Patients with cardiovascular risk factors can reduce their risk of cardiovascular disease by increasing their physical activity and their physical fitness. According to the guidelines for cardiovascular risk management, health professionals should encourage their patients to engage in physical activity. In this paper, we provide insight regarding the systematic development of a Web-based intervention for both health professionals and patients with cardiovascular risk factors using the development method Intervention Mapping. The different steps of Intervention Mapping are described to open up the “black box” of Web-based intervention development and to support future Web-based intervention development.
Background: In face-to-face therapy for eating disorders, therapeutic alliance (TA) is an important predictor of symptomreduction and treatment completion. To date, however, little is known about TA during web-based cognitive behavioral therapy(web-CBT) and its association with symptom reduction, treatment completion, and the perspectives of patients versus therapists.Objective: This study aimed to investigate TA ratings measured at interim and after treatment, separately for patients andtherapists; the degree of agreement between therapists and patients (treatment completers and noncompleters) for TA ratings;and associations between patient and therapist TA ratings and both eating disorder pathology and treatment completion.Methods: A secondary analysis was performed on randomized controlled trial data of a web-CBT intervention for eatingdisorders. Participants were 170 females with bulimia nervosa (n=33), binge eating disorder (n=68), or eating disorder nototherwise specified (n=69); the mean age was 39.6 (SD 11.5) years. TA was operationalized using the Helping AllianceQuestionnaire (HAQ). Paired t tests were conducted to assess the change in TA from interim to after treatment. Intraclasscorrelations were calculated to determine cross-informant agreement with regard to HAQ scores between patients and therapists.A total of 2 stepwise regressive procedures (at interim and after treatment) were used to examine which HAQ scores predictedeating disorder pathology and therapy completion.Results: For treatment completers (128/170, 75.3%), the HAQ-total scores and HAQ-Helpfulness scores for both patients andtherapists improved significantly from interim to post treatment. For noncompleters (42/170, 24.7%), all HAQ scores decreasedsignificantly. For all HAQ scales, the agreement between patients and therapists was poor. However, the agreement was slightlybetter after treatment than at interim. Higher patient scores on the helpfulness subscale of the HAQ at interim and after treatmentwere associated with less eating disorder psychopathology. A positive association was found between the HAQ-total patientscores at interim and treatment completion. Finally, posttreatment HAQ-total patient scores and posttreatment HAQ-Helpfulnessscores of therapists were positively associated with treatment completion.Conclusions: Our study showed that TA in web-CBT is predictive of eating disorder pathology and treatment completion. Ofparticular importance is patients’ confidence in their abilities as measured with the HAQ-Helpfulness subscale when predictingposttreatment eating disorder pathology and treatment completion.
Hoogwaardig afvalhout van bewoners, bouwbedrijven en meubelmakers blijft momenteel ongebruikt omdat het te arbeidsintensief is om grote hoeveelheden ongelijke stukken hout van verschillende afmetingen en soorten te verwerken. Waardevol hout wordt waardeloos afval, tegen de principes van de circulaire economie in. In CW.Code werken Powerhouse Company, Bureau HUNC en Vrijpaleis samen met de HvA om te onderzoeken hoe een toegankelijke ontwerptool te ontwikkelen om upcycling en waardecreatie van afvalhout te faciliteren. In andere projecten hebben HvA en partners verschillende objecten gemaakt van afvalhout: een stoel, een receptiebalie, kleine meubels en objecten voor de openbare ruimte, vervaardigd met industriële robots. Deze objecten zijn 3D gemodelleerd met behulp van specifieke algoritmen, in de algemeen gebruikte ontwerpsoftware Rhino en Grasshopper. De projectpartners willen nu onderzoeken hoe deze algoritmen via een toegankelijke tool bruikbaar te maken voor creatieve praktijken. Deze tool integreert generatieve ontwerpalgoritmen en regelsets die rekening houden met beschikbaar afvalhout, en de ecologische, financiële en sociale impact van resulterende ontwerpen evalueren. De belangrijkste ontwerpparameters kunnen worden gemanipuleerd door ontwerpers en/of eindgebruikers, waardoor het een waardevol hulpmiddel wordt voor het co-creëren van circulaire toepassingen voor afvalhout. Dit onderzoek wordt uitgevoerd door HvA Digital Production Research Group, met bovengenoemde partners. HUNC heeft ervaring met stadsontwikkeling waarbij gebruik wordt gemaakt van lokaal gekapt afvalhout. Vrijpaleis biedt toegang tot een actieve, lokale community van makers met een sterke band met buurtbewoners. Powerhouse Company heeft ervaring in het ontwerpen met hout in de bouw. Alle drie kunnen profiteren van slimmere circulaire ontwerptools, waarbij beschikbaar materiaal, productiebeperkingen en impactevaluatie worden geïntegreerd. De tool wordt ontwikkeld en getest voor twee designcases: een binnenmeubelobject en een buitengevelelement. Bevindingen hiervan zullen leidend zijn bij de ontwikkeling van de tool. Na afronding van het project is een bètaversie gereed voor validatie door ontwerpers, bewonerscollectieven en onderzoek/onderwijs van de HvA.
A huge amount of data are being generated, collected, analysed and distributed in a fast pace in our daily life. This data growth requires efficient techniques for analysing and processing high volumes of data, for which preserving privacy effectively is a crucial challenge and even a key necessity, considering the recently coming into effect privacy laws (e.g., the EU General Data Protection Regulation-GDPR). Companies and organisations in their real-world applications need scalable and usable privacy preserving techniques to support them in protecting personal data. This research focuses on efficient and usable privacy preserving techniques in data processing. The research will be conducted in different directions: - Exploring state of the art techniques. - Designing and applying experiments on existing tool-sets. - Evaluating the results of the experiments based on the real-life case studies. - Improving the techniques and/or the tool to meet the requirements of the companies. The proposal will provide results for: - Education: like offering courses, lectures, students projects, solutions for privacy preservation challenges within the educational institutes. - Companies: like providing tool evaluation insights based on case studies and giving proposals for enhancing current challenges. - Research centre (i.e., Creating 010): like expanding its expertise on privacy protection technologies and publishing technical reports and papers. This research will be sustained by pursuing following up projects actively.
