The effect of educational text message based on health belief model on osteoporosis preventive behaviors in women: a randomized controlled clinical trial.
Leila ParandehFahimeh Sehhati ShafaieJamileh MalakoutiFatemeh RashidiMohammad Asghari JafarabadiPublished in: Women & health (2019)
The purpose of this study was to investigate the effect of educational text messages, based on the health belief model, on osteoporosis preventive behaviors among women aged 30-45 years. This trial was conducted on 121 women from November until September 2017 in Shabestar, Iran. The intervention group received a daily educational text message about osteoporosis for one month, and the control group received educational text messages on frequently occurring cancers in women. Two months after the training, data were collected using the osteoporosis health belief scale, a food frequency questionnaire and the International Physical Activity Questionnaire. No significant differences were observed at baseline between the two groups, except for the perceived benefits construct. After the intervention, controlling for baseline score and adjusting for educational level, a statistically significant difference was observed between the two groups in HBM structures and nutrition performance, while no significant difference was observed in physical activity between the two groups. This study showed that educational text messages can be effective in increasing awareness, perceived susceptibility and severity, and nutritional behavior change related to risk of osteoporosis.
Keyphrases
- physical activity
- postmenopausal women
- polycystic ovary syndrome
- bone mineral density
- mental health
- smoking cessation
- healthcare
- public health
- pregnancy outcomes
- randomized controlled trial
- depressive symptoms
- cervical cancer screening
- clinical trial
- body mass index
- health information
- cross sectional
- breast cancer risk
- insulin resistance
- metabolic syndrome
- risk assessment
- pregnant women
- human health
- machine learning
- type diabetes
- electronic health record
- artificial intelligence
- big data
- skeletal muscle
- patient reported
- mass spectrometry