1 Introduction

Nonadherence is an important barrier to the treatment of hypertension [1–3]. Our previous work [e.g., 4, 5] demonstrated strong initial, but not sustained, benefits on adherence of the Multifaceted Prospective Memory Intervention (MPMI). We believe that incorporating the MPMI strategies into mobile devices, such as smartphones or tablets and/or incorporation of the strategies into web-based programs to reinforce the strategies; will help people maintain the benefits of the intervention.

The control of hypertension among older adults is a significant problem. The prevalence of hypertension in 2009-2010 was estimated at 66.7 % for people ≥ 60 years and 73 % for people ≥ 80 years of age [6]. The effects of poor blood pressure control in older adults are devastating and associated with cerebrovascular disease, coronary artery disease, aortic and peripheral arterial disease, and chronic kidney disease, and these chronic conditions affect quality of life [7]. Hypertension is the single most important risk factor for stroke [8–10] and a primary risk factor for myocardial infarction, heart failure, and end organ damage to the kidneys, retina, and brain [11–14]. Older individuals with a history of uncontrolled hypertension are at risk for cognitive decline, and this further compromises the capacity to self-manage chronic illness [15]. Given the prevalence and deleterious outcomes of uncontrolled hypertension among older adults, it is unfortunate that adherence to treatment is only 50 % [e.g., 1, 3].

We focused the medication adherence intervention on supporting the necessary cognitive processes for remembering to take medications as prescribed. Prospective memory is remembering to complete an intended action sometime in the future. Medication taking is a prospective memory activity since the taking of medication is planned for some time in the future and often, in the face of delays and distractions, it can be forgotten. There is good evidence associating cognitive function and medication adherence [15, 16 for a review see 17]. The most common reasons for nonadherence are cited as forgetfulness, changing medication schedules or busy lifestyles [17]. Each of these reasons is potentially cognitive in nature. Forgetfulness is failing to remember to take medications at the designated times, changing schedules is likely to interfere with memory strategies that are based on routine and on associated environmental cues in one’s routine context, and busy lifestyles contribute to nonadherence by adding cognitive distractions that challenge limited working memory capacity. Adherence may particularly depend on executive function and working memory [15] because past research demonstrates only small effects of interventions that address education [e.g., 18] or the design of medication instructions (and therefore patient understanding) [see for example 19]. Therefore, adherence may be improved by interventions that target executive function and working memory. We used the following model to create the MPMI and will use this model to augment the MPMI by using technology with the goal of sustaining the effectiveness of the intervention strategies.

2 Model of Cognitive Factors in Self-Management Among Older Adults

As shown, nonadherence to treatment increases the severity of hypertension leading to declines in cognitive function [20, 21], and cognitive function is related to medication adherence in real-world settings [15] and to poorer prospective memory performance in laboratory settings on tasks that do not have easily identifiable external cues [22].

Two conclusions from the prospective memory and aging literatures suggest that strategies that target memory processes will be successful. First, there is remarkable variability in age effects on laboratory tests of prospective memory, with some studies showing minimal or no age differences [23, 24] and others showing striking age differences [e.g., 25–27]. Second, there is evidence that normal aging has more pronounced disruptive effects on cognitive functioning mediated by the frontal lobes (e.g., working memory and executive attention) [28–30] than it does on cognitive functioning mediated by the medial temporal areas (e.g., relatively automatic associative retrieval processes). Consistent with reviews of the aging and prospective memory literature [24, 30, 31], the emerging pattern is that older adults show substantial deficits when they rely on working memory and executive resources for prospective remembering, but minimal deficits when they rely on mostly preserved and relatively automatic associative retrieval processes. For example, age differences are robust on prospective memory tasks that require strategic monitoring for the correct opportunity to perform an intended action or when the retrieved action must be delayed (thus placing a demand on working memory and attentional resources for keeping the retrieved intention activated over the delay). In contrast, age differences are minimal when there are good external or environmental cues that support relatively automatic retrieval of the intended action (cues that have been associated with intended actions) and when the action can be performed immediately [32]. Thus, the focus of technology can be to encourage older adults’ use of environmentally supported associative retrieval processes (thought to be relatively spared with age) in place of prospective memory processes that heavily rely on working memory and executive resources (thought to be compromised with age). Indeed, findings from our prior MPMI study suggest that older adults who scored lower on a composite measure of working memory/executive function benefitted more from the intervention, presumably because the intervention allowed them to use associative retrieval more than executive control processes in order to take their medications.

The intervention, supported by technology, needs to target all of the memory and attentional processes thought to be critical for successful prospective memory performance in everyday tasks such as medication taking [33, 34]. These include (1) forming a good encoding of the intended action and the condition(s) that is appropriate for initiating the action, (2) remembering the intention over the retention interval, (3) retrieving the intention at the appropriate point in time, (4) inhibiting other ongoing activities at the critical time and actually executing the action, and (5) monitoring performance of the action so that the person remembers performing it (and therefore does not repeat it). Failure at any one of these tasks could compromise medication adherence. For example, a person may form only a general intention to take her or his medication in the morning and may fail to think of it at the appropriate time. Or, that person may retrieve the intention to take the medication at the right time but because of distractions or interruptions at that time may fail to follow through and execute the action. Or, after establishing a routine, the person may automatically take a dose while deeply engaged in other thoughts and a few minutes later forget that he or she had already taken the medication and take it again resulting in taking too much medication.

3 The MPMI Strategies

We used a variety of strategies to facilitate medication taking. The training protocol for the interventionists included establishing a relationship and identifying individual goals that involved active listening to promote collaboration in medication taking. Using Leventhal’s Common-Sense Model of Self-Regulation [35], we sought comprehension of the patient’s illness representation. That is, what is the patient’s timeline (chronic or acute), what is the patient’s view of the causes, controllability and consequences of hypertension. If hypertension cannot be controlled because it is “God’s will,” it is important to understand that this is the patient’s perspective. We also examined how the individual talked about hypertension. What words were used to label hypertension and its causes, controllability and consequences? We then addressed beliefs through education and attention. Importantly, in the test of the MPMI both control condition and intervention groups received education and attention, the later which was accomplished by equating time spent with the participant. We then focused the intervention group on the strategies used for enhancing successful prospective remembering to take medications as intended. We helped the participant identify his/her routine, with the goal of taking medications at the same time and in the same place. If they got up at 4:00 a.m., we discussed medication taking strategies within the routine and honored that his/her day started at 4:00 a.m. We did not try to change the routine. Then, we asked how can plans for medication taking be linked to his/her routine? We asked that they use a diary to record when the routine changed and why and if this explained missing doses of medications. We discussed external strategies and worked with participants to place cues in the home environment that would facilitate remembering. All of the strategies mentioned were covered in an initial meeting with the participant. We also taught them to “do it now,” not to delay taking medications when they thought of them because we explained even a short delay of five seconds could lead to failure to take the medication as planned [36, 37]. We encouraged participants to elaborate the action of taking medications to make the action more memorable and to convert a medication taking event that was scheduled or time-based to a daily event, like eating breakfast or watching a particular television program [38]. We had them use organizers to enhance monitoring that the medication was taken as intended since habitual activities are repetitious and accurate completion of the activity can be confused [39].

Technology used to support medication taking must be designed to sustain the interaction with the intervention perhaps through ongoing coaching and/or by continuing the strategies even after the nurse leaves the home or the patient leaves the clinic. The technological support delivered by mobile devices or web based programs, would need, at minimum, to remind participants at the correct time and request that they indicate that the medication was taken. Individuals need some choice, for example, how reminders appear and how often they are reminded until the action is completed. If technology can be used to continue the strategies in the intervention, then theoretically the effects of the intervention can be sustained over time.

4 Technological Challenges

The tested in-home intervention, the MPMI, used several strategies [5]. Translation of these strategies to a mobile application or other technological support system is going to require creativity. Standard reminding devices are unlikely to result in the positive benefit found with the tested intervention. Also, there are many reminding devices and applications currently on the market, many of which are too complex for older and younger users alike and have no empirical testing and hence, no evidence based support. Older adults also represent a unique and evolving group in relationship to use of technology. A recent study examining baby boomers’ adoption of health technologies found that baby boomers were similar to younger age groups in readiness to use some technologies (websites, email, automated call centers, medical video conferencing and texting), but not others (smartphones, podcasts, kiosks, blogs and wikis) [40]. There is increasing evidence that older adults want to remain independent and find hope in the possibility of technology to allow them to do so [41]. Therefore, the challenges of developing support for self-management are outweighed by the opportunities involved. As baby boomers move into older years, they will take with them greater familiarity with technology and use of smartphones and tablets to improve quality of life and maintain function. They are also more likely to seek health information on the internet and could use internet based programs to reinforce learned strategies. Translating efficacious interventions to technologically supported interventions is challenging and presents opportunities for continued health and function in later years.