A Natural Experiment Created by Pandemic Restriction: Comparing In-Person, Hybrid, & Teletherapy Formats

The FL-REACH intervention for families in early stage post-dementia diagnosis was originally adapted from the REACH II program for use in an outpatient clinic. Pandemic restrictions forced an adaptation to a teletherapy format. The timing of changes allowed comparison of caregivers who participated in clinic (n=10), switched modalities mid-treatment (n=7), and participated as teletherapy (n=14). Groups were similar in age range, gender, and relationship, with both spouses and adult children participating. Participants in the fully online group were more likely than others to have high school or trade school education than to have graduated from college. All participants in the in-person and hybrid groups had incomes over $40,000/year, while 36% of the online sample had less household income, were more likely to be Hispanic-identifying (43% versus 6%), and had higher burden scores (M=41.43 versus M=32.56 in person, M=29.86 hybrid) and lower preparedness scores (M=19.86 versus M=22.90 in person, M=28.14 hybrid) at baseline (p<.05). The intervention proceeded with the same intervention dosage (8 hours total), and outcomes were essentially comparable, with all groups showing statistically significant improvement on measures of preparedness, burden, and risk. While in-person intervention helped strengthen relationships with the medical team, inclusion of family via telehealth provided opportunity for a more culturally responsive and inclusive engagement, although there remain questions regarding reasons for differences at baseline. Identification of differences in key outcomes for direct comparisons between in-person, hybrid, and teletherapy interventions are limited in the evidence base, making this a unique study at an important moment in time.

Evaluating RNR-Based Targeted Treatment and Intervention Dosage in the Context of Traumatic Exposure

Best practices in juvenile justice call for the individualized matching of services to assessed dynamic risk factors, with services delivered at sufficient dosage. However, prior work has largely ignored whether this recipe for recidivism reduction is as effective for adolescents with extensive traumatic exposure as it is for those without. The current study leverages a statewide sample of 1,666 juveniles released from residential placement (84.6% male, 59.8% Black, 11.9% Hispanic). We examine the associations of individual-level service matching and achieving dosage targets established by Lipsey’s Standardized Program Evaluation Protocol (SPEP) during residential placement with changes in dynamic risk during placement and recidivism post-release among juveniles with extensive adverse childhood experiences (ACE) exposure and those without. Results demonstrate heightened traumatic exposure is related to smaller reductions in dynamic risk and to an increased probability of reoffending, but that youth receiving matched services coupled with adequate dosage leads to greater treatment progress (dynamic risk reduction) and lower recidivism post-release for both low-ACE and high-ACE youth. Implications for juvenile justice practice and policy are discussed.

Process evaluation of the Cancer Home-Life Intervention: What can we learn from it for future intervention studies?

Background: The Cancer Home-Life Intervention showed no significant effects, and examination of the processes affecting or inhibiting outcomes is relevant. Aim: To evaluate the Cancer Home-Life Intervention for its processes of implementation, mechanisms of impact and contextual factors. Design: Process evaluation conducted alongside the randomised controlled trial, using quantitative and qualitative methods (ClinicalTrials.gov NCT02356627). The Cancer Home-Life Intervention is a tailored, occupational therapy–based programme. Setting/participants: This study took place in participants’ homes and at hospital. A total of 113 home-dwelling adults (⩾18 years) with advanced cancer who had received the Cancer Home-Life Intervention were included, together with five intervention-therapists. Results: All 113 participants (100%) received a first home visit; 32 participants (26%) received a second visit; and 4 participants (3%) received a third visit. Median number of delivered intervention components were 3 (interquartile range: 2; 4). Identified barriers for effect included unclear decision process for intervention dosage; participants’ low expectations; participants’ lack of energy; and insufficient time to adopt new strategies. The trial design constituted a barrier as the intervention could only be provided within a specific short period of time and not when relevant. Intervention components working to solve practical everyday problems, enhance enjoyment and increase a sense of safety were perceived as useful. Conclusion: Future interventions can benefit from inclusion criteria closely related to the intervention focus and clear procedures for when to continue, follow-up and terminate intervention. Decisions about dose and timing may benefit from learning theory by taking into account the time and practice needed to acquire new skills.

Tracking Intervention Dosage to Inform Instructional Decision Making

Intervention dosage is an often-overlooked aspect of implementation fidelity. Tracking intervention dosage is critical for ensuring students with disabilities were present for and received the intervention for as many minutes as intended. Used in tandem with student performance data, intervention dosage can provide a clearer picture of intervention success. This article presents strategies for how teachers can plan for, collect, and use intervention dosage data to inform instructional data-based decision making.

Teaching higher order thinking skills to gifted students: A meta-analysis

The current study examined the effects of higher order thinking skills (HOTS) interventions with gifted students in Taiwan. A total of 25 studies published between 1997 and 2017 were included. Twenty-nine effect sizes were extracted for the 25 studies. The small number of existing studies indicates a lack of scholarly attention to HOTS in gifted education in Taiwan in the past two decades. On the other hand, the effect sizes, ranged from 0.26 to 2.01, with a mean of 0.78 and standard deviation of 0.39, showed moderately large effect sizes for these interventions, which can be interpreted as evidence for general effectiveness. Subgroup analyses indicated that intervention effects did not vary significantly by grade level, type of program, intervention dosage, and type of dissemination. However, a statistically significant difference was found between the effect sizes in different types of instructional design (i.e. stand-alone HOTS unit vs. integrated HOTS unit). Implications are discussed.

Classification Agreement for Gated Screening in Mathematics: Subskill Mastery Measurement and Classwide Intervention

This study examined the classification accuracy for subskill mastery measures administered in mathematics for students in kindergarten and Grades 1, 3, 5, and 7 at fall ( n = 564) and winter ( n = 602) screening. In addition, response to classwide math intervention was examined as another layer of screening for students in kindergarten and Grades 1, 3, and 5 ( n = 387). Criterion measures were the year-end accountability measure for math in Grades 3, 5, and 7. For kindergarten and Grade 1 a researcher-constructed composite measure was used. For all measures (screening and criterion), 20th percentile performance was the risk criterion. Authors hypothesized that classwide intervention response would provide more accurate identification of risk than fall or winter screening. Receiver operating characteristic (ROC)–generated sensitivities and specificities supported this hypothesis. Data indicated that intervention dosage was adequate and did reduce the base rate of risk in each screening group. Posttest probabilities indicated that subskill mastery measures and response to classwide intervention could be used to accurately indicate math risk and the need for more intensive intervention for students in a multitier system of supports (MTSS) model.