Proactive Automatized Lifestyle Intervention

Study Overview
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Brief Summary
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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.

Official Title
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Proactive Automatized Lifestyle Intervention for Cancer Prevention

Conditions
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Health Risk Behaviors

Intervention / Treatment
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* Behavioral: Proactive Automatized Lifestyle intervention


Participation Criteria
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Eligibility Criteria
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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

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 64 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Prevention
Intervention Model: Single Group Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Computer-generated feedback on health risk behaviors<br>Proactive Automatized Lifestyle intervention Frequency: 3 times (month 0, 1, 3) Dosage: Individually tailored feedback corresponding to about 1-6 pages Duration: 3 months | Behavioral: Proactive Automatized Lifestyle intervention<br>* Multi-behavioral; including individually-tailored, theory-based, repetitive, ipsative and normative feedback.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Intervention reach | Proportion of participants among all eligible patients | Month 0 | 
| Intervention retention | Proportion of participants who continue participation 1 month after hospitalization | Month 1 | 
| Intervention retention | Proportion of participants who continue participation 3 months after hospitalization | Month 3 | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Satisfaction with intervention | Modified and adapted 29-item Multi-Dimensional Measure of Satisfaction with Behavioral Interventions; assessing process (intervention characteristic ratings, dose and format ratings, usage, overall intervention rating) and outcome (discomfort, attribution of outcomes to treatment) | Month 6 | 
| Change in physical activity | European Health Interview Survey-Physical Activity Questionnaire, three additional items | Month 0, 1, 3, 6 | 
| Change in diet | Self-reported number of servings of vegetable and fruit per day; Self-reported intake of fat (gram, kilojoule, kilocalories), fiber (gram), salt (gram) and sugar (gram) per day measured by a 16 item diet screener on the number of servings of vegetable, fruit, other food rich in fiber, sweets, added sugar, sweetened drinks, cheese, convenience food, salted snacks, eggs, fatty fish, red meat, processed meat, butter/ oil, milk and bread per day/ week | Month 0, 1, 3, 6 | 
| Change in alcohol use | Alcohol Use Disorder Identification Test - Consumption; alcohol use in past month | Month 0, 1, 3, 6 | 
| Change in tobacco smoking | Self-reported number of cigarettes per day; smoking status | Month 0, 1, 3, 6 | 
| Change in sum of behavioral health risk factors | Behavioral health risk factors are determined when recommendations (WHO, World Cancer Research Fund, German Center of Addiction Issues) are not met; with the total sum score ranging between 0 and 4 behavioral health risk factors (insufficient physical activity, unhealthy diet, at-risk alcohol use, tobacco smoking) | Month 0, 1, 3, 6 | 
| Change in body-mass-index | Obtained from self-reported body weight and height | Month 0, 6 | 
| Change in general health | 1 item on self-reported health ranging between poor (0) and excellent (4) | Month 0, 6 | 
| Change in mental health | 5-item Mental Health Inventory; Higher scores indicate better mental health | Month 0, 6 | 
| Change in sick days | Number of self-reported sick days past 6 months | Month 0, 6 | 
| Change in stage of change | Behavior-specific staging algorithms based on the transtheoretical model of intentional behavior change (TTM) | Month 0, 1, 3, 6 | 
| Change in decisional balance | Behavior-specific decisional balance questionnaires based on the TTM; higher scores indicate more pros and cons of physical activity / vegetable and fruit intake / alcohol use / tobacco smoking | Month 0, 1, 3, 6 | 
| Change in self-efficacy | Behavior-specific self-efficacy questionnaires based on the TTM; higher scores indicate higher self-efficacy to be physically active / to eat vegetable and fruit / to adhere to alcohol use limits / to refrain from tobacco smoking | Month 0, 1, 3, 6 | 
| Change in processes of change | Behavior-specific processes of change questionnaires based on the TTM; higher scores indicate higher process use in terms of increasing physical activity / eating more vegetable and fruit a day / reducing (or quitting) alcohol use / reducing (or quitting) tobacco smoking | Month 0, 1, 3, 6 |