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Which Bundles of Features in a Web-Based Personally Controlled Health Management System Are Associated With Consumer Help-Seeking Behaviors for Physical and Emotional Well-Being?
Annie YS Lau1, PhD; Judith Proudfoot2, PhD; Annie Andrews3; Siaw-Teng Liaw4, MBBS, PhD; Jacinta Crimmins5, MBBS; Ama?l Arguel1, PhD; Enrico Coiera1, MBBS, PhD
1Centre for Health Informatics, Australian Institute of Health Innovation, University of New South Wales, Sydney, Australia
2School of Psychiatry, University of New South Wales and Black Dog Institute, Sydney, Australia
3UNSW Counselling and Psychological Services, University of New South Wales, Sydney, Australia
4School of Public Health & Community Medicine, UNSW Centre for Primary Health Care and Equity, University of New South Wales, Sydney, Australia
5University Health Service, University of New South Wales, Sydney, Australia
Corresponding Author:Annie YS Lau, PhD
Centre for Health Informatics, Australian Institute of Health Innovation, University of New South Wales
Level 1, AGSM Building (G27) UNSW
Sydney, 2052
Australia
Phone: 61 431 599 890
Fax: 61 2 9385 8692
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ABSTRACT
Background: Personally controlled health management systems (PCHMS), which include a personal health record (PHR), health management tools, and consumer resources, represent the next stage in consumer eHealth systems. It is still unclear, however, what features contribute to an engaging and efficacious PCHMS.
Objective: To identify features in a Web-based PCHMS that are associated with consumer utilization of primary care and counselling services, and help-seeking rates for physical and emotional well-being concerns.
Methods: A one-group pre/posttest online prospective study was conducted on a university campus to measure use of a PCHMS for physical and emotional well-being needs during a university academic semester (July to November 2011). The PCHMS integrated an untethered personal health record (PHR) with well-being journeys, social forums, polls, diaries, and online messaging links with a health service provider, where journeys provide information for consumer participants to engage with clinicians and health services in an actionable way. 1985 students and staff aged 18 and above with access to the Internet were recruited online. Logistic regression, the Pearson product-moment correlation coefficient, and chi-square analyses were used to associate participants? help-seeking behaviors and health service utilization with PCHMS usage among the 709 participants eligible for analysis.
Results: A dose-response association was detected between the number of times a user logged into the PCHMS and the number of visits to a health care professional (P=.01), to the university counselling service (P=.03), and help-seeking rates (formal or informal) for emotional well-being matters (P=.03). No significant association was detected between participant pre-study characteristics or well-being ratings at different PCHMS login frequencies. Health service utilization was strongly correlated with use of a bundle of features including: online appointment booking (primary care: OR 1.74, 95% CI 1.01-3.00; counselling: OR 6.04, 95% CI 2.30-15.85), personal health record (health care professional: OR 2.82, 95% CI 1.63-4.89), the poll (health care professional: OR 1.47, 95% CI 1.02-2.12), and diary (counselling: OR 4.92, 95% CI 1.40-17.35). Help-seeking for physical well-being matters was only correlated with use of the personal health record (OR 1.73, 95% CI 1.18-2.53). Help-seeking for emotional well-being concerns (including visits to the university counselling service) was correlated with a bundle comprising the poll (formal or informal help-seeking: OR 1.03, 95% CI 1.00-1.05), diary (counselling: OR 4.92, 95% CI 1.40-17.35), and online appointment booking (counselling: OR 6.04, 95% CI 2.30-15.85).
Conclusions: Frequent usage of a PCHMS was significantly associated with increased consumer health service utilization and help-seeking rates for emotional health matters in a university sample. Different bundles of PCHMS features were associated with physical and emotional well-being matters. PCHMS appears to be a promising mechanism to engage consumers in help-seeking or health service utilization for physical and emotional well-being matters.
(J Med Internet Res 2013;15(5):e79)
doi:10.2196/jmir.2414
KEYWORDS
personal health record; Web-based intervention; health service; help-seeking; emotional well-being; physical well-being; preventative health; eHealth; consumer; university
Worldwide, governments have made multibillion dollar investments in eHealth to modernize health services delivery, with many questions still unanswered about the uptake, benefits, and cost-effectiveness of these investments [1,2]. In particular, personal health records (PHRs) now form a crucial component in many large-scale national eHealth reform strategies. However, uptake and utilization of PHRs is not as widespread as anticipated [1,2], and there are often gaps between proposed and actual benefits [3]. Finding approaches that effectively engage consumers in the use of PHRs, with the intention to improve health outcomes and reduce attrition rates, remains a high priority in consumer eHealth research [4-6].
PHRs have been advocated as the next generation tool that significantly improves consumers? health behaviors and health outcomes [7]. In a key discussion on personal health records (PHRs) presented by Tang and colleagues, a PHR is an electronic application through which individuals can access, manage, and share their health information [8]. A tethered PHR allows patients to view their own health information that is stored in their health care provider?s electronic health record, whereas an untethered PHR is a stand-alone application that does not connect with any other system [8]. A personally controlled health management system (PCHMS) in this instance is a health management system that allows consumers and patients to connect and engage with their health services online to access tools and resources to manage their health. In this paper, our PCHMS integrated an untethered PHR with well-being journeys, social forums, polls, diaries, and online messaging links with a health service provider.
However, a PCHMS often consists of multiple features, which refer to the functionalities available on the system. What are the features in a PCHMS that encourage consumers and patients to seek help or engage with health services for their well-being concerns? To date, it is still unclear what features contribute to an engaging and efficacious PCHMS.
Past studies have resulted in guidelines for the development of Internet interventions for consumer health [9-12]. Other studies have found features such as personalization, tailoring, and behavior feedback associated with significant consumer health behaviors when applied in the right context [13,14]. Researchers have also advocated for the use of behavioral theories, such as the health belief model (HBM) [15], social cognitive theory (SCT) [16], transtheoretical model (TTM) [17], and the theory of reasoned action / planned behavior [18], in the development of eHealth applications to increase their acceptability and efficacy. Yet, there is currently little literature to guide the features of PCHMS.
In parallel, the idea of creating a ?bundle? of actions has recently been advocated as a way to address system inertia to change [19]. While its clinical applications have been shown to improve the quality and safety in managing ventilation-assisted pneumonia [20] and sepsis in intensive care [21], its applicability in eHealth has not been examined previously. A care bundle is a grouping of care elements for a particular symptom, procedure, or treatment [22]. It follows the holistic principle where a bundle, as a grouping of several evidence-based practices, when used in combination or as a cluster, should have a greater effect on the positive outcome of patients [22]. In eHealth, while evidence is emerging on which ?individual? features are associated with significant consumer health behaviors, the concept of identifying a ?bundle? of effective features in eHealth interventions has not been addressed previously.
For this reason, identifying features (or ?bundles of features?) in a PCHMS that are associated with changes in consumers? health behaviors remains a crucial area for research. In response, we designed an online prospective study to examine how a group of participants in a university setting used a PCHMS to manage their physical and emotional well-being. University students are known to experience elevated distress levels over an academic semester [3,23-30]. Yet, they are infrequent users of health services and hardly engage with services for assistance [31-33]. The aim of this study is to (1) examine whether use of a PCHMS is associated with increased rates of health service utilization and help-seeking behaviors for physical and/or emotional well-being, and (2) identify whether use of any specific PCHMS feature (ie, journey, personal health record, forum, poll, diary, or online appointment service), or bundles of features, is associated with help-seeking behaviors and health service utilization for well-being matters.
Trial Design and Participants
A one-group pre/posttest online prospective study was conducted over a university academic semester (July to November 2011). Inclusion criteria were (1) aged 18 or above, and (2) with access to the Internet and email at least on a monthly basis.
Study Protocol
Students and staff were approached via email lists and advertisements in online print publications, which described the study and invited interested parties to use a PCHMS called Healthy.me developed at the University of New South Wales (UNSW) to manage their physical and emotional well-being for an academic semester. Written informed consent was sought online from each participant. Participants then completed a 15-minute online pre-study survey, followed by a 5-minute mandatory online tutorial about Healthy.me prior to using the site. At study completion (end of semester), participants received an email asking them to complete a 15-minute online post-study survey. Two follow-up emails 5 days apart were sent as reminders to noncompleters. Those who completed all surveys were entered into a draw for an AU$500 gift voucher. A researcher was available via a dedicated telephone line and email to answer participants? questions and concerns during the study. Ethics approval was obtained from the UNSW ethics committee.
Measures
At baseline, demographic information (such as age and gender) was collected, as well as information about their use of social networking websites, use of the Internet to find health-related information, and visits to a health professional (including whether they visited prior to the study a health care professional, University Health Service, and the University Counselling and Psychological Services).
In the pre- and post-study questionnaires, measures 1-3 were administered and additional measures (4-5) were administered in the postintervention questionnaire: (more details on each measure are available in Multimedia Appendix 1):
- COOP/WONCA charts were used to evaluate participants? functional status, defined as physical, emotional, and social status. These scales, which have been demonstrated to be a valid and feasible one-time screening assessment for mental disorders in primary care [34], measure six domains, namely physical fitness, feelings, daily activities, social activities, change in health, and overall health. Responses are via a 1-5 Likert-scale where higher scores indicate a poorer functional status.
- Well-being self-ratings and lifestyle intention: adapted from the last question in the standardized instrument EUROQOL (EQ-5D) [35], which measures health status, participants were asked to rate their physical and emotional well-being on a scale from 0 to 100. They were also asked to select one of four statements that best describes their intention to practice a lifestyle that benefits their well-being according to the transtheoretical model of behavior change [17].
- Health advice-seeking and health advice-providing networks: adapted from the Norbeck Social Support Questionnaire [36], participants were asked to nominate up to 5 people they have sought advice from, or provided advice to, before and during the study.
- Help-seeking behaviors and health service utilization: Help-seeking is defined as the behavior of actively seeking assistance [37], regardless of whether the source is informal or formal. A new scale was developed by the authors, adapted from the Actual Help-seeking Questionnaire (AHSQ) [37]. The scale covers help-seeking behaviors for physical and emotional well-being, informal and formal sources, as well as for self or others.
- Feedback on Healthy.me: participants were asked to provide feedback on their overall experience of using Healthy.me, as well as their feedback on specific features on the website, using a range of scale items such as Likert scale, free-text comments, and checkbox answer options.
This paper focuses on usage of PCHMS features with consumers? health behaviors and thus only reports participants? help-seeking behaviors and health service utilization rates collected at post-study.
PCHMS Usage Metrics
A recent review by Danaher and Seeley [38] concluded there is no single, universally accepted measure for website usage, and researchers are still debating the best methods for defining and measuring website engagement [38].
In this study, we used simple website engagement measures to track participants? activity on the website (ie, PCHMS login frequency and whether participants accessed, or did not access, each website feature). These measures were used to assess whether (1) there was a dose-response effect, that is, was the frequency of PCHMS login associated with rates of health service utilization and help-seeking behaviors, and whether (2) access to PCHMS feature(s) (ie, journey, personal health record, forum, poll, diary, and/or online appointment service) was associated with participants? health service utilization and help-seeking behaviors for physical and/or emotional well-being.
PCHMS Web logs were analyzed to determine whether participants accessed (or did not access) any of the features at any time during the study. Some of these website engagement measures have previously been used to measure user engagement of PHR systems [39].
Intervention
Theoretical Construct
The dose-response phenomenon tested in this study is related to the familiarity principle, reinforcement effect, and the mere exposure effect described by Zajonc [40], where the level of repeated exposure to an intervention is associated with participants developing a familiarity and preference for the intervention and thus increasing the likelihood to use it at times of need. Features such as length of exposure, the spread of experiences, the partitioning of episodes, the peak-and-end events in an incident, and the degradation or improvement in experience over time have been reported to influence a person?s overall impression of an experience [41]. While exposure to a website can be described using different measures, such as number of logins, repeated visits, and duration of visits, we used number of logins as our primary measure since it is one of the most common measures to describe participants? engagement with a website.
Healthy.me
Healthy.me was iteratively developed, and its first version was tested in other settings such as in vitro fertilization and influenza vaccination [42,43]. The first version contained features such as journey, the personal health record, and online appointment booking with the university primary care service. The version of Healthy.me (version 2.0) that was used in this study contained the above-mentioned features as well as online appointment booking with the university primary care and counselling services, a diary, forum, and poll. Details of each feature are described below:
- Personal Health Record (PHR) for self-recording of medical test results, medications, scheduled appointments, and personnel looking after one?s health (see Figure 1).
- Online appointment booking with the University Health Service (primary care) and the UNSW Counselling and Psychological Services (sent via email using the ?Book now? button in the PCHMS).
- Diary for participants to write down their thoughts about their health. By default, the diary is private. However, participants can select to share their diary with all participants enrolled in the PCHMS.
- Social communication spaces, which support interaction across the continuum of care between fellow participants and clinicians. Features include the poll system and forums moderated by clinicians. Poll system in which participants answer simple health questions (eg, how much sleep did you get last night?), where they can view and compare their response with other participants? aggregated answers in graph format (Figure 2). Forums moderated by clinicians (a primary care physician and a psychologist), where participants can either post their entries on the forum or send one-on-one email messages to other participants in the PCHMS (including clinicians). Guidelines on forum use and the protocol for responding to concerns reported in the forum were approved from the UNSW ethics committee. Posts sent by participants to the ?Report concern? feature on the forum were emailed to clinical and research personnel during the study, who investigated any reported concerns. A Uniform Resource Locator (URL) available in the email to the dedicated staff allowed them to withdraw the forum post. The primary care physician and the psychologist not only moderated the forum but were also available to answer questions posted on the forums. No harm from the use of the forum or the PCHMS was reported by participants during the study.
- Journeys that provide information for consumer participants to engage with clinicians and health services in an actionable way. Participants in this study had access to four well-being journeys for physical and emotional well-being: ?Stay Healthy?, ?Stressed out??, ?Feeling Anxious about the Exams??, and ?My Emotional Well-being Program?.
The four well-being journeys for physical and emotional well-being were designed and developed in consultation with University Counselling and Psychological Services psychologists and University Health Service primary care physicians, utilizing evidence-based consumer education material routinely used at UNSW to promote physical and emotional well-being. Written in youth-friendly language, using evidence-based mental health, psychoeducational, and psychosocial material, the journeys consisted of skills-focused content delivered online, as well as well-being workshops that participants could attend in-person at the University Counselling and Psychological Services. Participants could learn about mindfulness meditation, anxiety management, time management, and stress management at these workshops.
Journeys were delivered via the PCHMS at four pivotal time-points during a university academic semester (ie, beginning of semester, 4 weeks into semester, after mid-semester break, and before exams) to address physical and emotional well-being concerns likely to be concerning participants at each time-point. Participants were alerted with an email when a new journey became available on the PCHMS. These journeys provided task specific knowledge in an actionable way. For example, as participants read the journey for advice on physical or emotional well-being, they could immediately:
- book an appointment with a university primary care physician or a psychologist from the journey page,
- register to attend a well-being workshop,
- post a question on a forum to seek advice from fellow participants or a clinician (primary care physician or a psychologist), or
- send themselves an email reminder to do so later.
A pilot study was conducted in a controlled setting with 15 university staff and students of different ages, gender, and familiarity with computers to test the intervention, the measures, and the research design. Substantive usability issues were resolved before recruiting participants in their real-life setting.
Data Analysis
Analysis was conducted on an intention-to-treat basis. Sequential logistic regression analyses were undertaken to prospectively examine the crude and adjusted odds ratios (ORs) for participants? health service utilization and help-seeking behaviors for physical and emotional well-being matters [44]. Independent variables assessed included whether participants accessed (or did not access) each specific PCHMS feature (journey, personal health record, forum, poll, diary, and online appointment service), controlling for participant?s gender, age, and potential confounders (eg, whether the participant was a university service patient/client prior to the study) to provide a stratified estimate of intervention effect. The Pearson product-moment correlation coefficient was used to examine correlations among usage of features that were associated with consumers? behaviors.
Participants? health service utilization rates (ie, visits to a health professional, University Health Service, or the University Counselling and Psychological Services), and their help-seeking behaviors for physical or emotional well-being matters were compared at different PCHMS login frequency thresholds (zero logins, once only, two to five times, six to 10 times, more than 10 times). The rationale for selecting these login frequency cutoffs is based on using heuristics to ensure important login frequency thresholds are covered (ie, zero, once only, and ? a high login frequency threshold) and that there are sufficient data points in each frequency threshold to conduct analyses.
Between group analyses were conducted using chi-square analysis. Participants? pre-study characteristics (namely use of the Internet to find health information, use of social networking websites, visits to a health care professional in the past 6 months, and their self-rated well-being ratings classified as over or below 50 at pre-study) were compared between different PCHMS login frequencies using chi-square to assess whether these characteristics were associated with PCHMS usage levels. Descriptive analyses were conducted on participants? reasons for not seeking help during study.
Data analysis was performed using IBM SPSS Statistics 20 [45]. Tests performed were two-tailed and assumed a cutoff of P<.05 for statistical significance.
Source: http://www.jmir.org/2013/5/e79/
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Public release date: 21-May-2013
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