CClinicalTrials.gg
CompletedNCT04407962PUSHMEUpdated Jul 5, 2023

Primary Care Usage of Health Promoting Messages

An interventional study of SMS group in Hypertension and Cardiovascular Risk Factor, sponsored by Lund University. Completed at 9 sites in Sweden. Open to participants aged 40 Years to 85 Years. Per ClinicalTrials.gov, last updated 2023-07-05.

Sponsored by Lund University · Not applicable, Interventional, and Treatment

Phase
Not applicable
Study type
Interventional
Enrollment
400
Allocation
Randomized
Ages
40 Years to 85 Years
Sex
All
01

Study summary

This project aims to investigate the use of e-health to assist health personnel in primary health care to carry out preventive measures of cardiovascular disease.The primary objective of the study is to examine the impact of lifestyle advices, administered through regularly sent SMS, on hypertension in a primary health care setting. The secondary objective is to evaluate changes in other cardiovascular risk factors and general health, e.g. tobacco use, obesity, blood lipids, HbA1c, self-rated health and health-related quality of life.

Read the detailed description

This is a randomised controlled multi-centre study.The study will involve 400 patients from 9 primary health care centres located in four different regions in Sweden (Region Skåne, Region Kronoberg, Region Stockholm, Västra Götalandsregionen).

Patients in the intervention group will receive SMS messages aiming to remind, encourage and motivate patients to pursue healthy lifestyle changes. After baseline measurement, participants in the intervention group will receive four semi-personalized SMS messages per week for six months, in addition to their usual anti-hypertensive treatment. Each week, the participants will receive SMS from each of the following groups: A. Physical activity, B. Tobacco use, C. Dietary habits, and D. Cardiovascular health in general, except for non-smokers who, instead of the tobacco use-SMS, will get one extra randomly selected SMS.

Included patients that consent to take part in the study will be invited to their primary health care centre for a baseline visit. The following measurements will be assessed by a research assistant: blood pressure (in sitting position after 5 minutes rest; mean of two measurements in a standardized procedure with validated electronic BP devices), BMI and waist-hip circumference. Furthermore, the patients will complete a short questionnaire for evaluation of medical history, medication, tobacco and alcohol use, physical activity level, self-rated health and health-related quality of life. Blood samples for HbA1c and cholesterol will be drawn. Randomization will be performed after completion of baseline assessments and questionnaires. A follow up control will be performed after 6 months with the same assessments as at the baseline visit.

The primary endpoint is change inblood pressure (mmHg). Secondary endpoints are changes in Cholesterol (total cholesterol, high-density lipoprotein [HDL], low-density lipoprotein [LDL]) (mmol/l), Tobacco and alcohol use, BMI (kg/m2), waist circumference, HbA1c (mmol/mol), Self-rated health (five-graded Likert scale), Health related quality of life, as measured by EQ5D-5L, Self-reported physical activity.

The power analysis indicates a sample size of 189 patients in each arm. The calculation is based on an assumed statistical power of 80%, a two-sided test, using a significant level of 5% with a difference of 4 mm Hg between the groups, a standard deviation of 13 mm Hg and a drop out rate of 15%. Data will be analyzed according to the intention-to-treat principle. Differences in mean change of endpoints between intervention and control groups will be calculated by ANCOVA, with baseline values as covariates. Correlation between behavioral change (smoke cessation,increased level of physical activity) and behavioral predictors will be analyzed with logistic regression analysis.

02

Conditions studied

  • Hypertension
  • Cardiovascular Risk Factor

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Keywords

  • Hypertension
  • Text messaging
  • Primary Health Care
  • Health Promotion
  • Cardiovascular Risk Factor
  • Quality of Life
03

In context

Hypertension

6,689 studies on the registry are indexed under Hypertension; 965 are open to participants now.

This study's enrollment of 400 is above the median of 90 across 4,995 interventional studies indexed under Hypertension.

Browse Hypertension studies →

Lead sponsor

Lund University is the lead sponsor of 230 studies on the registry; 37 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
40 Years to 85 Years
Sexes eligible
All
Accepts healthy volunteers
No

Inclusion criteria

  1. Patients with hypertension (defined by the International classification of disease Manual ICD-10, diagnose code I10.9)
  2. 40-85 years
  3. Patient must own a smart mobile phone

Exclusion criteria

Exclusion Criteria:

  1. Blood pressure at baseline visit ≥180/110 mmHg or systolic blood pressure\<120 mmHg
  2. Serious illness with short life expectancy (\<1year)
  3. Predicted inability to comply with the study protocol e.g. language difficulties, interpreter needs, serious cognitive impairment
  4. Pregnancy
05

Study design

Phase
Not applicable
Primary purpose
Treatment
Allocation
Randomized
Intervention model
Parallel assignment
Masking
Triple (Care provider, Investigator, Outcomes assessor)
Enrollment
400 participants (actual)

Study arms

  • Experimental
    SMS group

    Participants in the intervention group will receive four semi-personalized messages per week in addition to their usual care according to the National Board of Health and Welfare guidelines for hypertension treatment.

    Behavioral: SMS group

  • No intervention
    Control group

    The control group will receive usual care according to the National Board of Health and Welfare guidelines for hypertension treatment.

Interventions

  • BehavioralSMS group

    The experimental treatment will consist of health promoting text messages addressing metabolic risk factors associated with cardiovascular disorders in patients with hypertension. The text messages will be developed to support healthy life style changes i.e. regarding general cardiovascular health, tobacco use, physical activity and diet.

06

What researchers measure

Primary outcomes

  1. Change in blood pressure

    Measured by automated devices (mmHg)

    Time frame: six months

Secondary outcomes

  1. Changes in cholesterol

    Measured by blood test, total cholesterol (mmol/l)

    Time frame: six months

  2. Changes in high-density lipoprotein [HDL]

    Measured by blood test, high-density lipoprotein \[HDL\] (mmol/l)

    Time frame: six months

  3. Changes in low-density lipoprotein [LDL]

    Measured by blood test, low-density lipoprotein \[LDL\] (mmol/l)

    Time frame: six months

  4. Changes in tobacco use

    self-reported. Do you smoke?: 1. Yes, 2. No, 3. Previous smoker. Any changes during study period will be registered.

    Time frame: six months

  5. Changes in Blood glucose

    HbA1c

    Time frame: six months

  6. Changes in self-rated health

    five-graded Likert scale from excellent to poor. The question posed is; in general, would you say that you health is excellent, very good, good, fair, or poor?

    Time frame: six months

  7. Changes in self rated quality of life

    EQ5D-5L (EuroQol 5 dimentions).The descriptive system comprises five dimensions: mobility, self-care, usual activities, pain/discomfort and anxiety/depression. Each dimension has 5 levels: no problems, slight problems, moderate problems, severe problems and extreme problems. The EQ VAS records the patient's self-rated health on a vertical visual analogue scale, where the endpoints are labelled 'The best health you can imagine' and 'The worst health you can imagine'.

    Time frame: six months

  8. Changes in level of physical activity

    self-reported physical activity: How much time do you spend during a typical week doing physical exercise, which will make you feel short of breath, such as running, fitness calsses, ball sports? 1. No time, 2. 0-29 min, 3. 30-59 min, 4. 60-120 min, 5.\>120 minHow much time do you spend during a typical week doing everyday exercise, such as walking, cycling, gardening? Adding together all the time (at least 10 minutes at the time) 1. No time, 2. 0-29 min, 3. 30-59 min, 4. 60-119 min, 5. 2-3 h, 6. \>3-5 h, 7. \>5 h

    Time frame: six months

  9. Changes in alcohol use

    self-reported. Do you drink alcohole? (wine, beer or spirits) See explanation of the term "standard glass of alcohole" 1. No, or \<1 glass/w, 2. 1-4 g/w, 3. 5-8 g/w, 4. 9-12 g/w, 5. 13-19 g/w, 6. \>20g/w

    Time frame: six months

07

Study locations

9 sites
  • Bokskogens Health Care Center
    Bara, Sweden
  • Laröds Health Care Center
    Helsingborg, Sweden
  • Vårdcentralen Delfinen
    Höganäs, Sweden
  • Vårdcentralen Nötkärnan
    Kållered, Sweden
  • Nöbbelövs Health Care Center
    Lund, Sweden
  • Rävlanda vårdcentral
    Rävlanda, Sweden
  • Närhälsan Tidaholm
    Tidaholm, Sweden
  • Skärvet Health Care Center
    Växjö, 35236, Sweden
  • Hovshaga Health Care Center
    Växjö, 35261, Sweden
08

References and documents

Publications

  • NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in blood pressure from 1975 to 2015: a pooled analysis of 1479 population-based measurement studies with 19.1 million participants. Lancet. 2017 Jan 7;389(10064):37-55. doi: 10.1016/S0140-6736(16)31919-5. Epub 2016 Nov 16. Erratum In: Lancet. 2020 Sep 26;396(10255):886. doi: 10.1016/S0140-6736(20)31972-3. PubMed 27863813 ↗
  • GBD 2016 Risk Factors Collaborators. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2017 Sep 16;390(10100):1345-1422. doi: 10.1016/S0140-6736(17)32366-8. Erratum In: Lancet. 2017 Oct 14;390(10104):1736. doi: 10.1016/S0140-6736(17)32485-6. Lancet. 2017 Oct 28;390(10106):e38. doi: 10.1016/S0140-6736(17)32649-1. PubMed 28919119 ↗
  • Schillaci G, Pirro M, Vaudo G, Gemelli F, Marchesi S, Porcellati C, Mannarino E. Prognostic value of the metabolic syndrome in essential hypertension. J Am Coll Cardiol. 2004 May 19;43(10):1817-22. doi: 10.1016/j.jacc.2003.12.049. PubMed 15145106 ↗
  • Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart JC, James WP, Loria CM, Smith SC Jr; International Diabetes Federation Task Force on Epidemiology and Prevention; Hational Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; International Association for the Study of Obesity. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009 Oct 20;120(16):1640-5. doi: 10.1161/CIRCULATIONAHA.109.192644. Epub 2009 Oct 5. PubMed 19805654 ↗
  • Grundy SM. Metabolic syndrome update. Trends Cardiovasc Med. 2016 May;26(4):364-73. doi: 10.1016/j.tcm.2015.10.004. Epub 2015 Oct 31. PubMed 26654259 ↗
  • Lindblad U, Ek J, Eckner J, Larsson CA, Shan G, Rastam L. Prevalence, awareness, treatment, and control of hypertension: rule of thirds in the Skaraborg project. Scand J Prim Health Care. 2012 Jun;30(2):88-94. doi: 10.3109/02813432.2012.684207. PubMed 22643153 ↗
  • Cottrell E, Chambers R, O'Connell P. Using simple telehealth in primary care to reduce blood pressure: a service evaluation. BMJ Open. 2012 Oct 31;2(6):e001391. doi: 10.1136/bmjopen-2012-001391. Print 2012. PubMed 23117563 ↗
  • Arambepola C, Ricci-Cabello I, Manikavasagam P, Roberts N, French DP, Farmer A. The Impact of Automated Brief Messages Promoting Lifestyle Changes Delivered Via Mobile Devices to People with Type 2 Diabetes: A Systematic Literature Review and Meta-Analysis of Controlled Trials. J Med Internet Res. 2016 Apr 19;18(4):e86. doi: 10.2196/jmir.5425. PubMed 27095386 ↗
  • Mussener U, Bendtsen M, Karlsson N, White IR, McCambridge J, Bendtsen P. Effectiveness of Short Message Service Text-Based Smoking Cessation Intervention Among University Students: A Randomized Clinical Trial. JAMA Intern Med. 2016 Mar;176(3):321-8. doi: 10.1001/jamainternmed.2015.8260. PubMed 26903176 ↗
  • Bengtsson U, Kjellgren K, Hallberg I, Lindwall M, Taft C. Improved Blood Pressure Control Using an Interactive Mobile Phone Support System. J Clin Hypertens (Greenwich). 2016 Feb;18(2):101-8. doi: 10.1111/jch.12682. Epub 2015 Oct 12. PubMed 26456490 ↗
  • Chow CK, Redfern J, Hillis GS, Thakkar J, Santo K, Hackett ML, Jan S, Graves N, de Keizer L, Barry T, Bompoint S, Stepien S, Whittaker R, Rodgers A, Thiagalingam A. Effect of Lifestyle-Focused Text Messaging on Risk Factor Modification in Patients With Coronary Heart Disease: A Randomized Clinical Trial. JAMA. 2015 Sep 22-29;314(12):1255-63. doi: 10.1001/jama.2015.10945. Erratum In: JAMA. 2016 Mar 8;315(10):1057. doi: 10.1001/jama.2016.0809. PubMed 26393848 ↗
  • Margolis KL, Asche SE, Bergdall AR, Dehmer SP, Maciosek MV, Nyboer RA, O'Connor PJ, Pawloski PA, Sperl-Hillen JM, Trower NK, Tucker AD, Green BB. A Successful Multifaceted Trial to Improve Hypertension Control in Primary Care: Why Did it Work? J Gen Intern Med. 2015 Nov;30(11):1665-72. doi: 10.1007/s11606-015-3355-x. PubMed 25952653 ↗
  • Godin G, Kok G. The theory of planned behavior: a review of its applications to health-related behaviors. Am J Health Promot. 1996 Nov-Dec;11(2):87-98. doi: 10.4278/0890-1171-11.2.87. PubMed 10163601 ↗
  • Johnston DW, Johnston M, Pollard B, Kinmonth AL, Mant D. Motivation is not enough: prediction of risk behavior following diagnosis of coronary heart disease from the theory of planned behavior. Health Psychol. 2004 Sep;23(5):533-8. doi: 10.1037/0278-6133.23.5.533. PubMed 15367073 ↗
  • Palmeira AL, Teixeira PJ, Branco TL, Martins SS, Minderico CS, Barata JT, Serpa SO, Sardinha LB. Predicting short-term weight loss using four leading health behavior change theories. Int J Behav Nutr Phys Act. 2007 Apr 20;4:14. doi: 10.1186/1479-5868-4-14. PubMed 17448248 ↗
  • Owen N, Sugiyama T, Eakin EE, Gardiner PA, Tremblay MS, Sallis JF. Adults' sedentary behavior determinants and interventions. Am J Prev Med. 2011 Aug;41(2):189-96. doi: 10.1016/j.amepre.2011.05.013. PubMed 21767727 ↗

Individual participant data

Plan to share: Yes — Individual participant data that underlie the results, after deidentification (text, tables, figures, and appendices).

Supporting information: Study protocol

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Jul 5, 2023, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT04407962
Lead sponsor
Lund University
Responsible party
Sponsor
First posted
May 29, 2020
Start date
Sep 1, 2020
Primary completion
Jun 15, 2023
Completion
Jun 15, 2023
Last update
Jul 5, 2023

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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This study is completed, as verified in Jul 2023. You cannot join it, but the record below documents what was studied.

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