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THEORY-918: Across 642 experimental tests to September 2019, forming implementation intentions improved outcomes, with uncorrected effects on behaviour (d = .27), cognitive performance (.47), affect regulation (.66) and social judgement (.52), but publication bias was substantial: the pooled d = .36 falls to a model-averaged d = .15 under robust Bayesian meta-analysis, which still found extreme evidence of an effect (BF10 = 319), with large heterogeneity

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Properties7
StatusActive
Version2
Tagsmotivation, behavioral-integration, social-science
SourceLIT-1488 — The when and how of planning: Meta-analysis of the scope and components of implementation intentions in 642 tests
Bears onQUESTION-310 — Does the effect of forming implementation intentions stay reliably above zero, and of the same small order, once tests published after September 2019 are added or preregistered multi-site replications are run with correction for publication bias, and does it hold outside the lab and online?
Cited as “corroborated by” byCLAIM-443 — A learned prior over which processes govern, P(g | z, H) ∝ exp(βQ(g, z) + b_H(g, z)), its bias b_H trained by reward-modulated Hebbian updates to the relations by which one process recruits or endorses another, is a candidate mechanism for durable authority and for amortized governance; but persistence is not amortization, which is shown only when earlier work replaces later computation, communication or recruitment, and a prior over authority differs from a prior over actions only when what is appropriate changes
Cited as “extends” byTHEORY-1192 — Across 642 experimental tests to September 2019, forming implementation intentions reliably improved behaviour, cognitive performance, affect regulation and social judgement, but publication bias was substantial: the pooled d = .36 falls to a model-averaged d = .15 under robust Bayesian meta-analysis, with large heterogeneity

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Source

Sheeran, Listrom & Gollwitzer, LIT-1488, read in full in NOTE-1131 from the version of record in KOPS: pp. 168–173, Tables 1 and 2, and p. 183.

What was actually shown

  • Pooled (p. 170). d = .36 [.33, .40] over 642 tests from 294 reports, experimental designs only.
  • Bias (p. 170). Egger’s regression b = 1.06, above the threshold for “substantial” bias; trim and fill .35; robust Bayesian meta-analysis: extreme evidence for an effect, for publication bias and for heterogeneity, model-averaged d = .15 [.08, .22]. “Thus, implementation intentions appear to have a robust impact on outcomes though the effect size is small according to conventional guidelines” (p. 170).
  • By outcome (Table 1, p. 171). Behaviour .27 (k = 301), cognitive performance .47 (k = 204), affect regulation .66 (k = 26), social judgement .52 (k = 20). Vaccination and voting did not differ reliably from zero.
  • By setting (Table 2). Lab .49, field .27; in person .53, online .31; objective outcomes .43, self-report .28.

What could have come out otherwise: the bias correction could have left no effect, as it has for some behavioural interventions in the debate the authors cite (p. 170).

What this does not say

  • That the per-outcome figures are corrected. Only the overall estimate was corrected; Tables 1–4 are uncorrected.
  • That the effect is up to date. The search ends in September 2019 and was not updated (p. 168).
  • How plans work. No mechanism was tested in this review.
  • That the 2006 estimate was wrong in kind. The two sets differ in inclusion (2024 excludes correlational designs and includes schedule plans and non-behavioural outcomes), so the comparison of .65 with .36 is not like for like.

Connections

  • CLAIM-443. The claim grounds part of its case on implementation intentions. The reliable existence of the effect supports the premise that pre-arranged situation–response links change what people do; the small corrected size is a reason not to cite it as large.
  • THEORY-913 holds the 2006 process evidence, which this review does not re-test.

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