Clinical trial · Interventional
Proactive Automatized Lifestyle Intervention
Proactive Automatized Lifestyle Intervention for Cancer Prevention
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Background: The co-occurrence of health risk behaviors (HRBs), namely of tobacco smoking, insufficient physical activity, unhealthy diet and at-risk alcohol use, more than doubles the risk of cancer, other chronic diseases and mortality; and applies to more than half of adult general populations. However, preventive measures that target all four HRBs and that reach the majority of the target populations and particularly those persons most in need and hard to reach (e.g. with low socio-economic status), are scarce. Electronic interventions may help to efficiently address multiple HRBs in whole populations, such as health care patients. The aim is to investigate the acceptance of a proactive and brief electronic multiple behavior change intervention among general hospital patients with regards to reach, retention, equity in reach and retention, satisfaction and subsequent trajectories of behavior change motivation, HRBs and health. Methods: A pre-post-intervention study with four time points will be conducted at a general hospital in Germany. Patients admitted to participating medical departments (internal medicine, general surgery, trauma surgery, ear-nose-throat medicine) and aged 18-64 years will be systematically approached and invited to participate, irrespective of reason for admission and HRB profile. Based on HRB profile and on psychological behavior change theory, participants (n=175) will receive individualized computer-generated feedback concerning all four HRBs and motivation-enhancing feedback for up to two HRBs; directly on the ward and 1 and 3 months later. Intervention reach and retention will be determined by the proportion of participants among eligible patients and participants, respectively. Equity in reach and retention will be measured with regards to school education and other socio-demographics. To investigate satisfaction with the intervention and trajectories of motivational measures, HRBs and health measures, a 6-month follow-up will be conducted. Descriptive statistics, multivariate regressions and latent growth modelling will be applied. Discussion: This study will be the first to investigate the acceptance of a proactive, electronic and brief multiple behavior change intervention among general hospital patients. If reach is high and efficacy established by a randomized controlled trial, the intervention has potential for public health impact in terms of primary and secondary prevention of diseases.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Health Risk Behaviors | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Proactive Automatized Lifestyle intervention | Behavioral | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- type
- EXPERIMENTAL
- label
- Computer-generated feedback on health risk behaviors
- description
- Proactive Automatized Lifestyle intervention Frequency: 3 times (month 0, 1, 3) Dosage: Individually tailored feedback corresponding to about 1-6 pages Duration: 3 months
- interventionNames
- Behavioral: Proactive Automatized Lifestyle intervention
Primary outcomes (3)
- measure
- Intervention reach
- timeFrame
- Month 0
- description
- Proportion of participants among all eligible patients
- measure
- Intervention retention
- timeFrame
- Month 1
- description
- Proportion of participants who continue participation 1 month after hospitalization
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
- Maximum age
- 64 Years
Show eligibility criteria text
Inclusion Criteria: \- General hospital patients admitted to participating wards of four medical departments (internal medicine, surgical medicine, trauma medicine, ear-nose-throat) at the University Medicine Hospital Greifswald in northeastern Germany Exclusion Criteria: * Cognitively or physically incapable * Presence of a highly infectious disease * Discharge or transferral within the first 24 hours * Already asked for participation during previous hospital stay * Insufficient language skills * Employed at the conducting research institute * Neither telephone nor email
References
Publications (4)
- DERIVEDTimm C, Tiede A, Krolo-Wicovsky F, Spielmann M, Bischof G, Meyer C, John U, Freyer-Adam J. General hospital patients' satisfaction with a proactive automatized multiple health behavior change intervention. BMC Health Serv Res. 2025 Sep 23;25(1):1209. doi: 10.1186/s12913-025-13425-x. PMID 40988066
- DERIVEDSpielmann M, Krolo-Wicovsky F, Tiede A, John U, Freyer-Adam J. Proactive automatized multiple health risk behavior change intervention: reach and retention among general hospital patients. Eur J Public Health. 2025 Aug 1;35(4):635-641. doi: 10.1093/eurpub/ckaf035. PMID 40101761
- DERIVEDTimm C, Krolo-Wicovsky F, Tiede A, Spielmann M, Gaertner B, John U, Freyer-Adam J. General hospital patients' attitude towards systematic health risk behavior screening and intervention. BMC Public Health. 2024 Oct 18;24(1):2877. doi: 10.1186/s12889-024-20410-2. PMID 39425090
- DERIVEDFreyer-Adam J, Krolo F, Tiede A, Goeze C, Sadewasser K, Spielmann M, Krause K, John U. Proactive automatised lifestyle intervention (PAL) in general hospital patients: study protocol of a single-group trial. BMJ Open. 2022 Sep 19;12(9):e065136. doi: 10.1136/bmjopen-2022-065136. PMID 36123081