Evidence map›Paper›PMID 29752248›Full record

ArticleJournal of medical Internet research2018

Psychobehavioral Profiles to Assist Tailoring of Interventions for Patients With Hypertension: Latent Profile Analysis.

Rika Tanaka, Robert P Nolan

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01541540 (Reducing Risk With E-based Support for Adherence to Lifestyle Change in Hypertension), which is not on this map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 20% of its field
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.

NCT01541540 nacompletednot on this map

Reducing Risk With E-based Support for Adherence to Lifestyle Change in Hypertension

TypeinterventionalSponsorUniversity Health Network, TorontoRan2012 to 2016Enrolled264ConditionsHypertensionArmse-Counseling plus Usual Care, Control
3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. From optimistic to overwhelmed: exploring health beliefs and barriers to oral anticancer medication adherence among cancer survivors.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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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

2 authors at 1 institution in 1 country.

Rika TanakaCardiac eHealth and Behavioural Cardiology Research Unit, Peter Munk Cardiac Centre, University Health Network, Toronto, ON, Canada.ORCID 0000-0002-8278-4704
Robert P NolanCardiac eHealth and Behavioural Cardiology Research Unit, Peter Munk Cardiac Centre, University Health Network, Toronto, ON, Canada.ORCID 0000-0002-5170-9840
University Health Network · CA

Funding

CIHR
6 · The paper itself

Abstract

backgroundPractice guidelines advocate combining pharmacotherapy with lifestyle counseling for patients with hypertension. To allow for appropriate tailoring of interventions to meet individual patient needs, a comprehensive understanding of baseline patient characteristics is essential. However, few studies have empirically assessed behavioral profiles of hypertensive patients in Web-based lifestyle counseling programs.

objectiveThe objectives of this study were to (1) specify baseline psychobehavioral profiles of patients with hypertension who were enrolled in a Web-based lifestyle counseling trial, and (2) examine mean differences among the identified profile groups in demographics, psychological distress, self-reported self-care behaviors, physiological outcomes, and program engagement to determine prognostic implications.

methodsParticipants (N=264; mean age 57.5 years; 154/264, 58.3% female; 193/264, 73.1% white) were recruited into a longitudinal, double-blind, randomized controlled trial, designed to evaluate an online lifestyle intervention for hypertensive patients. A series of latent profile analyses identified psychobehavioral profiles, indicated by baseline measures of mood, motivation, and health behaviors. Mean differences between profile groups were then explored.

resultsA 2-class solution provided the best model fit (the Bayesian information criterion (BIC) is 10,133.11; sample-size adjusted BIC is 10,006.54; Lo-Mendell-Rubin likelihood ratio test is 65.56, P=.001). The 2 profile groups were (1) adaptive adjustment, marked by low distress, high motivation, and somewhat satisfactory engagement in health behaviors and (2) affectively distressed, marked by clinically significant distress. At baseline, on average, affectively distressed patients had lower income, higher body mass index, and endorsed higher stress compared with their adaptive adjustment counterparts. At 12-months post intervention, treatment effects were sustained for systolic blood pressure and Framingham risk index in the adaptive adjustment group, and those in the adaptive adjustment group were 2.4 times more likely to complete the 12-month intervention study, compared with their affectively distressed counterparts.

conclusionsInterventions for patients who are adaptively adjusted may differ in focus from those designed for the affectively distressed patients. As such, this study underscores the importance of identifying psychobehavioral profiles, as they allow for evidence-based tailoring of lifestyle counseling programs for patients with hypertension.

trial registrationClinicalTrials.gov NCT01541540; https://clinicaltrials.gov/ct2/show/NCT01541540 (Archived by WebCite at http://www.webcitation.org/6yzZYZcWF).

Indexed as

Health BehaviorDouble-Blind MethodFemaleHumansHypertensionInternetMaleMiddle Agedcounselingdepressionhealth behaviorhypertensionlifestyle

Identifiers

PMID29752248
PMCPMC5970280
OpenAlexW2802362694

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.