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Background: Swedish municipalities are facing demographic challenges due to the growing number of older people and the resulting increased need for health care services. Welfare technologies are being launched as possible solutions for meeting some of these challenges.

Objective: The aim of this study was to explore the perception, experimentation, evaluation, and procurement of welfare technology practices among professionals working in municipal elder care in relation to their gender, age, and profession.

Methods: Data for this explorative cross-sectional study were collected from 393 responses to a web-based survey on municipal elder care in Sweden. Chi square tests were performed to determine the associations.

Results: The results revealed gender, age, and professional differences in perspectives of municipal elder care workers. Differences were particularly evident in attitudes toward technology, both the use of technology in general and in the workplace, and involvement and participation in decision making regarding the procurement of new welfare technologies. Men (37/53, 70%) expressed a more positive attitude toward and curiosity regarding new technologies than women (157/336, 46.7%) (P=.03). Regarding age, the younger respondents (18-24 years old) perceived the digital transformation in the workplace as “too slow” (4/4, 100%), whereas the majority of older respondents (65-74 years old) perceived it as happening at the “right pace” (4/7, 57%). The elder care personnel felt encouraged by management to explore and experiment with new welfare technologies, but never did so either for management or with patients. Even though the majority of the respondents were women, more men (4/7, 57%) were involved in the procurement process for welfare technology devices and solutions than women (98/336, 29.2%) (P<.001).

Conclusions: Personnel working within municipal elder care were generally very positive toward new technologies. However, both gender and age differences may influence these perspectives such as the personnel’s resistance to welfare technology and patients’ participation in welfare technology usage and deployment. Different levels of participation in the decision-making process regarding new technology deployment may negatively affect the overall digital transformation within municipal elder care.

Background: Many studies rely on self-reported anthropometric data. While paper-based self-reports have been the standard collection mode, the number of studies collecting self-reported data via the Web is increasing rapidly. Although numerous studies have shown good agreement between self-reported and measured weight using paper-based questionnaires, the validity of using the Web to inquire about weight is unknown. Objective: The objective of this study was to validate Web-based self-reports of bodyweight compared to weight measured at the study center. Methods: The validity of weight self-reported via the Web was assessed by comparing self-reports against measurements of weight in a convenience sample of 149 individuals (77.2% women, 115/149), aged 20-65 years. Study participants self-reported their weight via a Web-based questionnaire and thereafter had their weight measured in the research center. Results: The Spearman correlation coefficient between self-reported and measured weight was 0.98 (P<.001). The mean difference between self-reported and measured weight was -1.2 (SD 2.6) kg. There was a statistically significant difference between self-reported and measured weight with the self-reported being lower (P<.001). Subjects with a body mass index (BMI) >= 25 kg/m(2), and subjects >= 30 years of age, under-reported their weight statistically significantly more than subjects with a BMI <25 kg/m(2), and subjects <30 years of age, respectively. Conclusions: Our results show that self-reported weight via the Web can be a valid method of data collection.

Background: Increased use of the Internet provides new opportunities for collecting data in large studies. The aim of our new Web-based questionnaire, Active-Q, is to assess total physical activity and inactivity in adults. Active-Q assesses habitual activity during the past year via questions in four different domains: (1) daily occupation, (2) transportation to and from daily occupation, (3) leisure time activities, and (4) sporting activities. Objective: The objective of our study is to validate Active-Q's energy expenditure estimates using the doubly labeled water (DLW) method, and to assess the reproducibility of Active-Q by comparing the results of the questionnaire completed by the same group on two occasions. Methods: The validity and reproducibility of Active-Q were assessed in a group of 37 individuals, aged 20 to 65 years. Active-Q was distributed via email to the participants. The total energy expenditure of the participants was assessed using DLW for 11 consecutive days. Results: The median time to complete Active-Q was 6.1 minutes. The majority of participants (27/37, 73%) reported that the questionnaire was "easy" or "very easy" to answer. On average, Active-Q overestimated the total daily energy expenditure by 440 kJ compared with the DLW. The Spearman correlation between the two methods was r = 0.52 (P < .001). The intraclass correlation coefficient for total energy expenditure between the results of Active-Q completed on two occasions was 0.83 (95% CI 0.73-0.93). Conclusions: Active-Q is a valid and reproducible method of assessing total energy expenditure. It is also a user-friendly method and suitable for Web-based data collection in large epidemiological studies.

Background: The meal-and Web-based food frequency questionnaires, Meal-Q and MiniMeal-Q, were developed for cost-efficient assessment of dietary intake in epidemiological studies. Objective: The objective of this study was to evaluate the relative validity of micronutrient and fiber intake assessed with Meal-Q and MiniMeal-Q. The reproducibility of Meal-Q was also evaluated. Methods: A total of 163 volunteer men and women aged between 20 and 63 years were recruited from Stockholm County, Sweden. Assessment of micronutrient and fiber intake with the 174-item Meal-Q was compared to a Web-based 7-day weighed food record (WFR). Two administered Meal-Q questionnaires were compared for reproducibility. The 126-item MiniMeal-Q, developed after the validation study, was evaluated in a simulated validation by using truncated Meal-Q data. Results: The study population consisted of approximately 80% women (129/163) with a mean age of 33 years (SD 12) who were highly educated (130/163, 80% with >12 years of education) on average. Cross-classification of quartiles with the WFR placed 69% to 90% in the same/adjacent quartile for Meal-Q and 67% to 89% for MiniMeal-Q. Bland-Altman plots with the WFR and the questionnaires showed large variances and a trend of increasing underestimation with increasing intakes. Deattenuated and energy-adjusted Spearman rank correlations between the questionnaires and the WFR were in the range rho=.25-.69, excluding sodium that was not statistically significant. Cross-classifications of quartiles of the 2 Meal-Q administrations placed 86% to 97% in the same/adjacent quartile. Intraclass correlation coefficients for energy-adjusted intakes were in the range of .50-.76. Conclusions: With the exception of sodium, this validation study demonstrates Meal-Q and MiniMeal-Q to be useful methods for ranking micronutrient and fiber intake in epidemiological studies with Web-based data collection.

Background: Meal-Q and its shorter version, MiniMeal-Q, are 2 new Web-based food frequency questionnaires. Their meal-based and interactive format was designed to promote ease of use and to minimize answering time, desirable improvements in large epidemiological studies. Objective: We evaluated the validity of energy and macronutrient intake assessed with Meal-Q and MiniMeal-Q as well as the reproducibility of Meal-Q. Methods: Healthy volunteers aged 20-63 years recruited from Stockholm County filled out the 174-item Meal-Q. The questionnaire was compared to 7-day weighed food records (WFR; n=163), for energy and macronutrient intake, and to doubly labeled water (DLW; n=39), for total energy expenditure. In addition, the 126-item MiniMeal-Q was evaluated in a simulated validation using truncated Meal-Q data. We also assessed the answering time and ease of use of both questionnaires. Results: Bland-Altman plots showed a varying bias within the intake range for all validity comparisons. Cross-classification of quartiles placed 70%-86% in the same/adjacent quartile with WFR and 77% with DLW. Deattenuated and energy-adjusted Pearson correlation coefficients with the WFR ranged from r=0.33-0.74 for macronutrients and was r=0.18 for energy. Correlations with DLW were r=0.42 for Meal-Q and r=0.38 for MiniMeal-Q. Intraclass correlations for Meal-Q ranged from r=0.57-0.90. Median answering time was 17 minutes for Meal-Q and 7 minutes for MiniMeal-Q, and participants rated both questionnaires as easy to use. Conclusions: Meal-Q and MiniMeal-Q are easy to use and have short answering times. The ranking agreement is good for most of the nutrients for both questionnaires and Meal-Q shows fair reproducibility.

BACKGROUND: GPS alarms aim to support users in independent activities. Previous systematic reviews have reported a lack of clear evidence of the effectiveness of GPS alarms for the health and welfare of users and their families and for social care provision. As GPS devices are currently being implemented in social care, it is important to investigate whether the evidence of their clinical effectiveness remains insufficient. Standardized evidence frameworks have been developed to ensure that new technologies are clinically effective and offer economic value. The frameworks for analyzing existing evidence of the clinical effectiveness of GPS devices can be used to identify the risks associated with their implementation and demonstrate key aspects of successful piloting or implementation.

OBJECTIVE: The principal aim of this study is to provide an up-to-date systematic review of evidence based on existing studies of the effects of GPS alarms on health, welfare, and social provision in the care of older adults compared with non-GPS-based standard care. In addition, the study findings were assessed by using the evidence standards framework for digital health technologies (DHTs) established by the National Institute for Health and Care Excellence (NICE) in the United Kingdom.

METHODS: This review was conducted according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Primary studies published in peer-reviewed journals and gray literature from January 2005 to August 2020 were identified through searches in 13 databases and several sources of gray literature. Included studies had individuals (aged ≥50 years) who were receiving social care for older adults or for persons with dementia; used GPS devices as an intervention; were performed in Canada, the United States, European Union, Singapore, Australia, New Zealand, Hong Kong, South Korea, or Japan; and addressed quantitative outcomes related to health, welfare, and social care. The study findings were analyzed by using the NICE framework requirements for active monitoring DHTs.

RESULTS: Of the screened records, 1.6% (16/986) were included. Following the standards of the NICE framework, practice evidence was identified for the tier 1 categories Relevance to current pathways in health/social care system and Acceptability with users, and minimum evidence was identified for the tier 1 category Credibility with health, social care professionals. However, several evidence categories for tiers 1 and 2 could not be assessed, and no clear evidence demonstrating effectiveness could be identified. Thus, the evidence required for using DHTs to track patient location according to the NICE framework was insufficient.

CONCLUSIONS: Evidence of the beneficial effects of GPS alarms on the health and welfare of older adults and social care provision remains insufficient. This review illustrated the application of the NICE framework in analyses of evidence, demonstrated successful piloting and acceptability with users of GPS devices, and identified implications for future research.

BACKGROUND: The need to assess the effectiveness and value of interventions involving digital health and health and welfare technologies is becoming increasingly important due to the rapidly growing development of these technologies and their areas of application. Systematic reviews of scientific literature are a mainstay of such assessment, but publications outside the realm of traditional scientific bibliographic databases-known as gray literature-are often not included. This is a disadvantage, particularly apparent in the health and welfare technology (HWT) domain. OBJECTIVE: The aim of this article is to investigate the significance of gray literature in digital health and HWT when reviewing literature. As an example, the impact of including gray literature to the result of two systematic reviews in HWT is examined. METHODS: In this paper, we identify, discuss, and suggest methods for including gray literature sources when evaluating effectiveness and appropriateness for different review types related to HWT. The analysis also includes established sources, search strategies, documentation, and reporting of searches, as well as bias and credibility assessment. The differences in comparison to scientific bibliographic databases are elucidated. We describe the results, challenges, and benefits of including gray literature in 2 examples of systematic reviews of HWT. RESULTS: In the 2 systematic reviews described in this paper, most included studies came from context-specific gray literature sources. Gray literature contributed to the overall result of the reviews and corresponded well with the reviews' aims. The assessed risk of bias of the included studies derived from gray literature was similar to the included studies from other types of sources. However, because of less standardized publication formats, assessing and extracting data from gray literature studies were more time-consuming and compiling statistical results was not possible. The search process for gray literature required more time and the reproducibility of gray literature searches were less certain due to more unstable publication platforms. CONCLUSIONS: Gray literature is particularly relevant for digital health and HWT but searches need to be conducted systematically and reported transparently. This way gray literature can broaden the range of studies, highlight context specificity, and decrease the publication bias of reviews of effectiveness of HWT. Thus, researchers conducting systematic reviews related to HWT should consider including gray literature based on a systematic approach.

Background: An increasing number of patients expect and want to play a greater role in their treatment and care decisions. This emphasizes the need to adopt collaborative health care practices, which implies collaboration among interprofessional health care teams and patients, their families, caregivers, and communities. In recent years, digital health technologies that support self-care and collaboration between the community and health care providers (ie, participatory health technologies) have received increasing attention. However, knowledge regarding the features of such technologies that support effective patient-professional partnerships is still limited. Objective: This study aimed to map and assess published studies on participatory health technologies intended to support partnerships among patients, caregivers, and health care professionals in chronic care, focusing specifically on identifying the main features of these technologies. Methods: A scoping review covering scientific publications in English between January 2008 and December 2020 was performed. We searched PubMed and Web of Science databases. Peer-reviewed qualitative, quantitative, and mixed methods studies that evaluated digital health technologies for patient-professional partnerships in chronic care settings were included. The data were charted and analyzed thematically. The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist was used. Results: This review included 32 studies, reported in 34 papers. The topic of participatory health technologies experienced a slightly increasing trend across publication years, with most papers originating from the United States and Norway. Diabetes and cardiovascular diseases were the most common conditions addressed. Of the 32 studies, 12 (38%) evaluated the influence of participatory health technologies on partnerships, mostly with positive outcomes, although we also identified how partnership relationships and the nature of collaborative work could be challenged when the roles and expectations between users were unclear. Six common features of participatory health technologies were identified: patient-professional communication, self-monitoring, tailored self-care support, self-care education, care planning, and community forums for peer-to-peer interactions. Conclusions: Our findings emphasize the importance of clarifying mutual expectations and carefully considering the implications that the introduction of participatory health technologies may have on the work of patients and health care professionals, both individually and in collaboration. A knowledge gap remains regarding the use of participatory health technologies to effectively support patient-professional partnerships in chronic care management.

Worldwide, the number of people with Parkinson's disease (PD) is predicted to double between the years 2005 and 2030. Chronic care management requires active collaboration and knowledge exchange between patients and health care professionals (HCPs) for best possible health outcomes, which we describe as co-care. eHealth services have the potential to support the realization of co-care between people with PD (PwP) and HCPs. OBJECTIVE: This study aimed to explore how co-care could be operationalized in PD care, supported by eHealth. More specifically, this study explores PwP's and HCPs' expectations and desired eHealth functionalities to achieve co-care. METHODS: Principles of participatory design were used to enable the identification of co-care needs and design ideas, in a series of 4 half-day co-design workshops. The sample included 7 (4 women) PwP and 9 (4 women) HCPs, including 4 neurologists, 3 nurses, and 2 physiotherapists. The co-design process resulted in a functional prototype that was evaluated by the co-design participants in the last workshop. Data were collected through note cards produced by the participants during the first 3 workshops and focus group discussions during the 3rd and 4th workshops. The data were analyzed using qualitative thematic analysis. After the workshop series, the prototype was demonstrated at a Mini Fair for ongoing PD research and evaluated using a self-developed questionnaire with 37 respondents: 31 PwP (14 women) and 6 informal caregivers (3 women). Descriptive statistics are reported. RESULTS: The qualitative analysis of data resulted in 2 main themes. The first theme, core eHealth functionalities and their expected values, describes 6 desired eHealth functionalities for supporting PD co-care between PwP and HCPs: (1) self-tracking, (2) previsit forms, (3) graphical visualization, (4) clinical decision support, (5) self-care recommendations, and (6) asynchronous communication. The second theme, individual and organizational constraints, describes constraints that need to be addressed to succeed with an eHealth service for co-care. Individual constraints include eHealth literacy and acceptance; organizational constraints include teamwork and administrative workload. The majority of the questionnaire respondents (31/37, 84%) perceived that they would benefit from an eHealth service similar to the demonstrated prototype. All prototype functionalities were rated as very important or important by the majority of respondents (ranging from 86% to 97% per functionality). CONCLUSIONS: This study adds to our knowledge on how PD co-care could be operationalized. Co-care implies a shift from episodic routine-driven care to more flexible care management that is driven by the mutual needs of patients and HCPs and supported by active information exchange between them, as well as automated information processing to generate patient-specific advice. More research is needed to further explore the concept of co-care in chronic care management and what it means for self-care and health care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/11278.