Journal of Gerontological Nursing

Feature Article 

Self-Efficacy and Sleep Among Caregivers of Older Adults With Dementia: Effect of an Interprofessional Virtual Healthcare Neighborhood

Christianne Nesbitt Fowler, DNP, RN, GNP; Karen Kott, PhD, PT; Mona Newsome Wicks, PhD, RN, FAAN; Carolyn Rutledge, PhD, RN, FNP


An Interprofessional Virtual Healthcare Neighborhood (VHN) was designed to deliver information, peer support, and professional guidance to caregivers of individuals with dementia. The VHN was also enhanced with an actigraphy band to monitor caregivers' sleep. The study sample comprised two groups (N = 28): caregivers participating in the VHN and those receiving usual care. Measures of sleep quality and quantity, using an actigraphy band; general self-efficacy, using the General Self-Efficacy Scale; and insomnia, using the Insomnia Severity Index, were measured pre- and postintervention for the intervention and comparison groups. Neither group reported significant changes in sleep quality or quantity over time. Insomnia severity decreased for both groups. Self-efficacy became worse for the comparison group, yet remained virtually unchanged for the intervention group. Overall, the current study also showed an effective use of technology to reach homebound caregivers of older adults with dementia. [Journal of Gerontological Nursing, 42(11), 39–47.]


An Interprofessional Virtual Healthcare Neighborhood (VHN) was designed to deliver information, peer support, and professional guidance to caregivers of individuals with dementia. The VHN was also enhanced with an actigraphy band to monitor caregivers' sleep. The study sample comprised two groups (N = 28): caregivers participating in the VHN and those receiving usual care. Measures of sleep quality and quantity, using an actigraphy band; general self-efficacy, using the General Self-Efficacy Scale; and insomnia, using the Insomnia Severity Index, were measured pre- and postintervention for the intervention and comparison groups. Neither group reported significant changes in sleep quality or quantity over time. Insomnia severity decreased for both groups. Self-efficacy became worse for the comparison group, yet remained virtually unchanged for the intervention group. Overall, the current study also showed an effective use of technology to reach homebound caregivers of older adults with dementia. [Journal of Gerontological Nursing, 42(11), 39–47.]

The number of individuals with dementia in the United States continues to increase. Currently, more than 6 million Americans older than 65 have dementia, which means that one of every nine members of neighborhoods and surrounding communities have this disease (Alzheimer's Association, 2015). Informal caregivers, usually family members or friends, perform the majority of care for individuals with dementia. These caregivers provide more than 17.9 billion hours of care each year valued at >$217.7 billion (Alzheimer's Association, 2015). Mental, physical, social, and economic support that is available for caregivers varies widely from state to state, as well as among different regions of the same state.

Finding new and effective ways to provide support for caregivers is important, particularly because they are often socially isolated and have little time to attend to their personal needs and health. Caregiving can be emotionally and physically stressful. Studies have shown significant negative health effects of caregiving, especially for caregivers of individuals with dementia (Gaugler, Kane, Kane, & Newcomer, 2005; Roth, Fredman, & Haley, 2015; Schulz, Boerner, Shear, Zhang, & Gitlin, 2006). These caregivers are at increased risk for depression, with a rate approximately twice as high as the general population (Givens, Mezzacappa, Heeren, Yafee, & Fredman, 2014). In addition, poor sleep quality is a common problem for caregivers, particularly caregivers of individuals with dementia (Peng & Chang, 2013). Various types of caregiver support have been shown to improve caregivers' quality of life and delay nursing home placement for their care recipients (Mittelman, Haley, Clay, & Roth, 2006).

The use of technology to provide caregiver support is not a new idea. Many organizations have developed web-based support groups and information specifically for caregivers of individuals with dementia and have used them successfully for several years. Internet-based interventions have been shown to be viable methods to deliver support for caregivers (Boots, de Vugt, van Knippenberg, Kempen, & Verhey, 2014; Kajiyama et al., 2013; Lee, 2015; McKechnie, Barker, & Scott, 2014; O'Connor, Arizmendi, & Kaszniak, 2014). The use of this approach is increasing as more individuals look to the internet for answers to health-related questions and concerns (Amante, Hogan, Pagoto, English, & Lapane, 2015). The goal now is to create support that is more specific for caregivers of individuals with unique needs such as dementia. Moreover, caregivers need tools that foster their sense of self-efficacy to effectively care for their loved ones. To improve overall care for individuals with dementia and diminish caregiver stress, it is important to teach caregivers the skills they need and provide continuous support (Zabalegui et al., 2014).

The purpose of the current study was to evaluate the feasibility and effectiveness of an Interprofessional Virtual Healthcare Neighborhood (VHN) in assisting caregivers of individuals with dementia. This study measured the impact of the VHN, compared with usual care, on caregivers' self-efficacy, insomnia, and overall sleep quality, and hypothesized that the intervention caregiver group would have measurable improvement in self-efficacy and sleep measures compared to caregivers who did not receive the intervention.



A randomized two-group pre-/ post-test design was used to determine whether caregivers who participated in the VHN (hereafter referred to as the intervention group) reported greater improvements in sleep quality, insomnia, and general self-efficacy compared to caregivers who received standard care (hereafter referred to as the comparison group). The intervention group was also monitored to determine the frequency of visits to the VHN.

Study Population

The institutional review board of a major university approved this project. Participants of the current feasibility study comprised a convenience sample of 28 primary caregivers for homebound older adults with any form of dementia. Primary caregivers were those providing the majority of daily care. Homebound was defined as care recipients who were unable to leave the home without the assistance of another individual.

Thirty individuals qualified for the study, 27 from support groups and three referrals from enrolled caregivers (i.e., snowball recruitment). Most participants were recruited from the referrals received from eight local Alzheimer's Association support groups. Thirty-three of 65 support group members requested additional information about the study and 27 agreed to participate. These caregivers, in addition to the three referred by other participants, made a total of 30 participants. However, one individual required unexpected surgery before consent and one caregiver's mother died before completing enrollment. As a result, there were 28 qualified participants successfully enrolled in the study. All participants met inclusion criteria and completed written informed consent prior to initiating the study protocol. Participants were randomized, using a computer program, into one of two groups: (a) the intervention group (n = 15), who received the sleep actigraphy band and access to the VHN web-site; and (b) the comparison group (n = 13) who received only the sleep actigraphy band and continued their usual care.


Table 1 provides the study time-line. Prior to initiating the study protocol, home visits were made with each caregiver from both groups by one of two unblinded study investigators. This visit comprised addressing caregiver questions or concerns, electronically signing the consent, completing pre-intervention questionnaires, and reviewing the study schedule. All participants were given a copy of their consent. For the intervention group, investigators demonstrated how to access the VHN web-site and gather and upload data from the sleep actigraphy bands. Contact information for the investigator was provided to caregivers in the intervention group as well as instructions on how to obtain assistance from the VHN website administrator. Access to the various components of the VHN website was only available to the intervention group; these participants had a password that allowed full access to the website.

Study Timeline

Table 1:

Study Timeline

Comparison group participants also completed the same study questionnaires and informed consent and were shown how to use and upload their data from the actigraphy band to the VHN website. The comparison group used the VHN website solely to upload their sleep actigraphy information.

All study information was directly migrated from the VHN website into a secure database for analysis at the completion of the study. Caregivers from both groups were evaluated using the self-administered demographic, self-efficacy, and insomnia severity questionnaires. Self-efficacy and insomnia severity were assessed pre- and postintervention. In addition, each participant was monitored to assess quality and quantity of sleep using a sleep actigraphy band. Participants wore a sleep actigraphy band during specific periods of the study—2 weeks at the beginning and end of the study and 1 week per month during the 4-month study period.


All questionnaires were completed electronically on caregivers' home computers during the home visit with a study investigator. This approach allowed the caregivers' selections to be directly entered into the database and eliminated problems with staff data entry errors. Questionnaires were reviewed by the investigator to minimize missing data.

The researcher-developed demographic form was completed by both groups of caregivers at the start of the study. This questionnaire evaluated 11 characteristics with forced choice answers. The questions covered the age of the caregiver and care recipient, caregiver income, gender, education, marital status, race, months of caregiving, area of care (e.g., urban or suburban), employment status, and who they cared for (e.g., spouse, parent).

The General Self-Efficacy Scale, developed by Schwarzer and Jerusalem (1995), is an 8-item questionnaire with answer selections ranging from 1 = strongly disagree to 5 = strongly agree. The scale was developed to assess perceived self-efficacy and predict daily coping with different types of daily stresses (Schwarzer & Jerusalem, 1995). The total score ranges between 8 and 40, with higher scores indicating greater self-efficacy. This scale demonstrated a Cronbach's alpha of between 0.76 and 0.90 in the general population (Schwarzer & Jerusalem, 1995). The comparison and intervention groups completed this questionnaire preand postintervention.

The Insomnia Severity Index is a 7-item questionnaire that has been used to measure issues pertaining to daytime and nighttime insomnia symptoms (Bastien, Vallières, & Morin, 2001). The index measures issues with sleep onset, sleep maintenance, satisfaction with current sleep patterns, problems with daily functioning, and degree of distress caused by perceived sleep problems (Bastien et al., 2001). Scores range from 0 to 28, with higher scores indicating more difficulty with insomnia. All participants also completed this evaluation at the beginning and end of the study. The reliability has been established through numerous evaluations of this index, with Cronbach's alpha consistently approximately 0.90 (Bastien et al., 2001).

The sleep actigraphy band used was the Sleeptracker® by Innovative Sleep Solutions (2015). The manufacturer reports the device is within 95% accuracy of professional sleep monitors (Innovative Sleep Solutions, 2015). Data were tracked and analyzed using the manufacturer's website and its proprietary software. Figure 1 shows an example of one night's sleep data in graph form. The results were stored and available to participants and study personnel.

SleepTracker® screenshot.

Figure 1.

SleepTracker® screenshot.

Virtual Healthcare Neighborhood Intervention

The interprofessional health care team in collaboration with faculty and students from the Computer Science Department developed the VHN and implemented the use of the sleep actigraphy band. The team included a gerontological nurse practitioner, family nurse practitioner, physical therapist, clinical counselor, and dental hygienist. Caregivers in both groups used the sleep actigraphy band, whereas only the intervention group received access to the VHN. Both groups participated in a home visit where they completed the preintervention surveys and learned to use the actigraphy band, including how to download the data onto their computer. During the home visit, caregivers in the intervention group created passwords for the VHN as well as received instructions on how to navigate the website.

The VHN is an asynchronous website that provides social support through a blog, specific educational material, and the opportunity to ask questions of the interprofessional team participating in this project. The investigators monitored the VHN blog website daily. The blog was available for participants to use during the study period and provided peer support. The interprofessional team developed the educational material, which was posted weekly for a total of 16 weeks. Educational materials comprised a brief outline of each week's topic, or module, with accompanying information, links to pertinent websites, and relevant YouTube videos. Review questions were presented after each module and participants were given a simple activity related to the week's topic. Table 2 provides a summary of the specific topics covered. The VHN website also included a photograph, introduction, and description of the area of expertise for each of the study investigators. In addition, the website included a blog, “Ask the Expert,” which allowed caregivers to have a one-on-one discussion with investigators.

Virtual Healthcare Neighborhood Educational Topics

Table 2:

Virtual Healthcare Neighborhood Educational Topics

Sleep data were collected from the sleep actigraphy bands using the proprietary software, SleepTracker Analytics™, from Innovative Sleep Solutions. The device works by capturing movements during the period the band is “set.” This software was loaded on all participants' home computers and they uploaded their data from the sleep watch each morning during the scheduled use period. The data could then be analyzed by participants and study investigators. These data demonstrate the amount of total sleep (i.e., bedtime to awakening in the morning), sleep quality (based on interrupted moments during the night), and the amount of deep and light sleep. This information was tracked and trends were graphed (Figure 2).

Relationship between average sleep scores and sleep interruptions.

Figure 2.

Relationship between average sleep scores and sleep interruptions.

Statistical Analysis

Data were initially analyzed to determine whether scores reflected a normal distribution. Descriptive statistics, including means and percentages, were used to describe sample characteristics and study outcomes. Due to the small sample size, non-parametric tests were run to assess differences within (Wilcoxon signed ranks) and between (Mann-Whitney U) groups. A priori alpha was set at p ≤ 0.05.



Twenty-one of 28 participants completed the study; two participants withdrew, one was lost to follow up, and four care recipients died before their caregivers completed the study. The comparison group had a mean age of 67 versus 60 for the intervention group. The intervention group cared for an older care recipient, with a mean age of 85 years versus 78 years for the comparison group. The average number of months of caregiving was substantially different: the comparison group mean was 93 months versus 57 months for the intervention group. However, there was an outlier in the comparison group; one participant had cared for her 99-year-old mother for 27 years. With the outlier removed, the comparison group had an average of 74 months of caregiving. Participants' yearly income was similar in both groups; the lowest amount, <$20,000 per year, was reported by two caregivers in the comparison group and three in the intervention group. Incomes >$40,000 were reported by seven individuals in the comparison group and six in the intervention group, including three in the comparison group and two in the intervention group who reported >$100,000 per year. In general, both groups had a high level of education; seven caregivers in the comparison group and six in the intervention group had a 4-year degree or higher. In addition, the intervention group had a higher number of participants who were working, with 60% versus 15% in the comparison group. Table 3 provides demographics of both groups.

Demographics of Participants

Table 3:

Demographics of Participants

Insomnia Severity

There was no significant difference between the intervention and comparison groups in pre- or post-insomnia severity scores (Figure 3). Both groups of caregivers received and used sleep actigraphy bands and both groups experienced less insomnia over the course of the study. The improvement for the intervention group was minimal, from a mean of 15.3 to 14.3, and not significant. However, the insomnia severity improved significantly (p = 0.031) from a mean of 17.3 to 14.7 for the comparison group. Their scores were worse initially yet were similar to the intervention group scores at the end of the study.

Total scores for General Self-Efficacy Scale (SES) and Insomnia Severity Index (ISI).

Figure 3.

Total scores for General Self-Efficacy Scale (SES) and Insomnia Severity Index (ISI).

Sleep Actigraphy

No significant differences were noted for the mean number of sleep interruptions (p = 0.161) or sleep score (p = 0.09) between groups as noted in Figure 2. However, given the small relative effect sizes of 0.36 for sleep interruptions and 0.23 for sleep scores and 11 individuals in each group, the statistical power was only 17% to note a difference between groups. Using Pearson's Product correlation test, a significant (p = 0.003) and weak inverse correlation (r = −0.057) was noted for decreased sleep interruptions and higher sleep scores. For this measure, higher sleep scores are indicative of better sleep quality.


The differences of scores on self-efficacy between the comparison and intervention groups were not significant before or after the intervention (p > 0.05) (Figure 3). The intervention group changed slightly over the course of the study, from a mean of 36.4 to 36.2. However, the comparison group had a lower level of self-efficacy following the intervention period, decreasing from a mean of 31.1 to 27.1. Statistically significant differences were noted for specific items on the General Self-Efficacy Scale between groups pre- and postintervention. For the statement, “When facing difficult tasks, I am certain that I will accomplish them,” there was a decline in scores for the comparison group and an improvement in mean scores for the intervention group. For the statement, “I am confident that I can perform effectively on many different tasks,” a significant difference was noted between groups pre- and postintervention, with the intervention group having higher scores overall. Table 4 provides a summary of caregivers' responses to each individual item.

General Self-Efficacy Scale: Individual Item Scores

Table 4:

General Self-Efficacy Scale: Individual Item Scores


The goal of the VHN was to evaluate the feasibility of using this type of intervention to assist caregivers of individuals with dementia. Findings suggest that the VHN can be a successful method for delivering information to caregivers of individuals with dementia. Of the participants who began the study, 75% successfully completed it. Individuals in the intervention group were able to navigate the website with little difficulty. Both groups were able to successfully use the sleep actigraphy band and download the data. Intervention group participants were satisfied with the VHN and found it easy to use as indicated by several comments at the end of the study. These comments were made while answering follow-up questions at study completion to evaluate the ease of use. One participant stated that the “technology wasn't a problem at all,” another said “it was simple to use,” and one spouse caregiver stated, “I understand the importance of the study…it was painless.”

The researchers then examined the benefits of a VHN for improving the sleep of those who participated in the study. Participants in the intervention and comparison groups had improvement in their insomnia, with the comparison group having the greatest improvement. In that both groups improved, the results may have been related to using the sleep actigraphy band and being more cognizant of the importance of sleep as opposed to the materials provided on the VHN regarding sleep. The sleep scores of both groups were below the national average reported by Innovative Sleep Solutions, and remained at approximately the same level pre- and postintervention. Poor sleep has been shown to negatively affect caregivers' overall well-being and health (Family Caregiver Alliance, 2015; Peng & Chang, 2013). The findings of the current study suggest that caregivers experience poorer sleep than the general population and may require strategies, such as sleep actigraphy bands, for addressing sleep deprivation.

Overall, the results of the quantitative findings for the General Self-Efficacy Scale showed some difference between groups. However, the differences were not significant. Prior to the VHN intervention, the comparison group had lower levels of self-efficacy than the intervention group. The comparison group scores on self-efficacy decreased over the course of the study, whereas the intervention group was able to maintain their level of self-efficacy. This finding suggests that the VHN intervention may have been effective in decreasing the decline in self-efficacy for the intervention group. There were specific areas related to confidence in performing tasks where the intervention group had a significant improvement related to self-efficacy.


The current study had several limitations. The goal was to enroll 30 participants, with equal numbers of individuals in the comparison and intervention groups. However, due to drop out and unforeseen circumstances, only 28 individuals participated in the study at the start, with 21 completing the entire 4-month study period. These numbers, although relatively good in terms of retention, are low for evaluating statistical differences between groups. The trends that were noted on the impact of the VHN on sleep and self-efficacy may have become significant given a larger sample. Participation in the VHN was widely variable, with some caregivers using the VHN website almost daily and others using it only monthly. Finally, three participants commented that keeping up with the activities associated with the study and their caregiving responsibilities was at times difficult. There were no withdrawals due to this issue but it could have had a major impact on the dose of the intervention delivered as measured by frequency of VHN use.


Caregivers who completed the VHN intervention were able to maintain their level of self-efficacy, an important measure for caregivers. The Insomnia Severity Index scores, as well as the data collected from the sleep actigraphy bands, showed poor sleep quality and quantity for the entire sample. This finding may reflect the complex issues revolving around sleep for caregivers and care recipients in the context of dementia. The findings present an opportunity to explore the use of the intervention and the complexities of caregiving further with future VHN studies. Providing VHN website support and interventions to specifically address issues that are universal for caregivers could potentially reduce overall stress and help caregivers continue care in the home. Other research has shown that technology-based interventions used to address common concerns associated with dementia care, such as agitation and other behavioral issues, have shown promise in improving overall quality of life for caregivers. These interventions have also been shown to aid in keeping the care recipient at home longer by delaying higher cost institutional care (Hu, Kung, Rummans, Clark, & Lapid, 2014). The research completed with the current study encourages further interprofessional collaboration to evaluate the use and benefit of technology to meet the needs of homebound caregivers. This technology may be a cost-effective way to reach this vulnerable group and provide effective services to improve caregiver and care recipient well-being and make better use of health care resources.


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Study Timeline

MonthVHN InvestigatorsInterventionControl
1 to 3Website design, development of educational material, home visitsRecruitment, randomization, consent, teach actigraphy monitoring, completion of pre-survey questions
Teach uploading of actigraphy data and use of VHN website, including location of intervention materialsTeach uploading of actigraphy data on VHN website and usual care
4Website testing14 days of sleep monitoring
5 to 8 (Intervention)Implementation of websiteParticipate in VHN (view educational materials, blog website, ask professional)Usual care
7 days of sleep monitoring each month
9Home visits14 days of sleep monitoring, administer posttests, interview caregivers about VHN study
10 to 12Compile and evaluate data

Virtual Healthcare Neighborhood Educational Topics

1Social support—What it is and why it is important
2Social support—Types of support
3Social support—How to improve my network
4Social support and your health
6Home safety
7Tips for helping with activities of daily living
8Behavior concerns
9Sleep and the caregiver
10Sleep and understanding the actigraphy band
11Sleep and the person with dementia
12Movement and the person with dementia—Part 1
13Movement and the person with dementia—Part 2
14Community resources
15Oral health and the caregiver
16Gum disease and dentures

Demographics of Participants

VariableComparison Group (n = 13)Intervention Group (n = 15)
Mean (SD)
Age (years)
  Caregiver67 (12.2)60 (12.77)
  Care recipient78 (8.64)85 (9.71)
Months of caregiving93 (83.41)a/74 (49.91)b57 (38.78)
n (%)
  Female9 (69)4 (31)
  Male4 (26)11 (73)
Marital status
  Married9 (69)10 (67)
  Unmarried4 (31)5 (33)
Care recipient
  Spouse9 (69)4 (27)
  Parent3 (23)6 (40)
  Mother-in-law1 (8)1 (6.7)
  Other4 (27)
  Suburban9 (69)11 (73)
  Urban4 (31)4 (27)
  White8 (62)13 (87)
  Black3 (23)
  Asian/Hispanic/Hawaiian2 (15)2 (13)
  <$20,0002 (15)3 (20)
  $20,000 to $59,9995 (38)4 (27)
  $60,000 to $99,9992 (15)5 (33)
  ≥$100,0003 (23)2 (13)
  Prefer not to answer1 (8)1 (7)
  High school2 (15)4 (27)
  Some college or 4-year degree5 (38)8 (53)
  Graduate degree6 (46)3 (20)
  Not working8 (62)1 (7)
  Working full- or part-time2 (15)9 (60)
  Retired3 (23)5 (39)

General Self-Efficacy Scale: Individual Item Scores

General Self-Efficacy Scale ItemMean (SD)p Value
Comparison GroupIntervention Group
I will be able to achieve most of the goals that I have set for myself.Pre3.9 (0.69)4.2 (0.86)0.25
Post3.7 (1.25)3.7 (1.49)0.96
When facing difficult tasks, I am certain that I will accomplish them.Pre3.9 (0.64)4.3 (0.72)0.13
Post3.3 (1.25)4.6 (0.69)0.01*
In general, I think that I can obtain outcomes that are important to me.Pre3.9 (0.90)4.3 (1.0)0.18
Post4.0 (1.1)4.6 (0.67)0.11
I believe I can succeed at most any endeavor to which I set my mind.Pre3.8 (1.0)4.5 (0.83)0.06
Post3.7 (1.1)4.5 (0.69)0.07
I will be able to successfully overcome many challenges.Pre3.9 (1.0)4.5 (0.74)0.07
Post3.8 (1.3)4.6 (0.69)0.12
I am confident that I can perform effectively on many different tasks.Pre3.7 (0.86)4.5 (0.83)0.02*
Post3.7 (1.3)4.6 (0.81)0.05*
Compared to other people, I can do most tasks very well.Pre3.6 (1.0)4.3 (1.0)0.07
Post3.2 (0.79)4.4 (0.67)0.002*
Even when things are tough, I can perform quite well.Pre3.6 (0.88)4.3 (0.90)0.04*
Post3.5 (0.97)4.4 (0.51)0.02*

Dr. Fowler is Associate Professor, Dr. Rutledge is Professor, School of Nursing, and Dr. Kott is Associate Professor, School of Physical Therapy and Athletic Training, Old Dominion University, Norfolk, Virginia; and Dr. Wicks is Professor, College of Nursing, The University of Tennessee Health Science Center, Memphis, Tennessee.

The authors have disclosed no potential conflicts, financial or otherwise. This work was supported in part by Award No. 14-2 from the Commonwealth of Virginia's Alzheimer's and Related Diseases Research Award Fund, administered by the Virginia Center on Aging, School of Allied Health Professions, Virginia Commonwealth University.

Address correspondence to Christianne Nesbitt Fowler, DNP, RN, GNP, Associate Professor, School of Nursing, Old Dominion University, 4608 Hampton Boulevard, Room 3128, Norfolk, VA 23529; e-mail:

Received: February 23, 2016
Accepted: July 06, 2016
Posted Online: September 06, 2016


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