Terveyden edistäminen on kunnan tehtävä

Ensisijainen vastuu terveyden edistämisestä on kunnalla. Kunnassa tehdään päätökset siitä, miten terveyden edistäminen toteutuu kunnan alueella

Short Text Messages to Encourage Adherence to Medication and Follow-up for People With Psychosis (Mobile.Net): Randomized Controlled Trial in Finland

Background: A text messaging service (short message service [SMS]) has the potential to target large groups of people with long-term illnesses such as serious mental disorders, who may have difficulty with treatment adherence. Robust research on the impact of mobile technology interventions for these patients remains scarce.Objective: The main objective of our study was to investigate the impact of individually tailored short text messages on the rate of psychiatric hospital readmissions, health care service use, and clinical outcomes. In addition, we analyzed treatment costs.Methods: Between September 2011 and November 2012, we randomly assigned 1139 people to a tailored text message intervention (n=569) or usual care (n=570). Participants received semiautomated text messages for up to 12 months or usual care. The primary outcome, based on routinely collected health register data, was patient readmission into a psychiatric hospital during a 12-month follow-up period. Secondary outcomes were related to other service use, coercion, medication, adverse events, satisfaction, social functioning, quality of life, and economic factors (cost analysis).Results: There was 98.24% (1119/1139) follow-up at 12 months. Tailored mobile telephone text messages did not reduce the rate of hospital admissions (242/563, 43.0% of the SMS group vs 216/556, 38.8% of the control group; relative risk 1.11; 95% CI 0.92-1.33; P=.28), time between hospitalizations (mean difference 7.0 days 95% CI –8.0 to 24.0; P=.37), time spent in a psychiatric hospital during the year (mean difference 2.0 days 95% CI –2.0 to 7.0; P=.35), or other service outcomes. People who received text messages were less disabled, based on Global Assessment Scale scores at the time of their readmission, than those who did not receive text messages (odds ratio 0.68; 95% CI 0.47-0.97; P=.04). The costs of treatment were higher for people in the SMS group than in the control group (mean €10,103 vs €9210, respectively, PConclusions: High-grade routinely collected data can provide clear outcomes for pragmatic randomized trials. SMS messaging tailored with the input of each individual patient did not decrease the rate of psychiatric hospital visits after the 12 months of follow-up. Although there may have been other, more subtle effects, the results of these were not evident in outcomes of agreed importance to clinicians, policymakers, and patients and their families.</p

What do individuals with schizophrenia need to increase their well-being

The aim of this qualitative study was to deepen the knowledge of how individuals with schizophrenia themselves describe what they need in order to increase their well-being in everyday life. Seven patients were interviewed. An open explorative approach was applied and grounded theory was used for the analysis resulting in five categories illustrating how patients with schizophrenia handle their struggle for a normal life. The patients stressed first the importance of receiving information about the disease: for themselves, for society, and for their families. Taking part in social contacts such as attending meeting places and receiving home visits were identified as important as well as having meaningful employment. They also pointed out the importance of taking part in secure professional relationships. Mainly they expressed the need for continuity in the relationships and the wish to be heard and seen by the professionals. Finally, interviewees addressed the need for support for sustaining independent living through practical housekeeping and financial help. To conclude, the participants in the present study described their need for help as mainly linked to activities in their overall life situation rather than just their psychosis

We All Know How, Don’t We? On the Role of Scrum in IT-Offshoring

Part 2: Creating Value through Software DevelopmentInternational audienceOffshoring in the IT-industry involves dual interactions between a mother company and an external supplier, often viewed with an implicit perspective from the mother company. This article review general off shoring and IT offshoring literature, focusing on the proliferation of a globally available set of routines; Scrum and Agile. Two cases are studied; a small company and short process and a large mother company with a long process. The interactions of the set ups shows that global concepts like Scrum and Agile are far from a common platform. The “well known” concepts are locally shaped and the enterprises have mixed experiences

Connectivity to computers and the Internet among patients with schizophrenia spectrum disorders: a cross-sectional study

Maritta V&auml;lim&auml;ki,1&ndash;3 Lauri Kuosmanen,1,4,5 Heli H&auml;t&ouml;nen,1 Marita Koivunen,1,6 Anneli Pitk&auml;nen,7 Christina Athanasopoulou,1 Minna Anttila1 1Department of Nursing Science, Faculty of Medicine, University of Turku, Finland; 2Development Unit, Turku University Hospital, Turku, Finland; 3School of Nursing, Hong Kong Polytechnic University, Kowloon, Hong Kong, SAR, China; 4University of Helsinki and Helsinki University Hospital, Helsinki, Finland; 5Social and Healthcare Department, City of Vantaa, Vantaa, Finland; 6Administrative Centre, Research and Development, Satakunta Hospital District, Pori, Finland; 7Administration Centre, Pirkanmaa Hospital District, Tampere, Finland Purpose: Information and communication technologies have been developed for a variety of health care applications and user groups in the field of health care. This study examined the connectivity to computers and the Internet among patients with schizophrenia spectrum disorders (SSDs).Patients and methods: A cross-sectional survey design was used to study 311 adults with SSDs from the inpatient units of two psychiatric hospitals in Finland. The data collection lasted for 20 months and was done through patients&rsquo; medical records and a self-reported, structured questionnaire. Data analysis included descriptive statistics.Results: In total, 297 patients were included in this study (response rate =96%). More than half of them (n=156; 55%) had a computer and less than half of them (n=127; 44%) had the Internet at home. Of those who generally had access to computers and the Internet, more than one-fourth (n=85; 29%) used computers daily, and &gt;30% (n=96; 33%) never accessed the Internet. In total, approximately one-fourth of them (n=134; 25%) learned to use computers, and less than one-third of them (n=143; 31%) were known to use the Internet by themselves. Older people (aged 45&ndash;65 years) and those with less years of education (primary school) tended not to use the computers and the Internet at all (P&lt;0.001), and younger people and those with higher education were associated with more active use.Conclusion: Patients had quite good access to use computers and the Internet, and they mainly used the Internet to seek information. Social, occupational, and psychological functioning (which were evaluated with Global Assessment of Functioning) were not associated with access to and frequency of computer and the Internet use. The results support the use of computers and the Internet as part of clinical work in mental health care. Keywords: digital divide, technology, mental illness, psychosis, surve

Quality of monitoring for cellular networks

Abstract 5G networks and beyond introduce a larger number of Network Elements (NEs) and functions than former cellular generations. The increase in NEs will, thus, result in significantly increasing the Management-Plane (M-Plane) data collected from the NEs. Therefore, the conventional centralized Network Management Systems (NMSs) will face fundamental challenges in processing the M-Plane data. In this paper, we present the concept of Quality of Monitoring (QoM) as a solution, which is able to reduce the M-Plane data already at the NEs. First, QoM aggregates the raw M-Plane data into Key Performance Indicators (KPIs). To these KPIs, the QoM applies a data-driven algorithm to define information loss limits for QoM classes specific for each KPI time series. Then, the QoM applies the classes for compressing the KPI data utilizing a lossy-compression method, which is a derivative of the Piece-Wise Constant Approximation (PWCA) algorithm. To evaluate the performance of the QoM solution, we use M-Plane raw data from a live LTE network and calculate four KPIs, while each KPI has different statistical characteristics. We also define three QoM classes named Exact, Optimized, and Sharp. For all KPIs, the class Optimized has a higher compression rate than the class Exact, while the class Sharp has the highest compression rate. Assuming that, for example, NEs of a network produce 280 MB of raw data containing information that needs to be transferred to the network operations center; we use KPIs to represent the information contents of the data, and QoM solution to transfer the data over the network. As a result, the QoM solution achieves an estimated 95% compression gain from the raw data in transfer