Positive Parenting Program for Attention Deficit Hyperactivity Disorder: Maternal Perspective Shifts and Child Behavior Problems Reduction in a Clinical Trial

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Methods: A randomized controlled trial was conducted with 64 Palestinian mothers of children aged 5–13 diagnosed with ADHD. Participants were randomly assigned to either the intervention group (Triple P) or a control group receiving standard care. Pre- and post-intervention assessments were conducted using the Parenting Sense of Competence (PSOC) scale, the Parenting Scale (PS), and the Strengths and Difficulties Questionnaire (SDQ). Feasibility was assessed through retention rates, session adherence, cultural congruence, and participant satisfaction. Results: Feasibility findings indicated high session attendance, strong participant engagement, and positive reception of the program, including its online adaptation. Post-intervention, the intervention group reported significantly higher parenting competence (PSOC) compared to the control group ( p = .023, d = 0.59). There was also a significant reduction in lax parenting practices ( p = .04, d = −0.51) and an increase in children’s prosocial behavior ( p = .014, d = 0.64). Hyperactivity symptoms showed marginal improvement ( p = .053, d = 0.48). Conclusion: The culturally adapted Triple P intervention was both feasible and effective in enhancing parenting skills and improving child behavior among Palestinian families affected by ADHD. Findings support the integration of Triple P into national mental health services and highlight the importance of culturally responsive, evidence-based interventions in low-resource and conflict-affected settings. ADHD Triple P parenting intervention randomized controlled trial Palestine parenting self-efficacy child behavior feasibility Figures Figure 1 Key Practitioner Message What is known? ADHD Children experience significant behavioral difficulties,international Parenting interventions such as the Triple P (Positive Parenting Program), are effective in enhancing parenting self-agency and reducing child behavioral problems. However, its implementation, feasibility and effectiveness is undocumented in low-resource, conflict contexts like Palestine. What is new? The randomized controlled trial demonstrated the feasibility of the culturally adapted Triple P intervention for Palestinian mothers of ADHD children with a significant improvement in mothers' sense of competence and attitude, with a reduction in child problematic behaviors, and enhanced children’s prosocial behavior. What is significant for clinical practice? Health care Practitioners working with ADHD children in low-resource and conflict regions should consider integrating culturally adapted Triple P for parents as part of the management plan to enhance parenting skills and improve child outcomes and family well-being. Background Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder that affects approximately 5% of children globally (1), with symptoms often persisting into adolescence and adulthood, impairing academic, social, and occupational functioning (2). In the Middle East and North Africa (MENA) region, the prevalence is notably higher, reaching 10.3% according to a recent meta-analysis(3). ADHD diagnosis typically involves clinician assessments supported by parent and teacher reports, alongside standardized rating scales(4). According to a systematic review and meta-analysis study in Saudi Arabia, the frequency of ADHD ranged from 3.3–16.1%. Based on the meta-analysis, the estimated pooled prevalence was 9.95%(5). Effective management of ADHD increasingly emphasizes behavioral interventions. The American Academy of Pediatrics (AAP) recommends parent training in behavior management (PTBM) as a first-line treatment (6). Behavioral Parent Training (BPT) equips parents with strategies such as positive reinforcement, structured discipline, and problem-solving, promoting improved child behavior and parental competence. These approaches draw on social learning theory, self-regulation theory, and applied behavior analysis (7). Among BPT programs, the Triple P – Positive Parenting Program is one of the most widely implemented, offering multi-level interventions tailored to community and individual needs (8). Developed at the University of Queensland, Triple P aims to enhance parenting knowledge, confidence, and self-regulation while fostering child well-being through supportive environments, assertive discipline, and realistic expectations (9,10). Evidence from diverse contexts—including Singapore, Sweden, and Pakistan—demonstrates its effectiveness in reducing child behavior problems, parenting stress, and parental mental health symptoms while strengthening parent-child relationships and promoting long-term positive outcomes(11–18) Despite this global evidence, little is known about the applicability and impact of Triple P in Palestine, a region marked by high ADHD prevalence and unique sociocultural challenges. In a recent study, it was found that the frequency of ADHD signs among Palestinian school-age children was (8.7%)(19). There were no significant differences in prevalence among Arabs and Jews of 18.7%and 17.8% respectively(20).ADHD can profoundly impact family dynamics, with research indicating that mothers of children with ADHD often experience heightened feelings of anger, anxiety, and depression, feeling less effective and successful compared to mothers of children without ADHD (21). Moreover Mothers of children with ADHD are facing high burden of care and specifically in the region of Hebron(22,23).Adding to this burden the complex regional political and socioeconomical difficulties facing these families. Parenting programs that are effective in Western or high-resource contexts may not directly translate to Palestinian families facing chronic stress, limited mental health resources, and cultural barriers to help-seeking. Moreover, few studies have explored the maternal perspective specifically, despite mothers often being primary caregivers for children with ADHD. This study addresses this critical gap by evaluating the impact of the Triple P program among Palestinian mothers of children with ADHD. Specifically, it examines the program’s feasibility and cultural acceptability, its effects on maternal attitudes and parenting competence, and its efficacy in reducing ADHD-related behavioral symptoms in children. Ultimately, the study aims to inform the development of culturally sensitive, evidence-based interventions for ADHD in the Palestinian context. Methods Study Design and Setting This study employed a randomized controlled trial (RCT) design with pre-test and post-test assessments to evaluate the effectiveness of the Triple P – Positive Parenting Program among Palestinian mothers of children diagnosed with ADHD. The trial was conducted at Hebron Mental Health Center for Children, a governmental facility located north of Hebron. The center offers comprehensive services, including psychological support, speech therapy, behavioral interventions, and pharmacological treatment for children with mental and behavioral disorders. Participants and Recruitment Potential participants were identified from ADHD care centers across Palestine. Eligibility criteria included: (1) being the biological mother of a child aged 6–13 years formally diagnosed with ADHD and currently attending a child mental health clinic; and (2) not receiving parental support services from other professional agencies. Exclusion criteria encompassed children with neurological or medical disorders, intellectual disabilities, psychosis, bipolar disorder, or severe aggressive behaviors. Following ethical approval from the (Arab American University of Palestine) Institutional Review Board and authorization from the Palestinian Ministry of Health, eligible participants were contacted and invited to participate. Informed consent was obtained, and eligibility was confirmed through structured interviews and review of clinical records. Participants were assured of anonymity, voluntary participation, and the right to withdraw at any stage. All data were stored securely in password-protected digital folders and locked physical cabinets accessible only to the principal investigator. Randomization and Sample Size After confirming eligibility, participants were randomly assigned to the intervention (Triple P) or control group using a computer-generated randomization procedure in Microsoft Excel—the RAND () function generated random numbers. Participants were recruited between June 2023 and August 2024, sorted in ascending order to achieve a 1:1 allocation. Thirty-three participants were assigned to the intervention group and 31 to the control group (see Fig. 1 : CONSORT Flow Diagram). Sample size estimation was based on prior Triple P studies demonstrating moderate to large effect sizes (14,16). Using G*Power with an alpha level of 0.05, power of 0.80, and an anticipated effect size of 0.40, the required sample size was 66 participants (33 per group). Intervention: Triple P – Positive Parenting Program The Group Triple P Level 4 intervention was culturally adapted for the Palestinian context. The lead researcher completed a certified online training course through the Triple P Association (UK) and received accreditation to deliver the Level 4 program tailored for children with special needs. Core content was sourced from the official Triple P provider materials and Every Parent manual, which was translated into Arabic. Supplementary Arabic-language videos from the Triple P platform were used to enhance participant comprehension and engagement. The intervention was administered with fidelity, and according to the original manual checklist, began with an introductory session that introduced the program, obtained written informed consent, built rapport, and collected baseline demographic data and pre-intervention measures. The program was delivered across multiple group sessions (each lasting approximately two hours), incorporating instructional content, video modeling, group discussions, and structured activities (see Table 1). Adherence record indicated 85% of mothers attended at least 6 sessions out of 8. Following the group sessions, each mother received two to three individualized follow-up phone calls (30–50 minutes each) to support practical application, troubleshoot challenges, and reinforce learned strategies. Ongoing support was provided via a dedicated WhatsApp group, where participants received daily reinforcement through brief messages and multimedia content. These prompts encouraged reflection, reinforced parenting strategies, and supported the development of parental self-efficacy in managing disruptive behavior. Participants were instructed to unenroll in other parenting interventions until completion of the follow-up assessments Control Condition The control group received standard care, which typically included routine clinical follow-ups and general psychosocial support but no structured parenting intervention. Control group participants completed the same pre- and post-assessments as the intervention group, with a two-month interval between measurements. Participants in both groups continued to receive Concomitant Care. Outcome Assessment The effectiveness of the Triple P – Positive Parenting Program was evaluated using three validated instruments: two assessing maternal outcomes and one measuring child behavioral outcomes, all based on maternal report. 1. Strengths and Difficulties Questionnaire (SDQ) The Arabic version of the Strengths and Difficulties Questionnaire (SDQ) was used to assess children’s emotional and behavioral functioning, as reported by their mothers. Originally developed by(24), the SDQ comprises 25 items spanning five subscales: hyperactivity/inattention, emotional symptoms, peer problems, conduct problems, and prosocial behavior. It is validated for children aged 3 to 16 years. Previous studies have demonstrated adequate psychometric properties, with a Cronbach’s alpha of 0.73 for the subscales and 0.78 for the total difficulties score(25,26). In the current study, internal consistency for the SDQ total score was excellent (Cronbach’s α = 0.88). Test-retest reliability, measured using the intraclass correlation coefficient (ICC) via a two-way mixed-effects model, yielded an ICC of 0.88 (95% CI [0.83, 0.91]). 2. Parenting Scale (PS) The abbreviated 7-item Parenting Scale (PS) was employed to assess dysfunctional parenting practices, particularly discipline styles. It includes two subscales: laxness (three items) and over-reactivity (four items), each rated on a seven-point Likert scale(27,28). This tool has demonstrated good psychometric properties, with prior research reporting Cronbach’s alpha values ranging from 0.60 to 0.79(29). In this study, internal consistency was moderate (Cronbach’s α = 0.62). The ICC was 0.619 (95% CI [0.431, 0.766]), indicating moderate test-retest reliability across pre- and post-intervention measurements. 3. Parenting Sense of Competence Scale (PSOC) The Parenting Sense of Competence Scale (PSOC) was used to evaluate parental self-esteem, comprising 17 items that measure two domains: satisfaction and efficacy. Originally developed by (30) and revised by (31),the scale has shown robust internal reliability, with previous alpha values of 0.75 for Satisfaction, 0.76 for Efficacy, and 0.79 for the total score. The Arabic version was developed using forward and backward translation by bilingual experts. In this study, the PSOC demonstrated good reliability, with an ICC of 0.735 (95% CI [0.630, 0.821]) using a two-way mixed-effects model. Data Analysis All statistical analyses were conducted using IBM SPSS Statistics version 27. Data were first screened for completeness and accuracy. Missing data were assumed to be random of less than 3%, and were excluded using listwise deletion. Descriptive statistics (frequencies, percentages, means, and standard deviations) were used to characterize demographic variables and baseline measures. Reliability for each outcome instrument was assessed using Cronbach’s alpha coefficients and intraclass correlation coefficients (ICC). Normality of continuous variables was evaluated using the Kolmogorov-Smirnov test. To assess baseline equivalence between the intervention and control groups, independent samples t -tests were performed on all pre-intervention variables. The effectiveness of the Triple P intervention was analyzed by comparing pre- and post-intervention scores within and between groups using independent t -tests. Statistical significance was determined at an alpha level of 0.05 (two-tailed). The primary analyses focused on evaluating changes in parenting practices, parental competence, and child behavior. Differences in mean change scores between the two groups were used to assess the impact of the intervention relative to standard care. Sensitivity or subgroup analysis was not conducted. Results Participant Characteristics The final sample included 64 children diagnosed with ADHD and their mothers. The children had a mean age of 8.00 years (SD = 2.13), ranging from 5 to 13 years. The mothers' mean age was 36.75 years (SD = 7.54), with ages ranging from 23 to 53 years. The majority of children were male (68.75%, n = 44). Most participating mothers were married (90.6%, n = 58), while a smaller proportion were separated (6.3%, n = 4) or divorced (3.1%, n = 2). Regarding educational background, 28.1% of mothers (n = 18) held a Bachelor's degree. The majority were unemployed (70.3%, n = 45). In terms of healthcare access, 34.4% of children (n = 22) received ADHD treatment through governmental clinics. Most children (75.0%, n = 48) were enrolled in mainstream schools. (Table 2). Feasibility Results Feasibility was assessed through indicators including participant satisfaction, data completeness, cultural congruence, retention rates, and protocol adherence. The results demonstrated high feasibility, with strong maternal acceptance of the Triple P intervention. Most participants attended all sessions, despite logistical challenges such as transportation difficulties, financial constraints, and regional instability. Retention was high, with minimal dropout throughout the program. The intervention was culturally well-received, tolerated with no harm, with successful implementation among mothers who shared a common linguistic, religious, and sociocultural background. Additionally, the online delivery of some sessions proved feasible and acceptable for many participants, offering an alternative format when in-person meetings were not possible due to safety concerns or connectivity issues. Primary Outcome Measures Pre- and post-intervention assessments were conducted for both the intervention and control groups on all study measures. Independent samples t-tests were used to examine group differences at baseline and post-intervention (Table 3). All assumptions for parametric testing—including normality and homogeneity of variance—were confirmed before analysis. The independent variable was group assignment (intervention vs. control), while the dependent variables were the continuous outcome scores from the PS, PSOC, and SDQ. Child Behavioral Outcomes: SDQ At baseline, there were no statistically significant differences between the two groups in total SDQ scores, with the intervention group scoring M = 19.78 (SD = 5.56) and the control group M = 21.32 (SD = 6.09), t (61) = -1.05, p > .05. Similarly, post-test scores remained nonsignificant (intervention: M = 19.28, SD = 6.71; control: M = 21.52, SD = 5.54), t (61) = -1.44, p > .05. Analysis of the SDQ subscales revealed several notable patterns. For emotional symptoms, no statistically significant differences were observed between the intervention and control groups at either pre-test or post-test ( p > .05). Similarly, conduct problems showed no significant group differences at both time points ( p > .05). Peer problems also remained statistically non-significant across the two assessments ( p > .05), indicating no measurable change attributable to the intervention in this domain. However, for hyperactivity-inattention, a marginally significant difference was detected at post-test, with the intervention group reporting fewer symptoms (M = 6.78, SD = 2.70) compared to the control group (M = 7.97, SD = 2.00), t (61) = -1.97, p = .053. The associated effect size (Cohen’s d = 0.48) suggests a moderate positive impact of the intervention on hyperactivity symptoms. In contrast, prosocial behavior showed a statistically significant improvement post-intervention. The intervention group had higher prosocial scores (M = 7.72, SD = 2.20) than the control group (M = 6.19, SD = 2.57), t (61) = 2.53, p = .014. This difference corresponded to a medium to large effect size ( d = 0.64), indicating that the intervention enhanced children’s social functioning as perceived by their mothers. Parenting Practices: Parenting Scale (PS) Total PS scores did not significantly differ between groups at baseline ( t (60) = -0.911, p > .05) or post-intervention ( t (60) = -1.62, p > .05). Regarding the laxness Subscale: At pre-test, the intervention group scored significantly higher (M = 3.08, SD = 1.23) than the control group (M = 3.80, SD = 1.01), t (60) = -2.51, p = .015, with a medium to large effect size ( d = −0.73), indicating greater initial permissiveness. Post-test scores revealed a significant reduction in laxness in the intervention group (M = 3.31, SD = 1.45) compared to the control group (M = 3.95, SD = 0.93), t (60) = -2.07, p = .04, with a moderate effect size ( d = −0.51). regarding the over-reactivity Subscale: No significant differences were found between groups at either time point (pre-test: t (60) = 0.45, p > .05; post-test: t (60) = -0.32, p > .05). Parental Competence: Parenting Sense of Competence Scale (PSOC) Baseline total PSOC scores did not differ significantly between groups (intervention: M = 63.44, SD = 6.97; control: M = 65.03, SD = 8.38), t (60) = -0.82, p > .05. However, post-intervention analysis showed a statistically significant improvement in the intervention group (M = 68.28, SD = 9.67) compared to the control group (M = 62.80, SD = 8.81), t (60) = 2.30, p = .023. The effect size was moderate ( d = 0.59), indicating enhanced parental efficacy and satisfaction. Discussion Over the past two decades, behavioral parent training programs have demonstrated significant clinical benefits in enhancing parenting efficacy, reducing stress, and improving child outcomes in ADHD contexts. Despite such evidence, these interventions have rarely been tested in Arab populations, particularly in Palestine. This study marks the first evaluation of Triple P in Palestine and demonstrates the feasibility of culturally adapting and delivering the intervention in a complex sociopolitical environment. Mothers attended sessions with high adherence despite barriers such as stigma, transportation difficulties, financial constraints, and security challenges. These findings suggest that, when culturally tailored, Triple P is acceptable and implementable in low-resource and conflict-affected settings. Feasibility was also enhanced by offering remote options. Some mothers found online delivery more accessible, helping circumvent stigma and logistical constraints—an increasingly relevant format during periods of political instability. These results support previous findings indicating that digital adaptations of Triple P can sustain engagement in socially disadvantaged communities (32,33). Post-intervention results showed significant improvements in maternal sense of competence in the intervention group compared to controls. These findings align with previous studies confirming Triple P’s effectiveness in enhancing parenting self-efficacy, especially in populations managing childhood behavioral disorders (13,18,34) Increased parenting confidence is critical, as it is inversely associated with parenting stress and directly correlated with improved child outcomes and healthier parent-child interactions(11,17,35,36) The intervention also produced improvements in parenting practices. The results showed a significant reduction in permissive discipline (laxness) in the intervention group, while over-reactivity scores showed downward trends. This shift toward more consistent and constructive parenting aligns with literature emphasizing the role of positive discipline in mitigating disruptive child behavior and reducing parental distress(37,38). Further, significant improvements were observed in children’s prosocial behaviors post-intervention, as well as marginal reductions in hyperactivity symptoms. These outcomes underscore the broader efficacy of Triple P in promoting adaptive child behaviors, which not only enhance developmental trajectories but also reduce family stress (14,39,40). These results highlight the need to move beyond diagnosis and medication, advocating instead for holistic interventions that empower caregivers with evidence-based tools. The findings of this study need to be considered in light of their limitations. First, the study used a pre-post design with no long-term follow-up, limiting insight into sustained effects. Second, the sample size was modest, potentially affecting generalizability, although consistent with prior feasibility studies. Third, intervention delivery by a single researcher may have introduced social desirability bias. Lastly, data collection occurred during the Gaza conflict and lockdowns, which may have influenced participant stress levels and engagement. Despite these limitations, the study offers several strengths. It is among the first to evaluate a structured parenting program for ADHD in Palestine. The use of an RCT design, adherence to CONSORT guidelines, and cultural tailoring of session content contribute to its methodological rigor. The intervention’s flexibility in delivery and responsiveness to participants’ needs enhanced feasibility and ecological validity. Finally, following the completion of the study and preliminary findings, control group participants were granted access to the full Triple P intervention materials. These were delivered via a dedicated WhatsApp group with researcher support, ensuring equitable access to the benefits of the program and enabling asynchronous learning and application. Implications and Recommendations The results support the integration of Triple P into mental health services targeting ADHD in Palestine. Nurses, educators, and healthcare providers should be trained in delivering culturally adapted parenting programs. Policies should promote parent engagement, normalize behavioral parent training, and establish counseling centers focused on ADHD and caregiver well-being. Future studies should include larger and more diverse samples, incorporate longitudinal follow-up, and examine mediators (e.g., maternal mental health) and moderators (e.g., intervention level, child age) to optimize impact (41)(39). Inclusion of fathers and exploration of parental ADHD symptoms are also recommended, as these factors influence intervention adherence and outcomes. Embedding Triple P in academic curricula and primary care could ensure long-term sustainability. Conclusion This study provides an evidence that Triple P is both feasible and effective in the Palestinian context. The intervention led to meaningful reductions in child hyperactivity, increases in prosocial behavior, and significant improvements in maternal parenting confidence and discipline practices. Integrating Triple P into national mental health strategies could provide critical support for families affected by ADHD and foster resilience among caregivers in conflict-affected settings. Abbreviations ADHD:Attention Deficit Hyperactivity Disorder MENA:Middle East and North Africa Region PS:Parenting Scale PSOC:Parenting Sense of Competency PTBM:parent training in behavior management RCT:Randomized Control Trial SDQ:Strength and Difficulties Questioner Triple p: positive parenting program Declarations Ethics approval and consent to participate This study was conducted following the ethical standards of the Institutional Review Board of ( Arab American University of Palestine) at 19/August/2023, with approval number R-2024/A/131/N. Written informed consent was obtained from all parents or legal guardians of the participating children. Consent for publication: Not applicable Competing interests: The authors declare that they have no competing interests. Declaration of interests The authors declare no conflicts of interest relevant to this study. Data Availability The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. Funding : The study had no source of funding Authors' contributions Nadia Amro wrote and conducted the trial, reviewed and supervised by Dr Latifa Dardas . References Dalrymple RA, Maxwell LM, Russell S, Duthie J. {NICE} guideline review: Attention deficit hyperactivity disorder: diagnosis and management ({NG87}). Arch Dis Childhood-Education Pract. 2020;105:289–93. DuPaul GJ. The conceptual and diagnostic importance of ADHD-related impairment: a Commentary on Arildskov et al. (2021). J Child Psychol Psychiatry Allied Discip. 2022;63(2):238–40. Al-Wardat M, Etoom M, Almhdawi KA, Hawamdeh Z, Khader Y. Prevalence of attention-deficit hyperactivity disorder in children, adolescents and adults in the Middle East and North Africa region: A systematic review and meta-analysis. BMJ Open. 2024;14(1):e078849. 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Aghebati A, Gharraee B, Shoshtari MH, Gohari MR. Triple P-positive parenting program for mothers of ADHD children. Iran J Psychiatry Behav Sci. 2014;8(1):59–65. Li N, Peng J, Li Y. Effects and Moderators of Triple P on the Social, Emotional, and Behavioral Problems of Children: Systematic Review and Meta-Analysis. Front Psychol. 2021;12. Khademi M, Ayatmehr F, Khosravan Mehr N, Razjooyan K, Davari Ashtiani R, Arabgol F. Evaluation of the Effects of Positive Parenting Program on Symptoms of Preschool Children With Attention Deficit Hyperactivity Disorder. Pract Clin Psychol [Internet]. 2019 Jan 30;11–20. Available from: http://jpcp.uswr.ac.ir/article-1-512-en.html Kraemer WJ, Ratamess NA, French DN. CrossRef Listing of Deleted DOIs. CrossRef List Deleted DOIs [Internet]. 2007;1(3):165–71. Available from: https://doi.org/10.1007/s11932-002-0017-7 Tables Table 1 Contents of group triple p sessions Adapted from (Yusuf, Ö., et al,2019). Table 2 Participants Characteristics (N=64) Characteristics Control group (n=31) Intervention group (n=33) Age Child's Age in years, mean (SD) 8.81 (2.07) 8.7(2.19) Mother's Age in years, mean (SD) 39.7(8.09) 34.7 (7.16) Marital Status Married 28 (90.3%) 30 (90.9%) Divorced 0 (0.0%) 2 (6.1%) Separated 3 (9.7%) 1 (3.0%) Mother's Education Level Uneducated 2 (6.5%) 0 (0.0%) Primary 2 (6.5%) 2 (6.1%) Secondary 8 (25.8%) 7 (21.2%) Tawjihi 3 (9.7%) 7 (21.2%) Bachelor 10 (32.3%) 8 (24.2%) Diploma (2 years) 5 (16.1%) 6 (18.2%) Higher Studies 1 (3.2%) 3 (9.1%) Mother employment Status Yes 11 (35.5%) 8 (24.2%) No 20 (64.5%) 25 (75.8%) Child's Gender Male 21 (67.7%) 20 (60.6%) Female 10 (32.3%) 13 (39.4%) Other diagnosed Children Yes 2 (6.5%) 11 (33.3%) No 29 (93.5%) 22 (66.7%) Type of ADHD Treatment Center Governmental Clinic 13 (41.9%) 9 (27.3%) Specialized Center 3 (9.7%) 15 (45.5%) Private Clinic 10 (32.3%) 4 (12.1%) Not Affiliated 5 (16.1%) 5 (15.2%) School Mainstreaming Yes 22 (71.0%) 26 (78.8%) No 9 (29.0%) 7 (21.2%) Table 3 Pre and Post Differences in PSOC, PS, SDQ scales among Intervention and Control Groups Measure Intervention (M ± SD) Control (M ± SD) Total (M ± SD) t-value p-value SDQ-Emotional Problems (Pre) 4.56 ± 2.45 5.16 ± 2.38 4.88 ± 2.42 -.983 0.32 SDQ-Emotional Problems (Post) 4.94 ± 2.60 5.16 ± 2.24 5.06 ± 2.41 -0.36 0.716 SDQ-Conduct Problems (Pre) 3.91 ± 1.78 4.39 ± 2.58 4.16 ± 2.22 -.863 0.39 SDQ-Conduct Problems (Post) 3.59 ± 1.86 4.48 ± 2.42 4.04 ± 2.18 -1.639 0.10 SDQ-Hyperactivity (Pre) 8.22 ± 1.98 7.71 ± 2.04 7.96 ± 2.01 -1.849 0.06 SDQ-Hyperactivity (Post) 6.78 ± 2.70 7.97 ± 2.01 7.38 ± 2.42 -1.976 0.05* SDQ-Peer Problems (Pre) 4.38 ± 1.88 3.84 ± 1.51 4.10 ± 1.72 1.24 0.21 SDQ-Peer Problems (Post) 3.97 ± 1.71 3.90 ± 1.76 3.94 ± 1.73 0.150 0.881 SDQ-Prosocial (Pre) 7.47 ± 2.29 6.42 ± 2.81 6.92 ± 2.57 1.627 0.109 SDQ-Prosocial (Post) 7.72 ± 2.20 6.19 ± 2.57 6.98 ± 2.44 2.529 0.01* SDQ-Impact Score (Pre) 6.77 ± 4.43 5.19 ± 3.27 6.00 ± 3.90 1.598 0.115 SDQ-Impact Score (Post) 6.22 ± 4.24 5.06 ± 3.32 5.67 ± 3.83 1.201 0.234 SDQ-Total Score (Pre) 19.78 ± 5.56 21.32 ± 6.09 20.61 ±5.82 -1.049 0.298 SDQ-Total Score (Post) 19.28 ± 6.71 21.52 ± 5.54 20.42 ±6.13 -1.439 0.155 Parenting Scale - Laxness (Pre) 3.0 ± 1.2 3.8 ± 1.0 6.85 ± 2.35 -2.510 0.01* Parenting Scale - Laxness (Post) 3.3 ± 1.4 3.9 ± .9 15.94 ± 4.80 -2.27 0.04* Parenting Scale - Over reactivity (Pre) 4.0 ± 1.3 3.9± 1.0 15.19 ± 4.12 0.451 0.65 Parenting Scale - Over reactivity (Post) 3.6 ± 1.3 3.7 ± 0.9 14.94 ± 4.60 -0.324 0.74 Parenting Scale - Total (Pre) 3.77 ± 0.87 3.96 ± 0.76 3.86 ± 0.81 -0.91 0.36 Parenting Scale - Total (Post) 3.22 ± 0.86 3.53 ± 0.63 3.38 ± 0.76 -1.6 0.11 PSOC - Total (Pre) 63.44 ± 6.97 65.03 ± 8.38 64.22 ± 7.63 -.822 0.4 PSOC - Total (Post) 68.28 ± 9.67 62.80 ± 8.81 65.67 ± 9.44 2.3 0.02* Note. M = mean; SD = standard deviation; t = t-value;p = p-value. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 19 Nov, 2025 Read the published version in Child and Adolescent Psychiatry and Mental Health → Version 1 posted Editorial decision: Revision requested 13 Aug, 2025 Reviews received at journal 13 Aug, 2025 Reviewers agreed at journal 10 Aug, 2025 Reviews received at journal 08 Aug, 2025 Reviewers agreed at journal 07 Aug, 2025 Reviewers invited by journal 07 Aug, 2025 Editor assigned by journal 06 Aug, 2025 Submission checks completed at journal 05 Aug, 2025 First submitted to journal 30 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7250693","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":498300375,"identity":"bf1c53b5-1541-4224-bb39-d4435da04423","order_by":0,"name":"Nadia Amro","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYHACgwMQmhlKHyBeC1sC8VqgNI8BcVrM2Q9vPPCDwS7avL3n2+PCNgY5vhsJ+LVY9qQVHOxhSM6dc+bsduOZbQzGkoS0GBzIMTjA+485d4ZE7jZp3jaGxA0EtZx/Y3DwD0M9UEvOM5CWesJabuQYHOZhOAzSwgbSkmBAWMuzgsMyDMdzZ/AcMzeecU7CcOaZB4Qclrz54xuG6twZ7M3PHheU2cjzHSdgCzJgY2ZgkCBeOUzLKBgFo2AUjAJMAABjlkb2+ufhegAAAABJRU5ErkJggg==","orcid":"","institution":"Palestine Polytechnic University","correspondingAuthor":true,"prefix":"","firstName":"Nadia","middleName":"","lastName":"Amro","suffix":""},{"id":498300376,"identity":"f29e17b7-e7b7-4c9b-9e5c-b9040be8bde5","order_by":1,"name":"Latefa Dardas","email":"","orcid":"","institution":"University of Jordan","correspondingAuthor":false,"prefix":"","firstName":"Latefa","middleName":"","lastName":"Dardas","suffix":""}],"badges":[],"createdAt":"2025-07-30 08:53:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7250693/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7250693/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13034-025-00960-y","type":"published","date":"2025-11-19T15:58:27+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89066304,"identity":"473fd761-0dc5-4c64-b990-32d8c30be7e5","added_by":"auto","created_at":"2025-08-14 10:42:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":333773,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eCONSORT Flow Diagram\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7250693/v1/f29e07b96441b6b50047d861.png"},{"id":96650184,"identity":"beb10978-0294-4c4d-9f1f-b7ba769991ee","added_by":"auto","created_at":"2025-11-24 16:09:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1960978,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7250693/v1/f3cfe5b0-8628-4fae-bf8a-b2e1483b6403.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Positive Parenting Program for Attention Deficit Hyperactivity Disorder: Maternal Perspective Shifts and Child Behavior Problems Reduction in a Clinical Trial","fulltext":[{"header":"Key Practitioner Message","content":"\u003cp\u003e\u003cstrong\u003eWhat is known?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eADHD Children experience significant behavioral difficulties,international Parenting interventions such as the Triple P (Positive Parenting Program), are effective in enhancing parenting self-agency and reducing child behavioral problems. However, its implementation, feasibility and effectiveness is undocumented in low-resource, conflict contexts like Palestine.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat is new?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe randomized controlled trial demonstrated the feasibility of the culturally adapted Triple P intervention for Palestinian mothers of ADHD children with a significant improvement in mothers\u0026apos; sense of competence and attitude, with a reduction in child problematic behaviors, and enhanced children\u0026rsquo;s prosocial behavior.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat is significant for clinical practice?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHealth care Practitioners working with ADHD children in low-resource and conflict regions should consider integrating culturally adapted Triple P for parents as part of the management plan to enhance parenting skills and improve child outcomes and family well-being.\u003c/p\u003e"},{"header":"Background","content":"\u003cp\u003eAttention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder that affects approximately 5% of children globally (1), with symptoms often persisting into adolescence and adulthood, impairing academic, social, and occupational functioning (2). In the Middle East and North Africa (MENA) region, the prevalence is notably higher, reaching 10.3% according to a recent meta-analysis(3). ADHD diagnosis typically involves clinician assessments supported by parent and teacher reports, alongside standardized rating scales(4). According to a systematic review and meta-analysis study in Saudi Arabia, the frequency of ADHD ranged from 3.3–16.1%. Based on the meta-analysis, the estimated pooled prevalence was 9.95%(5).\u003c/p\u003e\u003cp\u003eEffective management of ADHD increasingly emphasizes behavioral interventions. The American Academy of Pediatrics (AAP) recommends parent training in behavior management (PTBM) as a first-line treatment (6). Behavioral Parent Training (BPT) equips parents with strategies such as positive reinforcement, structured discipline, and problem-solving, promoting improved child behavior and parental competence. These approaches draw on social learning theory, self-regulation theory, and applied behavior analysis (7).\u003c/p\u003e\u003cp\u003eAmong BPT programs, the Triple P – Positive Parenting Program is one of the most widely implemented, offering multi-level interventions tailored to community and individual needs (8). Developed at the University of Queensland, Triple P aims to enhance parenting knowledge, confidence, and self-regulation while fostering child well-being through supportive environments, assertive discipline, and realistic expectations (9,10). Evidence from diverse contexts—including Singapore, Sweden, and Pakistan—demonstrates its effectiveness in reducing child behavior problems, parenting stress, and parental mental health symptoms while strengthening parent-child relationships and promoting long-term positive outcomes(11–18)\u003c/p\u003e\u003cp\u003eDespite this global evidence, little is known about the applicability and impact of Triple P in Palestine, a region marked by high ADHD prevalence and unique sociocultural challenges. In a recent study, it was found that the frequency of ADHD signs among Palestinian school-age children was (8.7%)(19). There were no significant differences in prevalence among Arabs and Jews of 18.7%and 17.8% respectively(20).ADHD can profoundly impact family dynamics, with research indicating that mothers of children with ADHD often experience heightened feelings of anger, anxiety, and depression, feeling less effective and successful compared to mothers of children without ADHD (21). Moreover Mothers of children with ADHD are facing high burden of care and specifically in the region of Hebron(22,23).Adding to this burden the complex regional political and socioeconomical difficulties facing these families.\u003c/p\u003e\u003cp\u003eParenting programs that are effective in Western or high-resource contexts may not directly translate to Palestinian families facing chronic stress, limited mental health resources, and cultural barriers to help-seeking. Moreover, few studies have explored the maternal perspective specifically, despite mothers often being primary caregivers for children with ADHD.\u003c/p\u003e\u003cp\u003eThis study addresses this critical gap by evaluating the impact of the Triple P program among Palestinian mothers of children with ADHD. Specifically, it examines the program’s feasibility and cultural acceptability, its effects on maternal attitudes and parenting competence, and its efficacy in reducing ADHD-related behavioral symptoms in children. Ultimately, the study aims to inform the development of culturally sensitive, evidence-based interventions for ADHD in the Palestinian context.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eStudy Design and Setting\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study employed a randomized controlled trial (RCT) design with pre-test and post-test assessments to evaluate the effectiveness of the Triple P – Positive Parenting Program among Palestinian mothers of children diagnosed with ADHD. The trial was conducted at Hebron Mental Health Center for Children, a governmental facility located north of Hebron. The center offers comprehensive services, including psychological support, speech therapy, behavioral interventions, and pharmacological treatment for children with mental and behavioral disorders.\u003c/p\u003e\u003cp\u003e\u003cb\u003eParticipants and Recruitment\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePotential participants were identified from ADHD care centers across Palestine. Eligibility criteria included: (1) being the biological mother of a child aged 6–13 years formally diagnosed with ADHD and currently attending a child mental health clinic; and (2) not receiving parental support services from other professional agencies. Exclusion criteria encompassed children with neurological or medical disorders, intellectual disabilities, psychosis, bipolar disorder, or severe aggressive behaviors.\u003c/p\u003e\u003cp\u003e Following ethical approval from the (Arab American University of Palestine) Institutional Review Board and authorization from the Palestinian Ministry of Health, eligible participants were contacted and invited to participate. Informed consent was obtained, and eligibility was confirmed through structured interviews and review of clinical records. Participants were assured of anonymity, voluntary participation, and the right to withdraw at any stage. All data were stored securely in password-protected digital folders and locked physical cabinets accessible only to the principal investigator.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRandomization and Sample Size\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAfter confirming eligibility, participants were randomly assigned to the intervention (Triple P) or control group using a computer-generated randomization procedure in Microsoft Excel—the RAND () function generated random numbers. Participants were recruited between June 2023 and August 2024, sorted in ascending order to achieve a 1:1 allocation. Thirty-three participants were assigned to the intervention group and 31 to the control group (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e: CONSORT Flow Diagram).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eSample size estimation was based on prior Triple P studies demonstrating moderate to large effect sizes (14,16). Using G*Power with an alpha level of 0.05, power of 0.80, and an anticipated effect size of 0.40, the required sample size was 66 participants (33 per group).\u003c/p\u003e\u003cp\u003e\u003cb\u003eIntervention: Triple P – Positive Parenting Program\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe Group Triple P Level 4 intervention was culturally adapted for the Palestinian context. The lead researcher completed a certified online training course through the Triple P Association (UK) and received accreditation to deliver the Level 4 program tailored for children with special needs. Core content was sourced from the official Triple P provider materials and Every \u003cem\u003eParent\u003c/em\u003e manual, which was translated into Arabic. Supplementary Arabic-language videos from the Triple P platform were used to enhance participant comprehension and engagement. The intervention was administered with fidelity, and according to the original manual checklist, began with an introductory session that introduced the program, obtained written informed consent, built rapport, and collected baseline demographic data and pre-intervention measures. The program was delivered across multiple group sessions (each lasting approximately two hours), incorporating instructional content, video modeling, group discussions, and structured activities (see Table\u0026nbsp;1). Adherence record indicated 85% of mothers attended at least 6 sessions out of 8. Following the group sessions, each mother received two to three individualized follow-up phone calls (30–50 minutes each) to support practical application, troubleshoot challenges, and reinforce learned strategies.\u003c/p\u003e\u003cp\u003e Ongoing support was provided via a dedicated WhatsApp group, where participants received daily reinforcement through brief messages and multimedia content. These prompts encouraged reflection, reinforced parenting strategies, and supported the development of parental self-efficacy in managing disruptive behavior. Participants were instructed to unenroll in other parenting interventions until completion of the follow-up assessments\u003c/p\u003e\u003cp\u003e\u003cb\u003eControl Condition\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe control group received standard care, which typically included routine clinical follow-ups and general psychosocial support but no structured parenting intervention. Control group participants completed the same pre- and post-assessments as the intervention group, with a two-month interval between measurements. Participants in both groups continued to receive Concomitant Care.\u003c/p\u003e\u003cp\u003e\u003cb\u003eOutcome Assessment\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe effectiveness of the Triple P – Positive Parenting Program was evaluated using three validated instruments: two assessing maternal outcomes and one measuring child behavioral outcomes, all based on maternal report.\u003c/p\u003e\u003cp\u003e\u003cb\u003e1. Strengths and Difficulties Questionnaire (SDQ)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe Arabic version of the Strengths and Difficulties Questionnaire (SDQ) was used to assess children’s emotional and behavioral functioning, as reported by their mothers. Originally developed by(24), the SDQ comprises 25 items spanning five subscales: hyperactivity/inattention, emotional symptoms, peer problems, conduct problems, and prosocial behavior. It is validated for children aged 3 to 16 years. Previous studies have demonstrated adequate psychometric properties, with a Cronbach’s alpha of 0.73 for the subscales and 0.78 for the total difficulties score(25,26). In the current study, internal consistency for the SDQ total score was excellent (Cronbach’s α = 0.88). Test-retest reliability, measured using the intraclass correlation coefficient (ICC) via a two-way mixed-effects model, yielded an ICC of 0.88 (95% CI [0.83, 0.91]).\u003c/p\u003e\u003cp\u003e\u003cb\u003e2. Parenting Scale (PS)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe abbreviated 7-item Parenting Scale (PS) was employed to assess dysfunctional parenting practices, particularly discipline styles. It includes two subscales: laxness (three items) and over-reactivity (four items), each rated on a seven-point Likert scale(27,28). This tool has demonstrated good psychometric properties, with prior research reporting Cronbach’s alpha values ranging from 0.60 to 0.79(29). In this study, internal consistency was moderate (Cronbach’s α = 0.62). The ICC was 0.619 (95% CI [0.431, 0.766]), indicating moderate test-retest reliability across pre- and post-intervention measurements.\u003c/p\u003e\u003cp\u003e\u003cb\u003e3. Parenting Sense of Competence Scale (PSOC)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe Parenting Sense of Competence Scale (PSOC) was used to evaluate parental self-esteem, comprising 17 items that measure two domains: satisfaction and efficacy. Originally developed by (30) and revised by (31),the scale has shown robust internal reliability, with previous alpha values of 0.75 for Satisfaction, 0.76 for Efficacy, and 0.79 for the total score. The Arabic version was developed using forward and backward translation by bilingual experts. In this study, the PSOC demonstrated good reliability, with an ICC of 0.735 (95% CI [0.630, 0.821]) using a two-way mixed-effects model.\u003c/p\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eAll statistical analyses were conducted using IBM SPSS Statistics version 27. Data were first screened for completeness and accuracy. Missing data were assumed to be random of less than 3%, and were excluded using listwise deletion. Descriptive statistics (frequencies, percentages, means, and standard deviations) were used to characterize demographic variables and baseline measures. Reliability for each outcome instrument was assessed using Cronbach’s alpha coefficients and intraclass correlation coefficients (ICC). Normality of continuous variables was evaluated using the Kolmogorov-Smirnov test. To assess baseline equivalence between the intervention and control groups, independent samples \u003cem\u003et\u003c/em\u003e-tests were performed on all pre-intervention variables. The effectiveness of the Triple P intervention was analyzed by comparing pre- and post-intervention scores within and between groups using independent \u003cem\u003et\u003c/em\u003e-tests. Statistical significance was determined at an alpha level of 0.05 (two-tailed). The primary analyses focused on evaluating changes in parenting practices, parental competence, and child behavior. Differences in mean change scores between the two groups were used to assess the impact of the intervention relative to standard care. Sensitivity or subgroup analysis was not conducted.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eParticipant Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe final sample included 64 children diagnosed with ADHD and their mothers. The children had a mean age of 8.00 years (SD = 2.13), ranging from 5 to 13 years. The mothers\u0026apos; mean age was 36.75 years (SD = 7.54), with ages ranging from 23 to 53 years. The majority of children were male (68.75%, n = 44). Most participating mothers were married (90.6%, n = 58), while a smaller proportion were separated (6.3%, n = 4) or divorced (3.1%, n = 2). Regarding educational background, 28.1% of mothers (n = 18) held a Bachelor\u0026apos;s degree. The majority were unemployed (70.3%, n = 45). In terms of healthcare access, 34.4% of children (n = 22) received ADHD treatment through governmental clinics. Most children (75.0%, n = 48) were enrolled in mainstream schools. (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFeasibility Results\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFeasibility was assessed through indicators including participant satisfaction, data completeness, cultural congruence, retention rates, and protocol adherence. The results demonstrated high feasibility, with strong maternal acceptance of the Triple P intervention. Most participants attended all sessions, despite logistical challenges such as transportation difficulties, financial constraints, and regional instability. Retention was high, with minimal dropout throughout the program. The intervention was culturally well-received, tolerated with no harm, with successful implementation among mothers who shared a common linguistic, religious, and sociocultural background. Additionally, the online delivery of some sessions proved feasible and acceptable for many participants, offering an alternative format when in-person meetings were not possible due to safety concerns or connectivity issues.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrimary Outcome Measures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePre- and post-intervention assessments were conducted for both the intervention and control groups on all study measures. Independent samples t-tests were used to examine group differences at baseline and post-intervention (Table 3). All assumptions for parametric testing\u0026mdash;including normality and homogeneity of variance\u0026mdash;were confirmed before analysis. The independent variable was group assignment (intervention vs. control), while the dependent variables were the continuous outcome scores from the PS, PSOC, and SDQ.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChild Behavioral Outcomes: SDQ\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt baseline, there were no statistically significant differences between the two groups in total SDQ scores, with the intervention group scoring M = 19.78 (SD = 5.56) and the control group M = 21.32 (SD = 6.09), \u003cem\u003et\u003c/em\u003e(61) = -1.05, \u003cem\u003ep\u003c/em\u003e \u0026gt; .05. Similarly, post-test scores remained nonsignificant (intervention: M = 19.28, SD = 6.71; control: M = 21.52, SD = 5.54), \u003cem\u003et\u003c/em\u003e(61) = -1.44, \u003cem\u003ep\u003c/em\u003e \u0026gt; .05. Analysis of the SDQ subscales revealed several notable patterns. For emotional symptoms, no statistically significant differences were observed between the intervention and control groups at either pre-test or post-test (\u003cem\u003ep\u003c/em\u003e \u0026gt; .05). Similarly, conduct problems showed no significant group differences at both time points (\u003cem\u003ep\u003c/em\u003e \u0026gt; .05). Peer problems also remained statistically non-significant across the two assessments (\u003cem\u003ep\u003c/em\u003e \u0026gt; .05), indicating no measurable change attributable to the intervention in this domain. However, for hyperactivity-inattention, a marginally significant difference was detected at post-test, with the intervention group reporting fewer symptoms (M = 6.78, SD = 2.70) compared to the control group (M = 7.97, SD = 2.00), \u003cem\u003et\u003c/em\u003e(61) = -1.97, \u003cem\u003ep\u003c/em\u003e = .053. The associated effect size (Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e = 0.48) suggests a moderate positive impact of the intervention on hyperactivity symptoms. In contrast, prosocial behavior showed a statistically significant improvement post-intervention. The intervention group had higher prosocial scores (M = 7.72, SD = 2.20) than the control group (M = 6.19, SD = 2.57), \u003cem\u003et\u003c/em\u003e(61) = 2.53, \u003cem\u003ep\u003c/em\u003e = .014. This difference corresponded to a medium to large effect size (\u003cem\u003ed\u003c/em\u003e = 0.64), indicating that the intervention enhanced children\u0026rsquo;s social functioning as perceived by their mothers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParenting Practices: Parenting Scale (PS)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal PS scores did not significantly differ between groups at baseline (\u003cem\u003et\u003c/em\u003e(60) = -0.911, \u003cem\u003ep\u003c/em\u003e \u0026gt; .05) or post-intervention (\u003cem\u003et\u003c/em\u003e(60) = -1.62, \u003cem\u003ep\u003c/em\u003e \u0026gt; .05). Regarding the laxness Subscale: At pre-test, the intervention group scored significantly higher (M = 3.08, SD = 1.23) than the control group (M = 3.80, SD = 1.01), \u003cem\u003et\u003c/em\u003e(60) = -2.51, \u003cem\u003ep\u003c/em\u003e = .015, with a medium to large effect size (\u003cem\u003ed\u003c/em\u003e = \u0026minus;0.73), indicating greater initial permissiveness. Post-test scores revealed a significant reduction in laxness in the intervention group (M = 3.31, SD = 1.45) compared to the control group (M = 3.95, SD = 0.93), \u003cem\u003et\u003c/em\u003e(60) = -2.07, \u003cem\u003ep\u003c/em\u003e = .04, with a moderate effect size (\u003cem\u003ed\u003c/em\u003e = \u0026minus;0.51). regarding the over-reactivity Subscale: No significant differences were found between groups at either time point (pre-test: \u003cem\u003et\u003c/em\u003e(60) = 0.45, \u003cem\u003ep\u003c/em\u003e \u0026gt; .05; post-test: \u003cem\u003et\u003c/em\u003e(60) = -0.32, \u003cem\u003ep\u003c/em\u003e \u0026gt; .05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParental Competence: Parenting Sense of Competence Scale (PSOC)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBaseline total PSOC scores did not differ significantly between groups (intervention: M = 63.44, SD = 6.97; control: M = 65.03, SD = 8.38), \u003cem\u003et\u003c/em\u003e(60) = -0.82, \u003cem\u003ep\u003c/em\u003e \u0026gt; .05. However, post-intervention analysis showed a statistically significant improvement in the intervention group (M = 68.28, SD = 9.67) compared to the control group (M = 62.80, SD = 8.81), \u003cem\u003et\u003c/em\u003e(60) = 2.30, \u003cem\u003ep\u003c/em\u003e = .023. The effect size was moderate (\u003cem\u003ed\u003c/em\u003e = 0.59), indicating enhanced parental efficacy and satisfaction.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOver the past two decades, behavioral parent training programs have demonstrated significant clinical benefits in enhancing parenting efficacy, reducing stress, and improving child outcomes in ADHD contexts. Despite such evidence, these interventions have rarely been tested in Arab populations, particularly in Palestine. This study marks the first evaluation of Triple P in Palestine and demonstrates the feasibility of culturally adapting and delivering the intervention in a complex sociopolitical environment. Mothers attended sessions with high adherence despite barriers such as stigma, transportation difficulties, financial constraints, and security challenges. These findings suggest that, when culturally tailored, Triple P is acceptable and implementable in low-resource and conflict-affected settings. Feasibility was also enhanced by offering remote options. Some mothers found online delivery more accessible, helping circumvent stigma and logistical constraints\u0026mdash;an increasingly relevant format during periods of political instability. These results support previous findings indicating that digital adaptations of Triple P can sustain engagement in socially disadvantaged communities (32,33).\u003c/p\u003e\u003cp\u003ePost-intervention results showed significant improvements in maternal sense of competence in the intervention group compared to controls. These findings align with previous studies confirming Triple P\u0026rsquo;s effectiveness in enhancing parenting self-efficacy, especially in populations managing childhood behavioral disorders (13,18,34) Increased parenting confidence is critical, as it is inversely associated with parenting stress and directly correlated with improved child outcomes and healthier parent-child interactions(11,17,35,36) The intervention also produced improvements in parenting practices. The results showed a significant reduction in permissive discipline (laxness) in the intervention group, while over-reactivity scores showed downward trends. This shift toward more consistent and constructive parenting aligns with literature emphasizing the role of positive discipline in mitigating disruptive child behavior and reducing parental distress(37,38). Further, significant improvements were observed in children\u0026rsquo;s prosocial behaviors post-intervention, as well as marginal reductions in hyperactivity symptoms. These outcomes underscore the broader efficacy of Triple P in promoting adaptive child behaviors, which not only enhance developmental trajectories but also reduce family stress (14,39,40). These results highlight the need to move beyond diagnosis and medication, advocating instead for holistic interventions that empower caregivers with evidence-based tools.\u003c/p\u003e\u003cp\u003eThe findings of this study need to be considered in light of their limitations. First, the study used a pre-post design with no long-term follow-up, limiting insight into sustained effects. Second, the sample size was modest, potentially affecting generalizability, although consistent with prior feasibility studies. Third, intervention delivery by a single researcher may have introduced social desirability bias. Lastly, data collection occurred during the Gaza conflict and lockdowns, which may have influenced participant stress levels and engagement. Despite these limitations, the study offers several strengths. It is among the first to evaluate a structured parenting program for ADHD in Palestine. The use of an RCT design, adherence to CONSORT guidelines, and cultural tailoring of session content contribute to its methodological rigor. The intervention\u0026rsquo;s flexibility in delivery and responsiveness to participants\u0026rsquo; needs enhanced feasibility and ecological validity. Finally, following the completion of the study and preliminary findings, control group participants were granted access to the full Triple P intervention materials. These were delivered via a dedicated WhatsApp group with researcher support, ensuring equitable access to the benefits of the program and enabling asynchronous learning and application.\u003c/p\u003e\u003cp\u003e\u003cb\u003eImplications and Recommendations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe results support the integration of Triple P into mental health services targeting ADHD in Palestine. Nurses, educators, and healthcare providers should be trained in delivering culturally adapted parenting programs. Policies should promote parent engagement, normalize behavioral parent training, and establish counseling centers focused on ADHD and caregiver well-being. Future studies should include larger and more diverse samples, incorporate longitudinal follow-up, and examine mediators (e.g., maternal mental health) and moderators (e.g., intervention level, child age) to optimize impact (41)(39). Inclusion of fathers and exploration of parental ADHD symptoms are also recommended, as these factors influence intervention adherence and outcomes. Embedding Triple P in academic curricula and primary care could ensure long-term sustainability.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides an evidence that Triple P is both feasible and effective in the Palestinian context. The intervention led to meaningful reductions in child hyperactivity, increases in prosocial behavior, and significant improvements in maternal parenting confidence and discipline practices. Integrating Triple P into national mental health strategies could provide critical support for families affected by ADHD and foster resilience among caregivers in conflict-affected settings.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eADHD:Attention Deficit Hyperactivity Disorder\u003c/p\u003e\n\u003cp\u003eMENA:Middle East and North Africa Region\u003c/p\u003e\n\u003cp\u003ePS:Parenting Scale\u003c/p\u003e\n\u003cp\u003ePSOC:Parenting Sense of Competency\u003c/p\u003e\n\u003cp\u003ePTBM:parent training in behavior management\u003c/p\u003e\n\u003cp\u003eRCT:Randomized Control Trial\u003c/p\u003e\n\u003cp\u003eSDQ:Strength and Difficulties Questioner\u003c/p\u003e\n\u003cp\u003eTriple p: positive parenting program\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted following the ethical standards of the Institutional Review Board of ( Arab American University of Palestine) at 19/August/2023, with approval number R-2024/A/131/N. Written informed consent was obtained from all parents or legal guardians of the participating children.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest relevant to this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: The study had no source of funding\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e Nadia Amro wrote and conducted the trial, reviewed and supervised by Dr Latifa Dardas\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDalrymple RA, Maxwell LM, Russell S, Duthie J. {NICE} guideline review: Attention deficit hyperactivity disorder: diagnosis and management ({NG87}). 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Available from: https://publications.aap.org/pediatrics/article/131/2/e446/31908/Characteristics-of-the-Strengths-and-Difficulties\u003c/li\u003e\n\u003cli\u003eArnold DS, O\u0026rsquo;Leary SG, Wolff LS, Acker MM. The Parenting Scale: A Measure of Dysfunctional Parenting in Discipline Situations. Psychol Assess. 1993;5(2):137\u0026ndash;44. \u003c/li\u003e\n\u003cli\u003eIrvine AB, Biglan A, Smolkowski K, Ary D V. The value of the Parenting Scale for measuring the discipline practices of parents of middle school children. Behav Res Ther [Internet]. 1999 Feb;37(2):127\u0026ndash;42. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0005796798001144\u003c/li\u003e\n\u003cli\u003eFung S fu, Fung ALC. Development and evaluation of the psychometric properties of a brief parenting scale (PS-7) for the parents of adolescents. Olino TM, editor. PLoS One [Internet]. 2020 Jan 29;15(1):e0228287. 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Int J Nurs Sci [Internet]. 2023 Oct;10(4):518\u0026ndash;26. Available from: https://linkinghub.elsevier.com/retrieve/pii/S235201322300100X\u003c/li\u003e\n\u003cli\u003eStattin H, Enebrink P, \u0026Ouml;zdemir M, Giannotta F. A national evaluation of parenting programs in Sweden: The short-term effects using an RCT effectiveness design. J Consult Clin Psychol [Internet]. 2015 Dec;83(6):1069\u0026ndash;84. Available from: https://doi.apa.org/doi/10.1037/a0039328\u003c/li\u003e\n\u003cli\u003eDahlberg A, Salari R, F\u0026auml;ngstr\u0026ouml;m K, Fabian H, Sarkadi A. Successful implementation of parenting support at preschool: An evaluation of Triple P in Sweden. PLoS One. 2022;17(4 April):e0265589. \u003c/li\u003e\n\u003cli\u003eMoharreri F, Shahrivar Z, Tehranidoost M, Mahmoudi-Gharaei J, Sciences M, Sciences M. Efficacy of the Positive Parenting Program ( Triple-P ) for a Group of Parents of Children with Attention Deficit Hyperactivity Disorder. Iran J Psychiatry. 2008;3(December 2015):59\u0026ndash;63. \u003c/li\u003e\n\u003cli\u003ePinquart M. Associations of Parenting Dimensions and Styles with Internalizing Symptoms in Children and Adolescents: A Meta-Analysis. Marriage Fam Rev. 2017;53(7):613\u0026ndash;40. \u003c/li\u003e\n\u003cli\u003eAghebati A, Gharraee B, Shoshtari MH, Gohari MR. Triple P-positive parenting program for mothers of ADHD children. Iran J Psychiatry Behav Sci. 2014;8(1):59\u0026ndash;65. \u003c/li\u003e\n\u003cli\u003eLi N, Peng J, Li Y. Effects and Moderators of Triple P on the Social, Emotional, and Behavioral Problems of Children: Systematic Review and Meta-Analysis. Front Psychol. 2021;12. \u003c/li\u003e\n\u003cli\u003eKhademi M, Ayatmehr F, Khosravan Mehr N, Razjooyan K, Davari Ashtiani R, Arabgol F. Evaluation of the Effects of Positive Parenting Program on Symptoms of Preschool Children With Attention Deficit Hyperactivity Disorder. Pract Clin Psychol [Internet]. 2019 Jan 30;11\u0026ndash;20. Available from: http://jpcp.uswr.ac.ir/article-1-512-en.html\u003c/li\u003e\n\u003cli\u003eKraemer WJ, Ratamess NA, French DN. CrossRef Listing of Deleted DOIs. CrossRef List Deleted DOIs [Internet]. 2007;1(3):165\u0026ndash;71. Available from: https://doi.org/10.1007/s11932-002-0017-7\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 \u0026nbsp;\u003cem\u003eContents of group triple p sessions Adapted from (Yusuf, \u0026Ouml;., et al,2019).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" width=\"853\" height=\"488\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 \u003cem\u003eParticipants Characteristics (N=64)\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003egroup (n=31)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntervention\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003egroup (n=33)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eChild\u0026apos;s Age in years, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e8.81 (2.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e8.7(2.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eMother\u0026apos;s Age in years, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e39.7(8.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e34.7 (7.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e28 (90.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e30 (90.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2 (6.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eSeparated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e3 (9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1 (3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMother\u0026apos;s Education Level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eUneducated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e2 (6.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e2 (6.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2 (6.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e8 (25.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e7 (21.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eTawjihi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e3 (9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e7 (21.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eBachelor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e10 (32.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e8 (24.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eDiploma (2 years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e5 (16.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e6 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eHigher Studies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e1 (3.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMother employment Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e11 (35.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e8 (24.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e20 (64.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e25 (75.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChild\u0026apos;s Gender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e21 (67.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e20 (60.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e10 (32.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e13 (39.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther diagnosed Children\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e2 (6.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e11 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e29 (93.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e22 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of ADHD Treatment Center\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eGovernmental Clinic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e13 (41.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e9 (27.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eSpecialized Center\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e3 (9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e15 (45.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003ePrivate Clinic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e10 (32.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e4 (12.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eNot Affiliated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e5 (16.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e5 (15.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSchool Mainstreaming\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e22 (71.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e26 (78.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 330px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e9 (29.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e7 (21.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 \u003cem\u003ePre and Post Differences in PSOC, PS, SDQ scales \u0026nbsp;among Intervention and Control Groups\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"762\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeasure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntervention\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(M \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(M \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(M \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003et-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDQ-Emotional Problems (Pre)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.56 \u0026plusmn; 2.45\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.16 \u0026plusmn; 2.38\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.88 \u0026plusmn; 2.42\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-.983\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.32\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDQ-Emotional Problems (Post)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.94 \u0026plusmn; 2.60\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.16 \u0026plusmn; 2.24\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.06 \u0026plusmn; 2.41\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.36\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.716\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDQ-Conduct Problems (Pre)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.91 \u0026plusmn; 1.78\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.39 \u0026plusmn; 2.58\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.16 \u0026plusmn; 2.22\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-.863\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.39\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDQ-Conduct Problems (Post)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.59 \u0026plusmn; 1.86\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.48 \u0026plusmn; 2.42\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.04 \u0026plusmn; 2.18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-1.639\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDQ-Hyperactivity (Pre)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e8.22 \u0026plusmn; 1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e7.71 \u0026plusmn; 2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e7.96 \u0026plusmn; 2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e-1.849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDQ-Hyperactivity (Post)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.78 \u0026plusmn; 2.70\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.97 \u0026plusmn; 2.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.38 \u0026plusmn; 2.42\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e-1.976\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.05*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDQ-Peer Problems (Pre)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.38 \u0026plusmn; 1.88\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.84 \u0026plusmn; 1.51\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.10 \u0026plusmn; 1.72\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.24\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.21\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDQ-Peer Problems (Post)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.97 \u0026plusmn; 1.71\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.90 \u0026plusmn; 1.76\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.94 \u0026plusmn; 1.73\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.150\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.881\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDQ-Prosocial (Pre)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.47 \u0026plusmn; 2.29\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.42 \u0026plusmn; 2.81\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.92 \u0026plusmn; 2.57\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.627\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.109\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDQ-Prosocial (Post)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.72 \u0026plusmn; 2.20\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.19 \u0026plusmn; 2.57\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.98 \u0026plusmn; 2.44\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.529\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDQ-Impact Score (Pre)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.77 \u0026plusmn; 4.43\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.19 \u0026plusmn; 3.27\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.00 \u0026plusmn; 3.90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.598\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.115\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDQ-Impact Score (Post)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.22 \u0026plusmn; 4.24\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.06 \u0026plusmn; 3.32\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.67 \u0026plusmn; 3.83\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.201\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.234\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDQ-Total Score (Pre)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e19.78 \u0026plusmn; 5.56\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21.32 \u0026plusmn; 6.09\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20.61 \u0026plusmn;5.82\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-1.049\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.298\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDQ-Total Score (Post)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e19.28 \u0026plusmn; 6.71\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21.52 \u0026plusmn; 5.54\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n 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\u003cp\u003e\u003cstrong\u003e-2.27\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.04*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParenting Scale - Over reactivity (Pre)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.0 \u0026plusmn; 1.3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.9\u0026plusmn; 1.0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e15.19 \u0026plusmn; 4.12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.451\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.65\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParenting Scale - Over reactivity (Post)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.6 \u0026plusmn; 1.3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.7 \u0026plusmn; 0.9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14.94 \u0026plusmn; 4.60\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.324\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.74\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParenting Scale - Total (Pre)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.77 \u0026plusmn; 0.87\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.96 \u0026plusmn; 0.76\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.86 \u0026plusmn; 0.81\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.91\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.36\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParenting Scale - Total (Post)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.22 \u0026plusmn; 0.86\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.53 \u0026plusmn; 0.63\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.38 \u0026plusmn; 0.76\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-1.6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePSOC - Total (Pre)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e63.44 \u0026plusmn; 6.97\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e65.03 \u0026plusmn; 8.38\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e64.22 \u0026plusmn; 7.63\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e-.822\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;0.4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 318px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;PSOC - Total (Post)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e68.28 \u0026plusmn; 9.67\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e62.80 \u0026plusmn; 8.81\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e65.67 \u0026plusmn; 9.44\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;0.02*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote. M = mean; SD = standard deviation; t = t-value;p = p-value. \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"child-and-adolescent-psychiatry-and-mental-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"caph","sideBox":"Learn more about [Child and Adolescent Psychiatry and Mental Health](http://capmh.biomedcentral.com)","snPcode":"13034","submissionUrl":"https://submission.nature.com/new-submission/13034/3","title":"Child and Adolescent Psychiatry and Mental Health","twitterHandle":"@IACAPAP","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"ADHD, Triple P, parenting intervention, randomized controlled trial, Palestine, parenting self-efficacy, child behavior, feasibility","lastPublishedDoi":"10.21203/rs.3.rs-7250693/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7250693/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose: \u003c/strong\u003eTo evaluate the feasibility and effectiveness of the culturally adapted Triple P intervention in improving parenting competence and reducing behavioral symptoms among children with ADHD in Palestine.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA randomized controlled trial was conducted with 64 Palestinian mothers of children aged 5–13 diagnosed with ADHD. Participants were randomly assigned to either the intervention group (Triple P) or a control group receiving standard care. Pre- and post-intervention assessments were conducted using the Parenting Sense of Competence (PSOC) scale, the Parenting Scale (PS), and the Strengths and Difficulties Questionnaire (SDQ). Feasibility was assessed through retention rates, session adherence, cultural congruence, and participant satisfaction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eFeasibility findings indicated high session attendance, strong participant engagement, and positive reception of the program, including its online adaptation. Post-intervention, the intervention group reported significantly higher parenting competence (PSOC) compared to the control group (\u003cem\u003ep\u003c/em\u003e = .023, \u003cem\u003ed\u003c/em\u003e= 0.59). There was also a significant reduction in lax parenting practices (\u003cem\u003ep\u003c/em\u003e= .04, \u003cem\u003ed\u003c/em\u003e = −0.51) and an increase in children’s prosocial behavior (\u003cem\u003ep\u003c/em\u003e= .014, \u003cem\u003ed\u003c/em\u003e = 0.64). Hyperactivity symptoms showed marginal improvement (\u003cem\u003ep\u003c/em\u003e= .053, \u003cem\u003ed\u003c/em\u003e = 0.48).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThe culturally adapted Triple P intervention was both feasible and effective in enhancing parenting skills and improving child behavior among Palestinian families affected by ADHD. Findings support the integration of Triple P into national mental health services and highlight the importance of culturally responsive, evidence-based interventions in low-resource and conflict-affected settings.\u003c/p\u003e","manuscriptTitle":"Positive Parenting Program for Attention Deficit Hyperactivity Disorder: Maternal Perspective Shifts and Child Behavior Problems Reduction in a Clinical Trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-14 09:56:19","doi":"10.21203/rs.3.rs-7250693/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-13T22:43:51+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-13T12:08:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"244189818001190434514488344333570615693","date":"2025-08-10T13:24:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-08T16:01:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"24221539452693420261776954788380232728","date":"2025-08-07T20:12:08+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-07T16:23:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-06T08:19:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-05T13:43:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Child and Adolescent Psychiatry and Mental Health","date":"2025-07-30T08:40:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"child-and-adolescent-psychiatry-and-mental-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"caph","sideBox":"Learn more about [Child and Adolescent Psychiatry and Mental Health](http://capmh.biomedcentral.com)","snPcode":"13034","submissionUrl":"https://submission.nature.com/new-submission/13034/3","title":"Child and Adolescent Psychiatry and Mental Health","twitterHandle":"@IACAPAP","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b870f870-05ba-445a-9034-2a274590e6b6","owner":[],"postedDate":"August 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-24T16:03:19+00:00","versionOfRecord":{"articleIdentity":"rs-7250693","link":"https://doi.org/10.1186/s13034-025-00960-y","journal":{"identity":"child-and-adolescent-psychiatry-and-mental-health","isVorOnly":false,"title":"Child and Adolescent Psychiatry and Mental Health"},"publishedOn":"2025-11-19 15:58:27","publishedOnDateReadable":"November 19th, 2025"},"versionCreatedAt":"2025-08-14 09:56:19","video":"","vorDoi":"10.1186/s13034-025-00960-y","vorDoiUrl":"https://doi.org/10.1186/s13034-025-00960-y","workflowStages":[]},"version":"v1","identity":"rs-7250693","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7250693","identity":"rs-7250693","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}