Evidence map›Paper›PMID 42204082›Full record

ArticleJournal of prevention (2022)2026

Understanding Underinvestment in Prevention: A Behavioral Perspective.

Mohammad Ali Jamali, Hatra Voghouei

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of prevention (2022), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Mohammad Ali JamaliKeiser University, Tampa Campus, 5002 W Waters Ave, Tampa, FL, 33634, USA. mohammad.jamali@keiseruniversity.edu.ORCID http://orcid.org/0000-0003-1535-8542
Hatra VoghoueiKeiser University, New Port Richey Campus, 6300 US-19, New Port Richey, FL, 34652, USA.ORCID http://orcid.org/0000-0002-9610-5346

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although many preventive health interventions are highly cost-effective, participation and sustained engagement remain below recommended levels. This paper advances prevention science by offering a behavioral explanation for underinvestment in prevention at the level of individual preventive behavior, specifically, participation and adherence, rather than system-level funding decisions. Drawing on behavioral economics, it integrates two well-supported mechanisms, present bias and mental accounting, to explain failures both in initiating preventive actions and in maintaining them over time. The central argument is that underinvestment reflects a dual-margin behavioral problem. Mental accounting shapes whether individuals perceive preventive services as affordable in terms of monetary, time, effort, and psychological costs, even in settings where financial prices are zero or services are publicly funded. Present bias influences effort and persistence by causing individuals to overweight immediate inconveniences relative to future health benefits. By explicitly distinguishing individual-level decision-making from policy maker behavior, the framework clarifies its scope and avoids conflating distinct decision problems. Distinguishing between initiation and follow-through helps explain why many prevention policies increase uptake without producing sustained behavior change. The paper offers a conceptual framework for interpreting mixed findings in prevention research and develops testable predictions about when it is better to focus on participation versus adherence.

Indexed as

Behavioral frictionMental accountingPresent biasPreventive behavior

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.