When a Statistical Sequence Is Not a Developmental Sequence: A Theory-First Workflow for PROCESS Model 6 in Educational Research

Serial mediation is frequently selected from a statistical template before the ordering of mediators has been adequately justified. This methodological article develops a theory-first workflow for applying Hayes PROCESS Macro Model 6 in educational research and demonstrates the workflow using data from 400 novice public secondary-school teachers in five districts of Selangor, Malaysia. The novice-teacher dataset is used as a worked methodological illustration rather than as the article's primary substantive contribution. Mentoring was specified as the predictor (X), psychological capital as the first mediator (M1), work engagement as the second mediator (M2), and professional identity as the outcome (Y). The analysis used 5,000 bootstrap resamples and 95% confidence intervals. Mentoring was positively associated with psychological capital and work engagement, while psychological capital and work engagement were each positively associated with professional identity conditional on the other variables in the corresponding regression equations. All three specific indirect effects excluded zero: through psychological capital (0.17, 95% CI [0.14, 0.21]), through work engagement (0.13, 95% CI [0.10, 0.17]), and serially through psychological capital and work engagement (0.03, 95% CI [0.02, 0.05]). The remaining direct association between mentoring and professional identity was not statistically significant after accounting for the mediators. The example shows how Model 6 decomposes an overall association into substantively distinct routes, while demonstrating that a statistical sequence does not establish developmental succession. Bootstrap inference quantifies uncertainty in indirect-effect products; it does not establish temporal precedence, eliminate omitted-variable bias, validate measurement, or identify causal mediation effects. Researchers should therefore justify mediator order before estimation, report every constituent path and specific indirect effect, examine credible rival sequences, and reserve causal language for designs that support causal identification and temporal ordering.

PROCESS Macro, serial mediation, novice teachers, psychological capital

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