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Effectiveness of Specific Techniques in Behavioral Teacher Training for Childhood ADHD Behaviors: Secondary Analyses of a Randomized Controlled Microtrial

Effectiveness of Specific Techniques in Behavioral Teacher Training for Childhood ADHD Behaviors:... Behavioral teacher training is an effective intervention for children with attention-deficit/hyperactivity disorder (ADHD). Intervention effectiveness may be enhanced by including intervention components that carry the strongest evidence for their effectiveness. A previous article of this group showed that both antecedent- (i.e., stimulus-control) and consequent-based (i.e., contingency management) techniques were highly effective in reducing daily teacher-rated, individually selected problem behaviors in a specific situation of the child. Effects were observed up to three months post intervention. Here, we tested whether effects were also present in teacher-rated and masked DSM-based assessments that comprise the full range of ADHD and oppositional defiant disorder (ODD) symptoms, as well as on teacher-rated impairment. Teachers of 90 children with (subthreshold) ADHD (6–12 years) were randomly assigned to one of three conditions: a short (two sessions), individualized intervention consisting of either a) antecedent-based techniques or b) consequent-based techniques; or c) waitlist. Multilevel analyses showed that both sets of techniques were effective in reducing teacher-rated ADHD symptoms and impairment immediately after the intervention and up to three months later, as compared to waitlist. Masked observations of ADHD behavior were in line with teacher ratings, with effects being most pronounced for inattention. No effects on teacher-rated or masked ODD behavior were found. This study showed that antecedent- and consequent-based techniques were effective in improving classroom ADHD symptoms and impairment. Long-term changes in teacher-rated ADHD are promising. These results extend previous findings and show the potential of short individually tailored interventions in classroom settings as treatment of ADHD symptoms. Keywords ADHD · Behavioral teacher training · Antecedent-based techniques · Consequent-based techniques · Microtrial * Anouck I. Staff Introduction a.i.staff@vu.nl 1 Behavioral teacher training is an effective intervention to Department of Clinical, Neuro- and Developmental reduce children’s attention-deficit/hyperactivity disorder Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands (ADHD) symptoms and related behavioral problems in the classroom (DuPaul et al., 2012; Evans et al., 2018; Fabiano Faculty of Psychology and Educational Sciences, KU Leuven, Leuven, Belgium et al., 2009; Veenman et al., 2016; Ward et al., 2020). Effect sizes of current training programs generally range from small Department of Pediatrics, Amsterdam Reproduction & Development, Emma Children’s Hospital, Emma to medium (DuPaul et al., 2012; Ward et al., 2020), thus leav- Neuroscience Group, Amsterdam UMC, University ing room for improvement. Insight into which intervention of Amsterdam, Amsterdam, The Netherlands components are effective and which are not may contribute Department of Child and Adolescent Psychiatry, University to the development and improvement of behavioral teacher Medical Center Groningen, University of Groningen, trainings for ADHD (DuPaul et al., 2020; Schatz et al., 2020). Groningen, The Netherlands However, studies on the effectiveness of separate intervention Department of Clinical Psychology and Experimental components are scarce. Psychopathology, University of Groningen, Groningen, The Netherlands Vol.:(0123456789) 1 3 868 Research on Child and Adolescent Psychopathology (2022) 50:867–880 Behavioral teacher interventions for ADHD generally seatwork’ or ‘talking excessively during whole group include training teachers in the use of both antecedent- teaching’. Following EMA procedures, the four behav- based techniques (i.e., stimulus-control techniques such iors were daily assessed in the specific situation, maxi- as providing structure and clear instructions) and con- mizing the ecological validity and minimizing recall and sequent-based techniques (i.e., contingency management retrospection bias that may be observed using traditional techniques such as praise, reward and planned ignoring) questionnaires based on the Diagnostic and Statistical (DuPaul et  al., 2022). Teachers are typically taught to Manual of Mental Disorders (DSM) (Bentley et al., 2019; combine both sets of techniques, for example by giving a Shiffman et al., 2008). We showed that antecedent- and clear instruction to the child to raise his/her hand before consequent-based techniques were equally effective in speaking and praise the child when doing this (Patterson, reducing these four daily teacher-rated problem behav- 1982). Meta-analytic evidence from behavioral teacher iors in a specific situation. Effects were obtained directly and parent interventions suggests that both anteced- after the intervention (large effects, d = 0.89, 0.93, ent- and consequent-based techniques implemented by respectively),  and remained stable up to three months teachers and parents are effective to improve children’s later. ADHD symptoms and oppositional defiant (ODD) behav- Nevertheless, two important questions remained unan- iors (Gaastra et al., 2016; Leijten et al., 2019). However, swered, i.e., whether the promising findings on our EMA meta-analysis only allows testing whether intervention outcomes are reflected in: 1) broader assessments of effects are larger for interventions that include a particu- ADHD and ODD behaviors, and 2) impairment. Regard- lar intervention component (e.g., training teachers in a set ing the first question, we were interested whether effects of techniques) as compared to interventions that do not were also obtained if outcomes comprised the full range include that particular intervention component (Leijten of DSM-based teacher-rated ADHD and ODD symptoms et al., 2021). Thus each single intervention component is assessed on a rating scale, i.e., whether effects could also always studied in the context of other intervention com- be observed when teachers were asked to report behav- ponents (Lipsey, 2003). Meta-analyses can therefore be iors averaged over the past week and during all situations, used to generate hypotheses about effective intervention rather than during a specific situation during each day. components, but whether effect sizes are actually driven Using traditional DSM-based questionnaires also provides by a particular component remains to be studied (Leijten possibilities to compare results with the findings of other et  al., 2021). In contrast, microtrials are experimental behavioral interventions for ADHD. Further, we were inter- designs that can be used to test hypotheses regarding the ested whether effects were observed by raters who were not effectiveness of single intervention components by testing involved in treatment delivery and thus less susceptible the effects of relatively brief and focused environmental to social desirability and/or investment bias (Daley et al., manipulations, such as single intervention components, 2014; Sonuga-Barke et al., 2013). Regarding our second on proximal outcomes (Howe et al., 2010; Leijten et al., question, as functional impairment is often the primary 2015). Such a design allows to study the effectiveness reason for teachers to seek help (Coles et al., 2012), we of antecedent- and consequent-based techniques in isola- were interested whether effects are also observed in terms tion, which has not been done so far. Therefore, to test of functional impairment. the hypotheses about the effectiveness of antecedent- and The aim of the present study was thus to examine the consequent-based techniques derived from meta-analytic effectiveness of antecedent- and consequent-based tech- studies (Gaastra et  al., 2016; Leijten et  al., 2019), our niques on (1) teacher-rated and masked observations of study used a microtrial design to examine the effective- ADHD and ODD behaviors according to DSM-criteria, and ness of implementing antecedent- and consequent-based (2) teacher-rated functional impairment. Data were collected techniques in reducing the behavioral problems and in our randomized controlled microtrial that tested two short impairment children with ADHD often experience in the and individualized behavioral teacher interventions focusing classroom. on either antecedent- or consequent-based techniques. Based In a previous article of our group (Staff et al., 2021), on our previous findings regarding our EMA outcome, we we analyzed our randomized controlled microtrial using hypothesized that both sets of techniques would be effective an ecologically momentary assessment (EMA) meas- compared to a waitlist control condition in reducing ADHD ure of behavior as outcome measure (Shiffman et  al., and ODD symptoms as rated by teachers, both immediately 2008). Four preselected individual problem behaviors in after the intervention as well as at three months follow-up. a specific situation were assessed, and two of these were We expected smaller effect sizes compared to our EMA directly targeted in the intervention. The behaviors and outcomes (Howe et al., 2010), given that the current meas- situations thus differed per child-teacher dyad. Exam- ures reflect more distal outcomes. Further, we expected ples were ‘difficulties staying focused during individual effects to be most pronounced shortly after the intervention 1 3 Research on Child and Adolescent Psychopathology (2022) 50:867–880 869 compared to three months later (Lee et al., 2012). For our T2. In case the summer holiday started prior to T3, T3 took masked assessments of ADHD and ODD behaviors, struc- place three weeks prior to the end of the school year (but at tured classroom observations were conducted in a (randomly least four weeks after T2). Because there are no guidelines selected) subsample. Classroom observations have shown to for reporting on microtrials, we used the CONSORT guide- be a valid measure to assess ADHD and ODD in the class- lines for reporting on randomized controlled trials (Moher room (Minder et al., 2018) and to be sensitive to effects of et  al., 2001). More details on the design of the study are behavioral interventions (Pelham et al., 2005; Pfiffner et al., available in Staff et al. (2021). This study was registered at 2013). We expected both sets of techniques to be effective the Dutch Trial Register: https:// www. trial regis ter. nl/ trial/ in reducing observed ADHD and ODD behaviors (Pfiffner 6616. et al., 2013). Finally, we expected both sets of techniques to be effective in reducing functional impairment as rated by Participants the teacher (Groenman et al., 2021). The study sample comprised 90 regular primary school aged children (grades 1 to 6), from rural and urban areas Method in The Netherlands, showing ADHD symptoms, and their teachers who were in (self-reported) need of effective Design management techniques for their student(s). Inclusion cri- teria were: (a) high levels of ADHD symptoms (> 90th Teachers were randomized to one of two intervention con- percentile) as rated by teachers on the Inattention and/or ditions (i.e., antecedent- and consequent-based, see below) Hyperactivity-Impulsivity scale of the Disruptive Behavior or a waitlist control condition. A random list of numbers Disorders Rating Scale (DBDRS) (Oosterlaan et al., 2008), 1–90 was created to allocate participants to these condi- (b) at least three symptoms (item score ≥ 2) on the Inattention tions. Randomization occurred at school level to prevent and/or Hyperactivity-Impulsivity scale of the DSM-IV-TR contamination from teachers receiving different interven- based semi-structured Teacher Telephone Interview (TTI) tions. There was a maximum of two included students per (Tannock et al., 2002), and (c) a score > 5 (indicating func- participating teacher. Outcome measures were assessed at tional impairment, range 0—10) on at least one domain of three time points: at baseline prior to randomization (T0), functioning on a modified version of the teacher-rated Impair - during the week immediately after the intervention or the ment Rating Scale (IRS) (Fabiano et al., 2006). Exclusion cri- waiting period (T1), and three weeks after the intervention teria were: (a) an estimated full scale IQ < 70, assessed using or waiting period (T2). Figure 1 provides an overview of a short form of the Dutch version of the Wechsler Intelligence which measures were assessed at each time point. Class- Scale for Children-third edition (WISC-III-NL) including the room observations were conducted in a randomly selected subtests Block Design and Vocabulary (Sattler, 2008), (b) subsample of each condition (n = 20 per condition). Longer pharmacological treatment for ADHD symptoms during the term effects on teacher-rated ADHD and ODD were inves- last month, (c) a diagnosis of autism spectrum disorder or tigated three months after baseline (T3), in the intervention conduct disorder according to the DSM-IV-TR or DSM-5 as conditions only. The total study duration was three months reported by parents on a demographic questionnaire, or (d) (T0-T3) and allowed no holidays between randomization and the teacher being enrolled in a behavioral teacher training T0:baseline T1:directlypost T2:2 weekspost T3:13weeks intervention intervention post intervention b b c •SWAN •SWAN •SWAN •SWAN b b c •DBDRS:ODD •DBDRS:ODD •DBDRS:ODD •DBDRS:ODD •IRS •IRS •Classroom •Classroom a a observations observations Fig. 1 Overview of the outcomes assessed at the different time points. vations were conducted in a subset of the sample (N = 60). For analy- DBDRS Disruptive Behavior Disorders Rating Scale, IRS Impairment ses on short term effects, outcomes were averaged over T1 and T2. Rating Scale, ODD Oppositional Defiant Disorder, SWAN Strengths Longer term effects were assessed in the intervention conditions only and Weaknesses of ADHD and Normal Behavior. Classroom obser- 1 3 870 Research on Child and Adolescent Psychopathology (2022) 50:867–880 aimed at ADHD symptoms or other behavioral problems in antecedent-based intervention teachers were provided with the past year. supplemental psycho-education (step 1) on how stimuli evoke behaviors, how executive functioning deficits in chil- Interventions dren with ADHD may lead to difficulties adapting behavior to stimuli, and how antecedent-based techniques adapt to For the purpose of this microtrial, two short individual- this by changing the discriminative value of stimuli. The ized and manualized interventions consisting of two ses- behavioral analysis (step 3) focused on identifying anteced- sions were developed (see Staff et al. (2021) for a detailed ents that elicited the problem behavior. The intervention plan description). One intervention included only antecedent- (step 5) in this condition consisted of antecedent-based tech- based techniques (referred to as antecedent-based interven- niques only (i.e., setting clear rules, providing clear instruc- tion), the other only included consequent-based techniques tions, discussing challenging situations with the child in (referred to as consequent-based intervention). The inter- advance, and providing structure in time and space). These ventions were based on evidence-based behavioral parent techniques were briefly explained and could be part of the training programs aimed at remediating ADHD symptoms intervention plan. In the consequent-based intervention, and ADHD related behaviors (Barkley, 1987; McMahon & teachers’ psycho-education (step 1) was supplemented with Forehand, 2003; Van Den Hoofdakker et al., 2007). The first specific information on how consequences affect behavior, session took place at the school and lasted two hours, the that children with ADHD may suffer from an altered reward second session was scheduled one week later and took place sensitivity that may influence how their behavior is shaped by video conference, lasting 45 minutes. by the environment, and how consequent-based techniques At the beginning of the study period, teachers selected adapt to this by changing the consequences of behavior (Van four individual problem behaviors per child from a list of der Oord & Tripp, 2020). The behavioral analysis (step 3) 32 ADHD and oppositional behaviors in a specific situ- was targeted at identifying consequences that positively or ation (e.g., difficulties staying focused during individual negatively reinforce the problem as well as desired behav- seatwork) (Staff et al., 2021; Van Den Hoofdakker et al., ior (i.e., functional behavior assessment, FBA; Dunlap & 2007), from which two behaviors were directly targeted Kern, 2018). The following consequent-based techniques in the intervention. The first session of both interventions were explained and integrated in the intervention plan (step consisted of the following steps: (1) providing the teacher 5): praise, reward, planned ignoring, and negative conse- with psycho-education on ADHD; (2) selecting the prob- quences. Shaping was explained and used when the full lem behavior, based on the frequency (preferably daily) and desired target behavior was not displayed yet. Consequent- severity of behavior; (3) making a behavioral analysis of the based techniques such as token economy and time-out were behavior by the teacher and therapist; (4) defining desired not included in this intervention given that these also require target behaviors; (5) teaching teachers how to implement antecedent-based techniques (e.g., clear rules, structuring by either antecedent- or consequent-based techniques (depend- use of individual instructions). ing on the assigned intervention condition) most optimally, When teachers brought up that they could use techniques and making a behavioral intervention plan by the teacher from the other intervention (e.g., reward desired behavior and therapist. For each intervention plan, one or more tech- in the antecedent-based intervention), the therapists were niques of the assigned condition could be chosen to be part instructed to explain that the current intervention focused of the intervention plan, based on the behavioral analy- on the trained techniques and therefore the intervention plan sis; (6) practicing the intervention plan (i.e., techniques) consisted of these techniques only. The teacher was advised through visualization or role play; (7) instructing teachers to implement and/or optimize the trained techniques first to implement the intervention plan in the classroom for and at least until the last week of assessments, to monitor one week, after which the second session took place. The its effectiveness and to decide whether the use of other tech- second session started with evaluating the preceding week niques was needed at a later time. More information on the and adapting the intervention plan, if necessary. Thereafter, interventions and examples of intervention plans for every steps two to six of the first session were repeated. At the end intervention are available in our previous publication (Staff of the second session, teachers were provided with handouts et al., 2021). of the techniques and were instructed to implement both intervention plans directly after the session for at least four Therapists and Intervention Fidelity weeks. Teachers could contact the therapist if required. Differences between the two interventions concerned the Interventions were carried out by two psychologists with focus on either antecedent- or consequent-based techniques. postgraduate training in behavioral therapy and ADHD More specifically, interventions differed in steps 1, 3, and 5 (AS and RH) (see also Staff et  al. (2021)). Therapists (see also Table A in Supplementary Information S1). In the were trained in the program and supervised by licensed 1 3 Research on Child and Adolescent Psychopathology (2022) 50:867–880 871 supervisors in the postgraduate behavior therapy program symptoms. The internal consistency for the SWAN in this with ample experience in behavioral parent and teacher sample was good (α = 0.85) and convergent validity has been training programs (SvdO and BvdH). Supervision started established (Strengths and Difficulties Questionnaire (SDQ) with individual supervision sessions until quality was suf- Hyperactivity scale; r = 0.54) (Lakes et al., 2012). The Dutch ficient. Thereafter, there were group-based meetings every population based mean scores are M = 44.0 (boys)/M = 45.7 two weeks with the therapists and supervisors to monitor (girls), SD = 8.08 for the Inattention scale and M = 43.9 intervention fidelity (see below) and to provide supervision (boys)/M = 45.6 (girls), SD = 8.63 for the Hyperactivity/ until the end of the study period. At the beginning of the Impulsivity scale (scale 1 = far below average, 7 = far above study period, supervisors checked audiotaped sessions to average) (Polderman et al., 2007). assess the quality of the session(s) of each condition until optimal quality was reached (maximum scores), as well ODD‑symptoms Teacher ratings of symptoms of ODD were as to assess intervention fidelity (see below). Quality was measured with the ODD-scale of the DBDRS (Oosterlaan rated based on knowledge, structure, and therapeutic process et al., 2008). Teachers rated a child’s behavior over the past (e.g., providing clear instructions, adequately dealing with week on eight items, using a 4-point Likert scale ranging resistance), rated on a 3-point Likert scale (1 = needs work, from 0 (‘not at all’) to 3 (‘very much’). Scores may range 2 = acceptable, 3 = good work). Both therapists reached opti- between 0 and 24, with higher scores indicating more ODD mal quality scores for each condition after the first sessions. symptoms. The internal consistency for the teacher-rated Treatment fidelity was assessed by scoring contamination ODD-scale of the Dutch version of the DBDRS is high and by scoring the percentage of addressed session items (α = 0.95; α = 0.92 in this sample), and convergent valid- in each session. The procedure of Abikoff et al. (2013) was ity is strong (IOWA Conners’ Inattention/Overactivity used to score contamination. Contamination was defined as scale; r = 0.70, SDQ Hyperactivity scale; r = 0.79—0.83) a) the therapist recommending the use of non-assigned tech- (Oosterlaan et al., 2008). niques, b) therapists’ questions or remarks that could elicit teacher’s thoughts or comments on techniques belonging to Impairment An overall measure of functional impairment the non-assigned intervention, or c) the therapist actively of the child at school was assessed using an adjusted version supporting and elaborating on the teacher’s suggestion to of the teacher-rated Impairment Rating Scale (Fabiano et al., use of techniques specific to the non-assigned intervention. 2006). Teachers rated impairment over the past week on the The contamination score was based on the frequency of following four areas of functioning: peer, teacher, academ- contamination occurrences in a session. After optimal qual- ics, and classroom. An example of a question is: ‘How this ity scores were reached, a random sample of ten percent of child’s problems affect his or her relationship with other the sessions were listened back and scored on intervention children?’. Impairment was rated on a 10-point scale, rang- fidelity by independent evaluators during the entire study ing from 0 (‘no impairment’) to 10 (‘excessive impairment’), (all intervention sessions were audiotaped). In addition to in line with the Dutch system for academic grading. A score scoring the selected audiotapes, the percentage of addressed above 5 indicated functional impairment on that particular session items was also scored using session-forms that were area of functioning. Outcome was the average score on the completed by therapists after each session. four items (ranging from 0 to 10). Outcome Measures Classroom Observations of ADHD and ODD Behaviors Teacher Rating Scales Classroom observations were conducted in a randomly selected subset of the sample, given the time required for coding (i.e., 570 hours of coding for the subsample analyzed ADHD Symptoms Teacher ratings of symptoms of inatten- here). For twenty randomly selected children from every tion and hyperactivity-impulsivity were assessed using the condition (67%), classroom observations were coded. The scales Inattention (nine items) and Hyperactivity-Impulsivity total subsample did not differ from the full sample on base- (nine items) of the DSM-based Strengths and Weaknesses line characteristics nor in their response to the two interven- of ADHD-symptoms and Normal Behavior (SWAN) rating tions studied here as assessed in terms of the proximal out- scale (Swanson et al., 2012). Teachers rated a child’s behav- come (results available from the first author). Observations ior over the past week compared to peers on a 7-point Likert were conducted when children attended morning lessons in scale (-3 = far below average to + 3 = far above average). their own classroom led by their primary teacher, and were Scores were reverse scored for consistency with other meas- on similar time and day at both time points (e.g., Tuesday ures used in this study. Scores may range between -27 and 27 morning at the beginning of the school day) for approximately for both scales, with higher scores indicating more ADHD 90 minutes per child. The first 60 minutes that contained 1 3 872 Research on Child and Adolescent Psychopathology (2022) 50:867–880 actual lessons were used for coding (e.g., the observation frequency of oppositional behavior served as outcome (Staff started when children were arriving at the beginning of the et al., 2020). day, coding started when the teacher started the first les - Observations were coded by fourteen graduate psychology son) (coding duration M = 57.30 min, SD = 9.29 min for T0; students (i.e., observers), who were individually trained by M = 56.13 min, SD = 5.27 min for T2). the first author in at least two sessions of two hours. Observ - A Dutch adapted version of the Ghent University Class- ers coded a maximum of two scales, in order to increase accu- room Coding Inventory (GUCCI; Staff et al., 2020) was racy and inter-observer reliability (i.e., four observers coded used to code behavior, according to four scales: Attention Attention Problems, five others coded Motor Hyperactivity, Problems (i.e., visual attention to task), Motor Hyperac- and five others coded Verbal Hyperactivity and Oppositional tivity (i.e., motor movements), Verbal Hyperactivity (i.e., Behavior). Observers were masked to treatment condition of talking or other vocalizations), and Oppositional Behavior the child as well as to whether an observation was conducted (i.e., arguing, anger). Each scale comprised a categorical at pre- (T0) or post-intervention (T2). During the training variable of behavior to be coded as absent or present, catego- they were introduced to the behavioral categories of the ries within each scale were mutually exclusive (e.g., Motor scale(s) and the coding system. Observers practiced coding Hyperactivity consisted of the levels no motor hyperactivity until inter-observer agreement with the trainer reached ≥ 0.80 and motor hyperactivity, see Table 1). Scales were coded (see for detailed information: Staff et al. (2020)). Given that using continuous sampling, indicating that all behaviors we used continuous coding, rather than time sampling, inter- were coded throughout the coding period. For the Attention observer agreement was based on the percentage of time Problems scale, the percentage of time off-task was calcu- behaviors were scored in the same category by both raters lated by dividing the total time off-task by the total time and ranged between 82.9% and 99.8%. Additionally, intra- coded in which the child was expected to be involved in class coefficients (ICC, based on a one-way random model, class activities (sum of the time of on- and off-task). When Hallgren (2012)) for each scale were calculated to have an no involvement in class activities was expected, the interval estimation of inter-rater reliability corrected for measure- was coded as no-task. For the behavioral categories Motor ment error. Inter-rater agreement was excellent (ICC ≥ 0.86) Hyperactivity and Verbal Hyperactivity, percentage of total for this sample. Convergent validity of the GUCCI was ade- time the behaviors motor hyperactivity and verbal hyperac- quate (r = -0.04—0.29), although relatively low correlations tivity occurred was calculated. For Oppositional Behavior, between rating scale scores and observational scores indicate that both instruments measure different aspects of ADHD Table 1 Operational definitions of observed behaviors using the GUCCI Scale Coding category Description Outcome variable in statistical analysis Attention Problems On-task The child is involved in activities that are expected by the teacher (e.g., paying visual attention to task or to the teacher), and is following the teacher’s instructions and requests Off-task The child is involved in activities that are not expected by the teacher for % of time at least two seconds (e.g., not working on assignments, daydreaming) Motor Hyperactivity No motor hyperactivity The child has no difficulty sitting down. Little movements of arms, hands, feet, or legs are accepted and no gross movements that are observably annoying or disturbing peers are shown Motor hyperactivity The child is not sitting still on his/her chair (e.g., overturns or swings % of time his/her chair, squirms in chair). The child shows small movements that are annoying or disturbing for peers (e.g., tapping with a pen). The child is not sitting on the chair (e.g., standing up without permission, sitting on their knees) or is walking or running through the classroom Verbal Hyperactivity No verbal hyperactivity The child is quiet, or the child talks in reaction to the teacher’s request Verbal hyperactivity The child is talking or making vocal sounds (e.g., whispering to self, % of time humming) Oppositional behavior No oppositional The child does not show any oppositional behavior, anger, aggression, or behavior antisocial behavior against others Oppositional behavior The child shows oppositional behavior against the teacher (e.g., refuses Frequency something). The child shows angry behavior (e.g., shows tantrum) GUCCI Ghent University Classroom Coding Inventory 1 3 Research on Child and Adolescent Psychopathology (2022) 50:867–880 873 and ODD behavior (see for a detailed evaluation: Staff et al. within children (level 2), nested in classrooms (level 3), and (2020)). nested in schools (level 4). Random intercepts at classroom and school level were only included if significantly improv - Procedure ing model fit as determined by Likelihood Ratio Test. We inserted condition (waitlist, antecedent, consequent) as This study was carried out between April 2017 and April between subjects’ factor, and time (T1, T2) as within vari- 2019. Teachers were recruited through school principals, able. Baseline scores (T0) of the outcome were inserted as school collaboration networks, and an outpatient mental fixed factor, in order to control for problems at baseline. health clinic. Teachers showing interest in participation We investigated short-term effects of condition (averaged in the study received an information letter explaining the over T1 and T2) to compare the intervention conditions to research aims and responsibilities of all parties involved. the waitlist condition, and to compare the two intervention Teachers who agreed in participating enlisted one to two conditions to each other. Because effects were similar for T1 children showing profound and impairing ADHD symptoms and T2 on the proximal outcome (see Staff et al., 2021), we in the classroom, and informed parents about the study (i.e., used an aggregated outcome measure for the current study. provided them with the information letter and informed Longer term effects were assessed by examining whether consent). Written consent was obtained from teachers, par- problem behaviors remained stable from T2 to T3 within ents, and children older than 11 years. After receiving con- each intervention condition (i.e., whether the development sent, teachers administered the ADHD scales of the DBDRS of problem behaviors from T2 to T3 changed significantly). and TTI to screen for eligibility. If inclusion criteria were Two measures of hyperactivity were included in the class- met, baseline assessments (T0) took place through teacher room observations (i.e., motor and verbal), therefore alpha rating scales and classroom observations, all conducted in level was set at 0.05/2 for these outcomes. Given the lower the same week. For the classroom observations, observers number of participants for the observational measure in each were introduced as interns. Teachers explained to children separate condition, we explored whether weaker short-term that the interns had to observe how children are working effects on the classroom observations may have remained during lessons in different classes for study purposes. To undetected using sensitivity analyses. Therefore, we com- prevent target children being aware of being subject of the bined the antecedent and consequent condition into one observations, cameras were positioned in a corner at the “active” intervention condition (n = 40) and compared this front of the classroom, targeted at the whole classroom (but to the waitlist condition. Effect sizes (Cohen’s d ) were cal- zoomed in at a particular child). Randomization occurred culated by dividing the difference in mean scores between after baseline assessments were completed. Teachers of two conditions averaged over T1 and T2 by the pooled SD children in the waitlist condition were allowed to receive (Rosnow & Rosenthal, 1996), with 0.20, 0.50, and 0.80 as care as usual during the study period, and were offered the thresholds for small, medium, and large effects, respectively. possibility to use a self-directed behavioral teacher program To examine intervention fidelity (Abikoff et al., 2013), we targeting ADHD symptoms immediately after T2 (PR Pro- compared the intervention conditions on the contamination gram, Veenman et al., 2016). Longer term effects at T3 were scores and the average percentage of addressed session items therefore only explored in children of teachers in the active (as rated by therapists and independent coders) by using intervention arms and were only assessed by teacher ratings. independent t-tests. We also asked teachers in the anteced- The local medical ethical committee waived the need for ent and consequent condition to rate whether they would medical ethical approval (University Medical Center Gro- recommend the intervention to colleagues (yes, no, neutral) ningen, 2016/198). at T3 as an indication of the feasibility of the interventions. Statistical Analysis Results Analysis of variance (ANOVA), and chi-squared or Fisher’s exact tests were used to compare groups on the demographic Thirty children (from 25 teachers of 17 schools) were allo- variables assessed at baseline. cated to the antecedent condition, 30 children (from 26 Data were analyzed on an intention-to-treat basis. To teachers of 18 schools) to the consequent condition, and compare the intervention conditions to the waitlist condi- 30 children (from 26 teachers of 17 schools) to the waitlist tion and to each other, multilevel analyses (mixed model) condition. Table 2 displays demographic characteristics of were conducted in Stata (version 16). Missing data was ran- the sample. Children randomized to the three conditions did dom (≤ 5%) for all outcomes, and was taken into account not differ on any of the screening characteristics (p > 0.132), in multilevel analysis (Twisk et al., 2013). Four hierarchi- with the exception of hyperactivity-impulsivity symptoms on cal levels were distinguished: observations (level 1), nested the TTI and DBDRS on which lower ratings were obtained 1 3 874 Research on Child and Adolescent Psychopathology (2022) 50:867–880 Table 2 Sample description and baseline comparisons AC (n = 30) CC (n = 30) WC (n = 30) Group comparisons Age at assessment in years 8.53 (1.63) 9.08 (1.63) 8.76 (1.52) F(2, 89) = 0.88, p = 0.420 Sex, n (%) boys 23 (77) 23 (77) 28 (93) χ = 3.81, p = 0.150 IQ 99.77 (11.04) 99.33 (14.28) 104.07 (10.05) F(2, 89) = 1.45, p = 0.241 SES 5.22 (1.24) 5.24 (1.12) 5.00 (1.03) F(2, 88) = 0.41, p = 0.664 Caucasian, n (%) 28 (93) 27 (90) 30 (100) Fisher’s exact = 0.294, p = 0.363 ADHD diagnosis, n (%) 8 (27) 8 (27) 7 (23) χ = 0.12, p = 0.943 Other psychiatric diagnosis, n (%) 0 (0) 3 (10) 0 (0) Fisher’s exact = 4.22, p = 0.104 TTI symptom severity    Inattention 4.30 (1.58) 5.00 (1.86) 4.13 (1.91) F(2, 89) = 1.99, p = 0.143    Hyperactivity-Impulsivity 2.97 (1.85) 4.83 (2.38) 4.60 (2.22) F(2, 89) = 6.65, p = 0.002 (CC, WC > AC)    ODD 1.10 (1.45) 1.07 (1.46) 1.23 (1.61) F(2, 89) = 0.10, p = 0.903    CD 0.00 (0.00) 0.00 (0.00) 0.13 (0.51) F(2, 89) = 2.07, p = 0.132 DBDRS    Inattention 16.90 (4.96) 17.50 (3.92) 16.00 (5.57) F(2, 89) = 0.72, p = 0.488    Hyperactivity-Impulsivity 13.17 (6.21) 15.73 (6.49) 17.57 (6.60) F(2, 89) = 3.54, p = 0.033 (WC > AC) IRS impairment    Number of domains 3.07 (0.98) 2.97 (1.27) 3.24 (0.88) F(2, 84) = 0.45, p = 0.638    Average score 6.22 (1.65) 6.14 (1.97) 6.29 (1.28) F(2, 84) = 0.52, p = 0.948 Teacher ratings SWAN    Inattention 15.03 (4.41) 14.17 (5.11) 15.07 (5.07) F(2, 89) = 0.33, p = 0.721    Hyperactivity-Impulsivity 13.57 (6.77) 13.77 (6.35) 16.83 (6.26) F(2, 89) = 2.41, p = 0.096 DBDRS    ODD 8.00 (6.45) 5.00 (5.09) 8.97 (5.32) F(2, 89) = 4.02, p = 0.021 (AC, WC > CC) Parent ratings SWAN    Inattention 5.31 (8.58) 9.21 (7.54) 5.86 (5.53) F(2, 83) = 2.37, p = 0.100    Hyperactivity-Impulsivity 6.08 (8.24) 9.41 (6.20) 9.83 (6.61) F(2, 83) = 2.31, p = 0.106 DBDRS    ODD 5.90 (4.94) 5.28 (3.43) 6.17 (4.40) F(2, 88) = 0.33, p = 0.719 Classroom observations Inattention % 27.23 (15.96) 28.97 (10.88) 30.56 (16.66) F(2, 59) = 0.26, p = 0.774 Motor hyperactivity % 30.37 (19.63) 40.35 (20.47) 32.60 (15.67) F(2, 59) = 1.57, p = 0.217 Verbal hyperactivity % 5.73 (4.87) 9.08 (7.83) 10.69 (6.75) F(2, 59) = 2.94, p = 0.061 Oppositional behavior K 0.30 (1.13) 0.45 (1.00) 1.65 (3.08) F(2, 59) = 2.79, p = 0.070 M and SD are depicted unless otherwise stated AC antecedent condition, ADHD attention-deficit/hyperactivity disorder, CC consequent condition, CD conduct disorder, DBDRS Disruptive Behavior Disorder Rating Scale, IRS Impairment Rating Scale, K  count,  ODD oppositional defiant disorder, SES socioeconomic status, SWAN Strengths and Weaknesses of ADHD and Normal Behavior, TTI Teacher Telephone Interview, WC waitlist control condition SES was measured by parental educational level (average of both parents) through the Dutch classification system (1 = no education completed, 2 = early childhood education, 3 = primary education, 4 = lower secondary education, 5 = upper secondary education, 6 = undergraduate school, 7 = graduate school, 8 = post-graduate education) (CBS, 2016) Five children started directly after the summer holiday, but were screened before the summer holiday. As teachers were not able to rate impair- ment in the first week of school, for these children functional impairment ratings were missing Missing parent ratings: 1 parent (CC) did not fill in any questionnaire, and 5 other parents (4 AC, 1 CC) did not fill in the SWAN For analyses on classroom observations a subsample (n = 60) of children was used, see Supplementary Information S2 (Table B) for a descrip- tion of this subsample 1 3 Research on Child and Adolescent Psychopathology (2022) 50:867–880 875 for children in the antecedent condition than for children in Hence these levels were removed from the models that now the consequent condition (TTI) and waitlist condition (TTI included two levels (observations clustered in students). Only and DBDRS). Parents reported that 23 children (26%, evenly for the Verbal Hyperactivity scale of the GUCCI the level distributed over conditions, see Table 2) had been clinically classroom improved model fit and was thus included in diagnosed with ADHD and none had been diagnosed with the model. Two teachers discontinued participation after ODD. Based on the TTI, 42 children (47%) met the criteria T0 (change of job and illness, n = 1 for the antecedent and for DSM-V ADHD (i.e., at least six out of nine symptoms in waitlist condition), and two other teachers (n = 1 for the con- at least one domain) and 10 children (11%) met the criteria sequent and waitlist condition) discontinued after T2 due to for DSM-V ODD within the school setting. personal problems. Characteristics of the subset of the sample for which the classroom observations were coded is described in Supple- Teacher‑rated ADHD Symptoms mentary Information S2 (Table B). Results showed that for the teacher-rated inattention scale Effects of Techniques (effects averaged over T1 and T2 while controlling for T0, see Table 3) there was a medium sized, significant reduc- Intervention effects on all short-term outcomes are depicted tion of symptoms for the antecedent condition as compared in Table 3 (means and standard deviations at all four time to the waitlist condition, and a non-significant (although points on all outcomes are reported in Supplementary trend), small to medium effect for the consequent condition Information S3, Table C, and Figures of the development of compared to the waitlist condition. Regarding teacher-rated behavior over time for all outcomes are reported in Supple- hyperactivity-impulsivity symptoms, both intervention con- mentary Information S4, Fig. A). For all outcomes, the lev- ditions showed a significant decrease in symptoms as com- els ‘school’ and ‘classroom’ did not affect intercept variance. pared to the waitlist condition, with medium to large effects. Table 3 Short term effects of the antecedent- and consequent-based techniques on all outcomes AC vs WC CC vs WC AC vs CC Teacher ratings B (SE) p d (95% CI) B (SE) p d (95% CI) B (SE) p d (95% CI) Inattention -3.41 (1.13) 0.003 0.57 (0.30–0.84) -2.04 (1.13) 0.071 0.34 (0.08–0.60) -1.37 (1.12) 0.223 0.23 (-0.03–0.49) symptoms (SWAN) Hyperactivity- -4.70 (1.19) <0.001 0.69 0(0.42–0.96) -3.05 (1.19) 0.010 0.45 (0.19–0.72) -1.65 (1.16) 0.155 0.24 (-0.02–0.50) impulsivity symptoms (SWAN) ODD-symptoms -1.26 (0.97) 0.194 0.23 (-0.03–0.49) -0.39 (1.01) 0.699 0.07 (-0.19–0.33) -0.87 (0.99) 0.378 0.16 (-0.10–0.42) (DBDRS) Impairment (IRS) -1.08 (0.48) 0.023 0.62 (0.35–0.89) -1.11 (0.48) 0.021 0.63 (0.36–0.90) 0.03 (0.44) 0.954 0.01 (-0.25–0.27) average score Classroom observations Inattention (%) -8.82 (4.33) 0.042 0.55 (0.28–0.82) -10.48 (4.26) 0.014 0.65 (0.38–0.92) 1.66 (4.38) 0.704 0.10 (-0.16–0.36) Motor hyperactivity -6.06 (4.90) 0.216 0.34 (0.08–0.60) -7.99 (4.91) 0.103 0.45 (0.19–0.72) 1.94 (5.03) 0.700 0.11 (-0.15–0.37) (%) Verbal hyperactivity 3.10 (2.48) 0.212 0.42 (0.16–0.69) -3.49 (2.45) 0.154 0.47 (0.20–0.74) 6.59 (2.53) 0.009 0.88 (0.61–1.15) (%) Oppositional -0.90 (0.54) 0.097 0.43 (0.17–0.70) -0.58 (0.54) 0.278 0.28 (0.02–0.54) -0.32 (0.52) 0.544 0.15 (-0.11–0.41) behavior (K) The fixed effect of group represent group differences averaged over T1 and T2 while controlling for baseline scores (T0) The control condition or the consequent condition was used as reference group AC antecedent condition, ADHD attention-deficit/hyperactivity disorder, CC consequent condition, DBDRS Disruptive Behavior Disorder Rating Scale, ODD oppositional defiant disorder, IRS Impairment Rating Scale, K count, SWAN Strengths and Weaknesses of ADHD and Normal behavior rat- ing scale, WC waitlist-control condition Classroom observations were conducted in a subsample of children (n = 60), at T0 and T2. For descriptions of this sample see Supplementary Information S2 (Table B) Level child was included in the model Levels child and class were included in the model 1 3 876 Research on Child and Adolescent Psychopathology (2022) 50:867–880 Both intervention conditions did not significantly differ from Observed ODD Symptoms each other on the two symptom domains. Analyses of longer-term changes as assessed with teacher No significant reductions in ODD symptoms in the inter - ratings revealed that inattention symptoms remained low vention conditions compared to the waitlist condition were (even decreased) from T2 to T3 in both intervention condi- obtained with the masked classroom observations, see tions (for antecedent: B = -4.19, SE = 0.90, p < 0.001; for Table 3. consequent: B = -2.21, SE = 0.88, p = 0.012). Approximately similar effects were found for hyperactivity-impulsivity Impairment symptoms (for antecedent: B = -2.57, SE = 0.99, p = 0.001; for consequent: B = -2.38, SE = 0.97, p = 0.015). Significant and similar reductions of teacher-rated func- tional impairment were found in both intervention condi- Observed ADHD Symptoms tions as compared to the waitlist condition from T0 to T2, see Table 3, with medium effect sizes. Masked assessments of ADHD behavior using classroom observations revealed that there was a decrease in inatten- Sensitivity Analyses for Classroom Observations tion in children in both the antecedent- and consequent condition as compared to children in the waitlist condition Results showed a medium sized decrease in attention prob- from T0 to T2 with medium to large short-term effects, lems from T0 to T2 in the “active” intervention group see Table 3. Post-hoc analyses showed that this is likely as compared to the waitlist group (B = -9.68, SE = 3.70, to be explained by a trend significant increase in inatten - p = 0.009, d = 0.60). There was also a small to medium sized tion in the waitlist condition over time (B = 5.77, SE = 3.36, decrease (trend significant) in motor hyperactivity obtained p = 0.086), while the decrease in attention problems within between the “active” intervention condition compared to the antecedent- and consequent conditions was non- the waitlist group (B = -7.02, SE = 4.22, p = 0.096, d = 0.40). significant (B = -1.41, SE = 3.49, p = 0.687; B = -3.91, No significant differences in verbal hyperactivity and oppo- SE = 3.42, p = 0.254, respectively). For motor hyperactiv- sitional behavior were observed between the “active” ity and verbal hyperactivity, no significant reductions were intervention and waitlist condition (B = -0.29, SE = 2.23, observed when comparing the intervention conditions to p = 0.897, d = 0.04; B = -0.74, SE = 0.48, p = 0.120, d = 0.35, the waitlist condition. There were no significant differences respectively). between the antecedent and consequent condition in the effectivity of the two interventions on observed attention Intervention Fidelity and Feasibility problems and motor hyperactivity. For verbal hyperactivity, however, results showed that verbal hyperactivity increased Contamination occurred once in one session of the conse- over time in the antecedent condition as compared to the quent condition and did not occur in any of the sessions of consequent condition with a medium to large effect. Post- the antecedent condition. Contamination scores did not dif- hoc analyses within each condition revealed that there fer between the two interventions: t(3.00) = -1.00, p = 0.391. was a significant increase in verbal hyperactivity in the The average percentage of addressed session items was high antecedent condition from T0 to T2 (B = 5.24, SE = 2.05, in the antecedent and consequent condition according to p = 0.010), while verbal hyperactivity remained stable from both therapists’ self-report (98.9% and 99.4% respectively) T0 to T2 in the consequent condition (B = -2.91, SE = 2.02, and recorded sessions (98.0% and 97.8% respectively). Most p = 0.149). teachers would recommend the training to colleagues (ante- cedent: n = 21 [88%]; consequent; n = 17 [77%]), with no dif- Teacher‑rated ODD Symptoms ferences between the two conditions (χ = 0.84, p = 0.361). Analyses of short-term effects showed that there were no significant reductions in teacher-rated ODD  symptoms Discussion (DBDRS) in the intervention conditions compared to the waitlist condition, and when comparing both intervention Using a microtrial design, this study was aimed to gain conditions to each other, see Table 3. insight into whether previously found effects of anteced- Analyses of longer-term effects (T2 to T3) of teacher- ent- and consequent-based techniques in teacher training for rated ODD symptoms showed that there were no significant children with ADHD on EMA outcomes (Staff et al., 2021), changes in ODD symptoms in any of the intervention con- were also reflected in broader assessments. More specifically, ditions (for antecedent: B = -0.46, SE = 0.67, p = 0.492; for we examined the effectiveness of both sets of techniques on consequent: B = -0.96, SE = 0.67, p = 0.153). teacher ratings that comprise the full range of DSM-criteria 1 3 Research on Child and Adolescent Psychopathology (2022) 50:867–880 877 for ADHD and ODD behaviors, masked classroom observa- antecedent-based intervention was somewhat more effec- tions of ADHD and ODD behaviors, as well as teacher-rated tive than the consequent-based intervention in reducing functional impairment. teacher-rated inattention symptoms (i.e., medium-sized Effects on DSM-based teacher-rated ADHD were mostly effect for antecedent-based intervention versus a small to in line with our previously reported findings (Staff et al., medium-sized effect for consequent-based intervention). 2021), and with the broader literature on teacher trainings A similar study of our group into the effectiveness of both for ADHD (DuPaul et al., 2012; Evans et al., 2018; Fabiano types of intervention components in behavioral parent et al., 2009; Ward et al., 2020). The previous article showed training for ADHD also found this pattern (Hornstra et al., that both interventions were ee ff ctive in reducing four daily- 2021). As argued by Hornstra and colleagues, it may be rated, individually selected, problem behaviors of the child that antecedent-based techniques potentially require less in specific situations, of which two were directly targeted time and effort of teachers to implement during the train- in the intervention. The current article extends these find- ing as compared to consequent-based techniques, because ings by showing that intervention effects were also present antecedent-based techniques focus on the prevention of in reductions ADHD symptoms according to DSM-criteria problem behavior and can be implemented regardless of as rated by teachers averaged over the past week and all child behavior. In addition, before consequent-based tech- situations, and in reductions of teacher-rated impairment. niques can be effective, children may have to be repeatedly Teacher-rated ADHD symptoms in the antecedent and con- exposed to alternated contingencies in order to adapt their sequent conditions even improved up to levels close to the behavior, while antecedent-based techniques may have population based mean (Polderman et al., 2007), while chil- direct effects (Owen et al., 2012). dren in the waitlist condition continued to score one stand- Our findings were in line with studies showing that ard deviation above the population mean. As effects were teacher training has longer term effects over three months obtained on multiple measures (more and less susceptible to (DuPaul et al., 2012; Evans et al., 2018; Fabiano et al., 2009; bias) and outcomes, this strongly confirms the effectiveness Ward et al., 2020). Contrary to our expectations, there were of the interventions. even indications for the three months follow-up that teacher- No significant differences were observed in the effect rated ADHD symptoms further improved, regardless of the sizes of both interventions compared to the waitlist condi- techniques used, while such effects were not observed for tion. This is in contrast to meta-analytic results showing that our proximal outcome (i.e., these effects remained stable effect sizes of teacher programs that include consequent- from post-intervention to follow-up; Staff et al. (2021)), and based interventions are somewhat larger than programs behavior often deteriorates after treatment is withdrawn (Lee that include antecedent-based interventions (Gaastra et al., et al., 2012). However, we did not include the waitlist condi- 2016). However, as these meta-analytic findings only pre- tion at T3 as teachers in this condition were offered treat- sent evidence in the context of other intervention compo- ment after T2, so our results need to be confirmed in future nents (Lipsey, 2003), our findings support the importance studies. of testing hypotheses using experimental (microtrial) Further, our findings on masked observations of inatten- designs in order to draw more firm conclusions tion were consistent with effects obtained with teacher rat- on the effectiveness of intervention components (Leijten ings, suggesting that effects on inattention were not affected et al., 2021). Another explanation for the finding that our by possible social desirability and/or investment bias (Daley antecedent- and consequent-based interventions were both et al., 2014; Sonuga-Barke et al., 2013). Compared to the effective compared to waitlist condition with similar effect waitlist condition, observed attention problems decreased sizes, may be that antecedent-based interventions included in the active conditions, confirming the positive (and pro - in the meta-analysis by Gaastra et al. (2016) were mostly tective) effects of the interventions. Intervention effects on general educational accommodations (e.g., extended time) masked hyperactivity-impulsivity were in the same direction of which the evidence base is limited (Lovett & Nelson, as teacher ratings although effects did not reach statistical 2020). Furthermore, most of these antecedent-based inter- significance. This is likely to be explained by the limited ventions were not tailored to individual needs of the child, number of subjects included in our masked analyses, reduc- while included consequent-based interventions were. In ing power. Observed verbal hyperactivity, however, did not the current study, both interventions were tailored to indi- show such a pattern, and even increased in the antecedent vidual needs (using the behavioral analysis), which may condition over time. Although we cannot fully explain this have increased the relative effectiveness of antecedent- finding, this may be related to the low baseline levels of based interventions as compared to consequent-based this behavior in the antecedent condition (5.7%, see Table 2) interventions (Dunlap & Kern, 2018; Harrison et  al., compared to the other conditions, while at T2, group differ - 2019). When comparing the intervention conditions to ences in verbal hyperactivity between conditions were small. the waitlist condition, there were even indications that the Further research in larger samples is needed to conclude on 1 3 878 Research on Child and Adolescent Psychopathology (2022) 50:867–880 the effectiveness of the sets of techniques on masked out- our previously obtained results on a proximal EMA outcome comes of hyperactivity. (Staff et al., 2021). In contrast to ODD behaviors as measured with the daily Importantly, the effect sizes of these brief and individual- EMA ratings (Staff et al., 2021) and meta-analytic results ized interventions on our secondary outcomes appear similar showing effects of behavioral interventions on ODD symp- to those of full and longer interventions often containing toms (Daley et al., 2014; Leijten et al., 2019), we did not both sets of techniques (DuPaul et al., 2012; Evans et al., observe effects of the specific techniques on teacher-rated 2018; Fabiano et al., 2009; Ward et al., 2020). As described ODD symptoms, neither on the short term, nor on the longer previously (Staff et  al., 2021), the current interventions term, nor on classroom observations of oppositional defi- were short and individualized and were based on functional ant behaviors. This may be explained by the current sample behavioral analysis of the child’s problem behavior (FBA; in which children had low levels of baseline ODD symp- Dunlap & Kern, 2018), which may have added to their effec- toms, possibly indicating that there was not enough room tiveness (Chronis et al., 2004). Furthermore, the brief inter- for improvement on ODD behavior. However, given that we ventions seem acceptable and feasible for school based prac- obtained large effects on the daily ratings of oppositional tice as all teachers completed the intervention, the majority behavior assessed with the proximal EMA measure, one may of the teachers reported to use the techniques learned at also argue that a proximal measure such as daily ratings three months follow-up (Staff et al., 2021), and most of the using EMA may be more sensitive to observe effects com- teachers would recommend the training to colleagues. Such pared to measures assessing broadly defined ODD behavior. short individualized interventions well meet teachers’ needs Although the results of our study are promising, there (DuPaul et al., 2019; Egan et al., 2019; Gaastra et al., 2020), are limitations to note. First, this study was powered on our and t fi s with current ADHD guidelines suggesting that envi - primary outcome and therefore power for the secondary out- ronmental modifications are regarded as first-line interven- comes reported here may have been too low (Jakobsen et al., tions prior to more intensified treatment (Akwa GGZ, 2019; 2019), possibly leading to small effects being undetected. National Institute for Health and Care Excellence, 2018). This seems particularly relevant for antecedent versus conse- To increase suitability for schools, both sets of techniques quent comparisons as these are both active conditions. Sec- could be combined into one intervention. For example, a ond, classroom observations were conducted only in a sub- brief and individualized intervention combing the effective set of the sample, given the time-intensive nature of coding sets of techniques can be provided to teachers seeking help of the observations, and may have led to undetected small to cope with the disruptive behavior of an individual student effects. However, the effects obtained for attention problems showing ADHD symptoms (e.g., Tier 2 interventions). were robust and provide important corroborative information Supplementary Information The online version contains supplemen- next to our proximal daily ratings and questionnaire ratings tary material available at https://doi. or g/10. 1007/ s10802- 021- 00892-z . for the effectiveness of both sets of techniques. A third limi- tation is that we have not quantified teacher implementation Acknowledgements We thank all children, parents, and teachers of the techniques in the classroom (neither quality or dose), for participating in this study, and students for their support in data and such it cannot be used as a moderator in the analyses. collection. Fourth, our sample predominantly included children with Funding This work was supported by The Netherlands Organiza- subthreshold ADHD symptoms and low levels of ODD tion for Health Research and Development (ZonMw), grant number symptoms. Although our results provide useful information for children with (subthreshold) ADHD, effects may not be generalizable to children with more severe ADHD and/or Data Availability The data that support the findings of this study are ODD symptoms. Further, our sample was nearly 100% Cau- available from the corresponding author (AS), upon reasonable request. casian and we lack insight into other relevant child (e.g., parental income) and teacher (e.g., race) factors, which may Compliance with Ethical Standards  limit the representativeness or our sample. Ethical Approval The local medical ethical committee waived the need for medical ethical approval (University Medical Center Groningen, Conclusions and Clinical Implications 2016/198). Informed Consent Teachers, parents, and children older than 11 years This randomized controlled microtrial showed that provided written consent. antecedent- and consequent-based techniques are effec- tive in reducing children’s ADHD symptoms in the class- Conflict of Interest The authors report no conflict of interest. room, as assessed by teacher-rated DSM-based measures of ADHD symptoms and functional impairment, as well as masked observations of inattention. These findings extend 1 3 Research on Child and Adolescent Psychopathology (2022) 50:867–880 879 Open Access This article is licensed under a Creative Commons Attri- Egan, T. E., Wymbs, F. A., Owens, J. S., Evans, S. W., Hustus, C., & bution 4.0 International License, which permits use, sharing, adapta- Allan, D. M. (2019). Elementary school teachers’ preferences for tion, distribution and reproduction in any medium or format, as long school-based interventions for students with emotional and behavio- as you give appropriate credit to the original author(s) and the source, ral problems. Psychology in the Schools, 56(10), 1633–1653. provide a link to the Creative Commons licence, and indicate if changes Evans, S. W., Owens, J. S., Wymbs, B. T., & Ray, A. R. (2018). were made. The images or other third party material in this article are Evidence-based psychosocial treatments for children and ado- included in the article's Creative Commons licence, unless indicated lescents with attention deficit/hyperactivity disorder. Journal of otherwise in a credit line to the material. If material is not included in Clinical Child & Adolescent Psychology, 47(2), 157–198. the article's Creative Commons licence and your intended use is not Fabiano, G. A., Pelham, J., William, E., Waschbusch, D. A., Gnagy, E. permitted by statutory regulation or exceeds the permitted use, you will M., Lahey, B. B., Chronis, A. M., & Burrows-MacLean, L. (2006). need to obtain permission directly from the copyright holder. 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J., Kovshoff, H., Cortese, S., & Kreppner, Rosnow, R. L., & Rosenthal, R. (1996). Computing contrasts, effect J. (2020). The Effects of ADHD Teacher Training Programs on sizes, and counternulls on other people’s published data: General Teachers and Pupils: A Systematic Review and Meta-Analysis. procedures for research consumers. Psychological Methods, 1(4), Journal of Attention Disorders, 1–20. 331–340. Sattler, J. M. (2008). Resource guide to accompany assessment of chil- Publisher's Note Springer Nature remains neutral with regard to dren: Cognitive foundations. JM Sattler. jurisdictional claims in published maps and institutional affiliations. 1 3 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Research on Child and Adolescent Psychopathology Springer Journals

Effectiveness of Specific Techniques in Behavioral Teacher Training for Childhood ADHD Behaviors: Secondary Analyses of a Randomized Controlled Microtrial

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Springer Journals
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Copyright © The Author(s) 2022
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0091-0627
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2730-7174
DOI
10.1007/s10802-021-00892-z
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Abstract

Behavioral teacher training is an effective intervention for children with attention-deficit/hyperactivity disorder (ADHD). Intervention effectiveness may be enhanced by including intervention components that carry the strongest evidence for their effectiveness. A previous article of this group showed that both antecedent- (i.e., stimulus-control) and consequent-based (i.e., contingency management) techniques were highly effective in reducing daily teacher-rated, individually selected problem behaviors in a specific situation of the child. Effects were observed up to three months post intervention. Here, we tested whether effects were also present in teacher-rated and masked DSM-based assessments that comprise the full range of ADHD and oppositional defiant disorder (ODD) symptoms, as well as on teacher-rated impairment. Teachers of 90 children with (subthreshold) ADHD (6–12 years) were randomly assigned to one of three conditions: a short (two sessions), individualized intervention consisting of either a) antecedent-based techniques or b) consequent-based techniques; or c) waitlist. Multilevel analyses showed that both sets of techniques were effective in reducing teacher-rated ADHD symptoms and impairment immediately after the intervention and up to three months later, as compared to waitlist. Masked observations of ADHD behavior were in line with teacher ratings, with effects being most pronounced for inattention. No effects on teacher-rated or masked ODD behavior were found. This study showed that antecedent- and consequent-based techniques were effective in improving classroom ADHD symptoms and impairment. Long-term changes in teacher-rated ADHD are promising. These results extend previous findings and show the potential of short individually tailored interventions in classroom settings as treatment of ADHD symptoms. Keywords ADHD · Behavioral teacher training · Antecedent-based techniques · Consequent-based techniques · Microtrial * Anouck I. Staff Introduction a.i.staff@vu.nl 1 Behavioral teacher training is an effective intervention to Department of Clinical, Neuro- and Developmental reduce children’s attention-deficit/hyperactivity disorder Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands (ADHD) symptoms and related behavioral problems in the classroom (DuPaul et al., 2012; Evans et al., 2018; Fabiano Faculty of Psychology and Educational Sciences, KU Leuven, Leuven, Belgium et al., 2009; Veenman et al., 2016; Ward et al., 2020). Effect sizes of current training programs generally range from small Department of Pediatrics, Amsterdam Reproduction & Development, Emma Children’s Hospital, Emma to medium (DuPaul et al., 2012; Ward et al., 2020), thus leav- Neuroscience Group, Amsterdam UMC, University ing room for improvement. Insight into which intervention of Amsterdam, Amsterdam, The Netherlands components are effective and which are not may contribute Department of Child and Adolescent Psychiatry, University to the development and improvement of behavioral teacher Medical Center Groningen, University of Groningen, trainings for ADHD (DuPaul et al., 2020; Schatz et al., 2020). Groningen, The Netherlands However, studies on the effectiveness of separate intervention Department of Clinical Psychology and Experimental components are scarce. Psychopathology, University of Groningen, Groningen, The Netherlands Vol.:(0123456789) 1 3 868 Research on Child and Adolescent Psychopathology (2022) 50:867–880 Behavioral teacher interventions for ADHD generally seatwork’ or ‘talking excessively during whole group include training teachers in the use of both antecedent- teaching’. Following EMA procedures, the four behav- based techniques (i.e., stimulus-control techniques such iors were daily assessed in the specific situation, maxi- as providing structure and clear instructions) and con- mizing the ecological validity and minimizing recall and sequent-based techniques (i.e., contingency management retrospection bias that may be observed using traditional techniques such as praise, reward and planned ignoring) questionnaires based on the Diagnostic and Statistical (DuPaul et  al., 2022). Teachers are typically taught to Manual of Mental Disorders (DSM) (Bentley et al., 2019; combine both sets of techniques, for example by giving a Shiffman et al., 2008). We showed that antecedent- and clear instruction to the child to raise his/her hand before consequent-based techniques were equally effective in speaking and praise the child when doing this (Patterson, reducing these four daily teacher-rated problem behav- 1982). Meta-analytic evidence from behavioral teacher iors in a specific situation. Effects were obtained directly and parent interventions suggests that both anteced- after the intervention (large effects, d = 0.89, 0.93, ent- and consequent-based techniques implemented by respectively),  and remained stable up to three months teachers and parents are effective to improve children’s later. ADHD symptoms and oppositional defiant (ODD) behav- Nevertheless, two important questions remained unan- iors (Gaastra et al., 2016; Leijten et al., 2019). However, swered, i.e., whether the promising findings on our EMA meta-analysis only allows testing whether intervention outcomes are reflected in: 1) broader assessments of effects are larger for interventions that include a particu- ADHD and ODD behaviors, and 2) impairment. Regard- lar intervention component (e.g., training teachers in a set ing the first question, we were interested whether effects of techniques) as compared to interventions that do not were also obtained if outcomes comprised the full range include that particular intervention component (Leijten of DSM-based teacher-rated ADHD and ODD symptoms et al., 2021). Thus each single intervention component is assessed on a rating scale, i.e., whether effects could also always studied in the context of other intervention com- be observed when teachers were asked to report behav- ponents (Lipsey, 2003). Meta-analyses can therefore be iors averaged over the past week and during all situations, used to generate hypotheses about effective intervention rather than during a specific situation during each day. components, but whether effect sizes are actually driven Using traditional DSM-based questionnaires also provides by a particular component remains to be studied (Leijten possibilities to compare results with the findings of other et  al., 2021). In contrast, microtrials are experimental behavioral interventions for ADHD. Further, we were inter- designs that can be used to test hypotheses regarding the ested whether effects were observed by raters who were not effectiveness of single intervention components by testing involved in treatment delivery and thus less susceptible the effects of relatively brief and focused environmental to social desirability and/or investment bias (Daley et al., manipulations, such as single intervention components, 2014; Sonuga-Barke et al., 2013). Regarding our second on proximal outcomes (Howe et al., 2010; Leijten et al., question, as functional impairment is often the primary 2015). Such a design allows to study the effectiveness reason for teachers to seek help (Coles et al., 2012), we of antecedent- and consequent-based techniques in isola- were interested whether effects are also observed in terms tion, which has not been done so far. Therefore, to test of functional impairment. the hypotheses about the effectiveness of antecedent- and The aim of the present study was thus to examine the consequent-based techniques derived from meta-analytic effectiveness of antecedent- and consequent-based tech- studies (Gaastra et  al., 2016; Leijten et  al., 2019), our niques on (1) teacher-rated and masked observations of study used a microtrial design to examine the effective- ADHD and ODD behaviors according to DSM-criteria, and ness of implementing antecedent- and consequent-based (2) teacher-rated functional impairment. Data were collected techniques in reducing the behavioral problems and in our randomized controlled microtrial that tested two short impairment children with ADHD often experience in the and individualized behavioral teacher interventions focusing classroom. on either antecedent- or consequent-based techniques. Based In a previous article of our group (Staff et al., 2021), on our previous findings regarding our EMA outcome, we we analyzed our randomized controlled microtrial using hypothesized that both sets of techniques would be effective an ecologically momentary assessment (EMA) meas- compared to a waitlist control condition in reducing ADHD ure of behavior as outcome measure (Shiffman et  al., and ODD symptoms as rated by teachers, both immediately 2008). Four preselected individual problem behaviors in after the intervention as well as at three months follow-up. a specific situation were assessed, and two of these were We expected smaller effect sizes compared to our EMA directly targeted in the intervention. The behaviors and outcomes (Howe et al., 2010), given that the current meas- situations thus differed per child-teacher dyad. Exam- ures reflect more distal outcomes. Further, we expected ples were ‘difficulties staying focused during individual effects to be most pronounced shortly after the intervention 1 3 Research on Child and Adolescent Psychopathology (2022) 50:867–880 869 compared to three months later (Lee et al., 2012). For our T2. In case the summer holiday started prior to T3, T3 took masked assessments of ADHD and ODD behaviors, struc- place three weeks prior to the end of the school year (but at tured classroom observations were conducted in a (randomly least four weeks after T2). Because there are no guidelines selected) subsample. Classroom observations have shown to for reporting on microtrials, we used the CONSORT guide- be a valid measure to assess ADHD and ODD in the class- lines for reporting on randomized controlled trials (Moher room (Minder et al., 2018) and to be sensitive to effects of et  al., 2001). More details on the design of the study are behavioral interventions (Pelham et al., 2005; Pfiffner et al., available in Staff et al. (2021). This study was registered at 2013). We expected both sets of techniques to be effective the Dutch Trial Register: https:// www. trial regis ter. nl/ trial/ in reducing observed ADHD and ODD behaviors (Pfiffner 6616. et al., 2013). Finally, we expected both sets of techniques to be effective in reducing functional impairment as rated by Participants the teacher (Groenman et al., 2021). The study sample comprised 90 regular primary school aged children (grades 1 to 6), from rural and urban areas Method in The Netherlands, showing ADHD symptoms, and their teachers who were in (self-reported) need of effective Design management techniques for their student(s). Inclusion cri- teria were: (a) high levels of ADHD symptoms (> 90th Teachers were randomized to one of two intervention con- percentile) as rated by teachers on the Inattention and/or ditions (i.e., antecedent- and consequent-based, see below) Hyperactivity-Impulsivity scale of the Disruptive Behavior or a waitlist control condition. A random list of numbers Disorders Rating Scale (DBDRS) (Oosterlaan et al., 2008), 1–90 was created to allocate participants to these condi- (b) at least three symptoms (item score ≥ 2) on the Inattention tions. Randomization occurred at school level to prevent and/or Hyperactivity-Impulsivity scale of the DSM-IV-TR contamination from teachers receiving different interven- based semi-structured Teacher Telephone Interview (TTI) tions. There was a maximum of two included students per (Tannock et al., 2002), and (c) a score > 5 (indicating func- participating teacher. Outcome measures were assessed at tional impairment, range 0—10) on at least one domain of three time points: at baseline prior to randomization (T0), functioning on a modified version of the teacher-rated Impair - during the week immediately after the intervention or the ment Rating Scale (IRS) (Fabiano et al., 2006). Exclusion cri- waiting period (T1), and three weeks after the intervention teria were: (a) an estimated full scale IQ < 70, assessed using or waiting period (T2). Figure 1 provides an overview of a short form of the Dutch version of the Wechsler Intelligence which measures were assessed at each time point. Class- Scale for Children-third edition (WISC-III-NL) including the room observations were conducted in a randomly selected subtests Block Design and Vocabulary (Sattler, 2008), (b) subsample of each condition (n = 20 per condition). Longer pharmacological treatment for ADHD symptoms during the term effects on teacher-rated ADHD and ODD were inves- last month, (c) a diagnosis of autism spectrum disorder or tigated three months after baseline (T3), in the intervention conduct disorder according to the DSM-IV-TR or DSM-5 as conditions only. The total study duration was three months reported by parents on a demographic questionnaire, or (d) (T0-T3) and allowed no holidays between randomization and the teacher being enrolled in a behavioral teacher training T0:baseline T1:directlypost T2:2 weekspost T3:13weeks intervention intervention post intervention b b c •SWAN •SWAN •SWAN •SWAN b b c •DBDRS:ODD •DBDRS:ODD •DBDRS:ODD •DBDRS:ODD •IRS •IRS •Classroom •Classroom a a observations observations Fig. 1 Overview of the outcomes assessed at the different time points. vations were conducted in a subset of the sample (N = 60). For analy- DBDRS Disruptive Behavior Disorders Rating Scale, IRS Impairment ses on short term effects, outcomes were averaged over T1 and T2. Rating Scale, ODD Oppositional Defiant Disorder, SWAN Strengths Longer term effects were assessed in the intervention conditions only and Weaknesses of ADHD and Normal Behavior. Classroom obser- 1 3 870 Research on Child and Adolescent Psychopathology (2022) 50:867–880 aimed at ADHD symptoms or other behavioral problems in antecedent-based intervention teachers were provided with the past year. supplemental psycho-education (step 1) on how stimuli evoke behaviors, how executive functioning deficits in chil- Interventions dren with ADHD may lead to difficulties adapting behavior to stimuli, and how antecedent-based techniques adapt to For the purpose of this microtrial, two short individual- this by changing the discriminative value of stimuli. The ized and manualized interventions consisting of two ses- behavioral analysis (step 3) focused on identifying anteced- sions were developed (see Staff et al. (2021) for a detailed ents that elicited the problem behavior. The intervention plan description). One intervention included only antecedent- (step 5) in this condition consisted of antecedent-based tech- based techniques (referred to as antecedent-based interven- niques only (i.e., setting clear rules, providing clear instruc- tion), the other only included consequent-based techniques tions, discussing challenging situations with the child in (referred to as consequent-based intervention). The inter- advance, and providing structure in time and space). These ventions were based on evidence-based behavioral parent techniques were briefly explained and could be part of the training programs aimed at remediating ADHD symptoms intervention plan. In the consequent-based intervention, and ADHD related behaviors (Barkley, 1987; McMahon & teachers’ psycho-education (step 1) was supplemented with Forehand, 2003; Van Den Hoofdakker et al., 2007). The first specific information on how consequences affect behavior, session took place at the school and lasted two hours, the that children with ADHD may suffer from an altered reward second session was scheduled one week later and took place sensitivity that may influence how their behavior is shaped by video conference, lasting 45 minutes. by the environment, and how consequent-based techniques At the beginning of the study period, teachers selected adapt to this by changing the consequences of behavior (Van four individual problem behaviors per child from a list of der Oord & Tripp, 2020). The behavioral analysis (step 3) 32 ADHD and oppositional behaviors in a specific situ- was targeted at identifying consequences that positively or ation (e.g., difficulties staying focused during individual negatively reinforce the problem as well as desired behav- seatwork) (Staff et al., 2021; Van Den Hoofdakker et al., ior (i.e., functional behavior assessment, FBA; Dunlap & 2007), from which two behaviors were directly targeted Kern, 2018). The following consequent-based techniques in the intervention. The first session of both interventions were explained and integrated in the intervention plan (step consisted of the following steps: (1) providing the teacher 5): praise, reward, planned ignoring, and negative conse- with psycho-education on ADHD; (2) selecting the prob- quences. Shaping was explained and used when the full lem behavior, based on the frequency (preferably daily) and desired target behavior was not displayed yet. Consequent- severity of behavior; (3) making a behavioral analysis of the based techniques such as token economy and time-out were behavior by the teacher and therapist; (4) defining desired not included in this intervention given that these also require target behaviors; (5) teaching teachers how to implement antecedent-based techniques (e.g., clear rules, structuring by either antecedent- or consequent-based techniques (depend- use of individual instructions). ing on the assigned intervention condition) most optimally, When teachers brought up that they could use techniques and making a behavioral intervention plan by the teacher from the other intervention (e.g., reward desired behavior and therapist. For each intervention plan, one or more tech- in the antecedent-based intervention), the therapists were niques of the assigned condition could be chosen to be part instructed to explain that the current intervention focused of the intervention plan, based on the behavioral analy- on the trained techniques and therefore the intervention plan sis; (6) practicing the intervention plan (i.e., techniques) consisted of these techniques only. The teacher was advised through visualization or role play; (7) instructing teachers to implement and/or optimize the trained techniques first to implement the intervention plan in the classroom for and at least until the last week of assessments, to monitor one week, after which the second session took place. The its effectiveness and to decide whether the use of other tech- second session started with evaluating the preceding week niques was needed at a later time. More information on the and adapting the intervention plan, if necessary. Thereafter, interventions and examples of intervention plans for every steps two to six of the first session were repeated. At the end intervention are available in our previous publication (Staff of the second session, teachers were provided with handouts et al., 2021). of the techniques and were instructed to implement both intervention plans directly after the session for at least four Therapists and Intervention Fidelity weeks. Teachers could contact the therapist if required. Differences between the two interventions concerned the Interventions were carried out by two psychologists with focus on either antecedent- or consequent-based techniques. postgraduate training in behavioral therapy and ADHD More specifically, interventions differed in steps 1, 3, and 5 (AS and RH) (see also Staff et  al. (2021)). Therapists (see also Table A in Supplementary Information S1). In the were trained in the program and supervised by licensed 1 3 Research on Child and Adolescent Psychopathology (2022) 50:867–880 871 supervisors in the postgraduate behavior therapy program symptoms. The internal consistency for the SWAN in this with ample experience in behavioral parent and teacher sample was good (α = 0.85) and convergent validity has been training programs (SvdO and BvdH). Supervision started established (Strengths and Difficulties Questionnaire (SDQ) with individual supervision sessions until quality was suf- Hyperactivity scale; r = 0.54) (Lakes et al., 2012). The Dutch ficient. Thereafter, there were group-based meetings every population based mean scores are M = 44.0 (boys)/M = 45.7 two weeks with the therapists and supervisors to monitor (girls), SD = 8.08 for the Inattention scale and M = 43.9 intervention fidelity (see below) and to provide supervision (boys)/M = 45.6 (girls), SD = 8.63 for the Hyperactivity/ until the end of the study period. At the beginning of the Impulsivity scale (scale 1 = far below average, 7 = far above study period, supervisors checked audiotaped sessions to average) (Polderman et al., 2007). assess the quality of the session(s) of each condition until optimal quality was reached (maximum scores), as well ODD‑symptoms Teacher ratings of symptoms of ODD were as to assess intervention fidelity (see below). Quality was measured with the ODD-scale of the DBDRS (Oosterlaan rated based on knowledge, structure, and therapeutic process et al., 2008). Teachers rated a child’s behavior over the past (e.g., providing clear instructions, adequately dealing with week on eight items, using a 4-point Likert scale ranging resistance), rated on a 3-point Likert scale (1 = needs work, from 0 (‘not at all’) to 3 (‘very much’). Scores may range 2 = acceptable, 3 = good work). Both therapists reached opti- between 0 and 24, with higher scores indicating more ODD mal quality scores for each condition after the first sessions. symptoms. The internal consistency for the teacher-rated Treatment fidelity was assessed by scoring contamination ODD-scale of the Dutch version of the DBDRS is high and by scoring the percentage of addressed session items (α = 0.95; α = 0.92 in this sample), and convergent valid- in each session. The procedure of Abikoff et al. (2013) was ity is strong (IOWA Conners’ Inattention/Overactivity used to score contamination. Contamination was defined as scale; r = 0.70, SDQ Hyperactivity scale; r = 0.79—0.83) a) the therapist recommending the use of non-assigned tech- (Oosterlaan et al., 2008). niques, b) therapists’ questions or remarks that could elicit teacher’s thoughts or comments on techniques belonging to Impairment An overall measure of functional impairment the non-assigned intervention, or c) the therapist actively of the child at school was assessed using an adjusted version supporting and elaborating on the teacher’s suggestion to of the teacher-rated Impairment Rating Scale (Fabiano et al., use of techniques specific to the non-assigned intervention. 2006). Teachers rated impairment over the past week on the The contamination score was based on the frequency of following four areas of functioning: peer, teacher, academ- contamination occurrences in a session. After optimal qual- ics, and classroom. An example of a question is: ‘How this ity scores were reached, a random sample of ten percent of child’s problems affect his or her relationship with other the sessions were listened back and scored on intervention children?’. Impairment was rated on a 10-point scale, rang- fidelity by independent evaluators during the entire study ing from 0 (‘no impairment’) to 10 (‘excessive impairment’), (all intervention sessions were audiotaped). In addition to in line with the Dutch system for academic grading. A score scoring the selected audiotapes, the percentage of addressed above 5 indicated functional impairment on that particular session items was also scored using session-forms that were area of functioning. Outcome was the average score on the completed by therapists after each session. four items (ranging from 0 to 10). Outcome Measures Classroom Observations of ADHD and ODD Behaviors Teacher Rating Scales Classroom observations were conducted in a randomly selected subset of the sample, given the time required for coding (i.e., 570 hours of coding for the subsample analyzed ADHD Symptoms Teacher ratings of symptoms of inatten- here). For twenty randomly selected children from every tion and hyperactivity-impulsivity were assessed using the condition (67%), classroom observations were coded. The scales Inattention (nine items) and Hyperactivity-Impulsivity total subsample did not differ from the full sample on base- (nine items) of the DSM-based Strengths and Weaknesses line characteristics nor in their response to the two interven- of ADHD-symptoms and Normal Behavior (SWAN) rating tions studied here as assessed in terms of the proximal out- scale (Swanson et al., 2012). Teachers rated a child’s behav- come (results available from the first author). Observations ior over the past week compared to peers on a 7-point Likert were conducted when children attended morning lessons in scale (-3 = far below average to + 3 = far above average). their own classroom led by their primary teacher, and were Scores were reverse scored for consistency with other meas- on similar time and day at both time points (e.g., Tuesday ures used in this study. Scores may range between -27 and 27 morning at the beginning of the school day) for approximately for both scales, with higher scores indicating more ADHD 90 minutes per child. The first 60 minutes that contained 1 3 872 Research on Child and Adolescent Psychopathology (2022) 50:867–880 actual lessons were used for coding (e.g., the observation frequency of oppositional behavior served as outcome (Staff started when children were arriving at the beginning of the et al., 2020). day, coding started when the teacher started the first les - Observations were coded by fourteen graduate psychology son) (coding duration M = 57.30 min, SD = 9.29 min for T0; students (i.e., observers), who were individually trained by M = 56.13 min, SD = 5.27 min for T2). the first author in at least two sessions of two hours. Observ - A Dutch adapted version of the Ghent University Class- ers coded a maximum of two scales, in order to increase accu- room Coding Inventory (GUCCI; Staff et al., 2020) was racy and inter-observer reliability (i.e., four observers coded used to code behavior, according to four scales: Attention Attention Problems, five others coded Motor Hyperactivity, Problems (i.e., visual attention to task), Motor Hyperac- and five others coded Verbal Hyperactivity and Oppositional tivity (i.e., motor movements), Verbal Hyperactivity (i.e., Behavior). Observers were masked to treatment condition of talking or other vocalizations), and Oppositional Behavior the child as well as to whether an observation was conducted (i.e., arguing, anger). Each scale comprised a categorical at pre- (T0) or post-intervention (T2). During the training variable of behavior to be coded as absent or present, catego- they were introduced to the behavioral categories of the ries within each scale were mutually exclusive (e.g., Motor scale(s) and the coding system. Observers practiced coding Hyperactivity consisted of the levels no motor hyperactivity until inter-observer agreement with the trainer reached ≥ 0.80 and motor hyperactivity, see Table 1). Scales were coded (see for detailed information: Staff et al. (2020)). Given that using continuous sampling, indicating that all behaviors we used continuous coding, rather than time sampling, inter- were coded throughout the coding period. For the Attention observer agreement was based on the percentage of time Problems scale, the percentage of time off-task was calcu- behaviors were scored in the same category by both raters lated by dividing the total time off-task by the total time and ranged between 82.9% and 99.8%. Additionally, intra- coded in which the child was expected to be involved in class coefficients (ICC, based on a one-way random model, class activities (sum of the time of on- and off-task). When Hallgren (2012)) for each scale were calculated to have an no involvement in class activities was expected, the interval estimation of inter-rater reliability corrected for measure- was coded as no-task. For the behavioral categories Motor ment error. Inter-rater agreement was excellent (ICC ≥ 0.86) Hyperactivity and Verbal Hyperactivity, percentage of total for this sample. Convergent validity of the GUCCI was ade- time the behaviors motor hyperactivity and verbal hyperac- quate (r = -0.04—0.29), although relatively low correlations tivity occurred was calculated. For Oppositional Behavior, between rating scale scores and observational scores indicate that both instruments measure different aspects of ADHD Table 1 Operational definitions of observed behaviors using the GUCCI Scale Coding category Description Outcome variable in statistical analysis Attention Problems On-task The child is involved in activities that are expected by the teacher (e.g., paying visual attention to task or to the teacher), and is following the teacher’s instructions and requests Off-task The child is involved in activities that are not expected by the teacher for % of time at least two seconds (e.g., not working on assignments, daydreaming) Motor Hyperactivity No motor hyperactivity The child has no difficulty sitting down. Little movements of arms, hands, feet, or legs are accepted and no gross movements that are observably annoying or disturbing peers are shown Motor hyperactivity The child is not sitting still on his/her chair (e.g., overturns or swings % of time his/her chair, squirms in chair). The child shows small movements that are annoying or disturbing for peers (e.g., tapping with a pen). The child is not sitting on the chair (e.g., standing up without permission, sitting on their knees) or is walking or running through the classroom Verbal Hyperactivity No verbal hyperactivity The child is quiet, or the child talks in reaction to the teacher’s request Verbal hyperactivity The child is talking or making vocal sounds (e.g., whispering to self, % of time humming) Oppositional behavior No oppositional The child does not show any oppositional behavior, anger, aggression, or behavior antisocial behavior against others Oppositional behavior The child shows oppositional behavior against the teacher (e.g., refuses Frequency something). The child shows angry behavior (e.g., shows tantrum) GUCCI Ghent University Classroom Coding Inventory 1 3 Research on Child and Adolescent Psychopathology (2022) 50:867–880 873 and ODD behavior (see for a detailed evaluation: Staff et al. within children (level 2), nested in classrooms (level 3), and (2020)). nested in schools (level 4). Random intercepts at classroom and school level were only included if significantly improv - Procedure ing model fit as determined by Likelihood Ratio Test. We inserted condition (waitlist, antecedent, consequent) as This study was carried out between April 2017 and April between subjects’ factor, and time (T1, T2) as within vari- 2019. Teachers were recruited through school principals, able. Baseline scores (T0) of the outcome were inserted as school collaboration networks, and an outpatient mental fixed factor, in order to control for problems at baseline. health clinic. Teachers showing interest in participation We investigated short-term effects of condition (averaged in the study received an information letter explaining the over T1 and T2) to compare the intervention conditions to research aims and responsibilities of all parties involved. the waitlist condition, and to compare the two intervention Teachers who agreed in participating enlisted one to two conditions to each other. Because effects were similar for T1 children showing profound and impairing ADHD symptoms and T2 on the proximal outcome (see Staff et al., 2021), we in the classroom, and informed parents about the study (i.e., used an aggregated outcome measure for the current study. provided them with the information letter and informed Longer term effects were assessed by examining whether consent). Written consent was obtained from teachers, par- problem behaviors remained stable from T2 to T3 within ents, and children older than 11 years. After receiving con- each intervention condition (i.e., whether the development sent, teachers administered the ADHD scales of the DBDRS of problem behaviors from T2 to T3 changed significantly). and TTI to screen for eligibility. If inclusion criteria were Two measures of hyperactivity were included in the class- met, baseline assessments (T0) took place through teacher room observations (i.e., motor and verbal), therefore alpha rating scales and classroom observations, all conducted in level was set at 0.05/2 for these outcomes. Given the lower the same week. For the classroom observations, observers number of participants for the observational measure in each were introduced as interns. Teachers explained to children separate condition, we explored whether weaker short-term that the interns had to observe how children are working effects on the classroom observations may have remained during lessons in different classes for study purposes. To undetected using sensitivity analyses. Therefore, we com- prevent target children being aware of being subject of the bined the antecedent and consequent condition into one observations, cameras were positioned in a corner at the “active” intervention condition (n = 40) and compared this front of the classroom, targeted at the whole classroom (but to the waitlist condition. Effect sizes (Cohen’s d ) were cal- zoomed in at a particular child). Randomization occurred culated by dividing the difference in mean scores between after baseline assessments were completed. Teachers of two conditions averaged over T1 and T2 by the pooled SD children in the waitlist condition were allowed to receive (Rosnow & Rosenthal, 1996), with 0.20, 0.50, and 0.80 as care as usual during the study period, and were offered the thresholds for small, medium, and large effects, respectively. possibility to use a self-directed behavioral teacher program To examine intervention fidelity (Abikoff et al., 2013), we targeting ADHD symptoms immediately after T2 (PR Pro- compared the intervention conditions on the contamination gram, Veenman et al., 2016). Longer term effects at T3 were scores and the average percentage of addressed session items therefore only explored in children of teachers in the active (as rated by therapists and independent coders) by using intervention arms and were only assessed by teacher ratings. independent t-tests. We also asked teachers in the anteced- The local medical ethical committee waived the need for ent and consequent condition to rate whether they would medical ethical approval (University Medical Center Gro- recommend the intervention to colleagues (yes, no, neutral) ningen, 2016/198). at T3 as an indication of the feasibility of the interventions. Statistical Analysis Results Analysis of variance (ANOVA), and chi-squared or Fisher’s exact tests were used to compare groups on the demographic Thirty children (from 25 teachers of 17 schools) were allo- variables assessed at baseline. cated to the antecedent condition, 30 children (from 26 Data were analyzed on an intention-to-treat basis. To teachers of 18 schools) to the consequent condition, and compare the intervention conditions to the waitlist condi- 30 children (from 26 teachers of 17 schools) to the waitlist tion and to each other, multilevel analyses (mixed model) condition. Table 2 displays demographic characteristics of were conducted in Stata (version 16). Missing data was ran- the sample. Children randomized to the three conditions did dom (≤ 5%) for all outcomes, and was taken into account not differ on any of the screening characteristics (p > 0.132), in multilevel analysis (Twisk et al., 2013). Four hierarchi- with the exception of hyperactivity-impulsivity symptoms on cal levels were distinguished: observations (level 1), nested the TTI and DBDRS on which lower ratings were obtained 1 3 874 Research on Child and Adolescent Psychopathology (2022) 50:867–880 Table 2 Sample description and baseline comparisons AC (n = 30) CC (n = 30) WC (n = 30) Group comparisons Age at assessment in years 8.53 (1.63) 9.08 (1.63) 8.76 (1.52) F(2, 89) = 0.88, p = 0.420 Sex, n (%) boys 23 (77) 23 (77) 28 (93) χ = 3.81, p = 0.150 IQ 99.77 (11.04) 99.33 (14.28) 104.07 (10.05) F(2, 89) = 1.45, p = 0.241 SES 5.22 (1.24) 5.24 (1.12) 5.00 (1.03) F(2, 88) = 0.41, p = 0.664 Caucasian, n (%) 28 (93) 27 (90) 30 (100) Fisher’s exact = 0.294, p = 0.363 ADHD diagnosis, n (%) 8 (27) 8 (27) 7 (23) χ = 0.12, p = 0.943 Other psychiatric diagnosis, n (%) 0 (0) 3 (10) 0 (0) Fisher’s exact = 4.22, p = 0.104 TTI symptom severity    Inattention 4.30 (1.58) 5.00 (1.86) 4.13 (1.91) F(2, 89) = 1.99, p = 0.143    Hyperactivity-Impulsivity 2.97 (1.85) 4.83 (2.38) 4.60 (2.22) F(2, 89) = 6.65, p = 0.002 (CC, WC > AC)    ODD 1.10 (1.45) 1.07 (1.46) 1.23 (1.61) F(2, 89) = 0.10, p = 0.903    CD 0.00 (0.00) 0.00 (0.00) 0.13 (0.51) F(2, 89) = 2.07, p = 0.132 DBDRS    Inattention 16.90 (4.96) 17.50 (3.92) 16.00 (5.57) F(2, 89) = 0.72, p = 0.488    Hyperactivity-Impulsivity 13.17 (6.21) 15.73 (6.49) 17.57 (6.60) F(2, 89) = 3.54, p = 0.033 (WC > AC) IRS impairment    Number of domains 3.07 (0.98) 2.97 (1.27) 3.24 (0.88) F(2, 84) = 0.45, p = 0.638    Average score 6.22 (1.65) 6.14 (1.97) 6.29 (1.28) F(2, 84) = 0.52, p = 0.948 Teacher ratings SWAN    Inattention 15.03 (4.41) 14.17 (5.11) 15.07 (5.07) F(2, 89) = 0.33, p = 0.721    Hyperactivity-Impulsivity 13.57 (6.77) 13.77 (6.35) 16.83 (6.26) F(2, 89) = 2.41, p = 0.096 DBDRS    ODD 8.00 (6.45) 5.00 (5.09) 8.97 (5.32) F(2, 89) = 4.02, p = 0.021 (AC, WC > CC) Parent ratings SWAN    Inattention 5.31 (8.58) 9.21 (7.54) 5.86 (5.53) F(2, 83) = 2.37, p = 0.100    Hyperactivity-Impulsivity 6.08 (8.24) 9.41 (6.20) 9.83 (6.61) F(2, 83) = 2.31, p = 0.106 DBDRS    ODD 5.90 (4.94) 5.28 (3.43) 6.17 (4.40) F(2, 88) = 0.33, p = 0.719 Classroom observations Inattention % 27.23 (15.96) 28.97 (10.88) 30.56 (16.66) F(2, 59) = 0.26, p = 0.774 Motor hyperactivity % 30.37 (19.63) 40.35 (20.47) 32.60 (15.67) F(2, 59) = 1.57, p = 0.217 Verbal hyperactivity % 5.73 (4.87) 9.08 (7.83) 10.69 (6.75) F(2, 59) = 2.94, p = 0.061 Oppositional behavior K 0.30 (1.13) 0.45 (1.00) 1.65 (3.08) F(2, 59) = 2.79, p = 0.070 M and SD are depicted unless otherwise stated AC antecedent condition, ADHD attention-deficit/hyperactivity disorder, CC consequent condition, CD conduct disorder, DBDRS Disruptive Behavior Disorder Rating Scale, IRS Impairment Rating Scale, K  count,  ODD oppositional defiant disorder, SES socioeconomic status, SWAN Strengths and Weaknesses of ADHD and Normal Behavior, TTI Teacher Telephone Interview, WC waitlist control condition SES was measured by parental educational level (average of both parents) through the Dutch classification system (1 = no education completed, 2 = early childhood education, 3 = primary education, 4 = lower secondary education, 5 = upper secondary education, 6 = undergraduate school, 7 = graduate school, 8 = post-graduate education) (CBS, 2016) Five children started directly after the summer holiday, but were screened before the summer holiday. As teachers were not able to rate impair- ment in the first week of school, for these children functional impairment ratings were missing Missing parent ratings: 1 parent (CC) did not fill in any questionnaire, and 5 other parents (4 AC, 1 CC) did not fill in the SWAN For analyses on classroom observations a subsample (n = 60) of children was used, see Supplementary Information S2 (Table B) for a descrip- tion of this subsample 1 3 Research on Child and Adolescent Psychopathology (2022) 50:867–880 875 for children in the antecedent condition than for children in Hence these levels were removed from the models that now the consequent condition (TTI) and waitlist condition (TTI included two levels (observations clustered in students). Only and DBDRS). Parents reported that 23 children (26%, evenly for the Verbal Hyperactivity scale of the GUCCI the level distributed over conditions, see Table 2) had been clinically classroom improved model fit and was thus included in diagnosed with ADHD and none had been diagnosed with the model. Two teachers discontinued participation after ODD. Based on the TTI, 42 children (47%) met the criteria T0 (change of job and illness, n = 1 for the antecedent and for DSM-V ADHD (i.e., at least six out of nine symptoms in waitlist condition), and two other teachers (n = 1 for the con- at least one domain) and 10 children (11%) met the criteria sequent and waitlist condition) discontinued after T2 due to for DSM-V ODD within the school setting. personal problems. Characteristics of the subset of the sample for which the classroom observations were coded is described in Supple- Teacher‑rated ADHD Symptoms mentary Information S2 (Table B). Results showed that for the teacher-rated inattention scale Effects of Techniques (effects averaged over T1 and T2 while controlling for T0, see Table 3) there was a medium sized, significant reduc- Intervention effects on all short-term outcomes are depicted tion of symptoms for the antecedent condition as compared in Table 3 (means and standard deviations at all four time to the waitlist condition, and a non-significant (although points on all outcomes are reported in Supplementary trend), small to medium effect for the consequent condition Information S3, Table C, and Figures of the development of compared to the waitlist condition. Regarding teacher-rated behavior over time for all outcomes are reported in Supple- hyperactivity-impulsivity symptoms, both intervention con- mentary Information S4, Fig. A). For all outcomes, the lev- ditions showed a significant decrease in symptoms as com- els ‘school’ and ‘classroom’ did not affect intercept variance. pared to the waitlist condition, with medium to large effects. Table 3 Short term effects of the antecedent- and consequent-based techniques on all outcomes AC vs WC CC vs WC AC vs CC Teacher ratings B (SE) p d (95% CI) B (SE) p d (95% CI) B (SE) p d (95% CI) Inattention -3.41 (1.13) 0.003 0.57 (0.30–0.84) -2.04 (1.13) 0.071 0.34 (0.08–0.60) -1.37 (1.12) 0.223 0.23 (-0.03–0.49) symptoms (SWAN) Hyperactivity- -4.70 (1.19) <0.001 0.69 0(0.42–0.96) -3.05 (1.19) 0.010 0.45 (0.19–0.72) -1.65 (1.16) 0.155 0.24 (-0.02–0.50) impulsivity symptoms (SWAN) ODD-symptoms -1.26 (0.97) 0.194 0.23 (-0.03–0.49) -0.39 (1.01) 0.699 0.07 (-0.19–0.33) -0.87 (0.99) 0.378 0.16 (-0.10–0.42) (DBDRS) Impairment (IRS) -1.08 (0.48) 0.023 0.62 (0.35–0.89) -1.11 (0.48) 0.021 0.63 (0.36–0.90) 0.03 (0.44) 0.954 0.01 (-0.25–0.27) average score Classroom observations Inattention (%) -8.82 (4.33) 0.042 0.55 (0.28–0.82) -10.48 (4.26) 0.014 0.65 (0.38–0.92) 1.66 (4.38) 0.704 0.10 (-0.16–0.36) Motor hyperactivity -6.06 (4.90) 0.216 0.34 (0.08–0.60) -7.99 (4.91) 0.103 0.45 (0.19–0.72) 1.94 (5.03) 0.700 0.11 (-0.15–0.37) (%) Verbal hyperactivity 3.10 (2.48) 0.212 0.42 (0.16–0.69) -3.49 (2.45) 0.154 0.47 (0.20–0.74) 6.59 (2.53) 0.009 0.88 (0.61–1.15) (%) Oppositional -0.90 (0.54) 0.097 0.43 (0.17–0.70) -0.58 (0.54) 0.278 0.28 (0.02–0.54) -0.32 (0.52) 0.544 0.15 (-0.11–0.41) behavior (K) The fixed effect of group represent group differences averaged over T1 and T2 while controlling for baseline scores (T0) The control condition or the consequent condition was used as reference group AC antecedent condition, ADHD attention-deficit/hyperactivity disorder, CC consequent condition, DBDRS Disruptive Behavior Disorder Rating Scale, ODD oppositional defiant disorder, IRS Impairment Rating Scale, K count, SWAN Strengths and Weaknesses of ADHD and Normal behavior rat- ing scale, WC waitlist-control condition Classroom observations were conducted in a subsample of children (n = 60), at T0 and T2. For descriptions of this sample see Supplementary Information S2 (Table B) Level child was included in the model Levels child and class were included in the model 1 3 876 Research on Child and Adolescent Psychopathology (2022) 50:867–880 Both intervention conditions did not significantly differ from Observed ODD Symptoms each other on the two symptom domains. Analyses of longer-term changes as assessed with teacher No significant reductions in ODD symptoms in the inter - ratings revealed that inattention symptoms remained low vention conditions compared to the waitlist condition were (even decreased) from T2 to T3 in both intervention condi- obtained with the masked classroom observations, see tions (for antecedent: B = -4.19, SE = 0.90, p < 0.001; for Table 3. consequent: B = -2.21, SE = 0.88, p = 0.012). Approximately similar effects were found for hyperactivity-impulsivity Impairment symptoms (for antecedent: B = -2.57, SE = 0.99, p = 0.001; for consequent: B = -2.38, SE = 0.97, p = 0.015). Significant and similar reductions of teacher-rated func- tional impairment were found in both intervention condi- Observed ADHD Symptoms tions as compared to the waitlist condition from T0 to T2, see Table 3, with medium effect sizes. Masked assessments of ADHD behavior using classroom observations revealed that there was a decrease in inatten- Sensitivity Analyses for Classroom Observations tion in children in both the antecedent- and consequent condition as compared to children in the waitlist condition Results showed a medium sized decrease in attention prob- from T0 to T2 with medium to large short-term effects, lems from T0 to T2 in the “active” intervention group see Table 3. Post-hoc analyses showed that this is likely as compared to the waitlist group (B = -9.68, SE = 3.70, to be explained by a trend significant increase in inatten - p = 0.009, d = 0.60). There was also a small to medium sized tion in the waitlist condition over time (B = 5.77, SE = 3.36, decrease (trend significant) in motor hyperactivity obtained p = 0.086), while the decrease in attention problems within between the “active” intervention condition compared to the antecedent- and consequent conditions was non- the waitlist group (B = -7.02, SE = 4.22, p = 0.096, d = 0.40). significant (B = -1.41, SE = 3.49, p = 0.687; B = -3.91, No significant differences in verbal hyperactivity and oppo- SE = 3.42, p = 0.254, respectively). For motor hyperactiv- sitional behavior were observed between the “active” ity and verbal hyperactivity, no significant reductions were intervention and waitlist condition (B = -0.29, SE = 2.23, observed when comparing the intervention conditions to p = 0.897, d = 0.04; B = -0.74, SE = 0.48, p = 0.120, d = 0.35, the waitlist condition. There were no significant differences respectively). between the antecedent and consequent condition in the effectivity of the two interventions on observed attention Intervention Fidelity and Feasibility problems and motor hyperactivity. For verbal hyperactivity, however, results showed that verbal hyperactivity increased Contamination occurred once in one session of the conse- over time in the antecedent condition as compared to the quent condition and did not occur in any of the sessions of consequent condition with a medium to large effect. Post- the antecedent condition. Contamination scores did not dif- hoc analyses within each condition revealed that there fer between the two interventions: t(3.00) = -1.00, p = 0.391. was a significant increase in verbal hyperactivity in the The average percentage of addressed session items was high antecedent condition from T0 to T2 (B = 5.24, SE = 2.05, in the antecedent and consequent condition according to p = 0.010), while verbal hyperactivity remained stable from both therapists’ self-report (98.9% and 99.4% respectively) T0 to T2 in the consequent condition (B = -2.91, SE = 2.02, and recorded sessions (98.0% and 97.8% respectively). Most p = 0.149). teachers would recommend the training to colleagues (ante- cedent: n = 21 [88%]; consequent; n = 17 [77%]), with no dif- Teacher‑rated ODD Symptoms ferences between the two conditions (χ = 0.84, p = 0.361). Analyses of short-term effects showed that there were no significant reductions in teacher-rated ODD  symptoms Discussion (DBDRS) in the intervention conditions compared to the waitlist condition, and when comparing both intervention Using a microtrial design, this study was aimed to gain conditions to each other, see Table 3. insight into whether previously found effects of anteced- Analyses of longer-term effects (T2 to T3) of teacher- ent- and consequent-based techniques in teacher training for rated ODD symptoms showed that there were no significant children with ADHD on EMA outcomes (Staff et al., 2021), changes in ODD symptoms in any of the intervention con- were also reflected in broader assessments. More specifically, ditions (for antecedent: B = -0.46, SE = 0.67, p = 0.492; for we examined the effectiveness of both sets of techniques on consequent: B = -0.96, SE = 0.67, p = 0.153). teacher ratings that comprise the full range of DSM-criteria 1 3 Research on Child and Adolescent Psychopathology (2022) 50:867–880 877 for ADHD and ODD behaviors, masked classroom observa- antecedent-based intervention was somewhat more effec- tions of ADHD and ODD behaviors, as well as teacher-rated tive than the consequent-based intervention in reducing functional impairment. teacher-rated inattention symptoms (i.e., medium-sized Effects on DSM-based teacher-rated ADHD were mostly effect for antecedent-based intervention versus a small to in line with our previously reported findings (Staff et al., medium-sized effect for consequent-based intervention). 2021), and with the broader literature on teacher trainings A similar study of our group into the effectiveness of both for ADHD (DuPaul et al., 2012; Evans et al., 2018; Fabiano types of intervention components in behavioral parent et al., 2009; Ward et al., 2020). The previous article showed training for ADHD also found this pattern (Hornstra et al., that both interventions were ee ff ctive in reducing four daily- 2021). As argued by Hornstra and colleagues, it may be rated, individually selected, problem behaviors of the child that antecedent-based techniques potentially require less in specific situations, of which two were directly targeted time and effort of teachers to implement during the train- in the intervention. The current article extends these find- ing as compared to consequent-based techniques, because ings by showing that intervention effects were also present antecedent-based techniques focus on the prevention of in reductions ADHD symptoms according to DSM-criteria problem behavior and can be implemented regardless of as rated by teachers averaged over the past week and all child behavior. In addition, before consequent-based tech- situations, and in reductions of teacher-rated impairment. niques can be effective, children may have to be repeatedly Teacher-rated ADHD symptoms in the antecedent and con- exposed to alternated contingencies in order to adapt their sequent conditions even improved up to levels close to the behavior, while antecedent-based techniques may have population based mean (Polderman et al., 2007), while chil- direct effects (Owen et al., 2012). dren in the waitlist condition continued to score one stand- Our findings were in line with studies showing that ard deviation above the population mean. As effects were teacher training has longer term effects over three months obtained on multiple measures (more and less susceptible to (DuPaul et al., 2012; Evans et al., 2018; Fabiano et al., 2009; bias) and outcomes, this strongly confirms the effectiveness Ward et al., 2020). Contrary to our expectations, there were of the interventions. even indications for the three months follow-up that teacher- No significant differences were observed in the effect rated ADHD symptoms further improved, regardless of the sizes of both interventions compared to the waitlist condi- techniques used, while such effects were not observed for tion. This is in contrast to meta-analytic results showing that our proximal outcome (i.e., these effects remained stable effect sizes of teacher programs that include consequent- from post-intervention to follow-up; Staff et al. (2021)), and based interventions are somewhat larger than programs behavior often deteriorates after treatment is withdrawn (Lee that include antecedent-based interventions (Gaastra et al., et al., 2012). However, we did not include the waitlist condi- 2016). However, as these meta-analytic findings only pre- tion at T3 as teachers in this condition were offered treat- sent evidence in the context of other intervention compo- ment after T2, so our results need to be confirmed in future nents (Lipsey, 2003), our findings support the importance studies. of testing hypotheses using experimental (microtrial) Further, our findings on masked observations of inatten- designs in order to draw more firm conclusions tion were consistent with effects obtained with teacher rat- on the effectiveness of intervention components (Leijten ings, suggesting that effects on inattention were not affected et al., 2021). Another explanation for the finding that our by possible social desirability and/or investment bias (Daley antecedent- and consequent-based interventions were both et al., 2014; Sonuga-Barke et al., 2013). Compared to the effective compared to waitlist condition with similar effect waitlist condition, observed attention problems decreased sizes, may be that antecedent-based interventions included in the active conditions, confirming the positive (and pro - in the meta-analysis by Gaastra et al. (2016) were mostly tective) effects of the interventions. Intervention effects on general educational accommodations (e.g., extended time) masked hyperactivity-impulsivity were in the same direction of which the evidence base is limited (Lovett & Nelson, as teacher ratings although effects did not reach statistical 2020). Furthermore, most of these antecedent-based inter- significance. This is likely to be explained by the limited ventions were not tailored to individual needs of the child, number of subjects included in our masked analyses, reduc- while included consequent-based interventions were. In ing power. Observed verbal hyperactivity, however, did not the current study, both interventions were tailored to indi- show such a pattern, and even increased in the antecedent vidual needs (using the behavioral analysis), which may condition over time. Although we cannot fully explain this have increased the relative effectiveness of antecedent- finding, this may be related to the low baseline levels of based interventions as compared to consequent-based this behavior in the antecedent condition (5.7%, see Table 2) interventions (Dunlap & Kern, 2018; Harrison et  al., compared to the other conditions, while at T2, group differ - 2019). When comparing the intervention conditions to ences in verbal hyperactivity between conditions were small. the waitlist condition, there were even indications that the Further research in larger samples is needed to conclude on 1 3 878 Research on Child and Adolescent Psychopathology (2022) 50:867–880 the effectiveness of the sets of techniques on masked out- our previously obtained results on a proximal EMA outcome comes of hyperactivity. (Staff et al., 2021). In contrast to ODD behaviors as measured with the daily Importantly, the effect sizes of these brief and individual- EMA ratings (Staff et al., 2021) and meta-analytic results ized interventions on our secondary outcomes appear similar showing effects of behavioral interventions on ODD symp- to those of full and longer interventions often containing toms (Daley et al., 2014; Leijten et al., 2019), we did not both sets of techniques (DuPaul et al., 2012; Evans et al., observe effects of the specific techniques on teacher-rated 2018; Fabiano et al., 2009; Ward et al., 2020). As described ODD symptoms, neither on the short term, nor on the longer previously (Staff et  al., 2021), the current interventions term, nor on classroom observations of oppositional defi- were short and individualized and were based on functional ant behaviors. This may be explained by the current sample behavioral analysis of the child’s problem behavior (FBA; in which children had low levels of baseline ODD symp- Dunlap & Kern, 2018), which may have added to their effec- toms, possibly indicating that there was not enough room tiveness (Chronis et al., 2004). Furthermore, the brief inter- for improvement on ODD behavior. However, given that we ventions seem acceptable and feasible for school based prac- obtained large effects on the daily ratings of oppositional tice as all teachers completed the intervention, the majority behavior assessed with the proximal EMA measure, one may of the teachers reported to use the techniques learned at also argue that a proximal measure such as daily ratings three months follow-up (Staff et al., 2021), and most of the using EMA may be more sensitive to observe effects com- teachers would recommend the training to colleagues. Such pared to measures assessing broadly defined ODD behavior. short individualized interventions well meet teachers’ needs Although the results of our study are promising, there (DuPaul et al., 2019; Egan et al., 2019; Gaastra et al., 2020), are limitations to note. First, this study was powered on our and t fi s with current ADHD guidelines suggesting that envi - primary outcome and therefore power for the secondary out- ronmental modifications are regarded as first-line interven- comes reported here may have been too low (Jakobsen et al., tions prior to more intensified treatment (Akwa GGZ, 2019; 2019), possibly leading to small effects being undetected. National Institute for Health and Care Excellence, 2018). This seems particularly relevant for antecedent versus conse- To increase suitability for schools, both sets of techniques quent comparisons as these are both active conditions. Sec- could be combined into one intervention. For example, a ond, classroom observations were conducted only in a sub- brief and individualized intervention combing the effective set of the sample, given the time-intensive nature of coding sets of techniques can be provided to teachers seeking help of the observations, and may have led to undetected small to cope with the disruptive behavior of an individual student effects. However, the effects obtained for attention problems showing ADHD symptoms (e.g., Tier 2 interventions). were robust and provide important corroborative information Supplementary Information The online version contains supplemen- next to our proximal daily ratings and questionnaire ratings tary material available at https://doi. or g/10. 1007/ s10802- 021- 00892-z . for the effectiveness of both sets of techniques. A third limi- tation is that we have not quantified teacher implementation Acknowledgements We thank all children, parents, and teachers of the techniques in the classroom (neither quality or dose), for participating in this study, and students for their support in data and such it cannot be used as a moderator in the analyses. collection. Fourth, our sample predominantly included children with Funding This work was supported by The Netherlands Organiza- subthreshold ADHD symptoms and low levels of ODD tion for Health Research and Development (ZonMw), grant number symptoms. Although our results provide useful information for children with (subthreshold) ADHD, effects may not be generalizable to children with more severe ADHD and/or Data Availability The data that support the findings of this study are ODD symptoms. Further, our sample was nearly 100% Cau- available from the corresponding author (AS), upon reasonable request. casian and we lack insight into other relevant child (e.g., parental income) and teacher (e.g., race) factors, which may Compliance with Ethical Standards  limit the representativeness or our sample. Ethical Approval The local medical ethical committee waived the need for medical ethical approval (University Medical Center Groningen, Conclusions and Clinical Implications 2016/198). Informed Consent Teachers, parents, and children older than 11 years This randomized controlled microtrial showed that provided written consent. antecedent- and consequent-based techniques are effec- tive in reducing children’s ADHD symptoms in the class- Conflict of Interest The authors report no conflict of interest. room, as assessed by teacher-rated DSM-based measures of ADHD symptoms and functional impairment, as well as masked observations of inattention. These findings extend 1 3 Research on Child and Adolescent Psychopathology (2022) 50:867–880 879 Open Access This article is licensed under a Creative Commons Attri- Egan, T. E., Wymbs, F. A., Owens, J. S., Evans, S. W., Hustus, C., & bution 4.0 International License, which permits use, sharing, adapta- Allan, D. M. (2019). Elementary school teachers’ preferences for tion, distribution and reproduction in any medium or format, as long school-based interventions for students with emotional and behavio- as you give appropriate credit to the original author(s) and the source, ral problems. Psychology in the Schools, 56(10), 1633–1653. provide a link to the Creative Commons licence, and indicate if changes Evans, S. W., Owens, J. S., Wymbs, B. T., & Ray, A. R. (2018). were made. 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Journal

Research on Child and Adolescent PsychopathologySpringer Journals

Published: Jul 1, 2022

Keywords: ADHD; Behavioral teacher training; Antecedent-based techniques; Consequent-based techniques; Microtrial

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