2. Materials and Methods
Design
To compare the developmental course of children with and without therapy, we employed a randomized waiting-control-group design with pre-, peri-, and post-test measurements. The sample included a therapy group (children attending therapy) and a control group (children waiting for therapy). The participants were first and second graders (n = 121) who were randomly assigned to the therapy or control group (
Figure 1). Handwriting process measures were assessed five times, while self-concept and fine motor skills were only assessed twice at pre- and post-test. Over a 3-year period, we examined three independent cohorts. The assessments for each cohort started in August and ended in the following February; therefore, we studied the effectiveness of the treatments over 16 weeks.
The children of the therapy group attended between 9 and 18 therapy sessions (M = 12.7) carried out by experienced psychomotor therapists, with each session lasting 45 min. The therapists reported their interventions using a structured therapy protocol [
53,
82].
The children of the control group did not attend any therapy sessions, or any other service related to fine motor training, but received the usual handwriting lessons at school.
In February, after the end of the study, the children of the control group were also allowed to start therapy. Regarding the therapy group, the therapists decided on the continuation of the therapy depending on the needs of the particular child.
Participants
All participating children (n = 121) were recruited by psychomotor therapists employed by the city of Zurich. The children had been referred for PMT for the first time due to graphomotor impairments. The sample corresponded to 7.6% of all first and second graders registered in Zurich for a psychomotor assessment because of graphomotor difficulties in the years 2018–2021. To assign the children to the DCD- or the DD-group, the therapists used the German version of the Movement Assessment Battery for Children-Ed. 2 (M-ABC-2) [
83], a translated version of the DCD- Questionnaire 2007 (DCDQ’07) [
84,
85] and anamnestic data. Children assigned to the DCD-group met the criteria of ICD-10 yielding a M-ABC-2-score below the 16th percentile, as well as experienced handwriting problems that were serious enough to interfere with their academic performance and social integration. Moreover, their motor performance was poorer than expected given their chronological age and did not arise from neurological disease or mental retardation. A medical check-up was conducted for the children of the DCD group by the medical health services of the City of Zurich or by the families’ pediatrician to guarantee the fulfilment of the ICD-10 exclusion criteria. Children with M-ABC-2- scores on the 16th percentile and greater who also showed graphomotor problems were assigned to the DD group. ADHD or mild learning problems were not used as exclusion criteria. Through a random allocation procedure, the participating children were assigned to the therapy and control groups. Active consent for the participation in the study was given by all parents of the participating children.
The sample consisted of 48 first graders (39.7%) and 73 second graders (60.3%), among whom 74.4% were boys, 87.6% were righthanders, reflecting the general distribution of children attending PMT, 34.7% met the criteria of DCD, and 65.3% showed signs of DD without meeting the criteria of DCD. The proportion of children with DCD was higher among the first graders (58.3%) compared to the second graders (30.1%; χ2 = 9.50, df = 1, p =.002). The mean age measured at t1 was 7 years and 2 months (SD = 7 months, ranging from 6 years to 8 years 9 months).
During the study, one child broke his arm before t4 and had to be excluded for the fine motor and graphomotor examinations of t4 and t5. One child had to be excluded from the second fine motor test because he had started a medical treatment for ADHD before t5. Six children missed the 2nd fine motor test and the self-concept evaluation due to scheduling problems.
Table 1.
Description of the sample.
Table 1.
Description of the sample.
|
|
|
Therapy Group |
Control group |
|
|
Variable |
n |
% |
n |
% |
n |
% |
χ2
|
p |
|
121 |
100 |
61 |
50.4 |
60 |
49.6 |
|
|
Sex |
|
|
|
|
|
|
.068 |
n.s. |
- Female |
31 |
25.6 |
15 |
24.6 |
16 |
26.7 |
|
|
- Male |
90 |
74.4 |
46 |
75.4 |
44 |
73.3 |
|
|
Handedness |
|
|
|
|
|
|
.743 |
n.s. |
- Righthanders |
106 |
87.6 |
55 |
90.2 |
51 |
85 |
|
|
- Lefthanders |
15 |
12.4 |
6 |
9.8 |
9 |
15 |
|
|
Diagnosis |
|
|
|
|
|
|
.752 |
n.s. |
- DCD |
42 |
34.7 |
22 |
36.1 |
20 |
33.3 |
|
|
- DD |
79 |
65.3 |
39 |
63.9 |
40 |
66.7 |
|
|
Class |
|
|
|
|
|
|
.089 |
n.s. |
- First graders |
48 |
39.7 |
25 |
41 |
23 |
38.3 |
|
|
- Second graders |
73 |
60.3 |
36 |
59 |
37 |
61.7 |
|
|
|
|
|
|
|
|
|
|
|
Material
Handwriting movements were recorded using writing tablets (Wacom Intuos PRO-medium tablet) connected to a notebook. All tasks were written down with the “Wacom Inking Pen” KP130 - an induction pen with ballpoint refill. An extended version of the software CSWin DTW [
86] with CSWin DTW plugin [
87](Marquardt et al 2021), with a recording frequency of 200 Hz and an accuracy of 0.1 mm in the x- and y-axes, was used for recording and analysis. For the calculation and smoothing of the velocity and acceleration signals, non-parametric regression methods (kernel estimation) were included in the mathematical calculation procedures of CSWin [
88].
Procedure
There were 24 trained psychomotor therapists involved, working in the city of Zurich. They treated between one and four children per cohort, whereby some therapists were involved in all three cohorts and others only in one or two cohorts. The therapists did not receive information about the results in between the study cohorts, only at the end. After study completion, an information event was used to collect the therapists’ comments and interpretations on the revealed results.
The tablet recordings were conducted approximately every 4 weeks by trained university staff. Each child was examined individually in a separate room of the school building or in the therapy room. The child sat beside the test administrator. In front of the child was the Wacom tablet with the special pen and a sheet of paper attached to the surface of the tablet. The sequence of the 20-min examination was predetermined by the pre-programmed task sequence of the software. The original items of CSWin have been extended within several studies [
15,
53,
89] to include tasks that are typical for the stages of handwriting development. All participants performed 15 digital handwriting items in the same order, including basic graphomotor movements.
Table 2.
Items of handwriting measurement.
Table 2.
Items of handwriting measurement.
Item No. |
Task |
Item No. |
Task |
1 |
Scribbling (for trying out, not evaluated) |
8 |
Repetitive letter sequences (writing at least 8 times the letter “a,” no speed specification) |
2 |
Finger movements (no speed specification) |
9 |
Repetitive letter sequences (writing at least 8 times the letter “a,” as fast as possible) |
3 |
Finger movements (fast) |
10 |
Repetitive letter sequences (writing at least 8 times the letter “a,” as precisely as possible) |
4 |
Wrist movements (no speed specification) |
11 |
Patterns (garlands) |
5 |
Wrist movements (fast) |
12 |
Patterns (double loops) |
6 |
Combined finger and wrist movements when circling (no speed specification) |
13 |
Copying the word “neu” (new) three times |
7 |
Combined finger and wrist movements when circling (fast) |
14 |
Copying a sentence “Die Kinder fliegen nach Amerika» («The children fly to America», no speed specification) |
|
|
15 |
Copying a sentence “Die Kinder fliegen nach Amerika» («The children fly to America», fast) |
For reasons of efficiency, we have limited the statistical analyses to the faster, and usually better, second attempt of basic movements and omitted the first trial and the two difficult patterns (e.g., garlands and double loops cf. the evaluated tasks in the white fields).
The basic movements were directly demonstrated by the experimenter and the children were allowed to try them out on a laminated card; afterwards, the task was performed twice (the second one as fast as possible) to ensure the best possible performance based on the combined visual and tactile-kinaesthetic information.
With respect to writing repetitive letters sequences, many children were not capable of reproducing valid recognisable letters within the set time. Consequently, we offered (starting with measurement point 3) that the letter trace was first retraced with the finger on a laminated card with an enlarged a-shape to ensure that the correct sequence could be reproduced successfully without interruption.
The remaining tasks were presented visually using instruction cards, with ComicSansSerif used as the font for the text. The children were asked to use the writing type that they had learnt at school. Unstructured white paper was used for all items given that, according to Quenzel and Mai [
20], visual guidelines have a negative influence on writing speed. Only in the case of the tasks with repetitive letter sequences, was a discrete visual structure in the form of light grey bars provided for measurement purposes. Observations on validity, pen postures, and other difficulties were noted and used to clean the dataset. If a task was solved incorrectly (e.g., if it was aborted too early), a maximum of one repetition was allowed.
Measures
Process-based handwriting measures
Velocity: Stroke frequency (FREQ) refers to the number of upward and downward strokes per second. To calculate these strokes, the written trace is divided in subsequent up and down segments by CSWin [
92]. This measure seems more appropriate than assessing the absolute writing speed (mm/s) as the speed will directly depend on a person’s individual writing size. Children with handwriting difficulties have been found to perform slowly but steadily improve throughout PMT [
52]. Additionally, the data provide an insight into the level of motor control already achieved; thus, while visually controlled movements show up in a stroke frequency of approximately 2 hz or lower, values greater than this indicate that handwriting is performed by sufficiently automated movements [
17,
93]
Automaticity: We measured automaticity by the number of inversions in velocity (NIV). The NIV indicates the average number of velocity changes occurring within writing strokes. In the optimal case, the velocity profile is unimodal (acceleration followed by deceleration), resulting in a value of NIV = 1. A fluent adult handwriter requires nearly one velocity change per stroke (acceleration followed by deceleration) resulting in an NIV score that is close to 1 [
88]. Children with handwriting difficulties demonstrate a much higher NIV, indicating a substantial lack of automaticity [
52].
Dynamic time warping (DTW): The digital time normalization DTW is a method used for the pattern comparison of different sequences of values to calculate relative difference measures. The DTW analysis for writing [
94,
95] compares the spatial and temporal similarity of repeatedly written traces. Di Brina et al. [
47] used the DTW method to compare the shape of written letters to analyse the spatial properties of the handwriting of children with writing problems. The calculated DTW distance is the average point-to-point distance between the respective written letters and the individually calculated prototype of this letter with a normated size of 1. To better understand the distribution of the deviation, the percentages of coherent letters (named as percentage coherence, d < 0.05) and deviant letters (named as percentage deviation, d > 0.1) are calculated [
86,
87].
Handwriting self-concept
To assess the handwriting self-concept, an extended version of an instrument we had developed and used previously [
53,
96]. The children were interviewed by the therapists regarding their self-concept over eight aspects. They were asked whether they considered their handwriting to be nice, fluent, loose, and legible; if they use correct letter sequences; if they feel secure when writing; and if they write with joy and are satisfied with the product. The children were asked to use a token that they positioned on a six-step staircase made of building blocks, where the higher the step the more positive their estimation. The therapists noted the answers on the related 6-point scale. Within this study we used the scale twice, once at the pre-test and once at the post-test.
Therapy aims and therapy protocols
The 61 children attending PMT weekly from August to January were treated according to individual goals set at the beginning. All therapeutic interventions were recorded in terms of content and time by means of a therapy protocol [
82]; this yielded between 10 and 18 protocols per child, indicating the interventions chosen per session and the time spent on them. Within each focus area, the therapist indicated the selected sub-areas. The protocol dataset includes 671 protocols referring to comprehensive information on treatment contents and procedures [
82].
Data analysis
All statistical analyses were performed using the Statistical Package for the Social Sciences version 28. For the standardized tests (BOT-2), transformed T-values were used in the analysis.
To examine the intervention effects on fine motor control, a two-way analysis of variance (ANOVA) using time as a repeated factor, group and diagnosis as between factors, and grade as a covariate was employed.
Because of the young age of our sample and the resulting difficulties of many children with certain handwriting tasks, the respective data contain a significant number of missing data (indicating that a child was unable to perform the task at this trial). In addition, many of the handwriting process variables were skewed and not normally distributed (particularly the NIV) and therefore did not meet the requirements of the traditional ANOVA approach. Consequently, we calculated generalized estimating equations (GEE), which are designed to handle missing data and are also suitable for non-normal distributed variables given that the missing data were distributed completely at random (MCAR) [
97,
98]. When the MCAR requirement was not fulfilled (in addition to the non-normal distribution), we decided to perform separate non-parametric tests (Wilcoxon) for the therapy and waiting groups, comparing t1 vs. t5 only. The rational of the Wilcoxon analyses was to detect a significant change over time (t1 vs. t5) in one group but not in the other, indicating that there was a group difference.
Similarly to the process variables described above, the handwriting self-concept variables were not normally distributed, and the MCAR-criterion was not met. Therefore, we employed Wilcoxon tests as described previously.
3. Results
3.1. Fine motor skills
The 2 (group) x 2 (diagnosis) x 2 (time) repeated measures ANOVA revealed two significant main effects and one significant two-way interaction (
Table 3). Firstly, children with DCD performed poorer in fine manual control than children with DD. Secondly, the therapy group performed better than the waiting group taking both time points into account. Thirdly, children attending therapy improved in fine manual control over time, while this was not the case among the children of the waiting group who stagnated at the initial level (time*group interaction: F = 28.74, df = 1/108, p =.000, Eta2=.210). All other main or interaction terms turned out to be non-significant (including the three-way interaction).
Table 3.
Fine-manual control (T-values) from t1 to t5 by group and diagnosis.
Table 3.
Fine-manual control (T-values) from t1 to t5 by group and diagnosis.
|
Therapy group |
Control group |
|
|
|
DD |
DCD |
DD |
DCD |
Time |
Group |
Diagnosis |
Time* Group |
Time * Diagnosis |
Measures |
M (SD) |
M (SD) |
M (SD) |
M (SD) |
F df Eta2 p |
F df Eta2 p |
F df Eta2 p |
F df Eta2 p |
F df Eta2 p |
t1 |
39.40 (1.43) |
31.65 (1.89) |
37.41 (1.41) |
33.79 (1.96) |
2.699 1/108 .024 n.s. |
7.190 1/108 .062 .008 |
7.563 1/108 .065 .007 |
28.74 1/108 .210 .000 |
3.082 1/108 .028 .082 |
t5 |
45.81 (1.49) |
40.38 (1.96) |
34.98 (1.46) |
34.64 (2.04) |
Figure 2.
(a) Fine manual control (Brunininks-Oseretsky Test of Motor Proficiency BOT-2, T-values) among children with Developmental Dysgraphia (DD); (b) Fine manual control (Brunininks-Oseretsky Test of Motor Proficiency BOT-2, T-values) among children with Developmental Coordination Disorder (DCD).
Figure 2.
(a) Fine manual control (Brunininks-Oseretsky Test of Motor Proficiency BOT-2, T-values) among children with Developmental Dysgraphia (DD); (b) Fine manual control (Brunininks-Oseretsky Test of Motor Proficiency BOT-2, T-values) among children with Developmental Coordination Disorder (DCD).
3.2. Process-based handwriting results
In the following sections, we analyse how the process-based handwriting measures develop from t1 to t5 in both groups by means of the GEE procedure if the MCAR condition is fulfilled. If this requirement is not met, we analyse by means of nonparametric Wilcoxon tests only taking t1 and t5 into account. The means and standard deviations for all measures from t1 to t5 are reported in
Table A1 and
Table A2 in the Appendix, as well as missing data due to invalid attempts, which were more prevalent among the basic movements and over the first trials (t1 and t2).
GEE analyses: The GEE analyses revealed several handwriting fluency (FREQ) improvements over time for both groups; this was the case regarding fast finger movements (Wald-Chi2 = 10.5, df = 4, p <.05), repetitive letter sequences (without speed specification) (Wald-Chi2 = 30.8, df = 4, p <.001), copying a word (Wald-Chi2 = 101.6, df = 4, p <.001), and copying a sentence (without speed specification) (Wald-Chi2 = 116.1, df = 4, p <.001). The same analyses did not reveal any group effects and, with one exception, any group*time interactions. The exception was an unexpected group*time interaction with respect to repetitive letter sequences (without speed specification), indicating more improvement among the waiting group compared to the therapy group (Wald-Chi2 = 10.7, df = 4, p <.05).
Non-parametric analyses (Wilcoxon): Regarding handwriting fluency (FREQ), we found a time effect for both groups for repetitive letter sequences (as fast as possible) (therapy-group: z = –4.41, p <.001; waiting group: –4.23, p <.001). Only the waiting group but not the therapy group improved from t1 to t5 in wrist movements (fast) (z = –2.532, p =.011), combined finger and wrist movements when circling (z = –2.621, p =.009), and repetitive letter sequences (precisely) (z = 4.493, p <.001).
In contrast, the therapy group improved in automaticity (NIV) in combined finger and wrist movements (fast) (z = –2.634, p =.008).
Also with respect to automaticity, both groups improved from time 1 to time 5 in repetitive letter sequences (without speed specification) (therapy-group: z = –2.026, p =.043; waiting group: z = –4.163, p <.001), repetitive letter sequences (as fast as possible) (therapy-group: z = –4.597, p <.001; waiting group: z = –3.959, p <.001), repetitive letter sequences (as precisely as possible) (therapy-group: z =–2.121, p =.034; waiting group: z = –4.289, p <.001), in copying a word (therapy-group: z = –4.030, p <.001; waiting group: z = –5.103, p <.001), in copying a sentence without speed specification (therapy-group: z = –5.278, p <.001; waiting group: z = –5.530, p <.001), and under fast condition (therapy-group: z = –3.818, p <.001; waiting group: z = 4.803, p <.001).
Regarding the measures of DTW, for the criteria of distance, consistency, and deviance, we did not find any change over time for both groups, among all three conditions (repetitive letter sequences without speed specification, as fast as possible, and as precisely as possible), with one exception: Children of the waiting group wrote more coherent letters at t5 compared to t1 when writing repetitive letter sequences as fast as possible (z=-2.359, p= .018), whereas the children of the therapy group did not improve in this respect.
Despite several improvements over time (as reported above), a narrower inspection of the performance at t5 made it clear that, depending on the task, the children did not achieve the target of sufficient frequency (i.e., a frequency of 2 hz or greater). More than 75% of all children managed the basic movements in an automated manner, while in the remaining tasks 70–100% of the children were not able to do so (Figure 4).
Figure 3.
Performance regarding frequency over all items at t5 (freq.3 = Finger movements (fast); freq.5 = Wrist movements (fast); freq.7= Combined finger and wrist movements (fast); freq.8 = Repetitive letter sequences (no speed specification); freq.9 = Repetitive letter sequences (as fast as possible); freq.10 = Repetitive letter sequences (as precisely as possible); freq.13 = Copying the word “neu”; freq.14 = Copying a sentence (no speed specification); freq.15 = Copying a sentence (fast). Notes: The bar at 2 hz marks the threshold at which controlled movement changes to automated execution [
17].
Figure 3.
Performance regarding frequency over all items at t5 (freq.3 = Finger movements (fast); freq.5 = Wrist movements (fast); freq.7= Combined finger and wrist movements (fast); freq.8 = Repetitive letter sequences (no speed specification); freq.9 = Repetitive letter sequences (as fast as possible); freq.10 = Repetitive letter sequences (as precisely as possible); freq.13 = Copying the word “neu”; freq.14 = Copying a sentence (no speed specification); freq.15 = Copying a sentence (fast). Notes: The bar at 2 hz marks the threshold at which controlled movement changes to automated execution [
17].
3.3. Handwriting-self-concept
Because some of the children did not answer all questions, the number of participants of each item differs slightly (range: 108–114 children).
Compared to the baseline assessment (t1), the children of the therapy group rated their handwriting as more beautiful (z = –2.70, p =.007), more legible (z = –2.24, p =.025), more skilful in terms of letter sequences (z = –2.26, p =.024), and were more satisfied with their handwriting (z = –2.41, p =.016) at t5. In contrast, the respective ratings did not change over time among the waiting group children. Regarding the remaining self-concept variables, the ratings of both groups did not change over time.
4. Discussion
We found a significant treatment effect with respect to fine-motor control. PMT significantly improved fine motor skills in children with DCD and DD over a 5-month period compared to those in the waiting group regardless of diagnosis.
In contrast, we found no evidence, that the treated children improved more than the waiting children (regardless of diagnosis DD or DCD) with respect to their graphomotor skills, such as fluency (frequency), automaticity, and consistency of forming letters over the 16-week period, but we did find several time effects for both groups.
In relation to the self-concept of handwriting, the treated children rated some aspects better at t5 compared to t1, while the ratings of the children of the waiting group remained stable over time.
The results regarding fine motor control are in line with the fact that PMT often starts to work on fine motor development as a precursor skill to writing by hand, e.g., the strengthening and mobility of the fingers is built up in this way [
74]. The reasons for the increase in fine motor skills still need to be substantiated by the differentiated analysis of the protocol data, but they seem comprehensible. As the initial results of our therapy protocol analyses reveal [
82], the focus was indeed on directly handwriting-related precursor motor skills such as pen posture and finger movement control (25% of the total therapy time). Additionally, children usually respond very well to the game-centred approach of PMT to promote fine motor skills. The approach superficially allows for attractive choices and seems less school-related and less performance-oriented than training graphomotor skills; therefore, it can be worked with a high level of intrinsic motivation, as recommended by the medical guidelines [
64].
When it comes to the treatment of graphomotor difficulties, task-oriented therapy approaches are assumed to be more successful than process-oriented ones [
58]. The initial results of our therapy protocol analysis [
82] demonstrated that the pencil-and-paper-based promotion of visuomotor skills (11%) and direct handwriting training (15.5%) took up a quarter of all training units. Therefore, our zero finding regarding handwriting skills is unexpected, especially given the fact that even short-term task-based interventions improve handwriting fluency among struggling and typically developing young handwriters [
99]. These findings may have several explanations.
First, the duration of some therapies did not reach the intended duration in the 16 weekly sessions, as there were failures due to illness, holidays, and school projects. With at least 10 sessions among the shortest interventions, this was just below the recommended threshold of guidelines. According to the meta study of Smits-Engelsmann et al. [
58], most of the investigated interventions that were successful lasted longer than 10 weeks.
Second, during the intervention time, the pencil was used daily in class and explicit handwriting was taught and practiced several times a week. Therefore, the teaching effects probably supressed the therapy effects.
Third, learning processes in handwriting are known as non-linear; for example, children with ADHD initially show deterioration in their handwriting fluency when they obtain the perfect mix of medication and therapeutical treatment, at which time they are finally able to focus and learn, and therefore tend to write slower and in a less automated manner [
100]. This could be the case here as well. When children learn to focus during the first therapy weeks, they will be ready to learn, even in terms of handwriting, but the increase will not be immediately visible. Fortunately, most of PMTs last longer, so some starting difficulties or even regressions can be absorbed. Due to ethical constraints, it was not possible to extend the duration of the study time for each cohort, even though the usual therapies last longer.
Furthermore, it is possible that these children were too young for a purely task-oriented approach to promoting graphomotor skills. Fine and gross motor movement opportunities, such as those available in the therapy room, are more in line with the fundamental need for play at this age. It is known that children who lacked play opportunities for a variety of reasons show a pronounced need to catch up [
101] (p.254), [
102]. However, targeted work on handwriting corresponds less to the child's intrinsic motivation but is usually a concern of parents and teachers. The therapists cannot resolve this conflict of goals, at most they can steer it in a constructive direction by making agreements with the children, and they rely on the fact that playing creates an essential foundation for further development.
Regarding our data so far, we can conclude that all the children were making progress in terms of handwriting, but their performance at t5 was still far below the target range. As normally developed second graders can write common short words in a fast and almost automatized manner [
103], the children in our sample showed a lower speed (below 2 hz), indicating controlled fine motor steering even at t5 over all items that were more complex than basic movements. According to the cognitive load theory [
104] this lack of automaticity is unfavorable because children need to master basic handwriting and spelling skills in a fluent way to obtain more free resources in their working memory for the higher demands of writing.
The newly created DTW tasks unfortunately turned out to be too difficult for many children. Compared to the performance of a pilot study, many children of this sample of struggling handwriters were unable to write a sufficient number of valid letters in the given time or to reproduce non-recognizable or wrong letter forms. Additionally, due to the teaching material used in many classes, the children had surprisingly no experience with lowercase letters, not even with a common “a.” Therefore, our zero finding should be considered with caution. More research using a simpler task is necessary to come to a more comprehensive conclusion.
A comparison with the performance of normally developing second graders [
103] can reveal areas in which children with DCD or DD still require therapy and whether this can lead to values in the target range in the longer term. Further research is necessary to analyse the outcome of the therapy, which will be possible due to the therapy protocols that are planned to be examined in detail next.
The finding that the children in therapy improved their self-concept more than the waiting group children is not surprising and in line with our respective hypothesis as PMT has an explicit focus on individual progresses that are discussed at several instances with the child [
105,
106]. Regarding the Reciprocal Effect Model [
107], in which self-concept and performance influence each other, this improvement is important for the further course of therapy.
Finally, we emphasize that even regarding these limitations, the increase in a positive self-concept is a crucial first step to gain more joy in writing and motivation for a therapy that may simply take more time..
5. Conclusions
The present study successfully demonstrates that PMT improves fine-motor skills, which are assumably prerequisites of handwriting, among young children, as well as improves some aspects of the handwriting self-concept, which is expected to support further learning and training. Thus, despite the short-term limitations of this study, our results provide scientific evidence for the current PMT services in Switzerland.
As handwriting acquisition implies complex learning processes, PMT can be considered a long-term endeavor. Our study children who attended PMT for half a year remain below the level of automatized handwriting movements and clearly need additional therapeutic support. However, given the limited results with respect to handwriting fluency and consistency, more research, taking longer time periods into account to observe respective improvements, is necessary.
Limitations
Due to challenges associated with the pandemic, the data collection time was extended from two to three cohorts to meet the required sample size. Although there was no complete data loss, the precise rhythm of monthly examinations was difficult to fulfil e.g., due to illness of children, therapist, or teachers.
Author Contributions
Conceptualization, W.W. and S.H.; methodology, W.W. and S.H.; software, C.M. and C.B.; validation, S.H., M.N. and C.B.; formal analysis, W.W.; investigation, S.H., M.N. and S.W.; data curation, S.H.; writing—original draft preparation, S.H., W.W. and M.N.; writing—review and editing.; S.H., W.W., A.B., C.M., C.B., S.W. and M.N.; visualization, S.H. and M.N.; supervision, W.W.; project administration, M.N. and S.W.; funding acquisition, W.W., S.H. and A.B.