Surgically-treated Hip Fracture in older People. With Special Emphasis on Mortality Analysis

Hip fractures are associated with significant morbidity and mortality. Cervical and trochanteric fractures have a different morphometry, surgical treatment, and outcome. Polypharmacy, common in older people, is associated with increased mortality. The risk factors for mortality can be identified based on cause-of-death analysis. In this population-based study, 461 older, surgically in 1999-2000 treated hip fracture patients were enrolled. Incidence, morphometry, medication, mortality, and cause-of-death were analysed. Hip fractures were most commonly sustained by women, occurred mostly indoors, and often in institutions. One in four patients had sustained a previous fracture. Routine clinical radiographs revealed no differences in the hip geometry between hip fracture types. Age-adjusted mortality was higher in men than in women during the follow-up. Chronic lung disease and male sex were predictors of mortality after cervical fracture. In men, potent anticholinergics were associated with excess age-adjusted mortality. Men were more likely to die from circulatory disease and dementia after hip fracture than women. Mortality after hip fracture was 3-fold higher than that of the general population, including every cause-of-death class. Fracture prevention in institutions and homes, indoor safety measures, and treatment of chronic lung diseases should be encouraged. Hip morphometry analyses require more accurate measures than that provided by routine radiographs. Careful use of potent anticholinergics may reduce mortality. Compared to the general population, excess mortality after hip fracture was evident up to 9 years after hip fracture. Cause-of-death analysis indicates that all major comorbidities require optimal treatment after hip fracture surgery.

Forecasting with social media – Using Facebook likes to predict the results of the 2015 Finnish Parliamentary elections

Already one-third of the human population uses social media on a daily basis. The biggest social networking site Facebook has over billion monthly users. As a result, social media services are now recording unprecedented amount of data on human behavior. The phenomenon has certainly caught the attention of scholars, businesses and governments alike. Organizations around the globe are trying to explore new ways to benefit from the massive databases. One emerging field of research is the use of social media in forecasting. The goal is to use data gathered from online services to predict offline phenomena. Predicting the results of elections is a prominent example of forecasting with social media, but regardless of the numerous attempts, no reliable technique has been established. The objective of the research is to analyze how accurately the results of parliament elections can be forecasted using social media. The research examines whether Facebook “likes” can be effectively used for predicting the outcome of the Finnish parliament elections that took place in April 2015. First a tool for gathering data from Facebook was created. Then the data was used to create an electoral forecast. Finally, the forecast was compared with the official results of the elections. The data used in the research was gathered from the Facebook walls of all the candidates that were running for the parliament elections and had a valid Facebook page. The final sample represents 1131 candidates and over 750000 Facebook “likes”. The results indicate that creating a forecast solely based on Facebook “likes” is not accurate. The forecast model predicted very dramatic changes to the Finnish political landscape while the official results of the elections were rather moderate. However, a clear statistical relationship between “likes” and votes was discovered. In conclusion, it is apparent that citizens and other key actors of the society are using social media in an increasing rate. However, the volume of the data does not directly increase the quality of the forecast. In addition, the study faced several other limitations that should be addressed in future research. Nonetheless, discovering the positive correlation between “likes” and votes is valuable information that can be used in future studies. Finally, it is evident that Facebook “likes” are not accurate enough and a meaningful forecast would require additional parameters.

Evaluation of Mobile Telephone Text Message Reminders for People with Antipsychotic Medication

Nonadherence to treatment is a worldwide problem among people with severe mental disorders. Patient treatment adherence may be supported with simple reminding methods e.g. text message reminders. However, there is limited evidence of its benefits. Intervention evaluation is essential in mHealth research. Therefore, this evaluative study was conducted. This study aimed to evaluate text message reminder use in encouraging patients’treatment adherence among people with antipsychotic medication. The data were collected between September 2011 and December 2013. First, a systematic literature review revealed that text message reminders were widely used in healthcare. However, its impacts were conflicting. Second, a sub-sample (n = 562) analysis showed that patients preferred humorous text message reminders and preferred to receive them in the morning, at the beginning of the week. Age, gender and marital status seemed to have different effects on the preferred amount and timing of the selected reminders. Third, a cross-sectional survey revealed that people with antipsychotic medication (n = 408) expressed overall satisfaction towards the reminder system. Finally, the evaluative design showed that patient recruitment for a randomized controlled trial concerning people with antipsychotic medication was challenging due to low rates of eligible participants. Follow-up drop-out rates varied depending on the data collection method. Participants’ demographic characteristics were associated with the risk of dropping out from the trial. This study suggests that text messages are a potential reminder system in healthcare services among people with antipsychotic medication. More research is needed to gain a comprehensive picture of the impacts and effectiveness of text message reminders.