Home Medicine Optimizing chronic pain management through patient engagement with quality of life measures: a randomized controlled trial
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Optimizing chronic pain management through patient engagement with quality of life measures: a randomized controlled trial

  • John C. Licciardone EMAIL logo , Hanna McDonald , McKenna Yablon , Wayne Ngo , Kimberly Ann Cunanan Garza and Subhash Aryal
Published/Copyright: August 2, 2022
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Journal of Osteopathic Medicine
From the journal Journal of Osteopathic Medicine Volume 122 Issue 11

Abstract

Context

Health-related quality of life (HRQOL) represents a new approach for guiding chronic pain management because it is patient-centered and more likely to be understood and accepted by patients.

Objectives

To assess the value and utility of an eHealth intervention for patients with chronic low back pain (CLBP) that was primarily based on HRQOL measures and to measure the clinical outcomes associated with its use.

Methods

A randomized controlled trial was conducted within the Pain Registry for Epidemiological, Clinical, and Interventional Studies and Innovation (PRECISION Pain Research Registry) using participants screened from November 2019 through February 2021. A total of 331 registry participants within the 48 contiguous states and the District of Columbia met the eligibility criteria, which included having CLBP and HRQOL deficits. Almost three-fourths of the participants were enrolled after onset of the COVID-19 pandemic. The participants were randomized to an eHealth intervention for HRQOL or wait list control. The primary outcome measures involved HRQOL based on the Patient-Reported Outcomes Measurement Information System (PROMIS), including the SPADE cluster (Sleep disturbance, Pain interference with activities, Anxiety, Depression, and low Energy/fatigue) and each of its five component scales. Secondary outcome measures involved low back pain intensity and back-related functioning. Changes over time for each outcome measure reported by participants in each treatment group were compared utilizing the student’s t-test for statistical significance and Cohen’s d statistic for clinical importance. Outcomes were reported as between-group differences in change scores and the d statistic, with positive values favoring the experimental treatment group.

Results

There were no significant differences between the experimental and control treatment groups for changes over time in any primary outcome measure. The d statistic (95% confidence interval) for the difference between the experimental and control treatment groups on the SPADE cluster was 0.04 (−0.18–0.25). The corresponding d statistics for the SPADE scales ranged from −0.06 (−0.27 to 0.16) for anxiety to 0.11 (−0.10 to 0.33) for sleep disturbance. There were also no significant or clinically important differences between the experimental and control treatment groups on the secondary outcome measures. Additionally, in subgroup analyses involving participants treated by osteopathic vs allopathic physicians, no significant interaction effects were observed.

Conclusions

The eHealth intervention studied herein did not achieve statistically significant or clinically important improvements in any of the primary or secondary outcome measures. However, the validity and generalizability of the findings may have been limited by the unforeseen onset and impact of the COVID-19 pandemic shortly after beginning the trial.

Keywords: chronic low back pain; quality of life; randomized controlled trial

Chronic noncancer pain is an important healthcare issue that transcends the simplistic view that it serves only as a manifestation of more serious medical problems in a given patient. Chronic pain management in the United States has been hampered by an overreliance on pain intensity measures and corresponding treatment with pharmacological agents, including opioids [1]. Focusing on health-related quality of life (HRQOL) rather than on pain intensity represents a new approach for guiding chronic pain management because it is patient-centered and consistent with the cultural transformation advocated by the National Pain Strategy [2]. This patient-centeredness also aligns with osteopathic philosophy and its approach to chronic pain management [3]. Patient-reported HRQOL measures have been historically undervalued as medical decision-making tools [4]. However, the Patient-Reported Outcomes Measurement Information System (PROMIS) that was developed with support from the National Institutes of Health (NIH) now includes data elements that are recommended as part of a “minimum dataset” for research on chronic low back pain (CLBP) [5]. The latter include the PROMIS scales for pain interference with activities, physical function, depression, and sleep disturbance. Other commonly utilized PROMIS scales measure anxiety, energy/fatigue level, and participation in social roles.

The main objective of this study was to assess the value and utility of an eHealth intervention for patients with CLBP that was based on PROMIS measures of HRQOL and to assess the clinical outcomes associated with its use. Another objective was to conduct subgroup analyses according to the type of physician (i.e., osteopathic vs allopathic physician) who treated low back pain and to identify and further explore any significant interaction effects.

Methods

Research design

The Optimizing Chronic Pain Management through Patient Engagement with Quality of Life Measures (OPTIQUAL) Trial was conducted by the Osteopathic Research Center utilizing its Pain Registry for Epidemiological, Clinical, and Interventional Studies and Innovation (PRECISION Pain Research Registry). The registry utilizes a digital research platform to collect longitudinal self-reported data from participants with CLBP throughout the 48 contiguous states and the District of Columbia [6]. Methodological features of the registry, which include online screening for eligibility, remote participant consenting, and electronic data capture, represent a new clinical trial paradigm that facilitates the enrollment of large numbers of participants to study real-world effectiveness at a reasonable cost. The protocol for the OPTIQUAL Trial was approved by the North Texas Regional Institutional Review Board (protocol 2015–169) and posted at ClinicalTrials.gov (registry number NCT04168437) [7]. Informed consent was provided by all participants prior to enrolling in the trial, and a Data and Safety Monitoring Board was established to monitor it.

Inclusion and exclusion criteria

Registry participants were screened during the period from November 2019 through February 2021 to identify those who met the following general inclusion criteria: (1) being aged between 21 and 79 years at the time of registry enrollment; (2) having sufficient English language proficiency to complete informed consent and case report forms; and (3) having a physician who treated their low back pain. Registry participants who met all three of the aforementioned criteria were further screened to determine if they met the clinical inclusion criteria. First, they were required to report CLBP based on the case definition recommended by the NIH Task Force on Research Standards for Chronic Low Back Pain, which requires that patients have low back pain for at least the past 3–6 months and with a pain frequency of at least half of the days during the past 6 months [5]. Second, they must also have reported a SPADE (Sleep disturbance, Pain interference with activities, Anxiety, Depression, and low Energy/fatigue) cluster score ≥55 for HRQOL deficits on the PROMIS-29 instrument. Persons who report being pregnant or institutionalized are not enrolled in the PRECISION Pain Research Registry and thus were not eligible for the trial.

Experimental and control treatment arms

A random number generator within the Microsoft Excel software was utilized to allocate participants to treatment. Participants randomized to the experimental treatment group received an eHealth intervention consisting of a two-page HRQOL report and interpretation guide. The report was based exclusively on PROMIS-29 responses for the SPADE cluster and each of its five component scales. The first page included a graphic summary of scores on each of these measures, while the second page provided an interpretation guide that was suitable for both patients and physicians (Appendix 1). The participants were encouraged to utilize the report to identify aspects of their health that needed improvement and then take appropriate action. The latter may have involved such strategies as undertaking self-care or sharing the report with a physician to learn about other approaches or treatments to improve their HRQOL. There was no additional patient education or counseling provided as part of the intervention. The control treatment group was placed on a wait list to receive the eHealth intervention after completing the trial. This occurred 3 months later after reporting clinical outcomes at their exit encounter, and the report was based on HRQOL data provided at that time. Both the experimental and control treatment groups continued to receive their usual care for low back pain during the trial.

Baseline and follow-up measures

Trial baseline data were collected at the index encounter, which may have been at the time of registry enrollment or at any of the three subsequent quarterly encounters that occurred 3, 6, or 9 months following enrollment. Trial exit data were collected at the next quarterly encounter following the index encounter. Thus, participants were followed for only 3 months, regardless of whether they entered the study at the time of registry enrollment or at any quarterly encounter through the ninth month. The study case report forms collected data on basic sociodemographic and clinical variables utilized to describe the trial participants. They also measured the primary and secondary outcome variables. The participants also provided information on the type of physician (i.e., osteopathic or allopathic physician) who currently treated their low back pain at the index encounter to enable subgroup analyses relating to osteopathic medical care. The participants who were assigned to the experimental treatment group received the eHealth intervention no later than 1 week following the index encounter. They also completed a survey on the value and utility of the eHealth intervention at the end of the trial, 3 months following the index encounter.

Assessment of the eHealth intervention

The eHealth intervention was assessed utilizing a survey that queried participants in the experimental treatment group about the value and utility of their HRQOL report. The value of the report was measured utilizing a visual analogue scale ranging from 0 to 100. The utility of the report was based on such factors as participant actions in response to the report, sharing the report with their physician or others, actions recommended by the physician, and the SPADE scales targeted for improvement based on the report.

Primary outcome measures

Both the primary and secondary outcome measures utilized in the trial were recommended by the NIH Task Force on Research Standards for Chronic Low Back Pain [5]. The primary outcomes involving HRQOL were derived from the SPADE cluster of the PROMIS-29 instrument [8]. The latter includes items derived from the PROMIS pain behavior item bank that measures how low back pain interferes with normal activities, including physical and social functioning, and assesses levels of anxiety, depression, fatigue, and sleep disturbance [9]. Each of the five SPADE scales includes four items, which are rated on an ordinal scale from 1 to 5. Thus, crude scale scores may range from 4 to 20. These scores are then transformed and normed according to the US general population, utilizing “t scores” such that the population mean is 50 and the standard deviation is 10. The SPADE cluster score is the mean of its five component scale scores. Higher scores on each of the five SPADE scales, and on the SPADE cluster, represent greater HRQOL deficits (i.e., poorer HRQOL). Prior research on the PROMIS scales indicated that a minimally important change over time ranged from about 3.3 to 6.7; however, this was based on cancer patients and may not be generalizable to other populations [10].

Secondary outcome measures

The two secondary outcome measures involved low back pain intensity and back-related functioning. A numerical rating scale (NRS) was utilized to measure low back pain intensity on average over the past 7 days, utilizing an 11-point scale ranging from 0 (“no pain”) to 10 (“worst pain”). The Roland-Morris Disability Questionnaire (RMDQ) was utilized to measure back-related functioning. It consists of 24 items that address how much low back pain adversely affects patient functioning and activities [11]. Each item is scored as either 1 (low back pain has an adverse impact) or 0 (low back pain does not have an adverse impact). The RMDQ is scored as the sum of responses to each item, thereby potentially ranging from 0 to 24. The NRS for pain intensity and the RMDQ are the two patient-reported outcome measures most commonly utilized for low back pain, and research standards for their use and interpretation have been established [5, 12], [13], [14].

Statistical analysis

The baseline characteristics of the experimental and control treatment groups were compared utilizing contingency table methods and the Student’s t-test for categorical and continuous variables, respectively. Survey responses within the experimental treatment group regarding the eHealth intervention were summarized utilizing descriptive statistics. Subgroup differences between participants treated by osteopathic and allopathic physicians were also compared utilizing contingency table methods and the Student’s t-test for categorical and continuous variables, respectively. Specifically, the student’s t-test was utilized to compare trial outcomes (i.e., change scores for improvement in the clinical outcome measures over 3 months) in the experimental and control treatment groups. Between-group differences in change scores were utilized to report outcomes, with positive values favoring the experimental treatment group. Cohen’s d statistic was utilized to further assess the magnitude of the treatment effects attributable to the eHealth intervention. Any d value ≥0.20 was considered to reflect a clinically important outcome attributable to the eHealth intervention [15]. All analyses were conducted with the IBM SPSS Statistical Software (Version 28). Hypotheses were assessed at the level of p≤0.05 utilizing two-sided significance tests. An anticipated total sample size of 320 participants was estimated to provide 99% statistical power to detect significant differences between the experimental and control treatment groups that achieved at least a “medium” treatment effect size (d≥0.5) for each outcome measure, and to provide 80% statistical power to detect significant differences between the experimental and control treatment groups that were considered to be in the range of a “small-to-medium” treatment effect size (d≥0.32).

Results

A total of 331 participants were randomized, including 166 in the experimental treatment group and 165 in the control treatment group (Figure 1). The participants in each group were generally comparable (Table 1). Only marginally significant differences between groups were observed for the presence of chronic widespread pain and diabetes mellitus.

Figure 1: The flow of participants through the trial. SPADE denotes that the cluster score was derived from the Sleep disturbance, Pain interference with activities, Anxiety, Depression, and low Energy/fatigue scales of the Patient-Reported Outcomes Measurement Information System.
Figure 1:

The flow of participants through the trial. SPADE denotes that the cluster score was derived from the Sleep disturbance, Pain interference with activities, Anxiety, Depression, and low Energy/fatigue scales of the Patient-Reported Outcomes Measurement Information System.

Table 1:

Participant characteristics according to treatment group.a

Characteristic Experimental treatment (n=166) Control treatment (n=165) p-Value
No. % No. %
Age, y (mean ± SD; range) 51.9 ± 13.3

21–79		 50.2 ± 13.5

21–77		 0.26
Sex 0.46
 Female 122 73.5 127 77.0
 Male 44 26.5 38 23.0
Race 0.36
 Black 16 9.6 20 12.1
 Other 7 4.2 3 1.8
 White 143 86.1 142 86.1
Ethnicity 0.47
 Hispanic 8 4.8 11 6.7
 Non-Hispanic 158 95.2 154 93.3
Educational level 0.06
 High school or lower 29 17.5 22 13.3
 Some post-high school education 67 40.4 88 53.3
 College degree or higher 70 42.2 55 33.3
Cigarette smoking status 0.31
 Never or former smoker 139 83.7 131 79.4
 Current smoker 27 16.3 34 20.6
Body mass index (mean ± SD) 32.0 ± 8.2 32.7 ± 8.3 0.42
Duration of low back pain 0.69
 ≤5 years 43 25.9 46 27.9
 >5 years 123 74.1 119 72.1
History of low back surgery 0.81
 No 130 78.3 131 79.4
 Yes 36 21.7 34 20.6
Presence of chronic widespread pain 0.03
 No 53 31.9 35 21.2
 Yes 113 68.1 130 78.8
Work loss ≥1 month due to low back pain 0.62
 No 88 53.0 83 50.3
 Yes 78 47.0 82 49.7
Received disability or workers’ compensation benefits due to low back pain 0.12
 No 132 79.5 119 72.1
 Yes 34 20.5 46 27.9
Involved in a legal action due to low back pain 0.30
 No 149 89.8 142 86.1
 Yes 17 10.2 23 13.9
Pain catastrophizing (mean ± SD) 22.2 ± 13.2 23.1 ± 12.3 0.51
Pain self-efficacy (mean ± SD) 30.8 ± 13.4 29.1 ± 13.9 0.27
History of medical conditions
 Herniated disc 0.69
  No 91 54.8 94 57.0
  Yes 75 45.2 71 43.0
 Sciatica 0.97
  No 63 38.0 63 38.2
  Yes 103 62.0 102 61.8
 Osteoarthritis 0.77
  No 72 43.4 69 41.8
  Yes 94 56.6 96 58.2
 Osteoporosis 0.54
  No 140 84.3 135 81.8
  Yes 26 15.7 30 18.2
 Hypertension 0.35
  No 86 51.8 94 57.0
  Yes 80 48.2 71 43.0
 Heart disease 0.71
  No 150 90.4 151 91.5
  Yes 16 9.6 14 8.5
 Diabetes mellitus 0.02
  No 142 85.5 125 75.8
  Yes 24 14.5 40 24.2
 Asthma 0.26
  No 123 74.1 113 68.5
  Yes 43 25.9 52 31.5
 Depression 0.052
  No 53 31.9 37 22.4
  Yes 113 68.1 128 77.6
Type of physician 0.90
 Osteopathic 26 15.7 25 15.2
 Allopathic 140 84.3 140 84.8
Current use of opioids for low back pain 0.97
 No 111 66.9 110 66.7
 Yes 55 33.1 55 33.3
Health-related quality of life
 SPADE cluster (mean ± SD) 61.2 ± 5.5 61.1 ± 5.4 0.87
 Sleep disturbance (mean ± SD) 60.3 ± 7.2 60.2 ± 7.6 0.95
 Pain interference with activities (mean ± SD) 65.5 ± 6.1 64.8 ± 6.2 0.32
 Anxiety (mean ± SD) 59.5 ± 8.4 59.6 ± 7.9 0.91
 Depression (mean ± SD) 57.9 ± 8.2 58.3 ± 7.7 0.66
 Low energy/fatigue (mean ± SD) 63.1 ± 8.4 62.8 ± 8.5 0.76
Low back pain intensity (mean ± SD) 6.3 ± 1.7 6.1 ± 1.8 0.28
Back-related functioning (mean ± SD) 16.0 ± 5.3 15.8 ± 5.0 0.70

  1. aTable entries are No., and % unless otherwise indicated. Chronic widespread pain was present if participants were bothered “a little” or “a lot” by it. Continuous clinical measures included the Pain Catastrophizing Scale for pain catastrophizing, the Pain Self-Efficacy Questionnaire for pain self-efficacy, the Patient-Reported Outcomes Measurement Information System (PROMIS) with 29 items for health-related quality of life, the numerical rating scale from 0 to 10 for low back pain intensity, and the Roland-Morris Disability Questionnaire for back-related functioning. Higher scores represent worse clinical status on each of these measures. SD, standard deviation; SPADE, Sleep disturbance, Pain interference with activities, Anxiety, Depression, and low Energy/fatigue.

The survey for the value and utility of the eHealth intervention was completed by 158 (95.2%) participants randomized to the experimental treatment group. The mean overall value of the report was 63.7 (SD=26.7) (Table 2). A total of 36 (22.8%) participants shared the report with the physician who treated their low back pain. Most participants agreed that the report was easy to understand after reading the interpretation guide (83.5%) and that it provided HRQOL information that they did not know (57.0%). Pain interference with activities was identified as having the most harmful impact on HRQOL, whereas anxiety had the least harmful impact. The latter findings were highly consistent with the participant actions undertaken in response to the report, either individually through self-care or in consultation with their physician. There were no significant differences in the survey responses between the participants treated by osteopathic or allopathic physicians.

Table 2:

Survey responses on the value and utility of the eHealth intervention (n=158).a

Survey item %
Overall value (mean ± SD) 63.7 ± 26.7
“The report was easy for me to understand after reading the interpretation guide”
 Strongly agree 38
 Agree 46
 Neither agree nor disagree 11
 Disagree 5
 Strongly disagree 0
“The report provided information about my quality of life that I did not know”
 Strongly agree 19
 Agree 38
 Neither agree nor disagree 34
 Disagree 8
 Strongly disagree 2
Most harmful impact on health-related quality of life
 Sleep disturbance 23
 Pain interference with activities 45
 Anxiety 5
 Depression 13
 Low energy or fatigue 13
Least harmful impact on health-related quality of life
 Sleep disturbance 15
 Pain interference with activities 9
 Anxiety 29
 Depression 26
 Low energy or fatigue 21
Persons with whom the report was shared
 Spouse or significant other 40
 Other family member 22
 Friend 15
 Employer 3
 Health care provider other than physician 20
Participant actions based on the report
 Reading or learning more about improving health-related quality of life 76
 Beginning a new program to improve health-related quality of life 32
 Speaking to a healthcare provider other than physician about improving health-related quality of life 32
 Speaking to physician who treats their low back pain about improving health-related quality of life 51
Target of the participant actions based on the report (n=133)
 Sleep disturbance 73
 Pain interference with activities 83
 Anxiety 56
 Depression 53
 Low energy or fatigue 72
Report shared with physician who treats their low back pain
 Yes 23
 No 77
Results of sharing report with physician who treats their low back pain (n=36)
 Physician did not look at report 17
 Physician looked at it but did not address it 33
 Physician talked about it but did not recommend anything 6
 Physician made recommendations to improve health-related quality of life 44
Actions pertaining to health-related quality of life based on report sharing with physician (n=16)
 Participant self-care 100
 Specific instructions from physician to participant 75
 Prescription for new medication from physician 44
Target of participant actions based on instructions or new medication from physician (n=15)
 Sleep disturbance 53
 Pain interference with activities 93
 Anxiety 40
 Depression 53
 Low energy or fatigue 60

  1. aSurvey results are displayed as percentages, except for overall value (based on a visual analogue scale from 0 to 100). Percentages are based on 158 participants unless otherwise noted. Percentages may exceed 100% on items which allowed multiple responses.

The primary outcome measures for HRQOL reported on the prerandomization and exit case report forms were available for 326 (98.5%) trial completers, including 164 (98.8%) completers in the experimental treatment group and 162 (98.2%) completers in the control treatment group. There were no significant differences between the experimental and control treatment groups on any primary outcome measure (Table 3). Moreover, the d statistic for the difference between experimental and control treatment groups on the SPADE cluster was 0.04 (−0.18 to 0.25). The corresponding d statistics for the SPADE scales ranged from −0.06 (−0.27 to 0.16) for anxiety to 0.11 (−0.10 to 0.33) for sleep disturbance. Similarly, there were no significant or clinically important differences between the experimental and control treatment groups on the secondary outcome measures. Moreover, in subgroup analyses involving participants treated by osteopathic vs allopathic physicians, no significant interaction effects were observed. There were no serious adverse events reported during the trial. An intention-to-treat analysis was not performed because there were virtually no missing encounter data.

Table 3:

Changes in primary and secondary outcome measures according to treatment group (n=326).a

Outcome measure Experimental treatment group (n=164) Control treatment group (n=162) Difference between treatment groups Effect size
Mean improvement Mean improvement Mean (95% CI) d (95% CI) p-Value
Primary outcomes
 SPADE cluster score 0.99 0.84 0.15 −0.73 to 1.03 0.04 −0.18 to 0.25 0.73
 SPADE scale score
  Sleep disturbance 1.32 0.62 0.70 −0.65 to 2.05 0.11 −0.10 to 0.33 0.31
  Pain interference with activities 0.99 1.06 −0.07 −1.15 to 1.01 −0.01 −0.23 to 0.20 0.90
  Anxiety 0.66 1.03 −0.37 −1.84 to 1.10 −0.06 −0.27 to 0.16 0.62
  Depression 0.76 0.80 −0.04 −1.50 to 1.42 −0.01 −0.22 to 0.21 0.96
  Low energy/fatigue 1.25 0.70 0.55 −0.85 to 1.94 0.09 −0.13 to 0.30 0.44
Secondary outcomes
 Low back pain intensity 0.30 0.14 0.16 −0.20 to 0.51 0.10 −0.12 to 0.31 0.38
 Back-related functioning 0.57 0.44 0.12 −0.57 to 0.82 0.04 −0.18 to 0.26 0.73

  1. aPositive and negative differences between treatment groups and for effect size favor the experimental and control treatment groups, respectively, the reported p values are for the differences between treatment groups, SPADE, sleep disturbance, pain interference with activities, anxiety, depression, and low energy/fatigue.

Discussion

The eHealth intervention studied herein did not provide statistically significant or clinically important improvements in any of the primary outcome measures involving HRQOL or secondary outcome measures relating to low back pain intensity or back-related functioning. These findings are similar to those of a previous trial involving 300 participants that included many design features similar to the present study but that provided the HRQOL report to the physician prior to a patient encounter rather than to the patient directly [16]. However, the present findings are partially discrepant with those of the preliminary feasibility trial of the same eHealth intervention involving 102 participants over a 3 month period [17]. Therein, clinically important improvements in the realm of HRQOL involving depression (d=0.37) and anxiety (d=0.24) were observed, as well as improvements in back-related functioning (d=0.36). Because the feasibility trial was meant to inform the research design, experimental treatment, and other aspects of the OPTIQUAL Trial, it is unclear why none of the differences observed herein between the experimental and control treatment groups achieved either statistical significance or clinical importance.

There are at least two possible explanations for the negative findings of the present study. The feasibility trial recruited participants during the period from August 2019 through January 2020. All registry participants during this period resided in Texas, whereas the OPTIQUAL Trial participants were recruited from registry participants throughout the 48 contiguous states and the District of Columbia. Nevertheless, it is unlikely that treatments for and clinical outcomes of CLBP would have varied substantially by extending the research design from a statewide to a national level. More likely, the discrepant findings may have been attributable to the onset of the COVID-19 pandemic on March 13, 2020 [18]. Because almost three-fourths of participants in the OPTIQUAL Trial were enrolled during the pandemic, they may have had limited access to treatments for low back pain or to other facilities and the services needed to act in response to the HRQOL report. Our findings confirmed that less than one-fourth of the participants shared the report with the physician who treated their low back pain. In other studies, our registry found decreased utilization of several nonpharmacological treatments for low back pain among 528 participants within 3 months [19], and among 476 participants within 6 months [20] of the pandemic onset in the United States. Thus, limited sharing of the report with physicians and decreased access to and utilization of other related facilities and services may have attenuated the differences in outcomes between the experimental and control treatment groups that otherwise would have been observed if the pandemic had not occurred.

There were no significant subgroup differences observed in the reported value and utility of the eHealth intervention, or in the primary or secondary outcome measures, based on the type of physician who treated low back pain. A registry study of 313 participants demonstrated that patients treated for low back pain report better physician interpersonal manner and empathy with osteopathic physicians, as compared with allopathic physicians [21]. A subsequent registry study of 404 participants found better patient-centered care provided by osteopathic physicians in areas that may be germane to follow-up counseling for HRQOL as studied herein, such as being interested in the patient as a whole person [22]. Such osteopathic physician attributes, if present in this study, did not facilitate better outcomes among their patients with CLBP. Again, it is possible that decreased access to healthcare (including osteopathic manipulative treatment) during the COVID-19 pandemic [19, 20] may have attenuated osteopathic vs allopathic physician interaction effects relating to the association between treatment group assignment and outcomes for HRQOL, low back pain intensity, and back-related functioning.

This study had several strengths that should be noted. Randomized registry trials represent a new paradigm that facilitates the enrollment of sizable numbers of research participants quickly and at low cost, often utilizing a representative sample of persons with the target condition within a real-world setting [23]. The PRECISION Pain Research Registry facilitated the collection of data utilizing a battery of validated research instruments, with minimal attrition and missing data, by utilizing a digital research platform to interact with trial participants. Similarly, the registry enabled the delivery of the eHealth intervention to a national audience rapidly and inexpensively. The limitations of the trial were largely attributable to its performance during the COVID-19 pandemic, as described above, and to the eHealth intervention itself. The 3 month follow-up period prior to collecting exit data may not have been sufficiently lengthy to observe important improvements in the primary and secondary outcome measures. It is possible that many participants did not visit their physician for low back pain within the 3 month follow-up period, particularly during the pandemic In general, and especially because of decreased access to healthcare for low back pain during the pandemic, it may have been necessary to provide a more intensive eHealth intervention to the experimental treatment group. For example, additional self-care modules pertaining to each of the five SPADE scales could have been developed and delivered to participants utilizing the digital research platform. These modules could have been provided comprehensively as a package to all participants to address the overall SPADE cluster, or individually to selected participants according to the priority established by their reported HRQOL scale scores. Finally, the study findings may not be generalizable to patients without computers or cell phones or to those who are not comfortable utilizing such devices.

Conclusions

The eHealth intervention studied herein did not provide statistically significant or clinically important improvements in any of the primary outcome measures involving HRQOL or any of the secondary outcome measures relating to low back pain intensity or back-related functioning. Moreover, in subgroup analyses involving participants treated by osteopathic vs. allopathic physicians, no significant interaction effects were observed. Despite several strengths attributable to utilizing the PRECISION Pain Research Registry to conduct this randomized controlled trial, the validity and generalizability of its findings may have been limited by the unforeseen onset and impact of the COVID-19 pandemic shortly after beginning the trial.

Corresponding author: John C. Licciardone, DO, MS, MBA, FACPM, Osteopathic Research Center and the Department of Family Medicine, University of North Texas Health Science Center-Texas College of Osteopathic Medicine, 3500 Camp Bowie Blvd, Fort Worth, TX 76107-2699, USA, E-mail:

  1. Research funding: Dr. Licciardone received grants from the American Osteopathic Association and the Osteopathic Heritage Foundation.

  2. Author contributions: All authors provided substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; all authors drafted the article or revised it critically for important intellectual content; all authors contributed to the analysis and interpretation of data; all authors gave final approval of the version of the article to be published; and all authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

  3. Competing interests: None reported.

  4. Ethical approval: This study was approved by the North Texas Institutional Review Board (protocol 2015–169); ClinicalTrials registry number: NCT04168437.

  5. Informed consent: All participants in this study provided written informed consent prior to participation.

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Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/jom-2021-0296).

Received: 2021-12-22
Accepted: 2022-06-08
Published Online: 2022-08-02

© 2022 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

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https://doi.org/10.1515/jom-2021-0296
Keywords for this article
chronic low back pain; quality of life; randomized controlled trial
Creative Commons
BY 4.0

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Paralympic golf movement: the links between inclusion and treating the whole person to regain function
  4. General
  5. Original Article
  6. The effects of wearing a mask on an exercise regimen
  7. Medical Education
  8. Original Articles
  9. Promoting cultural competency and osteopathic medicine awareness among premedical students through a summer premedical rural enrichment program
  10. The effect of postgraduate osteopathic manipulative treatment training on practice: a survey of osteopathic residents
  11. Musculoskeletal Medicine and Pain
  12. Original Article
  13. Optimizing chronic pain management through patient engagement with quality of life measures: a randomized controlled trial
  14. Pediatrics
  15. Original Article
  16. Asthma medications in schools: a cross-sectional analysis of the Asthma Call-back Survey 2017-2018
  17. Public Health and Primary Care
  18. Review Article
  19. Thoracic outlet syndrome: a review for the primary care provider
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  21. Hermansky-Pudlak syndrome
  22. Letter to the Editor
  23. Comments on “Mini-medical school programs decrease perceived barriers of pursuing medical careers among underrepresented minority high school students”
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