Evidence map›Paper›PMID 32692740›Full record

ArticlePloS one2020

Determinants of lifestyle counseling and current practices: A cross-sectional study among Dutch general practitioners.

Lisanne Kiestra, Iris A C de Vries, Bob C Mulder

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Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

3 authors.

Lisanne KiestraStrategic Communication, Department of Social Sciences, Wageningen University & Research, Wageningen, The Netherlands.
Iris A C de VriesVereniging Arts en Leefstijl, Utrecht, The Netherlands.
Bob C MulderStrategic Communication, Department of Social Sciences, Wageningen University & Research, Wageningen, The Netherlands.ORCID 0000-0003-0357-1370

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to examine the amount of lifestyle counseling that Dutch general practitioners (GPs) generally provide to their patients, as well as the behavioral determinants of their lifestyle counseling practices. Lifestyle counseling was defined and operationalized through the 5As model (i.e. Assess, Advise, Agree, Assist and Arrange), while determinants were based on an adapted version of the theory of planned behavior. A cross-sectional study was conducted among a sample of 198 GPs, using an online survey questionnaire for collecting data. The results showed that 79.3% of the GPs assessed patients' current lifestyle often or always, while 60.1% reported they often or always assessed patients' motivation to improve their lifestyle. Depending on the lifestyle behavior, Advising to improve lifestyle ranged from 42.5% (sleep) to 92.4% (smoking), while Agree to set goals ranged from 21.7% (sleep) to 46.9% (smoking). Assisting patients to overcome barriers to lifestyle changes varied per patient barrier, ranging from lack of financial resources (25.7%) to stress (81.8%). The findings from the linear hierarchical regression revealed that GPs' self-efficacy (β = .46, p < .001), patient norm (β = .21, p < .001), and attitude (β = .20, p < .05) were the determinants with the strongest associations with lifestyle counseling. The full model explained 47% of the variance in counseling lifestyle. Implications for supporting GPs to counsel patients about their lifestyle are discussed.

Indexed as

Attitude of Health PersonnelHealth BehaviorHealth Knowledge, Attitudes, PracticeLife StyleAdultAgedCounselingCross-Sectional StudiesFemaleGeneral PractitionersHumansMaleMiddle AgedPractice Patterns, Physicians'Surveys and Questionnaires

Identifiers

PMID32692740
PMCPMC7373284

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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.