Caring for the Most Vulnerable: A Model for Managing Maladaptive Behavior in Children with Mental Special Needs During the COVID-19 Pandemic

On April 15, 2020, the system announced to media and all health care units. On May 7, a brief telephone survey, to determine the satisfaction level of users and possible feedback, was conducted. The system users were asked to rate the satisfaction level from the system out of 0–10, as 10 being fully satisfied. The users were also asked whether the problems they got support improved or not. The sociodemographic factors were also gathered from system registration records.

Statistical Analysis

The data obtained from the study were analyzed using the Statistical Package for Social Sciences (SPSS) 24.0 package program. Although frequency and percentage were used for categorical data, mean and standard deviation values were used for continuous data. Chi-square test was used in the analysis of categorical data. While making tests on continuous variables, the assumptions were checked. According to the assumptions, although parametric tests were applied to normally distributed variables, nonparametric tests were applied to non-normally distributed variables. “Single sample T test” and “independent sample T test” were applied for parametric conditions. For nonparametric cases, “Wilcoxon sign test” and “Mann–Whitney U test” were used. The tests were examined at a 95% confidence level and significant differences were interpreted as a result of the tests. Values with p < 0.05 were considered to be statistically significant, and p-value was directly written to indicate the level of significance in the findings.

Results

In total, 347 individuals used the system between April 15 and May 7, 2020. Mothers constitute the majority of applicants (88.7%, n = 332). The mean age of children was 9.8 years (±2.13), whereas the mean age of applying caregivers was 38.3 years (±4.53). Boys constitute 55% of children. Most of the users 60.9% (n = 228) were living in city centers, whereas 39.1% were living in villages and towns. Table 1 summarizes the sociodemographic factors of applicants.

Autism was the leading diagnosis of children (37.9%, n = 142) followed by intellectual disability (ID) (28.3%, n = 106) and Down syndrome (22.1%, n = 83). The most frequent reasons for the application were the increase in aggressive behavior (38.5%, n = 144) and overactivity (24.8%, n = 93). In total, 51 caregivers (13.6%) reported an organic comorbidity cerebral palsy (4.8%, n = 18) and genetic syndromes being the leading conditions (4.8%, n = 18).

The overall satisfaction from the system was 8.8/10. In terms of effectiveness, 63.3% (n = 237) of caregivers reported an improvement in the reason of application. Counselors decided on a need for follow-up visits for 36.6% (n = 137) of applications. Referral to a psychiatrist was asked for 40 patients (10.6%). The most common reason for child psychiatrist referrals was problems related to current medication 65% (n = 26) followed by the need for supportive therapy 30% (n = 12). Psychiatrists referred six cases (1.3%) to local psychosocial support teams for a face-to-face evaluation. One of them for inability to manage severe symptoms online, three of them having problems accessing medication due to parents’ problem-solving difficulties, and one for side effects of current medication. An 11-year-old boy evacuated from United Kingdom and quarantined in a dorm for 14 days with parents was the last kid referred to face-to-face support. Data regarding to CMSNs and their families are summarized in Table 2.

In contrast, there was no significant relationship between satisfaction level and sociodemographic characteristics of all examples. Also, there was no significant correlation between the reason for referral, reasons for referrals to child psychiatrists, previous diagnosis, comorbidity, and satisfaction level. Those who received local unit support and the need for follow-up visits were compared with other variables, and no statistically significant difference was found.

Discussion

The evidence suggests that best practice for managing MB in children with special needs is a combination of behavioral interventions with psychiatric support.¹⁸ But it was unclear how to implement this “best practice” in pandemic conditions. In this context, we used a three-stage telehealth-based integrative model. By adopting such an approach, we aimed at using ABA, which is known as the most effective tool in MB management, in the first line, and tries to handle most of the problems in this stage.¹⁹ We tried to operate child psychiatrist consultation and if required medications as the second line, for the cases whose more complicated problems could not be solved in the first stage. We also established local units as a third line for the cases whose needs cannot be covered by telehealth applications. This gradual structure seems to work in practice as hypothesized considering that first-line ABA was sufficient enough for most of the cases, only 10% of cases need to be referred to child psychiatrists, and ∼1% referred to local units. Beyond bringing the advantages of using the human resources effectively and economically, the model provided improvement in complaints of 63.3% cases that is also reasonable concerning the previous telehealth-based ABA applications.²⁰ In contrast, this result indicates that although telehealth-based ABA intervention seems to be effective for MB of children with special needs, it is not enough to cover all of the problems and needs to be a part of a multidisciplinary integrative approach including psychiatric support and face-to-face intervention alternatives. The previous findings showing high effectiveness levels of telehealth-based ABA conducted in ideal conditions may not apply to pandemic conditions.²¹

Another important finding from this study was the high satisfaction levels of caregivers from the system. Several factors might be related to this result. In this study, we preferred an MA rather than a telephone line. This choice provided us some advantages such as having videoconferencing, setting control visits to the same professional, and determining the current localization of individuals. Previous research shows that although nearly all relevant information exchange is possible by audio channels, videoconferencing allows more interpersonal interactions such as gestures and mimics that are so important in enhancing the quality of support.²²

Although we do not have direct data, beyond the quality of service gathered from experienced experts, getting help from a free-of-charge, unique-to-health care workers, 24/7 operating, and easy-to-use system might address a need for being supported and thus increase the satisfaction levels as well. The result showing that nearly one-third of counselors needed control visits for children was inconsistent with the previous telehealth-based ABA research that shows that multiple visits are required for MB management and maybe another factor enhancing the quality of service.²¹

The mean age of children who received support was 9.8 years (±2.13). This finding was consistent with previous research showing the curse of MB. In their study, examining the age-related changes in MBs among children with Down syndrome, Dykens et al. have shown that both internalizing and externalizing MBs were significantly higher in ages 10–13 years. Similarly in another study, children with autism were found to have higher levels of irritability and hyperactivity at age 9 years compared with other ages. Finding from this study supports the previous findings that special attention should be paid to mid-childhood in terms of MB.^23,24

Another important finding was the distribution of primary diagnosis of children who used the system. Autism was the leading diagnosis of children followed by ID and Down syndrome. Children with autism were shown to have more MB than children with IDs. On the contrary, children with Down syndrome were found to have lower MB than the other genetical disorder that causes ID and also to autism. The effect of pandemic-related changes in daily life routines is known to be more distressing for people with Autism Spectrum Disorder. Also, previous findings show that MB may be more prevalent in children with autism than in other groups. It is not also surprising to have children with autism in our study as the leading group.^13,25

CMSNs reported to be at increased risk for both encountering traumatic events and developing traumatic sequelae.²⁶ This may be related to several factors in a wide spectrum ranging from low thresholds for accepting events as trauma to insufficient coping skills.²⁷ In this study, the presentation of cases was in a broad range as expected and the most common reactions were aggressive behavior and sleep disturbances. These results were consistent with findings from many other studies showing that the most common reactions to trauma in CMSNs are aggression, distractibility, sleep disorders, agitation, and hyperactivity increase in stereotypes.²⁸

Conclusions

To our best knowledge, this is the first study presenting a model for managing MBs of CMSNs during the COVID-19 outbreak. In general, therefore, it seems that there is a need for unique systems to handle behavioral problems of CMSNs. The findings of this study suggest that it is possible to quickly establish an integrative multistep multidisciplinary telehealth-based approach to address behavioral problems in children with special needs during the COVID-19 pandemic. It was also shown that a team consisting of child psychiatrists, behavioral counselors, and field teams may cover most of the possible problems. A gradual approach may be useful for human resource and cost-effectiveness. Overall, this study strengthens the idea that the interventions for MBs should cover and primarily target mid-childhood. MAs may be preferred during pandemic instead of telephone lines, considering many advantages provided.

The most important limitation of this study is the relatively small sample size. The authors desire to share the knowledge as soon as possible that resulted in only the first weeks of application. Another limitation seems to be that all data were depending on self-reports of caregivers including diagnosis. We could not use long standardized measures and questionnaires that would be overwhelming for families who are struggling with many other problems.

Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was received for this article.