HLTH 4300 Week 9 Tracking Summary Example

Six Weeks of Calendar Marks and Phone Records, October 5 to November 15: What Janelle's Walking Plan Produced, Which Days Neither Record Captured and Which Gaps Change the Picture

Student Name

Walden University

HLTH 4300: Personal Health and Wellness

Instructor Name

Month Day, Year

Six Weeks of Calendar Marks and Phone Records, October 5 to November 15: What Janelle's Walking Plan Produced, Which Days Neither Record Captured and Which Gaps Change the Picture

The Records

For six weeks, from Monday, October 5, to Sunday, November 15, Janelle kept two records of her planned walks. Each evening she marked a paper calendar on her refrigerator: a check for a walk, an X for no walk. Her phone recorded steps whenever she carried it. Her plan called for a 20-minute walk on the Cedar Park loop on Monday, Tuesday and Wednesday of each day-shift week, with Thursday as a spare, and a 30-minute walk on Saturdays. In week 6 she worked a night-shift rotation, for which her setback plan set a minimum of three 10-minute walks.

A walk is counted as confirmed when the phone's count for the planned window clears the threshold her goal set, two thousand steps. This summary separates walks that were confirmed, walks recorded only on the calendar, walks that did not happen and days on which neither record says anything.

What the Records Show

Table 2

Planned Saturday Walks (6 Planned) and Night-Shift Week Minimum (3 Planned)

The missed Saturday, October 24, was a day her son was sick; the calendar note says so.

Separating Missing Entries From Walks That Did Not Happen

A blank in the record is not the same as a walk that did not happen. On October 20, the calendar shows a check but the phone shows nothing, because Janelle left her phone at work; her note says she walked the loop. That is a walk with incomplete evidence, not a missed walk. On November 4, both records are empty: the calendar was not marked and the phone had no data for the evening because its battery had died. That day is genuinely unknown.

The three workday misses are different. On each, the calendar shows an X and the phone, carried that day, recorded fewer than 500 steps in the after-work window. Those walks did not happen.

Keeping these categories apart matters because they change the summary in different ways. Treating unknown days as missed would understate what Janelle did; treating them as done would overstate it.

Which Gaps Change the Overall Picture

The two uncertain workdays move the completion rate by 13 percentage points, from 67% to 80%. That is enough to matter for a judgment about whether the plan is working: 67% means she met her goal of three workday walks in only some weeks, while 80% means she met it in most. The most defensible figure is 73%, which accepts the calendar check backed by her written note and treats the one fully unknown day as unknown.

On Saturdays, the gaps do not change the picture: four or five of six were done whatever the assumption. In the night-shift week, two of three minimum walks were done.

Table 3

Workday Completion Under Different Assumptions

The range from 67% to 80% reflects only two uncertain days.

Minutes and Steps

On the 10 confirmed workday walks, the phone recorded between 2,100 and 2,900 steps in the window, a mean of about 2,450, consistent with 20 to 25 minutes of brisk walking. Because a half hour of moderate walking is generally estimated at 3,000 to 4,000 steps (Tudor-Locke et al., 2011), 2,450 steps fits a walk of a little over 20 minutes. Counting confirmed walks only, Janelle averaged about 70 minutes of walking a week across the five day-shift weeks, including Saturdays.

Patterns in the Misses

The three missed workday walks were not spread randomly. Two fell on Wednesdays after overtime on Tuesday and Wednesday of the same week, and one fell on a Monday when she took a different route home to collect a prescription and never passed the park exit. All three were linked to the prompt or the time window rather than to a decision not to walk. The uncertain days, by contrast, were linked to the records: a phone left at work and a phone with a dead battery. Separating these two kinds of gap shows that the plan's weak point is the prompt on unusual days, and that the record's weak point is the phone. Each calls for a different fix: a backup prompt for days with a changed route, and a habit of charging the phone at work.

Weeks with a Saturday walk were also weeks with more workday walks, which may mean that weeks with fewer disruptions allowed both, rather than that one walk encouraged the other.

How Much to Trust Each Record

Neither record is perfect. The calendar depends on Janelle remembering to mark it, and self-reports of physical activity often disagree with direct measures, sometimes widely (Prince et al., 2008). The phone depends on being carried and charged; in a laboratory comparison, smartphone step counts were close to observed counts, but the phone can only count what it is present for (Case et al., 2015). Using both, and recording when they disagree, gives a more honest summary than either alone.

What the Summary Means for the Next Six Weeks

The summary suggests the plan is close to working and needs adjustment rather than replacement. A completion rate between two-thirds and four-fifths means most weeks met the three-walk target. The misses point to the prompt on unusual days, so the next six weeks will add a location-based phone reminder that fires when she leaves work by any route. The gaps in the record point to the phone, so she will charge it at work.

Conclusion

Over six weeks, Janelle completed 10 confirmed workday walks of 15 planned, plus one with calendar evidence only and one day on which neither record captured anything. Depending on how those two days are treated, workday completion ranges from 67% to 80%; the most defensible figure is 73%. Saturdays and the night-shift minimum were mostly met. Separating unknown days from missed walks shows that the uncertainty is small in number but large enough to change whether she met her weekly target.

References

Case, M. A., Burwick, H. A., Volpp, K. G., & Patel, M. S. (2015). Accuracy of smartphone applications and wearable devices for tracking physical activity data. JAMA, 313(6), 625-626. https://doi.org/10.1001/jama.2014.17841

Prince, S. A., Adamo, K. B., Hamel, M., Hardt, J., Connor Gorber, S., & Tremblay, M. (2008). A comparison of direct versus self-report measures for assessing physical activity in adults: A systematic review. International Journal of Behavioral Nutrition and Physical Activity, 5, Article 56. https://doi.org/10.1186/1479-5868-5-56

Tudor-Locke, C., Craig, C. L., Brown, W. J., Clemes, S. A., De Cocker, K., Giles-Corti, B., Hatano, Y., Inoue, S., Matsudo, S. M., Mutrie, N., Oppert, J.-M., Rowe, D. A., Schmidt, M. D., Schofield, G. M., Spence, J. C., Teixeira, P. J., Tully, M. A., & Blair, S. N. (2011). How many steps/day are enough? For adults. International Journal of Behavioral Nutrition and Physical Activity, 8, Article 79. https://doi.org/10.1186/1479-5868-8-79