Observational Measures of Parent-Child Interaction used with Neurodivergent Parents or Infants: A Systematic Review

Background: Parent-child interaction (PCI) in early childhood plays a key role in children's development. Despite the importance of such interactions for child outcomes, it is possible that observational PCI measures are only suitable for use with neurotypical dyads and are less appropriate when applied to neurodivergent samples (e.g. those who are autistic or have ADHD). Methods: A systematic review of observational PCI measures used with neurodivergent children or parents where the child was aged between 9- and 48-months was conducted. Results: Out of 294 eligible papers, only 19 noted that the PCI measure used had been developed or adapted to ensure that it was appropriate for use with neurodivergent participants. No coding schemes were developed using participatory methods and only one protocol was developed in consultation with the neurodivergent community. Conclusions: Future research should involve the neurodivergent community to develop new PCI measures that are suitable for samples that include neurodivergent individuals, or validate existing measures to check they are appropriate for such samples. Furthermore, researchers need to consider the neurotype of the parent, as well as the child, when applying PCI measures

Diffuse reflectance mid-infrared spectroscopy is viable without fine milling

While diffuse reflectance Fourier transform mid-infrared spectroscopy (mid-DRIFTS) has been established as a viable low-cost surrogate for traditional soil analyses, the assumed need for fine milling of soil samples prior to analysis is constraining the commercial appeal of this technology. Here, we reevaluate this assumption using a set of 2380 soil samples collected across North American agricultural soils. Cross-validation indicated that the best preprocessing (standard normal variate) and model form (memory-based learning) resulted in very good and nearly identical predictions for the <2 mm preparation and fine-milled preparation of these soils for total organic carbon (TOC), clay, sand, pH and bulk density (BD). Application of larger models built from the USDA NRCS mid-DRIFTS library also resulted in minimal performance differences between the two sample preps. Lower predictive performance of the existing library was attributed to less-than-perfect spectral representativeness of the library. Regardless of model form, there was very little variability between replicates of the <2 mm prep, suggesting that the lack of fine milling did not lead to more heterogeneous subsamples. Additionally, there was no relationship between residual error and soil texture, implying these results should be robust across most soil types. Overall, in agreement with other recent findings, these results suggest that routine scanning of standard <2 mm preparation does not degrade predictive performance of mid-DRIFTS-based inference systems. With good standard operating procedures including quality control and traditional analysis on a small percent of samples, mid-DRIFTS can become a routine tool in commercial soil laboratories

Validating DayCent-CR for cropland soil carbon offset reporting at a national scale

Regenerative soil management practices have been shown to increase soil organic carbon in cropland previously under conventional management, and farmers that adopt regenerative practices could be eligible to participate in carbon offset programs. Due to the high cost of soil sampling at large scales, project developers of agricultural carbon offset programs may employ a hybrid measurement and modeling approach to SOC quantification. While biogeochemical models allow for carbon crediting to occur on larger scales than soil sampling alone would allow, any model used must be unbiased and shown to adequately predict SOC changes, with known uncertainty, across the crops, practice changes, and geographies of interest. The “credit-ready” version of the DayCent ecosystem model, DayCent-CR, was evaluated for performance across 14 combinations of crops and practice categories. Model calibration and validation was performed with a Bayesian Markov chain Monte Carlo approach using k-fold cross validation and 668 SOC stock change measurements from 41 agricultural research sites. Overall model performance met the guidelines established by Climate Action Reserve’s Soil Enrichment Protocol: ≥90% of model prediction intervals covered the measured value, and mean bias in all categories was less than pooled measurement uncertainty. Importantly, posterior distributions of DayCent-CR parameters and variance components enable the calculation of variance, which can then be used to calculate an uncertainty deduction that is applied to overall project credits to ensure conservatism. The calibrated model parameters are therefore valid for use in crediting programs within the domain of the validation dataset

Predicting breakfast consumption: An application of the theory of planned behaviour and the investigation of past behaviour and executive function

Objectives. The objective of the current study is to examine the determinants of breakfast consumption with the application of the Theory of Planned Behaviour (TPB; 1991) and investigate the additional variables of past behaviour and executive function. Design. A prospective 1-week study investigating the predictive ability of TPB variables, past behaviour and executive function was utilized. Methods. Ninety-six participants were administered two measures of executive function (response inhibition and planning) and completed self-report questionnaires regarding their attitudes, subjective norms, perceived control, intentions and past behaviour of breakfast consumption. One week later, participants returned a follow-up questionnaire on their behaviour. Results. The result of the study showed that the TPB significantly predicted intentions and prospective behaviour of breakfast consumption, however, past behaviour was found to be the strongest predictor of future behaviour. Considering executive function, response inhibition was not found to predict behaviour, however, planning ability explained unique variance in behaviour and moderated the association between intention and behaviour. Conclusions. The findings support the use of the TPB in explaining breakfast eating habits, and suggest that executive function of planning may be somewhat useful to predict this behaviour. The significance of past behaviour also suggests that breakfast consumption may commonly be a stable, habitual behaviour that may undermine the need for self-regulation. Implications for creating behavioural-change interventions are discussed