Adolescent Knee Pain (AK-Pain) Prognostic Tool
Conditions: Knee Pain
Sponsor: Aalborg University

 
1 
Adolescent Knee Pain (AK-Pain) prognostic tool study 
protocol 
 
Protocol version number 1.1 (15-06-2019) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
2 
Revision history 
 
1.0 → 1.1 (section 2.8, 2.10, 2.11 and 2.12 have been modified on 15th of June 2019)

 
3 
Funding 
 
This study has been funded by a research grant obtained from the Danish foundation TrygFonden 
(https://www.trygfonden.dk/english). 
 
 
 
 
 
 
 
 

 
4 
Table of Contents 
1. 
Introduction ....................................................................................................................... 5 
1.1. 
Background and rationale for the study .................................................................................. 5 
1.2. 
Aim of the study .................................................................................................................... 8 
1.3. 
Importance of this study ........................................................................................................ 8 
1.4. 
Specific objectives of the study ............................................................................................... 8 
1.5. 
Study design ........................................................................................................................ 10 
2. 
Methods .......................................................................................................................... 11 
2.1. 
Study Setting ....................................................................................................................... 11 
2.2. 
Participants and eligibility criteria ........................................................................................ 11 
2.2.1. 
Inclusion criteria: ........................................................................................................................................11 
2.2.2. 
Exclusion criteria: .......................................................................................................................................11 
2.3. 
Outcome measures .............................................................................................................. 12 
2.4. 
Participant timeline ............................................................................................................. 13 
2.5. 
Sample size .......................................................................................................................... 14 
2.6. 
Development of the tool ...................................................................................................... 16 
2.7. 
Recruitment procedures ....................................................................................................... 19 
2.7.1. 
Recruitment and involvement of general practices into the study ...........................................................19 
2.7.2. 
Participant recruitment ..............................................................................................................................22 
2.7.3. 
Strategies to increase baseline participation and limit loss to follow-up ..................................................22 
2.8. 
Data collection methods ...................................................................................................... 26 
2.8.1. 
Tool delivery at baseline ............................................................................................................................26 
2.8.2. 
Collection of data during follow-up ...........................................................................................................26 
2.8.3. 
Information about non-participation to the study and loss to follow-up .................................................27 
2.8.4. 
Pain assessment .........................................................................................................................................27 
2.8.5. 
Study appreciation .....................................................................................................................................28 
2.8.6. 
Piloting the recruitment procedure and the prognostic tool ....................................................................28 
2.8.7. 
Stability of the prognostic tool study .........................................................................................................29 
2.9. 
Data management and confidentiality .................................................................................. 31 
2.10. 
Analysis plan ........................................................................................................................ 32 
2.11. 
Full analysis set .................................................................................................................... 34 
2.12. 
Timescale............................................................................................................................. 35 
2.13. 
Consent ............................................................................................................................... 37 
2.14. 
Impact/dissemination .......................................................................................................... 38 
3. 
Protocol amendments ...................................................................................................... 39 
4. 
Declaration of interest ..................................................................................................... 39 
5. 
Access to data .................................................................................................................. 39 
 
 

 
5 
1. Introduction 
 
1.1. Background and rationale for the study 
 
Knee pain is experienced by 33% of adolescents 1, and the prognosis of knee pain is often 
unfavorable, with approximately 50% of adolescents still reporting knee pain after 1 or 2 years 1,2. 
Common child and adolescent knee pain includes a variety of conditions (e.g. patellofemoral pain, 
patella tendinopathy, fat pad impingement, Osgood-Schlatter and Sinding-Larsen-Johansson 
disease), with specific treatments provided (e.g. education, activity modification, flexibility and 
strengthening exercises, cryotherapy, orthoses, patellar taping, medications) depending on the 
condition 3,4. Knee pain is linked to both health and social consequences 3. Children and 
adolescents with knee pain are more likely to reduce their sport participation, with following 
issues regarding the overall health (e.g. poor cardiovascular health, higher adiposity, impaired 
sleep) 1,5–8, to have a higher rate of school absence 6,9 and to be affected in the choice and 
performance of future work activities 10,11. Knee pain in children and adolescents has also an 
economic impact, which include both direct (e.g. primary care visits, community services use, 
medication use) and indirect (e.g. parental productivity work loss and days off work) costs 12,13. 
Knee pain in childhood and adolescence may also persist in adulthood; previous studies have 
shown that a high proportion of them experience recurrence of symptoms over up to 20 years of 
follow-up 14,15, and adolescent knee pain might be a precursor of adult knee conditions such as 
knee osteoarthritis 16–19. While there is a body of research on adult knee pain 20–22, less is known in 
children and adolescents, who are a distinct population compared to adults with different 
physiology and psychosocial development 5,23. Potential prognostic factors for knee pain identified 
in previous studies conducted in adolescents include female gender, high leisure time sport 

 
6 
participation, low health-related quality of life, high baseline frequency of knee pain 2. A 
proportion of children and adolescents with knee pain will consult the general practitioner 
because of their condition; previous research has shown an annual consultation prevalence for 
knee pain in children and adolescents of 119 24 - 200 25 per 10,000 registered persons.  
Once patients have consulted for their knee pain, general practitioners are left with the difficult 
task of figuring out how their patient’s condition can progress (i.e. if the patient will get better or 
not) in order to provide them with the best care 26,27. This include avoiding overdiagnosis (i.e. 
identification of a pathological state which will not result in a future poor outcome but might lead 
to unnecessary over-medicalization) and taking into account the patient’s entire biological, 
psychological and social context 27.  
General practitioners can be aided in the decision process by prognostic tools, which are tools that 
are used to stratify patients and match them to specific treatments depending on their risk of 
recurrence or persistence of a condition. This type of tools can help clinicians to identify 
subgroups of patients with different risk of recurrence or persistence of a pain condition 
depending on a prognostic score derived from a combination of individual prognostic factors 28. 
Examples of prognostic tools that have already been developed include the Keele STarT Back 
Screening Tool (SBST) for back pain in adults 29 or the Pediatric Pain Screening Tool (PPST) for 
general pediatric pain 28. However, a prognostic tool to be used specifically for the prognosis of 
knee pain in children and adolescents in primary care has not been developed yet, as the PPST 
included physical and psychosocial items that can be applied to general musculoskeletal and non-
musculoskeletal pain conditions and it was validated in tertiary care settings 28,30. Therefore, the 
development of a pediatric knee pain prognostic tool will fill this gap and will enable general 
practitioners to provide stratified care by tailoring the best targeted treatment to patients with 

 
7 
knee pain according to the category of risk. In summary, the development of a prognostic tool for 
child and adolescent knee pain within a primary care setting is important for three reasons: 
1. First, primary care is the place where the majority of health care is delivered 31, and 
consequently research carried out within this setting has the potential to have a significant 
impact in real-life.  
2. Second, a prognostic tool developed for knee pain will include items about factors that are 
specific to the prognosis of knee pain (e.g. pain duration, previous history of knee pain) and 
therefore would be more sensitive than other more general pediatric pain tools, such as 
the PPST. This is important considering that misclassification of patients might potentially 
lead to undertreat those misclassified as low-risk and overtreat those misclassified as high-
risk 32.  
3. Third, the subgroup of patients who refer to primary care is usually characterized by a 
different severity of symptoms compared to general population, second or tertiary care 
samples, as proposed by the iceberg theory of disease 33–35, and it is recommended that 
prognostic tools are validated in different care settings 36. Therefore, this research has the 
opportunity to provide information on the predictive ability of a prognostic tool in primary 
care compared to studies carried out within other samples of care settings, as it has 
previously been observed a difference in the efficacy of risk prediction potentially because 
of differences in patients case mix 37.  
 
 
 

 
8 
1.2. Aim of the study 
 
The overall aim of this study is to develop and test a prognostic tool for knee pain in children and 
adolescents to be used in general practice. 
 
1.3. Importance of this study 
 
The importance of this study lies in the fact that the development of a prognostic tool for children 
and adolescents with knee pain will allow general practitioners to categorize them according to 
their category of risk and consequently provide them the best targeted treatment.  
 
 
1.4. Specific objectives of the study 
 
1) Identification of prognostic factors for knee pain in children and adolescents 
a) Review of prognostic factors for knee pain in children and adolescents from current 
literature 
b) Selection of prognostic factors to be included in the prognostic tool 
2) Development of a prognostic model 
a) Development of the questions to be included in the prognostic tool 
b) Discussion about the questions wording with GPs 
c) Identification of the most suitable form to deliver the prognostic tool 
3) Piloting the prognostic tool and recruitment procedures 
a) Testing the prognostic tool at the general practices 
i) Assess time taken to use the prognostic tool 

 
9 
ii) Assess quality/acceptability of the prognostic tool (e.g. content of the questions and 
domains included, acceptability and understanding of the questions used, acceptability 
of the delivery of the tool, face validity, construct validity, criterion validity) 
b) Assess participants’ recruitment processes  
i) Assess baseline response (e.g. ratio between children who participated in the study 
over all those who consulted for knee pain as recorded with codes for consultation) 
and reasons for non-participation 
c) Improvement of the prognostic tool and of the recruitment procedures 
4) Recruitment of children and adolescents and collection and analysis of the data 
a) Description of the sample characteristics 
b) Assess the predictive ability of the prognostic tool 
i) Sensitivity 
ii) Specificity 
c) Assess baseline response and reasons for non-participation 
d) Assess loss to follow-up and reasons for dropping out of the study where possible 
5) Cost-effectiveness of the study (optional depending on time availability) 
a) Assess the workload for GPs, researchers and administrative staff 
b) Assess the time needed to deliver the tool in general practice and identification of 
alternative solutions to deliver the tool (e.g. by using iPads etc) 
c) Assess satisfaction of the participants and general practitioners with the study 
d) Evaluation of the effectiveness and suitability of this study in light of the resources 
available in general practice 

 
10 
1.5. Study design 
Prospective cohort study. Data will be collected at baseline through a questionnaire delivered at 
the general practice if the primary recruitment strategy will be applied. Otherwise, the baseline 
collection of the data will occur through a questionnaire home-mailed or delivered through a 
survey internet link if a strategy of recruitment through social media will be applied (please see 
section 2.7.2 for a description of the recruitment strategies). Outcomes will be collected by 
questionnaires either self-reported or parent-reported (collected through e-mail or text messages) 
at follow-up. 
 
 
 

 
11 
2. Methods 
 
2.1. Study Setting 
The aim is to collect data from general practices based in Denmark (with a potential 
complementary recruitment occurring through social media). For logistic reasons the recruitment 
will initially focus on large practices (populations around 10.000 each). However, smaller practices 
may be included too. For a calculation of the number of practices required to carry out the project 
please see section 2.5. 
 
 
2.2. Participants and eligibility criteria 
Children and adolescents who consult their general practitioner because of their knee pain (of 
both traumatic and non-traumatic origin) during a period of recruitment of 6 months (starting in 
July 2019) are eligible for inclusion. 
2.2.1. Inclusion criteria: 
• Age between 8 and 19 years old. The age of 8 is considered to be the lowest age for the 
children to be able to complete a pain questionnaire or a pain chart without adult guidance 
38 (provided that the questions are properly worded by taking into account the age-related 
cognitive abilities 39,40), and the age of 19 is defined as the upper limit for the period of 
adolescence by the World Health Organization 41. 
 
2.2.2. Exclusion criteria: 
• Age below 8 years old or over 19 years old 
• Consultation for musculoskeletal pain only in a body region different from the knee 

 
12 
• Pain originated by different conditions (e.g. cancer, infections) 
• Child is vulnerable (e.g. he/she has experienced a recent trauma and the distress may have 
an impact on the self-report making it not valid) 39 
• Inability to take part to the study because of inability to understand or comply 
 
2.3. Outcome measures 
The primary outcome measure will be the recurrence/persistence of activity-limiting knee pain 
(i.e. yes/no pain that is limiting activities in the same knee) at 3-month follow-up 42. Participants 
will also be asked about continuity of their knee pain (i.e. “how long have you been free of knee 
pain?”), to enable the distinction between recurrence (on/off knee pain episodes between 
baseline and follow-up) and persistence (continuous knee pain from baseline to follow-up) of knee 
pain. A secondary outcome measure that will be collected is the recurrence/persistence of 
activity-limiting knee pain at 6-month follow-up.  
Previous studies have shown an effect of the treatment received on the change in risk group for 
the recurrence/persistence of pediatric pain 43 and on the change in pain and function 44. 
Therefore, an additional outcome measure that might potentially be assessed include the 
treatment effectiveness on the recurrence/persistence of knee pain (provided that there will be 
the possibility to collect data on the treatment given). For practical reasons, it might be considered 
assessing this additional outcome on a subsample of children and adolescents. 
 
 
 

 
13 
2.4.  Participant timeline 
Examples of potential participants’ timeline are described in table 1. 
 
 
 
Table 1. Participants’ timeline 
 
Year 
2019 
2020 
 
Stage 
Jul 
Aug 
Sep 
Oct 
Nov 
Dec 
Jan 
Feb 
Mar 
Apr 
May 
Jun 
Jul 
 
Baseline participant 
recruitment 
 
 
 
 
 
 
 
 
 
 
 
 
 
Child 
nº1 
Baseline assessment 
 
 
 
 
 
 
 
 
 
 
 
 
 
3-month follow-up 
 
 
 
 
 
 
 
 
 
 
 
 
 
6-month follow-up 
 
 
 
 
 
 
 
 
 
 
 
 
 
Child 
nº2 
Baseline assessment 
 
 
 
 
 
 
 
 
 
 
 
 
 
3-month follow-up 
 
 
 
 
 
 
 
 
 
 
 
 
 
6-month follow-up 
 
 
 
 
 
 
 
 
 
 
 
 
 
Child 
nº3 
Baseline assessment 
 
 
 
 
 
 
 
 
 
 
 
 
 
3-month follow-up 
 
 
 
 
 
 
 
 
 
 
 
 
 
6-month follow-up 
 
 
 
 
 
 
 
 
 
 
 
 
 
Child 
nº4 
Baseline assessment 
 
 
 
 
 
 
 
 
 
 
 
 
 
3-month follow-up 
 
 
 
 
 
 
 
 
 
 
 
 
 
6-month follow-up 
 
 
 
 
 
 
 
 
 
 
 
 
 
Child 
nº5 
Baseline assessment 
 
 
 
 
 
 
 
 
 
 
 
 
 
3-month follow-up 
 
 
 
 
 
 
 
 
 
 
 
 
 
6-month follow-up 
 
 
 
 
 
 
 
 
 
 
 
 
 
Child 
nº6 
Baseline assessment 
 
 
 
 
 
 
 
 
 
 
 
 
 
3-month follow-up 
 
 
 
 
 
 
 
 
 
 
 
 
 
6-month follow-up 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
14 
2.5. Sample size 
The sample size for the development of the Pediatric Pain Screening Tool included 321 children 
aged 8-18 years old 28. A minimum of 100 subjects is required for a stable variance-covariance 
matrix 45, and following the rule of thumb of at least 10 events for variable (or items within the 
prognostic tool) 45, around 300 individuals would be necessary for a maximum of 30 items 
included in the tool. However, in case of presence of binary predictors with low prevalence, 20 
events per variable would be necessary 46 (this would consequently lower the number of items 
that it is possible to include in the prognostic tool).  
Previous studies have shown an annual consultation prevalence of 104 - 200 per 10,000 registered 
persons in children aged 3 to 19 years old 24,25,47. Here below, different potential scenarios about 
participants’ recruitment are described. These scenarios are calculated on a conservative estimate 
of 30% study participation rate. This is a worst-case scenario, and this approach is taken in order 
to have a safe recruitment that will provide us with enough children and adolescents for the 
development of the tool. 
Based on the prevalence estimate of 119 24 per 10,000 registered persons (which is a likely 
prevalence for children aged 8-19), at least 168 general practices of a medium size of 5000 
individuals each will be needed to recruit at least 300 participants at baseline (provided that 30% 
of all children aged 8-19 with a consultation for knee pain during a period of 6 month decide to 
take part in the study). This means that the overall target population includes 840.000 persons 
(168*5000) registered in general practices, which corresponds to 1/7 of the whole Danish 
population. Indeed, among these 840.000 persons, approximately 168.000 (20%) will be aged 
between 8 and 19 years old and 1,999 (119 per 10,000 registered persons) of these young people 
will have a consultation for knee pain in one year. Of these, 999 will have a consultation in a 6-

 
15 
month period (which is the duration of the baseline recruitment). If 30% of these children decide 
to take part in the study, there will be data on 300 children aged 8-19 at baseline.  
However, for the development of the START-BACK screening tool 244 patients were identified, of 
which only 131 (54%) returned the baseline questionnaire and 107 (82%) agreed to further 
contact 29. Therefore, if we aimed at only 100 children aged 8-19 years old with a consultation for 
knee pain in a 6-month period and by keeping the same proportions shown above (i.e. only 30% 
baseline participation rate), only 56 general practices of a medium size of 5000 individuals each 
would be needed (corresponding to a target population of 280.000 individuals, of which 56.000 
aged 8-19 years old). A target of 100 children would enable approximately 30 individuals in each 
prognostic risk group (low/medium/high). 
Conversely, based on the highest prevalence estimate (200 per 10,000 registered persons) and 
considering a 30% participation rate into the study, 33 general practices of a medium size of 5000 
individuals each would be needed (corresponding to a target population of 165.000 individuals, of 
which 33.000 aged 8-19 years old) to recruit at least 100 children. To recruit at least 300 children, 
100 general practices of a medium size of 5000 individuals each would be needed (corresponding 
to a target population of 500.000 individuals, of which 100.000 aged 8-19 years old). Alternatively, 
it might be possible to target fewer bigger general practices (e.g. 18 general practices of a medium 
size of 10.000 individuals to recruit 100 children). 
In addition, if only 100 children will be recruited from general practices, it might be possible to 
perform an extra recruitment through social media that would complement the group of children 
recruited through general practices, in order to achieve a total sample size of at least 300 children. 
In this case, sensitivity analysis would be performed to check for any potential difference in 
characteristics between the sample recruited through general practices and social media. 

 
16 
2.6. Development of the tool 
Clinically meaningful prognostic factors for knee pain in children and adolescents were identified 
from a review of the current literature on the topic. Initially, the most important domains for the 
prognosis of knee pain and the specific items to be included in the tool were selected based on the 
strength of association from previous studies identified within the literature and from meta-
analysis of individual participant data. Additional factors were included after discussion with 
general practitioners that agreed to take part to the study and staff working at the Center for 
General Practice at Aalborg University. During this stage, great emphasis was given to include only 
the most necessary factors taking in mind that the prognostic tool should be used in a reasonable 
time of a consultation within general practice. 
Items relative to the specific prognostic factors were initially selected from validated scales where 
possible (e.g. regarding pain characteristics, limitation in daily activities, sport participation, 
psychological factors). When multiple items within a scale or multiple scales were available for a 
prognostic factor, the relevant literature on the topic was identified and discussed at meetings 
with general practitioners and staff working at the Center of General Practice at Aalborg University 
in order to select the most appropriate items within the possible options. Following previous tools 
developed for pain in children and adolescents 28,48,49, items were properly worded for the age and 
properly framed with respect to the response options (e.g. direction, time intervals, avoiding 
double-barreled items).  
The initial version of the tool was tested and implemented during the pilot stage (great emphasis 
was given to the cognitive interviews that were carried out with children and adolescents), until 
reaching a final version that will be used for the collection of the data, as further described below 
in section 2.8.6. The outline of the final tool is provided in the figure below: 

 
17 
Knæ project 
Disse spørgsmål handler om dine knæsmerter. Sæt kryds i den boks som bedst beskriver hvordan du har det, eller skriv i tekstboksen. Hvis du er i tvivl, så bedes du svare så godt du kan. Spørgsmålene 
står i venstre side, og svarmulighederne i højre side af skemaet. 
Navn 
1. 
Hvor gammel er du? 
(                                                 ) 
2. 
Er du en pige eller en dreng? 
 Pige 
 Dreng 
3. 
Har du ondt i det ene knæ eller begge knæ? 
 Kun det ene knæ (højre knæ) 
 Kun det ene knæ (venstre knæ) 
 Begge knæ 
4. 
Hvor lang tid har du haft ondt i knæet?  
Hvis du har ondt i begge knæ skal du svare ud fra det knæ hvor 
smerterne har varet længst 
 
 under 3 måneder 
 3– 6 måneder  
 6–12 måneder  
 mere end 12 måneder (hvor mange år? ___________________________ ) 
5. 
Hvordan startede dine knæsmerter? 
Hvis du har ondt i begge knæ skal du svare ud fra det knæ hvor 
smerterne har varet længst 
 Kom pludseligt (f.eks. da jeg fik en skade)  
 Kom gradvist (f.eks. langsomt over en længere periode) 
6. 
Hvor ofte oplever du dine knæsmerter? 
Hvis du har ondt i begge knæ skal du svare ud fra det knæ hvor 
smerterne har varet længst 
 
 
 Sjældent 
 Månedligt 
 Ugentligt 
 Mere end en gang om ugen 
 Næsten dagligt  
7. 
Har du ondt andre steder i kroppen som gør at du ikke kan deltage i 
dine normale aktiviteter (leg i skolegården, sport og lignende)? I dette 
spørgsmål menes andre steder end knæet 
 Nej 
 Ja. Marker venligst hvor. Du må gerne afkrydse mere end et område: 
 Hovedet 
 Ryg eller nakke 
 Skulder 
 Albuen 
 Håndled eller hånden 
 Underbenet 
 Låret 
 Bækken (badebuksområdet) 
 Ankel, hælen eller foden 
 Andet (__________________________________________________________________) 
8. 
Under hver overskrift bedes du sætte kryds i DEN kasse, der bedst 
beskriver hvordan dine knæsmerter påvirker de ting du laver på en 
normal dag (f.eks., gå i skole, hobbyer, sport, være sammen med 
venner eller familie) 
Hvis du har ondt i begge knæ skal du svare ud fra det knæ hvor 
smerterne har varet længst 
 Jeg har ingen problemer med at udføre mine sædvanlige aktiviteter 
  
 Jeg har lidt problemer med at udføre mine sædvanlige aktiviteter 
 Jeg har nogle problemer med at udføre mine sædvanlige aktiviteter 
  
 Jeg har store problemer med at udføre mine sædvanlige aktiviteter 
 Jeg kan ikke udføre mine sædvanlige aktiviteter 
9. 
Hvor enig er du i dette udsagn ”Når jeg har ondt, er det forfærdeligt 
og jeg tror aldrig det bliver bedre” 
 
 
 
 
Sæt kryds i den kasse som bedst beskriver hvordan du har det i dag. 
Ængstelig/deprimeret svarer til at være ked af det (det handler om 
hvordan du har det, og ikke nødvendigvis på grund af dine smerter) 
 
 Overhovedet ikke 
 Lidt 
 I nogen grad 
 Meget  
 Rigtig meget 
 
 Jeg er ikke ængstelig eller deprimeret  
 Jeg er lidt ængstelig eller deprimeret 
 Jeg er i nogen grad ængstelig eller deprimeret  
 Jeg er meget ængstelig eller deprimeret  
 Jeg er ekstremt ængstelig eller deprimeret 
10. 
Har din mor eller stedmor ofte ondt i kroppen? (dette kan både være 
ondt i hovedet, ryggen, skulderen eller andre steder) 
 
Har din far eller stedfar ofte ondt i kroppen? (dette kan både være 
ondt i hovedet, ryggen, skulderen eller andre steder) 
 Nej 
 Ja 
 
 Nej 
 Ja 
11. 
Hvor mange gange per uge deltager du typisk i sport (udover idræt i 
skolen)?  
 
 
 
 
 
 
Hvilken type sport? (feks håndbold, fodbold, svømning, løb). Du må 
gerne skrive mere end en sport. 
 Aldrig 
 1 gange/uge 
 2 gange/uge 
 3 gange/uge 
 4 gange/uge 
 5 gange/uge 
 6 gange/uge 
 7 eller flere gange/uge 
 
(                                                                                                                                               ) 

 
18 
 
 
 
 
 
12. 
Har du røget cigaretter I de sidste 4 uger?  
 Nej 
 Ja 
13. 
Hvor enig er du i dette udsagn ”Jeg har problemer med at sove” (det 
behøver ikke nødvendigvis være på grund af smerter) 
 Aldrig 
 Næsten aldrig 
 Nogle gange 
 Ofte 
 Næsten altid 

 
19 
2.7. Recruitment procedures 
The recruitment strategy involves different stages (see figure 2), which include both the general 
practitioners’ and the participants’ recruitment. These stages are outlined below: 
 
 
2.7.1. Recruitment and involvement of general practices into the study 
 
This stage involves the recruitment of general practitioners. It is important to recruit enough 
general practitioners in order to have an adequate number of participants to the study (section 
2.5). Insufficient recruitment can result in a limitation in power and generalizability of the study 50. 
In order to obtain enough general practitioners involved in the study, efforts were done to comply 
with the Solberg’s seven R-factors 50. These factors include the relationship between recruiters 
and general practitioners, the reputation of recruiters, the requirements for study participation, 
the reward for participating to the study, reciprocity between what is provided by recruiters and 
what is expected by participants, resolute behavior of recruiters and respect between recruiters 
and participants 50. Several sub-stages are included within the stage of recruitment of general 
practitioners: 
1. Getting in touch with the general practitioners in order to ask them their availability to join 
the research (large clinics of general practitioners are preferred). The first contact was brief 
but informative. General practitioners were contacted by: 
o In-person presentations at general practitioners’ professional meetings 
o Cold calls to practices identified using local telephone books 
o Exploiting previous relationships between our general practitioners and their 
colleagues 
o Distributing flyers with the description of the study to general practitioners 

 
20 
2. Introductory meetings with general practitioners, the secretaries and nurses to confer the 
importance, contents and goals of the study. 
Goals to be achieved with these meeting: 
o General practitioners and their staff’s understanding of the importance of the 
study.  
o General practitioners and their staff’s understanding of the recruitment methods. 
o General practitioners and their staff’s trust in the study and confidence in 
communicating research to their patients.  
o General practitioners and their staff will have to feel morally rewarded by taking 
part in this research. 
 
3. Meeting for the implementation of the recruitment strategy with general practitioners and 
their staff 
o General practitioners were asked to help us advertising the study to other general 
practitioners. 
o General practitioners were involved in the design of tailored recruitment procedures 
(i.e. in the initial brainstorming meetings and during the piloting stage of the 
recruitment) and as a source of feedback in the process of recruitment. 
o Definition of the specific workload for each member of the study (e.g. researchers, 
general practitioners and their staff). 
 
 
 

 
21 
4. Beginning of recruitment after implementation of the recruitment strategy 
o A collaboration agreement and a data handling agreement with general 
practitioners was signed in order to avoid potential breach of data confidentiality 
and privacy. 
5. Regular follow-up meetings with the general practitioners and the recruitment staff will be 
held in order to monitor the recruitment rate 
o Feedback about recruitment achievements will regularly be provided to the general 
practitioners and their staff. The recruitment rates from every practice will be 
monitored and every month an e-mail will be sent to each general practitioner who 
takes part in the study to provide them with statistics of both the overall and 
individual recruitment rate. If the number of participants recruited is lower than the 
expected rate (which will vary depending on the practice size), practices will be 
contacted to discuss reasons for the low participant rate 51.  
 
 
 

 
22 
2.7.2. Participant recruitment 
 
Simple and broad entry criteria (described above in section 2.2) will be applied, in order to get as 
many participants as possible. A combination of strategies (please see figure 3), which are 
described below, has been taken into consideration. 
The primary participant recruitment strategy will be the recruitment occurred at general practices 
on the day of consultation for knee pain (called “warm recruitment” within this document).  
1. Warm recruitment. This method involves the invitation to join the study directly when 
children and adolescents have a consultation for knee pain at the general practice. If they 
agree to participate to the study, they will be provided with the study material (i.e. 
prognostic tool to be completed). In case children decide not to participate, the reason for 
non-participation will be asked from a list of options. 
  
Alternative recruitment strategies that might be applied in order to maximize the recruitment rate 
1. Advertisement of the study through social media (e.g. Facebook, Twitter, Snapchat). 
2. Advertisement of the study through explicative posters that will be displayed at the 
participating general practices. 
 
2.7.3. Strategies to increase baseline participation and limit loss to follow-up 
In order to promote baseline participation and limit loss to follow-up from the study, children will 
be given two cinema tickets if they decide to take part in the study. The first ticket will be given at 
baseline, when children decide to take part in the study and after returning the questionnaire, and 
the second ticket will be given only if the children will have completed the follow-up (e.g. provided 

 
23 
information at both the 3-month and 6-month follow-up points). The ethics committee was be 
informed about the cinema tickets to be given to participants and approved this method. 
 
 

 
24 
Figure 2 
 
The study staff contacts the practice 
manager 
Practice decline to participate 
Practice agrees to participate 
Practice agrees to recruit patient 
Practice decline to recruit patients 
Invitation to patients 
Patients’ agreement to participate 
Patients’ agreement to remain in the 
study 
Patients’ decline to participate 
Patients’ drop-out from the study 
Stage 1 
Practice 
recruitment 
Stage 2 
Participant 
recruitment 
Stage 3 
Participant 
retention 

 
25 
Figure 3 
 
 
 
Children and their parents agree to take 
part to the study 
Warm recruitment 
High participation rate into the study 
Low participation rate into the study 
No other recruitment strategies will be 
applied 
Alternative recruitment strategies 
Social media 
Posters 

 
26 
2.8. Data collection methods 
2.8.1. Tool delivery at baseline 
Data will be collected at baseline by means of a questionnaire (either with a paper-based 
questionnaire or collected with the support of a tablet) directly at the general practice when 
children and adolescents consult for knee pain. Alternatively, the questionnaire will be delivered 
at home or through a survey delivered with an internet link after that the children or their parents 
agreed to take part to the study if an alternative recruitment strategy will be applied (e.g. social 
media recruitment). In this case, children and their parents will be given the opportunity to choose 
between providing data through a paper-based questionnaire or a questionnaire delivered with an 
internet link. 
 
2.8.2. Collection of data during follow-up 
Data will be collected during follow-up from the children or parents through a questionnaire  
email-based or to be completed by text messages depending on the participants’ preference. The 
questionnaire will include questions about pain characteristics (e.g. severity of pain, period free of 
knee pain, disability and activity limitations due to pain 42,48) and about who is the person replying 
to the questionnaire (child alone/parent alone/child together with the parent). These questions 
will be taken from previously validated pain questionnaires or pain scales. Data collected at 3-
month follow-up will be used to assess the primary outcome of the study, and data collected at 6-
month follow-up will be used to assess the secondary outcome. In order to limit loss to follow-up, 
an e-mail/text message reminder will be sent to participants if they do not complete the follow-up 
questionnaire within one week from the day when they are supposed to reply. A second reminder 

 
27 
will be sent one week after the first reminder if they still will not have completed the follow-up 
questionnaire. 
 
2.8.3. Information about non-participation to the study and loss to follow-up 
Information about reasons for baseline non-participation to the study (e.g. participant is too busy 
or not interested in the topic, or the participant has been considered not suitable to take part in 
the study by the general practitioner, or the general practitioner is too busy) will be collected by 
the person in charge of inviting the children to join the study. Information about reasons for 
baseline non-participation together with other data regarding non-participants (e.g. number, age, 
gender) will be used to describe the process of selection of participants 51. 
Reasons for loss to follow-up will be assessed by contacting through a phone call/e-mail/text 
message those participants who do not reply to 3 consecutive follow-up reminders and asking 
about reasons for leaving the study. 
 
 
2.8.4. Pain assessment 
Parents are involved in both the decision of seeking healthcare for musculoskeletal pain and in the 
discussion with the general practitioner during the clinical encounter 52. Therefore, it may occur 
that data reporting will actually be parent-report rather than child self-report, and this might 
introduce bias about the pain measurement, especially in longitudinal studies (i.e. children are too 
young to reliably self- report at the initial assessments, but they might self-report at later follow-
up points) 52. Current evidence on pain reporting suggest that children are able to self-report from 
the age of 8 38, and that the agreement between child and parental report for the presence of pain 

 
28 
is around 50-70%, although the concordance is higher if the pain is of greater intensity and of 
longer duration 52. In addition, when their child's pain is severe, parents might over-report the 
severity of the impacts of pain on their children as they become more concerned about potential 
consequences of pain 52. Potential inaccuracies in the measurement of knee pain will be 
considered by means of a question about the persons responding to the follow-up questionnaire 
(e.g. child alone/parent alone/child together with the parent) as reported in section 2.7.2. Efforts 
will be done to encourage the same person to respond to all the follow-up questionnaires in order 
to reduce inaccuracies in pain reporting. For example, a strategy that might be adopted is to 
provide children with cinema tickets only if they will be the person responding to all the 
questionnaires. 
 
2.8.5. Study appreciation 
 
Information about study appreciation will be collected by asking participants questions about the 
acceptability of the questions, acceptability of the time needed for questionnaire completion and 
the most preferred frequency and method of contact. In addition, evaluation questions about 
information on the study, the study processes, time required to participate in the study, 
motivation, future participation to similar studies and potential strategies to implement the study 
will also be asked to the general practitioners. 
 
2.8.6. Piloting the recruitment procedure and the prognostic tool 
 
This project included a stage where the prognostic tool was piloted, which included a 
development, testing and implementation stage. Cognitive interviews were carried out after 
completion of the questionnaires to assess the appropriateness, comprehensibility, wording and 

 
29 
potential lack of items relating to the prognosis of knee pain, as previously done for other tools 
that evaluated pain status in children and adolescents 45,48,49,53. The aim was to improve the face, 
construct and content validity of the tool at this stage. This is important especially considering that 
a worse outcome can result if a general practitioner makes an inaccurate diagnosis of the child’s 
knee pain or if there is a lack of communication between the general practitioner and the child 
with knee pain 54. In addition, children of different age interpret the pain questions differently 
because of their cognitive development 39,40,54,55. Several self-report measures for pain intensity or 
the impact of pain exist, with a set of appropriate pain scales for each different age range 39,40, and 
age-appropriate analogies or metaphors can be used in the knee pain questions in order for the 
children to understand the questions better 54–56. Therefore, questions as simple as possible were 
developed in order for the tool to be understandable from individuals of any age 45. 
After this testing and feedback stage, the prognostic tool was implemented and tested again 
(during a period of 2 months) in an iterative process until reaching the optimal version which will 
then be used in the data collection stage. 
 
2.8.7. Stability of the prognostic tool study 
A pilot study to assess the stability of the prognostic tool (test-retest reliability 45) in children pre- 
and post- consultation was carried out. Children who refer to primary care for knee pain and their 
parents were given the prognostic tool (together with the informed consent) to be completed in 
the waiting room of the general practice before the consultation. Subsequently, after the 
consultation with the general practitioner, children and their parents were asked to complete the 
prognostic tool again in order to assess the stability of the tool parameters and the general 

 
30 
practitioner’s influence on the parameters (e.g. pain perception and psychological factors) 
assessed with the tool.  
 
 
 
 

 
31 
2.9. Data management and confidentiality 
The participant submitted responses will be automatically registered in a database through the 
Red-cap system (https://www.project-redcap.org). Handling of data will comply to the General 
Data Protection Regulation and the concomitant local data handling instructions for Center of 
General Practice at Aalborg University. Data will be stored at a server at Aalborg University (a 
request will be done to store the data for 30 years), this will ensure a safe and legal handling of 
data. The accuracy of the data will be checked through screening of data outliers and potentially 
“wrong” or “strange” data will be identified and corrected.  
 
 
 

 
32 
2.10. 
Analysis plan 
The analysis plan that will lead to the development of the final prognostic tool will include the 
following stages: 
 
1. Descriptive analysis of the collected data. Results will be presented as means with SDs and 
as percentages. 
2. Assessment of potential floor and ceiling effects of the items included in the prognostic 
tool. This will be done by checking that for those items that represent an ordinal or 
categorical variable with more than two potential response categories, the responses given 
are not skewed towards the top or bottom extreme of the scales (e.g. a ceiling or floor 
effect is present if >15% of the respondents report the lowest/highest score of the scale 
42,45,57). 
3. Estimation of knee pain prognosis (i.e. recurrence/persistence of knee pain, dichotomous 
outcome) at 3-month and 6-month follow-up by means of multiple logistic regression to 
estimate ORs and 95% confidence intervals for each item included in the tool. This will 
inform on which factors are most related to the prognosis of knee pain and will provide an 
insight on the scores of the prognostic tool (both overall and for subscales) to be applied 
for the creation of the initial risk groups. Alternatively, the RR will be estimated if a general 
linear model analysis will be carried out. 
4. Discriminant validity of the prognostic score will be assessed by using receiver operating 
characteristics (ROC) curves and by calculating the area under the curve (AUC) for the 
overall score and subscales of the prognostic tool.  

 
33 
5. Creation of risk groups for the recurrence/persistence of knee pain on the basis of cut-off 
scores identified using the ROC curves for the overall tool score. The initial idea is to have 
three risk groups (low/medium/high), which have to be clinically meaningful. More 
importance will be given to the sensitivity of the tool over the specificity. 
6. Assessment of the predictive ability of the risk groups defined at baseline by calculating the 
sensitivity, specificity and negative and positive likelihood ratios (LRs) against the primary 
and secondary outcome (i.e. 3-month and 6-month recurrence/persistence of knee pain; 
disability/activities limitation due to knee pain). 
7. Assessment of the potential influence of non-modifiable patients’ characteristics on the 
predictive ability of the risk groups defined at baseline by stratifying the former analysis by 
age groups and sex. 
8. Calculation of the 3-month and 6-month knee pain prognosis stratified by treatment 
received and baseline prognostic risk group, provided that data on the treatment given to 
the patients can be collected. Alternatively, instead of stratifying the analysis by treatment, 
analysis can be adjusted by treatment received.  
In addition, potential changes of the risk groups at 3-month follow-up depending on the 
treatment received might be calculated provided that the prognostic tool is delivered at 
the 3-month follow-up as well. In this way it might be possible to track the effectiveness of 
the treatment and if it resulted in a change of risk group. 
 
 
 
 

 
34 
2.11. 
Full analysis set 
In order to obtain a “full analysis set” for the project, participants will have to provide data from 
baseline through the 3-month and 6-month follow-up, which will allow to estimate the short-term 
and long-term knee pain prognosis. Please refer to figure 4 for a description of the full analysis set. 
Data completeness (i.e. completion and accuracy of data forms) will be monitored and actions will 
be taken to overcome potential problems such as missing data 51. In case of missing data, the 
missing observation will be replaced by means of an imputation process (e.g. multiple imputation 
by chained equation) depending on the number of missing observations for the follow-up stages 
(i.e. multiple imputation is usually performed when the percentage of missing data is low). A 
sensitivity analysis will also be carried out in order to compare results between the analysis carried 
out on the dataset with missing observation (complete-case analysis) and the multiple imputed 
dataset (multiple imputation analysis). A backup copying of the dataset will be performed daily. 
 
Figure 4. Complete-case and multiple imputed data 
 
 
Timeline 
Participant’ code 
Baseline 
3-month follow-up 
6-month follow-up 
AA01 
 
 
 
AB01 
 
 
 
AC01 
 
 
 
AD01 
 
 
 
AE01 
 
 
 
AF01 
 
 
 
AG01 
 
 
 
AH01 
 
 
 
AI01 
 
 
 
AJ01 
 
 
 
 
 
Complete dataset 
Multiple imputation 

 
35 
2.12. 
Timescale 
The overall planned study period is 24 months. This will include the following stages: 
• Protocol development (3 months) 
• General practitioners´ recruitment (4 months) 
• Identification of prognostic factors (3 months) 
• Selection of prognostic factors (2 months) 
• Development of the prognostic tool (4 months)  
• Piloting the prognostic tool (5 months)  
• Piloting the recruitment procedures (5 months)  
• Implementation of the recruitment procedure and prognostic tool (2 months) 
• Collection of the data (12 months)  
• Analysis of the data (11 months)  
 
There will be some overlap between the different stages, which are visually described in the 
GANTT chart outlined in the following page.  
 
 

 
36 
 
 
Year and month 
 
2018 
2019 
2020 
Task 
Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug 
Protocol 
development 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
GPs recruitment 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Identification of 
prognostic factors 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Selection of 
prognostic factors 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Development of 
the prognostic tool 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Piloting the 
prognostic tool 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Piloting the 
recruitment 
procedures 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Implementation of 
the recruitment 
procedure and 
prognostic tool 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Collection of the 
data 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Analysis of the 
data 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
37 
2.13. 
Consent 
A unique written informed consent (including consent to take part to the study, provide personal 
information and being contacted at each follow-up time-point) will be obtained by the adolescents 
if aged 15 years old or more or from the parents if aged less than 15 years old when they will be 
invited to take part to the study. Participants will be reassured that they may, at any time and 
without any consequence (except for not receiving the cinema tickets) discontinue participation to 
the study. 
 
 
 

 
38 
2.14. 
Impact/dissemination 
The present study will provide data on the prognosis for knee pain in children and adolescents 
who present to primary care. In addition, this study will provide data on the usability of a 
prognostic tool to allocate children and adolescents to a category of risk for knee pain recurrence 
and consequently provide them with the best targeted treatment. The study results will be 
disseminated at scientific conferences and through appropriate scientific journals. In addition, 
general practitioners, children and parents participating into the study will be regularly provided 
with feedback about the ongoing study. 
 
Examples of papers that might be developed from this study (provisional names are provided): 
1) The Adolescent Knee Pain (AK-Pain) prognostic tool: protocol for a prospective cohort study 
2) Stability of prognostic factors for knee pain collected with a questionnaire in general practice 
3) The development of a prognostic tool for knee pain in children and adolescents in general 
practice 
4) Effect on the treatment delivered on the knee pain prognosis on a subsample of the 
participants recruited in the AK-pain project 
 
 
 

 
39 
3. Protocol amendments 
Potential protocol amendments might occur during the prognostic tool piloting and development 
stage. Protocol amendments will be disseminated to proper scientific journals. 
 
4. Declaration of interest 
The study’s investigators have no conflicts of interest to declare. 
 
5. Access to data 
The final dataset will be accessed by Alessandro Andreucci, Michael Skovdal Rathleff, Martin Bach 
Jensen and Sinead Holden. 
 
 

 
40 
References 
1.  
Rathleff MS, Rathleff CR, Olesen JL, Rasmussen S, Roos EM. Is Knee Pain during Adolescence 
a Self-limiting Condition? Am J Sports Med. 2015;44(5):1165-1171. 
doi:10.1177/0363546515622456 
2.  
Rathleff CR, Olesen JL, Roos EM, Rasmussen S, Rathleff MS. Half of 12-15-year-olds with 
knee pain still have pain after one year. Dan Med J. 2013;60(11). 
3.  
Houghton KM. Review for the generalist: Evaluation of anterior knee pain. Pediatr 
Rheumatol. 2007;5:1-10. doi:10.1186/1546-0096-5-8 
4.  
Lipman R, John RM. Knee Pain in Adolescent Females. nurse Pract. 2015;40(7):29-36. 
5.  
Rathleff MS. Patellofemoral pain during adolescence: Much more prevalent than 
appreciated. Br J Sports Med. 2016;50(14):831-832. doi:10.1136/bjsports-2016-096328 
6.  
Haraldstad K, Sørum R, Eide H, Natvig GK, Helseth S. Pain in children and adolescents: 
Prevalence, impact on daily life, and parents’ perception, a school survey. Scand J Caring Sci. 
2011;25(1):27-36. doi:10.1111/j.1471-6712.2010.00785.x 
7.  
Kosola S, Mundy LK, Sawyer SM, et al. Pain and learning in primary school. Pain. 
2017;158(9):1825-1830. doi:10.1097/j.pain.0000000000000984 
8.  
Sandow JM, Goodfwllow JW. The natural history of anterior knee pain in adolescents. J 
bone Jt Surg. 1985;67(1):36-38. 
9.  
Holm S, Ljungman G, Soderlund A. Pain in children and adolescents in primary care; chronic 
and recurrent pain is common. Acta Paediatr. 2012;101(12):1246-1252. doi:10.1111/j.1651-
2227.2012.02829.x [doi] 
10.  
Wynne-Jones G, Main CJ. Overcoming pain as a barrier to work. Curr Opin Support Palliat 
Care. 2011;5(2):131-136. doi:10.1097/SPC.0b013e3283460b3a 

 
41 
11.  
Buck R, Wynne-Jones G, Varnava A, Main CJ, Phillips CJ. Working with Musculoskeletal Pain. 
Rev pain. 2009;3(1):6-10. doi:10.1177/204946370900300103 
12.  
Groenewald CB, Essner BS, Wright D, Fesinmeyer MD, Palermo TM. The economic costs of 
chronic pain among a cohort of treatment seeking adolescents in the United States. J Pain. 
2014;15(9):925-933. doi:doi:10.1016/j.jpain.2014.06.002 
13.  
Henschke N, Harrison C, McKay D, et al. Musculoskeletal conditions in children and 
adolescents managed in Australian primary care. BMC Musculoskelet Disord. 2014;15:164. 
doi:10.1186/1471-2474-15-164 [doi] 
14.  
Nimon G, Murray D, Sandow M, Goodfellow J. Natural history of anterior knee pain: a 14- to 
20-year follow-up of nonoperative management. J Pediatr Orthop. 1998. 
15.  
Stathopulu E, Baildam E. Anterior knee pain: A long-term follow-up. Rheumatology. 2003. 
doi:10.1093/rheumatology/keg093 
16.  
Thomas MJ, Wood L, Selfe J, Peat G. Anterior knee pain in younger adults as a precursor to 
subsequent patellofemoral osteoarthritis: A systematic review. BMC Musculoskelet Disord. 
2010;11:4-11. doi:10.1186/1471-2474-11-201 
17.  
Conchie H, Clark D, Metcalfe A, Eldridge J, Whitehouse M. Adolescent knee pain and 
patellar dislocations are associated with patellofemoral osteoarthritis in adulthood: A case 
control study. Knee. 2016;23(4):708-711. doi:10.1016/j.knee.2016.04.009 
18.  
Peat G, Bergknut C, Frobell R, Jo¨ud A, Englund M. Population-wide incidence estimates for 
soft tissue knee injuries presenting to healthcare in southern Sweden: Data from the Ska˚ne 
healthcare register. Arthritis Res Ther. 2014;16(4):1-9. doi:10.1186/ar4678 
19.  
Antony B, Jones G, Jin X, Ding C. Do early life factors affect the development of knee 
osteoarthritis in later life: a narrative review. Arthritis Res Ther. 2016;18(1):202. 

 
42 
doi:10.1186/s13075-016-1104-0 
20.  
Peat G, McCarney R, Croft P. Knee pain and osteoarthritis in older adults: a review of 
community burden and current use of primary health care. Ann Rheum Dis. 2001;60(2):91-
97. doi:10.1136/ard.60.2.91 
21.  
Jinks C, Jordan K, Ong BN, Croft P. A brief screening tool for knee pain in primary care 
(KNEST). 2. Results from a survey in the general population aged 50 and over. 
Rheumatology. 2004;43(1):55-61. doi:10.1093/rheumatology/keg438 
22.  
Thomas E, Dunn KM, Mallen C, Peat G. A prognostic approach to defining chronic pain: 
Application to knee pain in older adults. Pain. 2009;139(2):389-397. 
doi:10.1016/j.pain.2008.05.010 
23.  
Hestbaek L, Leboeuf-Yde C, Kyvik KO. Are lifestyle-factors in adolescence predictors for 
adult low back pain? A cross-sectional and prospective study of young twins. BMC 
Musculoskelet Disord. 2006;7:29. doi:10.1186/1471-2474-7-29 
24.  
Michaleff ZA, Campbell P, Protheroe J, Rajani A, Dunn KM. Consultation patterns of children 
and adolescents with knee pain in UK general practice: analysis of medical records. BMC 
Musculoskelet Disord. 2017;18(1):239. doi:10.1186/s12891-017-1586-1 
25.  
de Inocencio J. Musculoskeletal pain in primary pediatric care: analysis of 1000 consecutive 
general pediatric clinic visits. Pediatrics. 1998;102(6):E63. doi:10.1542/peds.102.6.e63 
26.  
Peat G, Riley RD, Croft P, et al. Improving the Transparency of Prognosis Research: The Role 
of Reporting, Data Sharing, Registration, and Protocols. PLoS Med. 2014;11(7). 
doi:10.1371/journal.pmed.1001671 
27.  
Croft P, Altman DG, Deeks JJ, et al. The science of clinical practice: Disease diagnosis or 
patient prognosis? Evidence about “what is likely to happen” should shape clinical practice. 

 
43 
BMC Med. 2015;13(1):1-8. doi:10.1186/s12916-014-0265-4 
28.  
Simons LE, Smith A, Ibagon C, et al. Pediatric Pain Screening Tool (PPST): Rapid identification 
of risk in youth with pain complaints. 2015;156(8):1511-1518. 
doi:doi:10.1097/j.pain.0000000000000199 
29.  
Hill JC, Dunn KM, Lewis M, et al. A primary care back pain screening tool: Identifying patient 
subgroups for initial treatment. Arthritis Care Res. 2008. doi:10.1002/art.23563 
30.  
Heathcote LC, Rabner J, Lebel A, Hernandez JM, Simons LE. Rapid screening of risk in 
pediatric headache: Application of the pediatric pain screening tool. J Pediatr Psychol. 
2018;43(3):243-251. doi:10.1093/jpepsy/jsx123 
31.  
Cardy A, Holden S, Watson D, Nelson D, Turner S. Recruiting children onto research studies 
by the Scottish Primary Care Research Network: A real team effort. Qual Prim Care. 
2012;20(3):199-206. 
32.  
Karran EL, McAuley JH, Traeger AC, et al. Can screening instruments accurately determine 
poor outcome risk in adults with recent onset low back pain? A systematic review and 
meta-analysis. BMC Med. 2017;15(13):1-15. doi:10.1186/s12916-016-0774-4 
33.  
Campbell SM, Roland MO. Why do people consult the doctor? Fam Pract. 1996;13(1):75-83. 
doi:10.1093/fampra/13.1.75 
34.  
Last JM, Adelaide DP. The iceberg: “completing the clinical picture” in general practice. 
1963. Int J Epidemiol. 2013;42(6):1608-1613. doi:10.1093/ije/dyt113 
35.  
Bhopal R. Concepts of Epidemiology - an Integrated Introduction to the Ideas, Theories, 
Principles and Methods of Epidemiology. 2nd ed. Oxford University Press; 2002. 
36.  
Moons KGM, Altman DG, Vergouwe Y, Royston P. Prognosis and prognostic research: 
Application and impact of prognostic models in clinical practice. BMJ. 2009. 

 
44 
doi:10.1136/bmj.b606 
37.  
Morsø L, Kent P, Manniche C, Albert HB. The predictive ability of the STarT Back Screening 
Tool in a Danish secondary care setting. Eur Spine J. 2014;23(1):120-128. 
doi:10.1007/s00586-013-2861-y 
38.  
von Baeyer CL, Lin V, Seidman LC, Tsao JC, Zeltzer LK. Pain charts (body maps or manikins) in 
assessment of the location of pediatric pain. Pain Manag. 2011;1(1):61-68. 
doi:10.2217/pmt.10.2 
39.  
Michaleff ZA, Kamper SJ, Stinson JN, et al. Measuring Musculoskeletal Pain in Infants, 
Children, and Adolescents. J Orthop Sport Phys Ther. 2017;47(10):712-730. 
doi:10.2519/jospt.2017.7469 
40.  
Stinson JN, Kavanagh T, Yamada J, Gill N, Stevens B. Systematic review of the psychometric 
properties, interpretability and feasibility of self-report pain intensity measures for use in 
clinical trials in children and adolescents. Pain. 2006;125(1-2):143-157. doi:S0304-
3959(06)00257-0 [pii] 
41.  
World Health Organization. WHO - Definition of key terms. 
www.who.int/hiv/pub/guidelines/arv2013/intro/keyterms/en/. Published 2013. Accessed 
September 3, 2018. 
42.  
Örtqvist M, Iversen MD, Janarv PM, Broström EW, Roos EM. Psychometric properties of the 
knee injury and osteoarthritis outcome score for children (KOOS-Child) in children with knee 
disorders. Br J Sports Med. 2014;48(19):1437-1446. doi:10.1136/bjsports-2013-093164 
43.  
Vuorimaa H, Leppänen L, Kautiainen H, Mikkelsson M, Hietanen M. Risk severity moderated 
effectiveness of pain treatment in adolescents. 2018. 
44.  
Palermo TM, Law EF, Zhou C, Holley AL, Logan D, Tai G. Trajectories of Change During a 

 
45 
Randomized Controlled Trial of Internet-delivered Psychological Treatment for Adolescent 
Chronic Pain: How does Change in Pain and Function Relate? 2015;156(4):626-634. 
doi:doi:10.1097/01.j.pain.0000460355.17246.6c 
45.  
Terwee CB, Bot SDM, de Boer MR, et al. Quality criteria were proposed for measurement 
properties of health status questionnaires. J Clin Epidemiol. 2007;60(1):34-42. 
doi:10.1016/j.jclinepi.2006.03.012 
46.  
Ogundimu EO, Altman DG, Collins GS. Adequate sample size for developing prediction 
models is not simply related to events per variable. J Clin Epidemiol. 2016;76:175-182. 
doi:10.1016/j.jclinepi.2016.02.031 
47.  
Tan A, Strauss VY, Protheroe J, Dunn KM. Epidemiology of paediatric presentations with 
musculoskeletal problems in primary care. BMC Musculoskelet Disord. 2018;19(1):1-6. 
doi:10.1186/s12891-018-1952-7 
48.  
Örtqvist M, Roos EM, Broström EW, Janarv PM, Iversen MD. Development of the Knee 
Injury and Osteoarthritis Outcome Score for Children (KOOS-Child): Comprehensibility and 
content validity. Acta Orthop. 2012;83(6):666-673. doi:10.3109/17453674.2012.747921 
49.  
Iversen MD, Lee B, Connell P, Andersen J, Anderson AF, Kocher MS. Validity and 
comprehensibility of the International Knee Documentation Committee Subjective Knee 
Evaluation form in Children. Scand J Med Sci Sport. 2010;20:e87-e95. doi:10.1111/j.1600-
0838.2009.00917.x 
50.  
Riis A, Jensen CE, Maindal HT, Bro F, Jensen MB. Recruitment of general practices: Is a 
standardised approach helpful in the involvement of healthcare professionals in research? 
SAGE Open Med. 2016;4:205031211666280. doi:10.1177/2050312116662802 
51.  
Riis A, Jensen CE, Bro F, et al. Enhanced implementation of low back pain guidelines in 

 
46 
general practice: study protocol of a cluster randomised controlled trial. Implement Sci. 
2013;8(124):1-10. doi:10.1186/s13012-016-0509-0 
52.  
Kamper SJ, Dissing KB, Hestbaek L. Whose pain is it anyway ? Comparability of pain reports 
from children and their parents. Chiropr Man Therap. 2016:1-7. doi:10.1186/s12998-016-
0104-0 
53.  
Varni JW, Stucky BD, Thissen D, et al. PROMIS Pediatric Pain Interference Scale: An Item 
Response Theory Analysis of the Pediatric Pain Item Bank. 2010;11(11):1109-1119. 
doi:doi:10.1016/j.jpain.2010.02.005 
54.  
Robins H, Perron V, Heathcote L, Simons L. Pain Neuroscience Education: State of the Art 
and Application in Pediatrics. Children. 2016;3(4):43. doi:10.3390/children3040043 
55.  
Pate J, Hush J, Hancock M, et al. A Child’s Concept of Pain: An International Survey of 
Pediatric Pain Experts. Children. 2018;5(1):12. doi:10.3390/children5010012 
56.  
Coakley R, Schechter N. Chronic pain is like… The clinical use of analogy and metaphor in 
the treatment of chronic pain in children. Pediatr Pain Lett. 2013;15(1):1-8. 
doi:10.2522/ptj.20100278 
57.  
Kocher MS, Smith JT, Iversen MD, et al. Reliability, validity, and responsiveness of a 
modified international knee documentation committee subjective knee form (Pedi-IKDC) in 
children with knee disorders. Am J Sports Med. 2011;39(5):933-939. 
doi:10.1177/0363546510383002