Theory & Hypotheses (commres-theory-building)

SkillDev tools

Use when building the theoretical argument and hypotheses of a Communication Research (CR) manuscript into a testable, mechanism-level contribution. CR rewards explicit constructs, a stated communication process, and numbered hypotheses with mediation/moderation, not a bare effect. Structures the argument; it does not run analyses.

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Theory & Hypotheses (commres-theory-building) skill

What this skill tells your AI

The instructions your AI receives, as published by brycewang-stanford/awesome-journal-skills in Communication-Research-Skills/skills/commres-theory-building/SKILL.md and read by ahel’s review.

At CR a result is not a contribution until it is attached to a testable communication mechanism. This skill turns an idea into theory: precise constructs, an explicit process, and numbered hypotheses that the design will test. CR is a hypothetico-deductive journal — a paper that documents an effect without a tested mechanism rarely clears the bar.

When to trigger

  • The empirics are strong but the "so what / why" is thin
  • A reviewer said the paper is "atheoretical," "ad hoc," or "just a main effect"
  • You need to state constructs, mechanisms, and predictions explicitly before collecting data
  • Connecting your work to (or extending) an established communication theory

Build the argument (theory → mechanism → hypotheses)

  1. Concept. Define the key constructs precisely (e.g., exposure, framing, presence, perceived norms); distinguish each from its near neighbors so measurement is unambiguous.
  2. Mechanism. State the communication process: who sends/receives what, through which channel, with what cognitive/affective/social step that produces the outcome. This is the mediator.
  3. Boundary conditions. Name the moderators — which audiences, messages, and contexts strengthen or reverse the effect. CR rewards "for whom / when," not just "whether."
  4. Hypotheses. Translate the mechanism into explicit, numbered hypotheses (and research questions where theory is thin): H1 (effect), H2 (mediation path), H3 (moderation). These become the tests in commres-research-design and commres-data-analysis.

The mediation/moderation core (CR-specific)

CR is the home of process models — message → mediator → outcome, conditioned by moderators. State the causal ordering the model assumes and how the design licenses it: a mediator measured on the same cross-sectional wave as the outcome cannot carry a causal-process claim (defer the temporal warrant to design). Pre-specify the indirect-effect test; do not fit a PROCESS model post hoc and narrate it as theory.

The theory-contribution bar at CR (calibration anchor, hedged)

A common substantive rejection is "theory cited but not advanced." Citing a theory is not moving it. Calibrate where a paper sits:

LevelWhat the paper does to theoryCR verdict (typical)
Appliesuses an existing framing/priming/cultivation account as-israrely enough alone
Extendsadds a moderator/boundary condition to a known effectcompetitive if consequential
Specifiesopens a mediating process a prior account left as a black boxstrong fit
Adjudicatespits two mechanisms and lets the data choosehigh-end contribution

The bar is the tested theoretical move, not the method. A heuristic, not an editorial rule.

Reviewer-pushback patterns and the theory-level fix

Referee commentUnderlying gapFix at the argument stage
"Theory cited but not advanced"applies, does not extendname the boundary or black box the study opens
"Effect without a mechanism"no mediatorstate the cognitive/affective/social step and a mediation hypothesis
"Why doesn't this travel?"boundary conditions absentspecify moderators where the effect holds and breaks
"Construct slippage"measured thing isn't the constructre-anchor the definition; split from neighbors; revisit the scale
"HARKing suspected"hypotheses look post hocpreregister; present theory before results, RQs where theory is thin

Worked micro-example: from effect to mechanism (illustrative)

A study finds gain-framed vaccine messages raise intention more than loss-framed ones — a bare effect. Lifted to a CR argument: framing shifts perceived response-efficacy (mediator, H2), which raises intention (H1); the path is stronger for low-prior-knowledge audiences (moderator, H3). The constructs are defined and distinguished from "perceived threat," the indirect effect is pre-specified with bootstrap CIs, and the moderator gives a "for whom" — a portable, tested mechanism rather than a re-documented framing effect.

Anti-patterns

  • "Hypothesizing after results are known" (HARKing) — state hypotheses before tests; preregister
  • A main effect with no mediator/moderator — CR wants the process and the boundary
  • Mechanisms named but never made into a testable, numbered hypothesis
  • Universal claims with no boundary conditions (which audiences? which messages? which contexts?)
  • A PROCESS model whose causal ordering the design cannot support

Output format

【Core claim】one sentence
【Mechanism】the communication process (the mediator)
【Constructs】defined + distinguished from neighbors
【Hypotheses】H1 (effect) / H2 (mediation) / H3 (moderation) → research-design
【Boundary conditions】which audiences / messages / contexts
【Causal-ordering warrant】how the design licenses the process claim
【Next】commres-research-design

Supplementary resources

Signals

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Item type
skill
Key
commres-theory-building
Source
github.com/brycewang-stanford/awesome-journal-skills