Which outcome is most likely if a school psychologist conducts a stratified random sample for intervention research?

When a school psychologist conducts a stratified random sample for intervention research, the primary benefit is that the findings will be applicable to a broader population. Stratified random sampling involves dividing the population into subgroups (or strata) that share similar characteristics, and then randomly selecting samples from each of these strata. This method ensures that various segments of the population are represented in the study, which enhances the generalizability of the findings to a wider audience.

By ensuring that diverse groups are included in the sample, the research is more likely to capture the variability and complexity of the entire population, resulting in insights that apply beyond just the immediate study group. This approach provides a more comprehensive understanding of how an intervention might work across different contexts and demographics, thereby increasing the relevance of the research outcomes in practical settings.

Other outcomes, such as limited relevance, inconclusive results, or small impact, are less likely when stratified random sampling is used effectively. In fact, these outcomes would typically result from sampling methods that do not adequately represent the population, thereby missing key variables that could influence the effectiveness of an intervention.