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Psychological Methodology

Projects

Projects financed by Third-Party-Funds

  • DiabPeerS

    Diabetes Peer Messaging: Improving glycaemic control in patients with type 2 diabetes mellitus through peer support instant messaging: a randomized controlled trial (diabetes peer messaging)

    • Project Number: LSC18-021
    • Project Lead: Elisabeth Höld, FH St. Pölten / Institute of Health Sciences
    • Project Partner: Karl Landsteiner University of Health Sciences / Division of Internal Medicine 1 (University Hospital St. Pölten), Karl Landsteiner University of Health Sciences / Division Psychological Methodology
    • Duration: 36 months starting from 01.11.2020

    Background

    Diabetes mellitus is one of the four priority non-communicable diseases worldwide. Globally, 425 million adults suffered
    from diabetes mellitus (7.2-11.3%) in 2017 and the International Diabetes Federation estimates an increase of 48% of
    the prevalence until 2045. Type 2 diabetes, which is the most common type of diabetes, is mainly seen in adults older
    than 40 years. Diabetes can lead to serious long-term complications as well as a lower quality of life, worse mental
    health and a reduced life expectancy. These health consequences produce significant health care costs. Due to the
    chronical character of diabetes, the disease requires continuous therapy, regular medical appointments and a good
    adherence of those suffering. Therefore, diabetes self-management education (DSME) plays a significant role to
    increase patient’s self-management capacity and improve diabetes therapy. Research indicates that these outcomes
    might be difficult to maintain and seem to decline soon after DSME ends. Consequently, effective strategies to preserve
    the positive effects of DSME are needed. Preliminary results show that peer support, which means support from a
    person who has experiential knowledge of a specific behaviour or stressor and similar characteristics as the target
    population, is associated with better outcomes in terms of HbA1c, cardiovascular disease risk factors or self-efficacy at
    lower cost compared to standard therapy. Although those results are promising, research on peer support in diabetes
    care is still in its infancy and the influence of various factors is unclear. Peer support instant messaging services (IMS)
    approaches have significant potential for diabetes management because support can be provided easily and prompt, is
    inexpensive and needs less effort to attend compared to standard therapy. Furthermore, almost half of the 40-69 year
    old age group, which is mostly affected by the onset of type 2 diabetes, use IMS.
    Aim
    The major objective of the project is to analyse the impact of a peer supported IMS intervention in addition to a
    standard diabetes therapy on the glycaemic control of type 2 diabetic patients.
    Methods
    A total of 198 participants with type 2 diabetes mellitus, older than 40 years, and insured by the Insurance Company for
    Railways and Mining will be included and randomly assigned to intervention or control group. Both groups will receive
    standard therapy, but the intervention group will use the peer support IMS tool, additionally. The duration of the
    intervention will last for seven months, followed by an follow-up of seven months. Biochemical, behavioural and
    psychosocial parameters will be measured before, in the middle, and after the intervention as well as after the
    follow-up.

  • Wearables

    Experience sampling with wearables: An open-source solution

    • Project Number: P 31800-N38
    • Project Lead: Stefan Stieger, Karl Landsteiner University of Health Sciences / Division Psychological Methodology
    • Duration: 54 months starting from 01.03.2019

    Background

    We all know diaries. They are used to record, capture, and monitor our everyday experiences in our own words and are habitually kept on a daily basis. But diaries are also used in science in order to systematically assess life experiences, mostly in a structured form (closed questions) referring to a specific topic (e.g., well-being). Participants may not just answer questions at the end of the day, but also at any time during the day (so-called event- and time-based sampling). In the past, these scientific diaries were used in printed form. However, due to technical progress, nowadays diaries are also digital, and come in new forms and shapes such as Personal Digital Assistants (also known as PDAs) and smartphones. An even more recent development offers further potential as a technological platform for diary studies – wearables. Currently, wearables are predominantly used in sports to measure heart rate and blood pressure, as a pedometer, or to determine the exact GPS position. Meanwhile, the potential to use wearables for scientific purposes, e.g., data collection in diary studies seems substantial. Wearables offer various major advantages, such as being unobtrusive (important for the direct measurement of sensitive topics), not disturbing our daily routines (important for very frequent daily measurements), and being capable of running autonomously (i.e., independent from smartphones and Internet connections). This being said, the present project sets out to develop an open-source software for scientific purposes which should be easily adaptable (e.g., through further sensors, buttons) and work autonomously while implementing low power consumption and the option to store data locally altogether based on a freely available development board.

Self-financed Projects

ESM Wearable / ESM Board Admin

(c) Mbientlab

MetaWear Admin is a tool for using mbientlab MetaWear boards in experience sampling (ESM) research, which was developed at KL. The app is mainly tested and used with the wearable MetaMotion R. The idea is that researchers can use this tool to configure a device according to their needs (e.g. time/frequency of prompts, vibration, LED lights). The wearable can then be used independently and without having to be connected to a smartphone. All data is stored on the device itself and can be downloaded by reconnecting to the app at a later point in time.

ESMira

The science application ESMira was specially developed at the Karl Landsteiner University of Health Sciences (KL) for scientific ESM studies and is improved steadily by extending the technical possibilities of the tool. The app was developed to fulfil scientific requirements such as the presentation of an informed consent, data security (data is transferred encrypted to the KL server), and anonymity (randomized number of participants). Furthermore, ESMira does not evaluate any sensor data or other personal settings (e.g. the telephone number) or personal settings (e.g., number of apps installed). The app has a number of functions such as personalization of the timing of prompts ("bings") or graphical feedback for participants. It is also possible to send an e-mail to the principal investigator to request further information. Participation in the study can be terminated at any time with the option "quit study".

ESMira can be installed free of charge via the App Store on smartphones with Android operating system or on iPhones via the App Store. Access to projects can be restricted by using keywords (i.e. only participants who know the keyword have access to the study).

TWEETWORKS | cooperation with HTL Krems

The aim of the joint project with the HTL Krems (IT department) was to retrieve Twitter messages that meet certain criteria (searchterm plus geolocation). Past research has shown that the mood of users is reflected in the content of the tweets. The so-called hedonometers were developed through text analysis, i.e. the affective evaluation of individual words in the tweet allows conclusions to be drawn about the mood of the user (e.g., Dodds et al., 2015; for non-geotagged tweets, see Stieger & Swami, 2014). With the present project, it is possible to locate the mood geographically and chronologically.

SATELIFE | cooperation with HTL Krems

The aim of the joint project with the HTL Krems (IT department) was to read out from satellite data of the Sentinel series (3 and 5P) the corresponding values that meet certain criteria (specific area, specific day, etc.). An API of the browser of the Sentinel Hub is used for this purpose.

Sentinel 5P provides high resolution indicators of air pollutants and cloud cover composition up to twice daily for specific locations. The data is freely available online.

The data obtained will later be linked to psychological variables in order to be able to analyse the impact of pollutants etc. on the psyche globally.

Device

Self-report data, i.e., data from classic questionnaires, are repeatedly criticized because they have disadvantages that call the validity of the data into question (e.g., memory bias, social desirability, prerequisite of introspection ability). Non-reactive data can be an important complement to reduce or quantify this negative influence. The following Device will be used to collect social contacts and non-reactively - via the number of smartphones in the immediate environment.

Events

  1. 01 Dec
  2. 15 Dec

    KL Lunchtime Seminar: Towards Natural Killer Cell-Based Immune Therapy in Leukemia

    15. December 2021, 12:00 - 13:00
    Karl Landsteiner University, 3500 Krems/Donau, Wing Y, KL Auditorium
  3. 19 Jan

    KL Lunchtime Seminar: Extramedullary hematopoiesis as part of the innate immune defence against infections

    19. January 2022, 12:00 - 13:00
    Karl Landsteiner University, 3500 Krems/Donau, Wing Y, KL Auditorium