Osteoarthritis
Conditions
Keywords
mobile, sleep, physical activity, older adults
Brief summary
More than 50% of older persons with osteoarthritis (OA) experience disrupted sleep and insomnia symptoms of difficulty falling asleep, awakening during the night, and awakening too early and being unable to fall back to sleep. Because OA pain has been implicated in sleep problems and because physical exercise interventions have been found to improve pain and sleep quality, staying physically active during the daytime is likely advantageous in terms of improving sleep. Physical exercise interventions with a duration between 10 and 16 weeks have been shown to improve quality of sleep in older adults with self-reported disrupted sleep. Unfortunately, recent reports show that older adults with OA are mainly sedentary and few meet national guidelines for recommended amounts of daily physical activity. A self-management intervention that integrates use of mobile technology to prompt older adults to be physically active, provides ongoing monitoring of the amount of their physical activity and includes self-efficacy enhancements is a novel non-pharmacological intervention both for prevention and treatment of sleep deficiency in persons with OA. The proposed study will involve delivery of automatic physical activity-focused text messages, a novel sleep self-management diary (SleepTight) and motivational interviewing in participants with OA of the hip or knee (most commonly affected joints). The purpose of this Project is to pilot test a new self-management program: MobMPATI, a multidimensional, tailored intervention for sleep deficiency in for older adults with OA. The specific aims are to: 1. Test the acceptability of MobMPATI for older adults with OA and poor sleep quality as a manifestation of sleep deficiency. 2. Test the feasibility of implementing MobMPATI for older adults with OA, as well as collecting electronic data from the sample. 3. Explore pre/posttest changes in self-efficacy, motivation and sleep deficiency measures \[total sleep time (TST) and sleep efficiency (SE)\] with the MobMPATI intervention. This study will provide feasibility/acceptability and preliminary data necessary for a larger clinical trial of MobMPATI intervention to encourage physical activity and reduce sedentary behavior in older adults with OA as a way of reducing sleep deficiency. Preliminary testing of the intervention will indicate what measures are more sensitive in promoting self-efficacy and motivation so that a smaller number of outcomes could be monitored to reduce participant burden. This study is the first step in this innovative program of research. The knowledge gained will provide data on the benefit of a potentially cost-effective intervention that could be implemented on a large scale to improve health of older adults with OA.
Interventions
BEHAVIORALMotivaltional interviews and infrequent motivational text messages
A self-management intervention will integrate use of mobile technology to prompt older adults to be physically active, provides ongoing monitoring of the amount of their physical activity and includes self-efficacy enhancements is a novel non-pharmacological intervention both for prevention and treatment of sleep deficiency in persons with OA
Sponsors
University of Washington
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
TREATMENT
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
65 Years to No maximum
Healthy volunteers
No
Inclusion criteria
\>65 years of age Clinically diagnosed OA of hip or knee Positive for sleep deficiency, defined as Insomnia Severity Index\>=12 Low physical activity based on Rapid Assessment of Physical Activity \<=2 Stable use of pain, sleep and/or mood regulating medications over the past month Resides in Seattle metropolitan area
Exclusion criteria
Acute injury associated with hip or knee pain Inability to stand up without assistance Memory Impairment Screen for Telephone (MIS-T) score of \<4, suggesting cognitive impairment Severe hearing or visual impairment An acute episode or change in the treatment of psychiatric problems within the past 3 months Diagnosed sleep disorder (e.g., sleep disordered breathing; insomnia).
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Mixed Effect Model Inferential Estimates of Longitudinal Changes Across 3 Time Points (Baseline, Week 14, Week 19) in Insomnia Severity Index | Assessed at Baseline, week 14, week 19; change from baseline throughout three time points reported | Insomnia Severity Index (ISS) Score range 0 to 28 at each time point, with higher scores indicating more severe insomnia symptoms A single value for change in ISS across three-time points was calculated using linear mixed effect modeling |
| Mixed Effect Model Inferential Estimates of Longitudinal Changes Across Three Time Points (Baseline, Week 14, Week 19) in Actigraphy Total Sleep Time (TST) | Assessed at Baseline, week 14, week 19; change from baseline throughout three time points reported | Actigraphy Total Sleep Time (TST) in minutes was calculated using baseline, week 14, and week 19 data from a wrist-worn actigraph A single value for change in TST across three-time points was calculated using linear mixed effect modeling A negative change score indicates lower TST ( in min) over time |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Mixed Effect Model Inferential Estimates of Longitudinal Changes Across Three Time-points (Baseline, Week 14, Week 19) in Self-Efficacy (SE) to Manage Chronic Disease Scale | Assessed at Baseline, week 14, week 19; change from baseline throughout three time points reported | Self-Efficacy to Manage Chronic Disease Scale Score range 1 to 10, with higher scores indicating better efficacy. A single value for change in SE across three-time points was calculated using linear mixed effect modeling Positive change score indicates an improvement in self-efficacy over time |
| Mixed Effect Model Inferential Estimates of Longitudinal Changes Across Three Time-points (Baseline, Week 14, Week 19) in Pain Score | Assessed at Baseline, week 14, week 19; change from baseline throughout three time points reported | Pain Score range 1 to 10, with higher scores indicating worse symptoms. A single value for change in pain across three-time points was calculated using linear mixed effect modeling Positive change score indicates worsening in pain over time |
| Mixed Effect Model Inferential Estimates of Longitudinal Changes Across Three Time-points (Baseline, Week 14, Week 19) in Objectively Measured Step Count | Assessed at Baseline, week 14, week 19; change from baseline throughout three time points reported | Fitbit devices were used to measure weekly step count at baseline, and week 14, and week 19 A single value for change in step count across three-time points was calculated using linear mixed effect modeling A positive change indicates increased step count over time |
Countries
United States
Participant flow
Participants by arm
| Arm | Count |
|---|---|
| Motivational Interview and Text Messages Multidimensional, tailored intervention for sleep deficiency in for older adults with OA
Motivaltional interviews and infrequent motivational text messages: A self-management intervention will integrate use of mobile technology to prompt older adults to be physically active, provides ongoing monitoring of the amount of their physical activity and includes self-efficacy enhancements is a novel non-pharmacological intervention both for prevention and treatment of sleep deficiency in persons with OA | 24 |
| Total | 24 |
Baseline characteristics
| Characteristic | Motivational Interview and Text Messages |
|---|---|
| Age, Continuous | 71 years STANDARD_DEVIATION 4 |
| Race (NIH/OMB) American Indian or Alaska Native | 0 Participants |
| Race (NIH/OMB) Asian | 1 Participants |
| Race (NIH/OMB) Black or African American | 0 Participants |
| Race (NIH/OMB) More than one race | 0 Participants |
| Race (NIH/OMB) Native Hawaiian or Other Pacific Islander | 0 Participants |
| Race (NIH/OMB) Unknown or Not Reported | 0 Participants |
| Race (NIH/OMB) White | 23 Participants |
| Sex: Female, Male Female | 17 Participants |
| Sex: Female, Male Male | 7 Participants |
Adverse events
| Event type | EG000 affected / at risk |
|---|---|
| deaths Total, all-cause mortality | 0 / 24 |
| other Total, other adverse events | 0 / 24 |
| serious Total, serious adverse events | 0 / 24 |
Outcome results
Primary
Mixed Effect Model Inferential Estimates of Longitudinal Changes Across 3 Time Points (Baseline, Week 14, Week 19) in Insomnia Severity Index
Insomnia Severity Index (ISS) Score range 0 to 28 at each time point, with higher scores indicating more severe insomnia symptoms A single value for change in ISS across three-time points was calculated using linear mixed effect modeling
Time frame: Assessed at Baseline, week 14, week 19; change from baseline throughout three time points reported
Population: Mixed effect models were utilized because of the time repeated structure of the data. Data collection occasions were also entered in the models to account for change over time. The adjusted for age and gender main effects for time for the ISS was tested for significance and reported as estimates and 95% confidence intervals (CI)
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Motivational Interview and Text Messages | Mixed Effect Model Inferential Estimates of Longitudinal Changes Across 3 Time Points (Baseline, Week 14, Week 19) in Insomnia Severity Index | -1.24 units on a scale |
Primary
Mixed Effect Model Inferential Estimates of Longitudinal Changes Across Three Time Points (Baseline, Week 14, Week 19) in Actigraphy Total Sleep Time (TST)
Actigraphy Total Sleep Time (TST) in minutes was calculated using baseline, week 14, and week 19 data from a wrist-worn actigraph A single value for change in TST across three-time points was calculated using linear mixed effect modeling A negative change score indicates lower TST ( in min) over time
Time frame: Assessed at Baseline, week 14, week 19; change from baseline throughout three time points reported
Population: Mixed effect models were utilized because of the time repeated structure of the data. Data collection occasions were also entered in the models to account for change over time. The adjusted for age and gender main effects for time for the TST was tested for significance and reported as estimates and 95% confidence intervals (CI)
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Motivational Interview and Text Messages | Mixed Effect Model Inferential Estimates of Longitudinal Changes Across Three Time Points (Baseline, Week 14, Week 19) in Actigraphy Total Sleep Time (TST) | -4.5 minutes |
Secondary
Mixed Effect Model Inferential Estimates of Longitudinal Changes Across Three Time-points (Baseline, Week 14, Week 19) in Objectively Measured Step Count
Fitbit devices were used to measure weekly step count at baseline, and week 14, and week 19 A single value for change in step count across three-time points was calculated using linear mixed effect modeling A positive change indicates increased step count over time
Time frame: Assessed at Baseline, week 14, week 19; change from baseline throughout three time points reported
Population: Mixed effect models were utilized because of the time repeated structure of the data. Data collection occasions were also entered in the models to account for change over time. The adjusted for age and gender main effects for time for the step count was tested for significance and reported as estimates and 95% confidence intervals (CI)
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Motivational Interview and Text Messages | Mixed Effect Model Inferential Estimates of Longitudinal Changes Across Three Time-points (Baseline, Week 14, Week 19) in Objectively Measured Step Count | 45.6 step count |
Secondary
Mixed Effect Model Inferential Estimates of Longitudinal Changes Across Three Time-points (Baseline, Week 14, Week 19) in Pain Score
Pain Score range 1 to 10, with higher scores indicating worse symptoms. A single value for change in pain across three-time points was calculated using linear mixed effect modeling Positive change score indicates worsening in pain over time
Time frame: Assessed at Baseline, week 14, week 19; change from baseline throughout three time points reported
Population: Mixed effect models were utilized because of the time repeated structure of the data. Data collection occasions were also entered in the models to account for change over time. The adjusted for age and gender main effects for time for the pain scores was tested for significance and reported as estimates and 95% confidence intervals (CI)
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Motivational Interview and Text Messages | Mixed Effect Model Inferential Estimates of Longitudinal Changes Across Three Time-points (Baseline, Week 14, Week 19) in Pain Score | -0.13 score on a scale |
Secondary
Mixed Effect Model Inferential Estimates of Longitudinal Changes Across Three Time-points (Baseline, Week 14, Week 19) in Self-Efficacy (SE) to Manage Chronic Disease Scale
Self-Efficacy to Manage Chronic Disease Scale Score range 1 to 10, with higher scores indicating better efficacy. A single value for change in SE across three-time points was calculated using linear mixed effect modeling Positive change score indicates an improvement in self-efficacy over time
Time frame: Assessed at Baseline, week 14, week 19; change from baseline throughout three time points reported
Population: Mixed effect models were utilized because of the time repeated structure of the data. Data collection occasions were also entered in the models to account for change over time. The adjusted for age and gender main effects for time for the self-efficacy was tested for significance and reported as estimates and 95% confidence intervals (CI)
| Arm | Measure | Value (MEAN) |
|---|---|---|
| Motivational Interview and Text Messages | Mixed Effect Model Inferential Estimates of Longitudinal Changes Across Three Time-points (Baseline, Week 14, Week 19) in Self-Efficacy (SE) to Manage Chronic Disease Scale | 0.28 score on a scale |