ObjectiveTo explore ehealth literacy, ability to actively engage with healthcare providers and health system navigation among pregnant immigrant women and their descendants compared with women of Danish origin.Design and settingA cross-sectional survey at antenatal clinics in 2016, Denmark.ParticipantsPregnant women attending antenatal care (n=405).Outcome measuresThe eHealth Literacy Questionnaire (eHLQ) and two domains from the Health Literacy Questionnaire (HLQ): ability to actively engage with healthcare providers and health system navigation. Range of response options for eHLQ (1–4) and HLQ (1–5). With mixed-effect linear regressions, eHLQ and HLQ among immigrants and their descendants compared with women of Danish origin were assessed.ResultsThe response rate was 75%. The overall trend was lower ehealth literacy and HLQ domains among immigrants and their descendants compared with women of Danish origin. For ehealth literacy, the results suggest that challenges related more to digital abilities than motivation, trust and access to technology. The mean ability to engage with digital services was 3.20 (SD 0.44) for women of Danish origin. Non-Western descendants (−0.14, 95% CI −0.31 to 0.02), non-Western (−0.20, 95% CI −0.34 to −0.06) and Western (−0.22, 95% CI −0.39 to −0.06) immigrants had lower adjusted means of this outcome. No differences in motivation to engage with digital services were found for descendants (−0.00, 95% CI −0.17 to 0.17), non-Western (0.03, 95% CI −0.11 to 0.18) or Western (−0.06, 95% CI −0.23 to 0.10) immigrants compared with the mean of the reference (2.85, SD 0.45). Lower ability to engage with healthcare providers was found for non-Western born immigrants (−0.15, CI 95% −0.30 to −0.01) compared with the mean of women with Danish origin (4.15, SD 0.47).ConclusionGenerally, descendant and immigrant women had lower levels of ehealth literacy and health literacy than women of Danish origin. These differences are potentially antecedents of adverse birth outcomes and could inform structural efforts to mitigate health inequalities.

No abstract

Super-resolution techniques are used to reconstruct an image with a high resolution from one or more low-resolution image(s). In this paper, we proposed a single image super-resolution algorithm. It uses the nonlocal mean filter as a prior step to produce a denoised image. The proposed algorithm is based on curvelet transform. It converts the denoised image into low and high frequencies (sub-bands). Then we applied a multi-dimensional interpolation called Lancozos interpolation over both sub-bands. In parallel, we applied sparse representation with over complete dictionary for the denoised image. The proposed algorithm then combines the dictionary learning in the sparse representation and the interpolated sub-bands using inverse curvelet transform to have an image with a higher resolution. The experimental results of the proposed super-resolution algorithm show superior performance and obviously better-recovering images with enhanced edges. The comparison study shows that the proposed super-resolution algorithm outperforms the state-of-the-art. The mean absolute error is 0.021 ± 0.008 and the structural similarity index measure is 0.89 ± 0.08.

BACKGROUND Posttraumatic stress disorder (PTSD) is a common disorder for which more treatment options are needed. Mental health app (mHealth) interventions are promising to patients suffering from PTSD, however, knowledge about mHealth interventions is sparse and primarily based on quantitative studies. OBJECTIVE The aim of this study was to qualitatively explore PTSD patients’ experiences with using a mHealth app as a stand-alone intervention before commencing psychotherapeutic treatment. METHODS Semi-structured interviews were conducted with fourteen partients, who were interviewed six weeks after receiving the app. An inductive analysis style was used and interviews were analyzed using thematic analysis. RESULTS Three overall themes were identified: Use of app, Being a patient and Overall evaluation of the app. Use of the app was described with the subtheme of habits and and the theme of being a patient included the subthemes of negative experiences with the app and being a part of a research project. Use of the app encompassed how psychological factors and technical problems could interfere with the use of the app. Being a patient depicted that the waiting time before starting treatment felt long, and a subgroup of patients experienced feeling worse during this time, which they partly attributed to using the app. Several suggestions of change were described in the overall evaluation of the app. CONCLUSIONS The findings in this study revealed that emotional arousal influenced the use of the app and that it was difficult for patients to establish a habit of using the app thus reflecting the importance of supporting habit formation when implementing an mHealth app into mental health care services. Some patients shared having negative experiences from using the app reflecting the potential harm from having an mHealth app without the support from a clinician. It is therefore recommended to use a blended-care treatment or an approach where mental health care professionals “prescribe” a mHealth app for relevant patients to avoid increased suicidal risk. INTERNATIONAL REGISTERED REPORT RR2-10.2196/preprints.26852