ArticleConnections (Toronto, Ont.)2024
Contagion and Interpersonal Influence: Distinguishing Mechanisms of Behavior Change Using Social Network Theory.
Article in Connections (Toronto, Ont.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Article
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
The present paper articulates the many ways social network researchers conceptualize and operationalize network influences on people's behaviors. Four categories of network influences are described: (1) personal network, (2) positional, (3) network-level, and (4) individual network-level interactions. Personal network effects are based on data from the individual's direct and indirect contacts. Positional effects are derived from the individual's position in the network such as being central or peripheral. Network-level effects are measured using network-level indicators such as centralization or clustering. Interaction effects occur when there is consideration of both the individual and network level measures such as understanding the influence of being in a central position in a centralized or decentralized network. These various network effects are contrasted with contagion, which is the most frequently used mechanism for diffusion. One conclusion drawn from this review is that when we invoke contagion explanations, we give agency to the product, whereas when we invoke interpersonal influence explanations, we give agency to people and social systems.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.