Browsing by Subject "mobile phone"

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  • Vepsäläinen, Henna; Skaffari, Essi; Wojtkowska, Katarzyna; Barlińska, Julia; Kinnunen, Satu Marjaana; Makkonen, Riikka Kyllikki; Heikkilä, Maria; Lehtovirta, Mikko; Ray, Carola Marie-Lousie; Suhonen, Eira; Nevalainen, Jaakko; Sajaniemi, Nina; Erkkola, Maijaliisa (2022)
    Background: Early childhood education and care (ECEC) centers are ideal venues for food education. As smartphones and tablets are becoming increasingly popular in ECEC centers, technology can be used to deliver such pedagogical content. Evidence suggests that video games can affect fruit and vegetable (FV) consumption among 9-to 12-year-old children, but studies among preschoolers are scarce. Objective: This paper describes the development of the Mole's Veggie Adventures app and its effectiveness in increasing FV acceptance among Finnish and Polish preschoolers aged 3 to 6 years. Methods: A multiprofessional team created an app to be used in ECEC centers in groups of 3 to 10 children. The app aimed to increase vegetable acceptance, and it was built using elements that support the development of self-regulation and social skills. Altogether, 7 Finnish and 4 Polish ECEC centers participated in the study. Before randomization, parents reported background factors and their children's willingness to taste different FVs. The ECEC professionals in the intervention arm were instructed to use the app at least once a week during the 3-to 4-week intervention period. The main outcomes in this unblinded, cluster-randomized study were FV acceptance and relative FV acceptance. The first was calculated as a sum variable describing the children's willingness to taste 25 different FVs, the second as FV acceptance divided by the number of FVs served. We used analysis of covariance to compare the FV acceptance and relative FV acceptance scores between the intervention and control groups at follow-up. Results: A total of 221 children were included in the analysis. At follow-up, the intervention group (115/221, 52%) had higher FV acceptance scores (baseline adjusted difference of mean 7.22; 95% CI 1.41-13.03) than the control group (106/221, 48%). The intervention effect was parallel for relative FV acceptance scores (baseline adjusted difference of mean 0.28; 95% CI 0.05-0.52). Conclusions: The Mole's Veggie Adventures app has the potential to increase FV acceptance among preschoolers and can be a valuable tool in supporting food education in ECEC centers. Furthermore, the app can be feasibly incorporated into preschool routines in countries with different educational environments. Trial Registration: ClinicalTrials.gov NCT05173311; https://tinyurl.com/4vfbh283 (JMIR Mhealth Uhealth 2022;10(1):e30352) doi: 10.2196/30352
  • Kouvonen, Anne; Kemppainen, Laura; Ketonen, Eeva-Leena; Kemppainen, Teemu; Olakivi, Antero; Wrede, Sirpa (2021)
    Background: Previous studies have found that in general, poor health is associated with a lower likelihood of internet use in older adults, but it is not well known how different indicators of health are associated with different types of digital information technology (DIT) use. Moreover, little is known about the relationship between health and the types of DIT use in older ethnic minority and migrant populations. Objective: The aim of this study is to examine the associations among depressive symptoms and self-rated health (SRH) with different dimensions of DIT use in older migrants. Methods: We analyzed data from the Care, Health and Ageing of Russian-speaking Minority (CHARM) study, which is based on a nationally representative sample of community-dwelling, Russian-speaking adults aged 50 years or older residing permanently in Finland (men: 616/1082, 56.93%; age: mean 63.2 years, SD 8.4 years; response rate: 1082/3000, 36.07%). Data were collected in 2019 using a postal survey. Health was measured using depressive symptoms (measured using the Center for Epidemiologic Studies Depression Scale) and SRH. Binary logistic regression analyses were used to investigate the associations between the two health indicators and the following six outcomes: daily internet use, smartphone ownership, the use of the internet for messages and calls, social media use, the use of the internet for personal health data, and obtaining health information from the internet. A number of sociodemographic and socioeconomic factors were controlled for in the logistic regression regression analysis. Analyses were performed with weights accounting for the survey design and nonresponse. Results: After adjusting for sociodemographic and socioeconomic factors, depressive symptoms (odds ratio [OR] 2.68, 95% CI 1.37-5.24; P=.004) and poor SRH (OR 7.90, 95% CI 1.88-33.11; P=.005) were associated with a higher likelihood of not using the internet daily. Depressive symptoms (OR 1.88, 95% CI 1.06-3.35; P=.03) and poor SRH (OR 5.05, 95% CI 1.58-16.19; P=.006) also increased the likelihood of smartphone nonuse. Depressive symptoms were additionally associated with a lower likelihood of social media use, and poor SRH was associated with a lower likelihood of using the internet for messaging and calling. Conclusions: Poor SRH and depressive symptoms are associated with a lower likelihood of DIT use in older adults. Longitudinal studies are required to determine the directions of these relationships.
  • Jauhiainen, Milla; Puustinen, Juha; Mehrang, Saeed; Ruokolainen, Jan; Holm, Anu; Vehkaoja, Antti; Nieminen, Hannu (2019)
    Background: Clinical characterization of motion in patients with Parkinson disease (PD) is challenging: symptom progression, suitability of medication, and level of independence in the home environment can vary across time and patients. Appointments at the neurological outpatient clinic provide a limited understanding of the overall situation. In order to follow up these variations, longer-term measurements performed outside of the clinic setting could help optimize and personalize therapies. Several wearable sensors have been used to estimate the severity of symptoms in PD; however, longitudinal recordings, even for a short duration of a few days, are rare. Home recordings have the potential benefit of providing a more thorough and objective follow-up of the disease while providing more information about the possible need to change medications or consider invasive treatments. Objective: The primary objective of this study is to collect a dataset for developing methods to detect PD-related symptoms that are visible in walking patterns at home. The movement data are collected continuously and remotely at home during the normal lives of patients with PD as well as controls. The secondary objective is to use the dataset to study whether the registered medication intakes can be identified from the collected movement data by looking for and analyzing short-term changes in walking patterns. Methods: This paper described the protocol for an observational case-control study that measures activity using three different devices: (1) a smartphone with a built-in accelerometer, gyroscope, and phone orientation sensor, (2) a Movesense smart sensor to measure movement data from the wrist, and (3) a Forciot smart insole to measure the forces applied on the feet. The measurements are first collected during the appointment at the clinic conducted by a trained clinical physiotherapist. Subsequently, the subjects wear the smartphone at home for 3 consecutive days. Wrist and insole sensors are not used in the home recordings. Results: Data collection began in March 2018. Subject recruitment and data collection will continue in spring 2019. The intended sample size was 150 subjects. In 2018, we collected a sample of 103 subjects, 66 of whom were diagnosed with PD. Conclusions: This study aims to produce an extensive movement-sensor dataset recorded from patients with PD in various phases of the disease as well as from a group of control subjects for effective and impactful comparison studies. The study also aims to develop data analysis methods to monitor PD symptoms and the effects of medication intake during normal life and outside of the clinic setting. Further applications of these methods may include using them as tools for health care professionals to monitor PD remotely and applying them to other movement disorders.
  • Ervasti *, Mari; Kallio *, Johanna; Määttänen *, Ilmari; Mäntyjärvi, Jani; Jokela, Markus (2019)
    Background: Excessive stress has a negative impact on many aspects of life for both individuals and societies, from studying and working to health and well-being. Each individual has their unique level of stress-proneness, and positive or negative outcomes of stress may be affected by it. Technology-aided interventions have potential efficacy in the self-management of stress. However, current Web-based or mobile stress management solutions may not reach the individuals that would need them the most, that is, stress-sensitive people. Objective: The aim of this study was to examine how personality is associated with stress among Finnish university students and their interest to use apps that help in managing stress. Methods: We used 2 structured online questionnaires (combined, n=1001) that were advertised in the University of Helsinki's mailing lists. The first questionnaire (n=635) was used to investigate intercorrelations between the Big Five personality variables (neuroticism, extraversion, openness, agreeableness, and conscientiousness) and other stress-related background variables. The second questionnaire (n=366) was used to study intercorrelations between the above-mentioned study variables and interest in using stress management apps. Results: The quantitative findings of the first questionnaire showed that higher levels of extraversion, agreeableness, and conscientiousness were associated with lower self-reported stress. Neuroticism, in turn, was found to be strongly associated with rumination, anxiety, and depression. The findings of the second questionnaire indicated that individuals characterized by the Big Five personality traits of neuroticism and agreeableness were particularly interested to use stress management apps (r=.27, P Conclusions: Our results indicated that personality traits may have an influence on the adoption interest of stress management apps. Individuals with high neuroticism are, according to our results, adaptive in the sense that they are interested in using stress management apps that may benefit them. On the contrary, low agreeableness may lead to lower interest to use the mobile stress management apps. The practical implication is that future mobile stress interventions should meaningfully be adjusted to improve user engagement and support health even among less-motivated users, for instance, to successfully engage individuals with low agreeableness.
  • Inkinen, Mikko (Helsingfors universitet, 2009)
    Flow experience is often defined either as an experience of high concentration and enjoyment or as a situation, where high challenges are matched with high skills. According to core-emotion theories, the experience of any emotion contains two core emotions: valence and arousal. Through an accurate mathematical model, the present study investigated, whether the experience of concentration and enjoyment is related to situations where both challenge and skills are high and in balance. Further, it was investigated what sort of core emotions are related to differing relationships between challenge and skills. Finally, university students' experiences of their natural study environments were described in terms of core emotions and in terms of relationships between challenge and skills. Participants were 55 university students who participated two weeks research period. Altogether 3367 questionnaire answers were collected with the CASS experience-sampling method, operating in 3G-mobile phones. The relationship between challenge and skills (competence) was defined in an exact way in polar coordinates. An enjoyable and concentrated flow experience was defined as a sum variable of absorption, interest and enthusiasm. Core emotions were calculated with factor analysis from nine emotion variables. As expected, an experience of concentration and enjoyment was, on average, related to the situations where both challenge and skills were high and in balance. This was not, however, the case in every situation. Thus, it should be taken into consideration how flow experience is operationalised in experience sampling studies. When flow experience was defined as a situation of high challenge and high skills, it was often related to high valence and arousal emotions such as excitement or enthusiasm. A happier or a more tranquil enjoyment was related to situations of moderate challenge and high skills. Experiences differed clearly between various natural study environments. At lectures students were often bored or mentally absent, and did not experience challenges. In a small group students were often excited or enthusiastic, and showed optimal balance between challenge and skills. At library students felt satisfied and were engaged in highly challenging work.
  • Kulathinal, Sangita; Joseph, Bijoy; Säävälä, Minna (2019)
    Background: Researchers and activists have expressed concerns over the lack of availability and nonuse of reversible, modern, contraceptive methods in India for decades. New attempts to increase access, availability, and acceptance of reversible contraceptives need to be developed, instead of relying solely on female sterilization. Mobile health (mHealth) initiatives may offer one way to serve underprivileged populations who face challenges in sexual and reproductive health (SRH) in countries such as India. Objective: This study aimed to examine the outcome of an mHealth intervention for enhancing knowledge of, and practices related to, reversible contraceptives in rural Western India. Methods: We implemented a nonrandomized controlled trial (before-and-after study in an intervention area and a control area) in the Indian state of Maharashtra. The intervention in this case was a mobile-based SRH helpline provided by a nongovernmental organization (NGO). Baseline and follow-up surveys were carried out in two government-run primary health center areas, one each in the intervention and control area, and 405 respondents were surveyed in the two rounds. An interview-based structured questionnaire suitable for a low-literacy environment was used to collect data. The effect of the intervention was estimated using logistic regression, adjusted for gender, by calculating robust standard errors to take into account the clustering of individuals by the area (intervention or control). In each regression model, the effect of intervention was estimated by including a term for interaction between the intervention area and the period before and after the intervention. The exponent of the regression coefficient of the interaction term corresponding to the period after the intervention, along with the 95% CI, is reported here. The odds ratio for the control village multiplied by this exponent gives the odds ratio for the intervention village. Calls received in the intervention were recorded and their topics analyzed. Results: The current use of reversible contraception (18% increase in intervention area vs 2% increase in control area; 95% CI) has seen changes. The proportion of respondents who had heard of contraception methods from an NGO rose in the intervention area by 23% whereas it decreased in the control area by 1% (95% CI). However, the general level of awareness of reversible contraception, shown by the first contraceptive method that came to respondents' mind, did not improve. Demand for wider SRH information beyond contraception was high. Men and adolescents, in addition to married women, made use of the helpline. Conclusions: A mobile helpline that one can confidentially approach at a time most convenient to the client can help provide necessary information and support to those who need reversible contraception or other sexual health information. Services that integrate mHealth in a context-sensitive way to other face-to-face health care services add value to SRH services in rural India
  • M-RESIST Grp; Seppala, Jussi; De Vita, Ilaria; Miettunen, Jouko; Isohanni, Matti; Rubinstein, Katya; Feldman, Yoram; Grasa, Eva; Corripio, Iluminada; Berdun, Jesus; D'Amico, Enrico; Bulgheroni, Maria (2019)
    Background: Mobile Therapeutic Attention for Patients with Treatment-Resistant Schizophrenia (m-RESIST) is an EU Horizon 2020-funded project aimed at designing and validating an innovative therapeutic program for treatment-resistant schizophrenia. The program exploits information from mobile phones and wearable sensors for behavioral tracking to support intervention administration. Objective: To systematically review original studies on sensor-based mHealth apps aimed at uncovering associations between sensor data and symptoms of psychiatric disorders in order to support the m-RESIST approach to assess effectiveness of behavioral monitoring in therapy. Methods: A systematic review of the English-language literature, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, was performed through Scopus, PubMed, Web of Science, and the Cochrane Central Register of Controlled Trials databases. Studies published between September 1, 2009, and September 30, 2018, were selected. Boolean search operators with an iterative combination of search terms were applied. Results: Studies reporting quantitative information on data collected from mobile use and/or wearable sensors, and where that information was associated with clinical outcomes, were included. A total of 35 studies were identified; most of them investigated bipolar disorders, depression, depression symptoms, stress, and symptoms of stress, while only a few studies addressed persons with schizophrenia. The data from sensors were associated with symptoms of schizophrenia, bipolar disorders, and depression. Conclusions: Although the data from sensors demonstrated an association with the symptoms of schizophrenia, bipolar disorders, and depression, their usability in clinical settings to support therapeutic intervention is not yet fully assessed and needs to be scrutinized more thoroughly.
  • Asare, Kennedy Opoku; Terhorst, Yannik; Vega, Julio; Peltonen, Ella; Lagerspetz, Eemil; Ferreira, Denzil (2021)
    Background: Depression is a prevalent mental health challenge. Current depression assessment methods using self-reported and clinician-administered questionnaires have limitations. Instrumenting smartphones to passively and continuously collect moment-by-moment data sets to quantify human behaviors has the potential to augment current depression assessment methods for early diagnosis, scalable, and longitudinal monitoring of depression. Objective: The objective of this study was to investigate the feasibility of predicting depression with human behaviors quantified from smartphone data sets, and to identify behaviors that can influence depression. Methods: Smartphone data sets and self-reported 8-item Patient Health Questionnaire (PHQ-8) depression assessments were collected from 629 participants in an exploratory longitudinal study over an average of 22.1 days (SD 17.90; range 8-86). We quantified 22 regularity, entropy, and SD behavioral markers from the smartphone data. We explored the relationship between the behavioral features and depression using correlation and bivariate linear mixed models (LMMs). We leveraged 5 supervised machine learning (ML) algorithms with hyperparameter optimization, nested cross-validation, and imbalanced data handling to predict depression. Finally, with the permutation importance method, we identified influential behavioral markers in predicting depression. Results: Of the 629 participants from at least 56 countries, 69 (10.97%) were females, 546 (86.8%) were males, and 14 (2.2%) were nonbinary. Participants' age distribution is as follows: 73/629 (11.6%) were aged between 18 and 24, 204/629 (32.4%) were aged between 25 and 34, 156/629 (24.8%) were aged between 35 and 44, 166/629 (26.4%) were aged between 45 and 64, and 30/629 (4.8%) were aged 65 years and over. Of the 1374 PHQ-8 assessments, 1143 (83.19%) responses were nondepressed scores (PHQ-8 score = 10), as identified based on PHQ-8 cut-off. A significant positive Pearson correlation was found between screen status-normalized entropy and depression (r=0.14, P Conclusions: Our findings demonstrate that behavioral markers indicative of depression can be unobtrusively identified from smartphone sensors' data. Traditional assessment of depression can be augmented with behavioral markers from smartphones for depression diagnosis and monitoring.
  • Sousa-Pinto, Bernardo; Halonen, Jaana; Anto, Aram; Jormanainen, Vesa; Czarlewski, Wienczyslawa; Bedbrook, Anna; Papadopoulos, Nikolaos G.; Freitas, Alberto; Haahtela, Tari; Anto, Josep M.; Fonseca, Joao Almeida; Bousquet, Jean (2021)
    Background: In contrast to air pollution and pollen exposure, data on the occurrence of the common cold are difficult to incorporate in models predicting asthma hospitalizations. Objective: This study aims to assess whether web-based searches on common cold would correlate with and help to predict asthma hospitalizations. Methods: We analyzed all hospitalizations with a main diagnosis of asthma occurring in 5 different countries (Portugal, Spain, Finland, Norway, and Brazil) for a period of approximately 5 years (January 1, 2012-December 17, 2016). Data on web-based searches on common cold were retrieved from Google Trends (GT) using the pseudo-influenza syndrome topic and local language search terms for common cold for the same countries and periods. We applied time series analysis methods to estimate the correlation between GT and hospitalization data. In addition, we built autoregressive models to forecast the weekly number of asthma hospitalizations for a period of 1 year (June 2015-June 2016) based on admissions and GT data from the 3 previous years. Results: In time series analyses, GT data on common cold displayed strong correlations with asthma hospitalizations occurring in Portugal (correlation coefficients ranging from 0.63 to 0.73), Spain (rho=0.82-0.84), and Brazil (rho=0.77-0.83) and moderate correlations with those occurring in Norway (rho=0.32-0.35) and Finland (rho=0.44-0.47). Similar patterns were observed in the correlation between forecasted and observed asthma hospitalizations from June 2015 to June 2016, with the number of forecasted hospitalizations differing on average between 12% (Spain) and 33% (Norway) from observed hospitalizations. Conclusions: Common cold-related web-based searches display moderate-to-strong correlations with asthma hospitalizations and may be useful in forecasting them.