difficulty levels (N = 12, 60%). Across all mnemonic strategy tasks, 22.2% of the users chose the easiest level, 66.5% the medium level and in 11.4% the highest difficulty level.

Perceived impact

The mean self-efficacy was rated within the positive range (> 2 points on the Likert scale) but was lower compared to the other feasibility scores. Some of the users stated that they improved their performance during the training (N = 16, 80%) and that they managed the tasks to their satisfaction (N = 18, 90%). Most of the users did not report a change in their school performance (N = 14, 70%) or daily life (N = 13, 65%), indicated that they have learned new mnemonic strategies (N = 18, 90%) and that they are using them in daily and school life (N = 13, 65%).

Preferences, motivation and suggestions for potential improvements

There was no clear preference for any specific task. Tasks were neither to easy (N = 13, 65%) nor too difficult (N = 10, 50%). Motivating factors included the reward system (N = 4, 20%), the design (N = 4, 20%), the narrative and curiosity about training progression (N = 4, 20%), learning new things (N = 3, 15%), helping other children (N = 3, 15%), and fun (N = 1, 5%). Most trained at home (N = 13, 65%), while others trained both at home and on the go (N = 7, 35%).

Suggestions for improvement focused mainly on design adjustments (e.g., colors, character details). Regarding the narrative, one user preferred less, another more, while most were satisfied. To enhance enjoyment, users suggested more task variation (N = 5, 25%), improved task design (N = 4, 20%), fixing technical issues (N = 2, 10%), revising coordinative challenges (N = 3, 15%), adapting for younger children (N = 1, 5%), and enabling interaction with other users (N = 1, 5%). Six users (30%) would not change anything in the Mio-Training. Eight users (40%) reported minor technical errors.

Users gave suggestions for the coordinative challenges, including improving the visuals and fun of the coordinative challenges, clearer progress reporting, adding dance steps for enjoyment, offering an option to continue or skip challenges, using outdoor or colorful backgrounds and emphasizing the positive impact on concentration. Two users (10%) suggested making coordinative challenges more demanding. Six users (30%) would not change anything.

Table 2

Feasibility and user data of the Mio-Training
	Mean (SD)	Range
Enjoyment
Enjoyment of the training	3.00 (0.53)	1.90-4.00
Pressure/tension	3.42 (0.56)	2.33-4.00
Perceived difficulty	3.17 (0.54)	2.00–4.00
Motivation	2.97 (0.80)	1.25-4.00
App use in everyday life	2.05 (0.51)	1.00-2.50
Design of the training	3.22 (0.40)	2.29–3.71
Metacognitive questions	3.09 (0.77)	1.00–4.00
Physical activity	3.00 (0.57)	2.00–4.00
Usability
Usability	3.36 (0.47)	2.50-4.00
Perceived duration of the training	2.66 (0.68)	1.50–3.75
Level of autonomy
Accessibility	3.55 (0.63)	2.00–4.00
Perceived flexibility	2.85 (0.71)	1.67-4.00
Perceived impact
Self-efficacy	2.70 (0.52)	1.56–3.67
Strategy use	2.94 (0.74)	1.20-4.00
User data
Compliance (N; %)	19; 95.00%	47–100%
Session done	14.30 (1.89)	7.00–15.00
Session duration	19.28 (8.73)	14.28–23.30
Note. Data presented as mean (standard deviation) or incidence (%).

Mean < 2.0 = negative rating, > 2.0 = positive rating).

3.3. Within-training performance

Mnemonic strategy training

In four of the mnemonic strategy games, we observe a significant difference between the performance before and after the teaching and practicing of mnemonic strategies with small to large effect sizes (“tricks”, Table 3). Relative change scores are highest for the “similarity trick” and lowest for the “story trick”, indicating the most versus least benefit from these mnemonic strategies when compared to others. Data from the mnemonic strategy game “symbol trick” is missing, as technical error occurred, such as reported by some users (N = 2, 10%).

Figure 2 visualizes the within-training performance changes between the performance before and after the teaching and practicing of mnemonic strategies (“trick”) and the subsequent long-term recall. The users show the highest performance change with the use of the “similarity trick”. Interestingly, performance in the long-term was significantly better than after learning the “similarity trick” (U = 0.0, p = .002, g = .387). Performance during the “TV-trick”, “story trick” and “echo trick” increases after acquiring the mnemonic strategy and slightly decrease in the long-term recall (Table 3, Table S4 Performance changes after learning strategy to long-term recall). Significant differences between performance before strategy use and long-term recall occurred for the “similarity trick” (U = 1.0. p < .001, g = 1.45) and the “story trick” (U = 14.0. p = .030, g = .298; Table S3 Performance changes before learning strategy to long-term recall).

Short-term and working memory training: Mean working memory performance showed a slight, non-significant increase from the first two to the last two sessions (Table 4). Individual progress patterns varied: 12 users (70.59%) improved after short-term memory training, eight (47.06%) after visuospatial working memory training and 12 (63.16%) after auditive working memory training. In contrast, five (29.41%), nine (52.94%) and seven (36.84%) users, respectively, showed decreases in performance.

Table 3

Absolute and relative changes and group differences in performance before and after the teaching and practicing of mnemonic strategies (“tricks”)
	Without mnemonic strategy use	With mnemonic strategy use	Absolute change	Relative change	U	p	g
Similarity trick	26.19 (35.84)	62.86 (43.38)	36.67 (43.74)	1.51 (2.97)	4.5	.003	.881
TV-trick	35.34 (38.97)	57.14 (43.03)	21.81 (31.01)	0.88 (1.32)	0.0	.004	.508
Story trick	47.30 (33.67)	65.71 (36.65)	18.41 (18.15)	0.42 (0.82)	3.5	< .001	.496
Symbol trick	56.89 (41.96)	-	-	-	-	-	-
Echo trick	25.10 (24.93)	36.11 (31.33)	11.02 (12.82)	0.49 (0.61)	0.0	.005	.327
Notes. Group differences were calculated to compare the mean values between the timepoints ”without trick” and “with trick”: U = Mann-Whitney-U-test; p = significance (α < .05 = , α < .01 = *); g = effect size (Hedge’s g; small effect g = 0.2, moderate effect g = 0.5, large effect g = 0.8). Change scores were calculated accordingly: absolute changes (with trick – without trick), relative changes (with trick – without trick/without trick).

Table 4 Differences between performance in the first two sessions and last two sessions of short-term and working memory training

	First two sessions	Last two sessions	U	p	g
Short-term memory (visual)	38.94 (13.33)	44.41 (21.33)	44.0	.222	.290
Working memory (visual)	31.62 (19.60)	35.35 (21.47)	39.5	.432	.181
Working memory (auditive)	20.53 (16.57)	32.37 (23.53)	41.5	.102	.435
Notes. Group differences were calculated to compare the mean values between the
performance in ”first two sessions” and “last two sessions”: U = Mann-Whitney-U-test;
p = significance (α < .05 = , α < .01 = *); g = effect size (Hedge’s g; small effect

g = 0.2, moderate effect g = 0.5, large effect g = 0.8).

Coordinative challenges: No within-training performance data is available from the coordinative challenges as task performance was neither recorded via video nor via motion-tracking. However, the feasibility questionnaire on the coordinative challenges reveal that the mean feasibility rating was 3.00 (SD 0.57). Eight users (40%) reported to have completed all coordinative challenges, five almost all (25%) and three (15%) only few coordinative challenges (4, 20% did not answer this question). Fourteen (70%) users reported active engagement in all tasks. Users rated the design of the coordinative challenges as positive (N = 17, 85%; design scale: M = 3.25, SD = 0.85), as fun (N = 16, 80%; fun scale: M = 3.10, SD = 0.72), as boring (N = 3, 15%; boring scale: M = 3.45, SD = 0.76), as motivating (N = 15, 75%; motivation scale: M = 3.10, SD = 0.79) and as demanding (N = 2, 10%; demand scale: M = 3.45, SD = 0.69). Four users (20%) repeated the tasks outside the training (repetition scale: M = 1.65, SD = 1.14).

Metacognitive reflections: The mean rating of the metacognitive questions was 3.09 (SD = 0.77). Eight users (40%) rated the questions as not useful, 12 (60%) as useful (usefulness scale: M = 2.45, SD = 1.00). One user (5%) described the questions as demanding, 19 (95%), as manageable (demand scale: M = 3.45, SD = 0.76), three (15%) as stressful compared to 16 users (80%) who rated them as not stressful (stressfulness scale: M = 3.42, SD = 0.90).

In respect to metacognitive reflections, the participants reported higher perceived difficulty in the games before learning the strategies and a benefit of the strategy use after learning and practicing the mnemonic strategies (Table 5).

Table 5

Metacognitive reflections before and after learning and practicing of mnemonic strategies (“tricks”)
	Mean (SD)	Median	Range
Similarity trick Perception of difficulty (before teaching of strategy)	41.05 (18.40)	43.00	0–76
Benefit of strategy (after strategy use)	57.57 (32.79)	55.00	0-100
TV-trick Perception of difficulty (before teaching of strategy)	47.65 (51.18)	0.00	0-100
Benefit of strategy (after strategy use)	62.38 (27.15)	67.00	0-100
Story trick
Perception of difficulty (before teaching of strategy)	55.00 (51.04)	100.00	0-100
Benefit of strategy (after strategy use)	64.70 (28.46)	67.00	0-100
Symbol trick
Perception of difficulty (before teaching of strategy)	47.68 (25.23)	49.00	0-100
Benefit of strategy (after strategy use)	-	-	-
Echo trick
Perception of performance (before teaching of strategy)	21.68 (23.40)	22.00	0–77
Benefit of strategy (after strategy use)	47.21 (28.82)	52.00	0-100
Notes. Data presented as mean (standard deviation), median and range. Lower scores represent higher perceived game difficulty and less benefit of the strategy use, whereas higher scores represent lower perceived game difficulty and a higher subjective benefit of the strategy use.

The present study examined the feasibility of the Mio-Training, a digital cognitive training program for children and adolescents aged 8–16 years. Overall, the findings demonstrate that the Mio-Training is a feasible and enjoyable cognitive training for youth. It is characterized by high compliance (95%) and positive user experience ratings across enjoyment, usability, level of autonomy and perceived impact. This study presents within-training cognitive improvement, particularly for mnemonic strategy use. Socioeconomic status was positively associated with several feasibility dimensions, including perceived design, flexibility, and self-efficacy. Compliance was positively associated with several subscales of the enjoyment of the Mio-Training, the perceived flexibility and self-efficacy, while neither age, sex, nor intelligence influenced the feasibility ratings.

The high completion and compliance rates indicate strong user engagement and acceptability, comparable to or exceeding those reported in other pediatric cognitive training interventions (44–47). Most participants reported that the training was enjoyable, understandable, and easy to use, supporting the intervention’s accessibility and appropriateness for the targeted age group (8 to 16 years old).

Interestingly, socioeconomic status was positively associated with design perception, flexibility, and self-efficacy. This may reflect differences in the access to technological resources, familiarity with digital platforms, or variations in parental involvement and support. All these factors may affect children’s learning experiences (48, 49). Only two significant subscales of the feasibility ratings differed between male and female. No significant associations between feasibility and user experience with age and intelligence were found. This supports the accessibility of the Mio-Training in the typically developing children age group.

Further, compliance was positively associated with the enjoyment, the perceived difficulty, the motivation, the design, the perceived duration of the training, the perceived flexibility and self-efficacy. As compliance plays an important role in determining the efficacy of the training (50) it is of importance to evaluate factors supporting the compliance with the training. A recent study examined whether personal factors such as age, sex, cognitive ability, grit, ambition, personality, and socioeconomic status predict adults’ compliance with a cognitive training program. They concluded that none of these factors reliably predict compliance suggesting that shared factors across individuals may be more influential (51). Contradictory, our results show that personal factors such as motivation and self-efficacy are associated with compliance. Additionally, gamification can help to increase compliance but the effect on the cognitive outcome is still unclear (52). Our results support the benefits of incorporating diverse gamification elements to enhance compliance, including adjustable difficulty levels to mitigate underchallenge and overchallenge, as well as engaging design and enjoyment to boost motivation. Furthermore, we found that the perceived duration of the training was significantly associated with compliance. Individual intervention sessions should be kept brief to maintain engagement. Allowing children to choose when to engage in training is associated with greater compliance and can enhance their sense of autonomy.

Despite overall positive evaluations, several participants indicated that the perceived duration of the sessions was somewhat long and that integrating the training into daily routines was sometimes challenging. These findings align with prior reports emphasizing the importance of brief, adaptable training formats to sustain engagement in young users (53). Suggestions for improvement, such as increasing task variety, enhancing visual design, and integrating more interactive or social features, highlight the value of an iterative user-centered design to further optimize the training experience.

In our feasibility study significant within-training performance gains were observed across most mnemonic strategy games after introducing strategies, particularly the “similarity” and “story” tricks. These results confirm that children can learn and apply mnemonic techniques in a gamified context, improving short- and long-term recall, consistent with prior evidence that explicit instruction enhances encoding and retrieval (54). Similarly, recent findings on digital metacognitive training support the feasibility and benefits of strategy learning via digital tools (55). The sustained effects for the “similarity” and “story” tricks suggest that the Mio-Training successfully supports strategy acquisition rather than just implementing a transient performance boost. Despite overall positive outcomes, individual variability was notable. Data loss in the “symbol trick” game due to technical issues highlights the need for technical improvements. Self-ratings indicated that most children found the strategies useful.

The absence of significant changes in working memory performance after the working memory games may indicate that longer or more adaptive and individualized training protocols are required to elicit measurable gains in working memory such as suggested in previous studies (56–58). Furthermore, the mean intelligence of the study participants was within the high average range, suggesting that cognitive gains may have been constrained by ceiling effects, as participants were already performing at a relatively high level prior to the intervention. The observed performance variability among participants - where about half demonstrated improvement - further supports the notion that individual differences in motivation, baseline capacity, and engagement may moderate training efficacy.

Although no performance data were available for the coordinative challenges, subjective feedback revealed high enjoyment, motivation, and positive task design ratings. The coordination challenges implemented in the Mio-Training align with the growing literature linking cognitive–motor interventions to improvements in executive functioning and attentional control in children (28, 29, 59). However, the variability in completion rates and reports of unsatisfying task demand suggest that the coordinative elements may benefit from enhanced difficulty levels or gamified reward mechanisms.

The metacognitive reflections were perceived as moderately useful, though some participants found the questions repetitive. Metacognitive training is a key mechanism for promoting self-regulated learning (60). Hence, we are still convinced that focusing on metacognitive reflections maintains training engagement. However, incorporating more interactive, adaptive, or feedback-based metacognitive elements could enhance user experience and perceived relevance. Explaining more clearly why metacognition might be helpful before the training starts may increase the engagement of the users.

A strength of this study is its comprehensive feasibility assessment combining quantitative metrics (compliance, performance) with qualitative user feedback allowing for a holistic evaluation of the Mio-Training. The user data provide valuable opportunities to analyse training outcomes, get insights into performance progression, user compliance, and technical errors and through this optimize the application.

However, several limitations should be noted. The sample size was relatively small, limiting statistical power and precluding subgroup analyses. The training was evaluated in healthy controls and feasibility is likely different in children and adolescents with cognitive difficulties such as children with cancer or ADHD. Technical errors led to partial data loss in one mnemonic game, emphasizing the importance of technical stability for digital interventions. Further, the feasibility questionnaire was developed for the current study, therefore no established psychometric properties (e.g., reliability, validity) are available. Future analysis should include standardized pre–post cognitive assessments including academic performance to evaluate transfer effects in a randomized controlled study.

In summary, the findings suggest that the Mio-Training represents a feasible and engaging digital training program for delivering mnemonic strategies, metacognitive reflections, working memory training and coordination challenges to children and adolescents with the aim to strengthen cognitive performance in the long-term and to facilitate the transfer of learned skills to everyday and school life. By integrating features such as adaptivity, immediate feedback, and reward systems, the training was designed as an App to promote autonomous use in a home environment, eliminating the need for external supervision or professional support. With further optimization and validation in larger trials, the Mio-Training presents a user-friendly tool for promoting cognitive development and self-regulated learning in children and adolescents.

ADHD = Attention Deficit Hyperactivity Disorder

BMI = Body mass index

IQ = Intelligence quotient

WISC-V = Wechsler Intelligence Scale for Children – Fifth Edition

6.1. Ethics approval and consent to participate

The study with the healthy children and adolescents was approved by the ethics committee of the University of Berne (2023-12-05). The study will be conducted in accordance with the current version of the World Medical Association Declaration of Helsinki (61), and ICH-GCP guidelines as well as the local legally applicable requirements. Written consent was obtained from one parent or legal guardian. Participants aged 14 years or older additionally provided their own written consent.

6.2. Consent for publication

Not applicable

6.3. Availability of data and materials

All anonymized data are available from the corresponding author on reasonable request.

6.4. Competing interests

The authors declare that they have no competing interests.

6.5. Funding

The study is financially supported by the Swiss Cancer Research, the Cancer Foundation of Thun-Berner Oberland, the Zoé4Life Foundation, the Kinderinsel Foundation, the Johanna Dürmüller-Bol Foundation, the R. and V. Draksler Foundation and the Marie-Lou Ringgenberg Foundation.

6.6. Authors’ contributions

The conception and design of the study was developed by SS, VB, ALMN, and RE. The Mio-Training was conceptualized and developed by SS, VB and RE. ALMN provided advisory support. SS performed the assessments and analyzed the data, SS and RE drafted and revised the initial manuscript. RE, VB, ALMN and SG were responsible for funding. All authors contributed to the refinement of the article, were involved in revising, editing and providing feedback on the final draft. RE is Principal Investigator of the study. All authors approved the final manuscript.

6.7. Acknowledgments

The authors thank Pioneo AG for the technical development of the Mio-App. Further, we thank all the children and adolescents who participated in the study, as well as their parents. Further, we thank the psychology students Nora Bähler, Luisa Lampert und Sarina Wyss for helping to collect the data.

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No competing interests reported.

Supplementaryfeasibilitymiostudy.docx

Feasibility of the Mio-Training: A metacognitive training for children and adolescents

Status:

Version 1

Abstract

Figures

1. Background

2. Methods

2.1. Participants

2.2 Study Design

2.3. Outcome Measures

2.4. Development of Mio-Training

2.5. Mio-Training

2.6. Statistical analysis

3. Results

3.1. Demographics

3.2. Feasibility of the Mio-Training

3.3. Within-training performance

4. Discussion

5. Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1